diff --git a/.gitignore b/.gitignore index dbc8f310b..71d5e3364 100644 --- a/.gitignore +++ b/.gitignore @@ -17,6 +17,7 @@ eggs/ .eggs/ lib/ lib64/ +!ci/hetzner/lib/ parts/ sdist/ var/ @@ -167,6 +168,9 @@ docs/source/_static/*woff* packages/buckaroo-js-core/tsconfig.tsbuildinfo +# Downloaded CI logs (stress-test analysis) +ci-logs/ + # Large data files - should not be in repo *.parq *.parquet diff --git a/CLAUDE.md b/CLAUDE.md index 490adcc14..fd3763892 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -40,6 +40,17 @@ Test suite should complete in under 40 seconds. If it doesn't, something is wron Runs on push to main and PRs. Key jobs: LintPython, TestJS, BuildWheel, TestPython (3.11-3.14), Playwright (Storybook, Jupyter, Marimo, WASM). Uses `depot-ubuntu-latest` runners. +### Hetzner CI (manual/agent pre-push) + +Fast self-hosted CI on Hetzner. Trigger: `docker exec buckaroo-ci bash /opt/ci-runner/run-ci.sh `. + +**Every time a CI experiment completes, report:** +- Wallclock total runtime +- Runtime of each phase (Phase 1 / 2 / 3 / 4 / 5a / 5b) +- Pass/fail per job + +Parse from `/opt/ci/logs//ci.log` — lines like `[HH:MM:SS] START/PASS/FAIL `. + ## Architecture Notes - **Column renaming**: Internally rewrites column names to a,b,c... — use `orig_col_name` to map back to real names. diff --git a/ci/hetzner/.env.example b/ci/hetzner/.env.example new file mode 100644 index 000000000..50e509105 --- /dev/null +++ b/ci/hetzner/.env.example @@ -0,0 +1,15 @@ +# Copy to /opt/ci/.env and fill in values before starting the webhook service. + +# Fine-grained PAT with "commit statuses: read & write" on buckaroo-data/buckaroo +GITHUB_TOKEN=ghp_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx + +# Random secret shared with GitHub webhook settings (Settings → Webhooks → Secret) +# Generate with: openssl rand -hex 32 +WEBHOOK_SECRET=your_webhook_secret_here + +# GitHub repo in "owner/name" format +GITHUB_REPO=buckaroo-data/buckaroo + +# Hetzner server details (from `hcloud server list` after provisioning) +HETZNER_SERVER_ID=12345678 +HETZNER_SERVER_IP=1.2.3.4 diff --git a/ci/hetzner/Dockerfile b/ci/hetzner/Dockerfile new file mode 100644 index 000000000..8290c0c16 --- /dev/null +++ b/ci/hetzner/Dockerfile @@ -0,0 +1,72 @@ +FROM ubuntu:24.04 + +ENV DEBIAN_FRONTEND=noninteractive +ENV PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright +ENV PNPM_STORE_DIR=/opt/pnpm-store + +# 1. OS + base tools +RUN apt-get update && apt-get install -y --no-install-recommends \ + curl git ca-certificates gnupg \ + build-essential libffi-dev libssl-dev tini \ + && rm -rf /var/lib/apt/lists/* + +# 2. uv (pinned — bump when needed, not on a schedule) +COPY --from=ghcr.io/astral-sh/uv:0.6.6 /uv /usr/local/bin/uv + +# 3. Python 3.11-3.14 via uv (no deadsnakes PPA needed) +RUN uv python install 3.11 3.12 3.13 3.14 + +# 4. Node 22 LTS + pnpm 9.10.0 (pinned) +RUN curl -fsSL https://deb.nodesource.com/setup_22.x | bash - \ + && apt-get install -y --no-install-recommends nodejs \ + && rm -rf /var/lib/apt/lists/* \ + && corepack enable \ + && corepack prepare pnpm@9.10.0 --activate + +# 5. JS deps — populate pnpm content-addressable store +# Reproduces the packages/ workspace structure so pnpm install works. +# At runtime, pnpm install is ~50ms (just creates hard links from the store). +WORKDIR /build-js +COPY packages/pnpm-lock.yaml packages/pnpm-workspace.yaml packages/package.json ./ +COPY packages/buckaroo-js-core/package.json ./buckaroo-js-core/ +COPY packages/js/package.json ./js/ +RUN pnpm install --frozen-lockfile --store-dir /opt/pnpm-store + +# 6. Python deps — one venv per Python version, all extras, no project install +# At runtime, `uv sync` installs only buckaroo itself (editable), which is instant. +WORKDIR /build-py +COPY pyproject.toml uv.lock ./ +RUN for v in 3.11 3.12 3.13 3.14; do \ + uv venv /opt/venvs/$v --python $v && \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/$v \ + uv sync --locked --dev --all-extras --no-install-project; \ +done + +# 7. Playwright chromium — install system deps + browser for Python playwright. +# JS playwright (pnpm exec playwright) uses the same PLAYWRIGHT_BROWSERS_PATH, +# so it will find the same browser or install its version alongside it. +RUN /opt/venvs/3.13/bin/playwright install --with-deps chromium +RUN cd /build-js/buckaroo-js-core && pnpm exec playwright install chromium + +# 8. Bake CI runner scripts into the image at a stable path so they survive +# `git checkout` of arbitrary SHAs inside /repo at runtime. +COPY ci/hetzner/run-ci.sh ci/hetzner/lib/ /opt/ci-runner/ +COPY scripts/test_playwright_jupyter_parallel.sh /opt/ci-runner/ +ARG GIT_SHA=unknown +RUN echo "$GIT_SHA" > /opt/ci-runner/VERSION && \ + chmod +x /opt/ci-runner/run-ci.sh /opt/ci-runner/test_playwright_jupyter_parallel.sh + +# Allow JupyterLab to start as root (container runs as root). +# This avoids needing --allow-root in every script that starts Jupyter. +RUN mkdir -p /root/.jupyter && \ + echo "c.ServerApp.allow_root = True" >> /root/.jupyter/jupyter_lab_config.py + +# Source code is bind-mounted at /repo at runtime — not baked in. +# Allow git to operate on the bind-mounted repo (owned by ci on host, root in container). +RUN git config --system --add safe.directory /repo +WORKDIR /repo +# tini as PID 1 reaps zombie processes from docker exec'd CI runs. +# Without it, sleep-infinity PID 1 doesn't call wait(), zombies accumulate, +# and back-to-back CI runs fail. +ENTRYPOINT ["/usr/bin/tini", "--"] +CMD ["sleep", "infinity"] diff --git a/ci/hetzner/ci-queue.sh b/ci/hetzner/ci-queue.sh new file mode 100755 index 000000000..ca6390dd9 --- /dev/null +++ b/ci/hetzner/ci-queue.sh @@ -0,0 +1,340 @@ +#!/bin/bash +# CI Job Queue — directory-based queue with flock for single-worker enforcement. +# +# Deploy to HOST at /opt/ci/ci-queue.sh, symlink to /usr/local/bin/ci-queue. +# +# Usage: +# ci-queue push SHA BRANCH [ARGS...] # Enqueue + auto-start worker +# ci-queue status # Show running/pending/recent +# ci-queue cancel # Kill current job +# ci-queue clear # Remove all pending jobs +# ci-queue log [SHA] # Tail active job's CI log +# ci-queue repeat SHA BRANCH N # Push same SHA N times +# ci-queue worker # (internal) Run worker loop + +set -uo pipefail + +QUEUE_DIR=/opt/ci/queue +PENDING_DIR=$QUEUE_DIR/pending +ACTIVE_DIR=$QUEUE_DIR/active +DONE_DIR=$QUEUE_DIR/done +FAILED_DIR=$QUEUE_DIR/failed +WORKER_LOCK=$QUEUE_DIR/worker.lock +WORKER_PID=$QUEUE_DIR/worker.pid +WORKER_LOG=$QUEUE_DIR/worker.log +CONTAINER=${HETZNER_CONTAINER:-buckaroo-ci} + +# ── Helpers ────────────────────────────────────────────────────────────────── + +ensure_dirs() { + mkdir -p "$PENDING_DIR" "$ACTIVE_DIR" "$DONE_DIR" "$FAILED_DIR" +} + +ts() { + date -u +%Y-%m-%dT%H:%M:%SZ +} + +log() { + echo "[$(date +'%H:%M:%S')] $*" | tee -a "$WORKER_LOG" +} + +# Generate a sortable job filename: timestamp + random suffix +job_filename() { + echo "$(date +%Y%m%d%H%M%S)-$$-$RANDOM.job" +} + +# Read a field from a job file +job_field() { + local file=$1 field=$2 + grep "^${field}=" "$file" 2>/dev/null | head -1 | cut -d= -f2- +} + +# Update/add a field in a job file +job_set() { + local file=$1 field=$2 value=$3 + if grep -q "^${field}=" "$file" 2>/dev/null; then + sed -i "s|^${field}=.*|${field}=${value}|" "$file" + else + echo "${field}=${value}" >> "$file" + fi +} + +# ── Commands ───────────────────────────────────────────────────────────────── + +cmd_push() { + local sha=${1:?usage: ci-queue push SHA BRANCH [ARGS...]} + local branch=${2:?usage: ci-queue push SHA BRANCH [ARGS...]} + shift 2 + local args="$*" + + ensure_dirs + local jobfile="$PENDING_DIR/$(job_filename)" + cat > "$jobfile" < /dev/null 2>&1 & + disown + echo "Worker started (pid $!)" + fi +} + +cmd_status() { + ensure_dirs + + # Active job + local active_jobs + active_jobs=$(ls "$ACTIVE_DIR"/*.job 2>/dev/null) + if [[ -n "$active_jobs" ]]; then + echo "RUNNING:" + for f in $active_jobs; do + local sha=$(job_field "$f" SHA) + local branch=$(job_field "$f" BRANCH) + local started=$(job_field "$f" STARTED_AT) + echo " $sha ($branch) started $started" + done + else + echo "RUNNING: (none)" + fi + + # Pending jobs + local pending_jobs + pending_jobs=$(ls "$PENDING_DIR"/*.job 2>/dev/null | sort) + local pending_count=$(echo "$pending_jobs" | grep -c '.job$' 2>/dev/null || echo 0) + echo "" + echo "PENDING: $pending_count" + if [[ -n "$pending_jobs" ]]; then + for f in $pending_jobs; do + local sha=$(job_field "$f" SHA) + local branch=$(job_field "$f" BRANCH) + echo " $sha ($branch)" + done + fi + + # Recent completed (last 5) + echo "" + echo "RECENT:" + local done_jobs + done_jobs=$(ls -t "$DONE_DIR"/*.job "$FAILED_DIR"/*.job 2>/dev/null | head -5) + if [[ -n "$done_jobs" ]]; then + for f in $done_jobs; do + local sha=$(job_field "$f" SHA) + local status=$(job_field "$f" STATUS) + local duration=$(job_field "$f" DURATION) + local exit_code=$(job_field "$f" EXIT_CODE) + echo " $sha $status ${duration}s exit=$exit_code" + done + else + echo " (none)" + fi + + # Worker status + echo "" + if _worker_alive; then + echo "Worker: running (pid $(cat "$WORKER_PID" 2>/dev/null))" + else + echo "Worker: stopped" + fi +} + +cmd_cancel() { + local active_jobs + active_jobs=$(ls "$ACTIVE_DIR"/*.job 2>/dev/null) + if [[ -z "$active_jobs" ]]; then + echo "No active job to cancel" + return 0 + fi + + for f in $active_jobs; do + local sha=$(job_field "$f" SHA) + echo "Cancelling: $sha" + # Kill the docker exec process for this SHA + docker exec "$CONTAINER" pkill -f "run-ci.sh.*$sha" 2>/dev/null || true + job_set "$f" STATUS "cancelled" + job_set "$f" FINISHED_AT "$(ts)" + mv "$f" "$FAILED_DIR/" + done + echo "Cancelled. Pending jobs will continue when worker restarts." +} + +cmd_clear() { + local count + count=$(ls "$PENDING_DIR"/*.job 2>/dev/null | wc -l) + rm -f "$PENDING_DIR"/*.job + echo "Cleared $count pending jobs" +} + +cmd_log() { + local sha=${1:-} + + if [[ -n "$sha" ]]; then + # Tail specific SHA's CI log + local logfile="/opt/ci/logs/$sha/ci.log" + if [[ -f "$logfile" ]]; then + tail -f "$logfile" + else + echo "No log found: $logfile" + return 1 + fi + else + # Find active job and tail its log + local active_job + active_job=$(ls "$ACTIVE_DIR"/*.job 2>/dev/null | head -1) + if [[ -z "$active_job" ]]; then + echo "No active job. Tailing worker log instead." + tail -f "$WORKER_LOG" + return + fi + sha=$(job_field "$active_job" SHA) + local logfile="/opt/ci/logs/$sha/ci.log" + echo "Tailing $sha ..." + tail -f "$logfile" + fi +} + +cmd_repeat() { + local sha=${1:?usage: ci-queue repeat SHA BRANCH N} + local branch=${2:?usage: ci-queue repeat SHA BRANCH N} + local n=${3:?usage: ci-queue repeat SHA BRANCH N} + + for ((i=1; i<=n; i++)); do + cmd_push "$sha" "$branch" + done + echo "Queued $n runs of $sha" +} + +# ── Worker ─────────────────────────────────────────────────────────────────── + +_worker_alive() { + [[ -f "$WORKER_PID" ]] && kill -0 "$(cat "$WORKER_PID")" 2>/dev/null +} + +cmd_worker() { + ensure_dirs + + # flock for single-worker enforcement + exec 9>"$WORKER_LOCK" + if ! flock -n 9; then + echo "Worker already running" + return 0 + fi + + echo $$ > "$WORKER_PID" + log "Worker started (pid $$)" + + # Recover orphaned jobs in active/ (from a crash) + for f in "$ACTIVE_DIR"/*.job; do + [[ -f "$f" ]] || continue + local sha=$(job_field "$f" SHA) + log "Recovering orphaned job: $sha → failed" + job_set "$f" STATUS "failed" + job_set "$f" FINISHED_AT "$(ts)" + job_set "$f" EXIT_CODE "-1" + mv "$f" "$FAILED_DIR/" + done + + # Process queue + while true; do + local next + next=$(ls "$PENDING_DIR"/*.job 2>/dev/null | sort | head -1) + if [[ -z "$next" ]]; then + log "Queue empty — worker exiting" + break + fi + + # Move to active + mv "$next" "$ACTIVE_DIR/" + local jobfile="$ACTIVE_DIR/$(basename "$next")" + + local sha=$(job_field "$jobfile" SHA) + local branch=$(job_field "$jobfile" BRANCH) + local args=$(job_field "$jobfile" ARGS) + local start_ts + start_ts=$(date +%s) + + job_set "$jobfile" STATUS "running" + job_set "$jobfile" STARTED_AT "$(ts)" + + log "START $sha ($branch) args=[$args]" + + # Load env for docker exec + local env_args=() + if [[ -f /opt/ci/.env ]]; then + while IFS='=' read -r key val; do + [[ -z "$key" || "$key" == \#* ]] && continue + env_args+=("-e" "${key}=${val}") + done < /opt/ci/.env + fi + + # Ensure log directory exists (run-ci.sh creates it too, but we need + # it before docker exec for our own redirection). + mkdir -p "/opt/ci/logs/$sha" + + # Run CI — run-ci.sh already writes to /opt/ci/logs/$sha/ci.log via + # tee internally, so we just capture docker exec stdout/stderr to a + # separate file to avoid double-writing. + local rc=0 + docker exec "${env_args[@]}" "$CONTAINER" \ + bash /opt/ci-runner/run-ci.sh "$sha" "$branch" $args \ + > "/opt/ci/logs/$sha/queue-exec.log" 2>&1 || rc=$? + + local end_ts + end_ts=$(date +%s) + local duration=$((end_ts - start_ts)) + + job_set "$jobfile" FINISHED_AT "$(ts)" + job_set "$jobfile" EXIT_CODE "$rc" + job_set "$jobfile" DURATION "$duration" + + if [[ $rc -eq 0 ]]; then + job_set "$jobfile" STATUS "passed" + mv "$jobfile" "$DONE_DIR/" + log "PASS $sha (${duration}s)" + else + job_set "$jobfile" STATUS "failed" + mv "$jobfile" "$FAILED_DIR/" + log "FAIL $sha (${duration}s, exit=$rc)" + fi + done + + rm -f "$WORKER_PID" + # flock released automatically when fd 9 closes +} + +# ── Dispatch ───────────────────────────────────────────────────────────────── + +cmd=${1:-help} +shift 2>/dev/null || true + +case "$cmd" in + push) cmd_push "$@" ;; + status) cmd_status ;; + cancel) cmd_cancel ;; + clear) cmd_clear ;; + log) cmd_log "$@" ;; + repeat) cmd_repeat "$@" ;; + worker) cmd_worker ;; + help|--help|-h) + echo "Usage: ci-queue [args]" + echo "" + echo "Commands:" + echo " push SHA BRANCH [ARGS...] Enqueue a CI run" + echo " status Show queue status" + echo " cancel Kill current job" + echo " clear Remove all pending jobs" + echo " log [SHA] Tail active job's CI log" + echo " repeat SHA BRANCH N Push same SHA N times" + echo " worker (internal) Run worker loop" + ;; + *) + echo "Unknown command: $cmd (try: ci-queue help)" + exit 1 + ;; +esac diff --git a/ci/hetzner/cloud-init.yml b/ci/hetzner/cloud-init.yml new file mode 100644 index 000000000..90bd4dc0d --- /dev/null +++ b/ci/hetzner/cloud-init.yml @@ -0,0 +1,145 @@ +#cloud-config +# Hetzner CCX33 provisioning for Buckaroo CI. +# +# Usage: +# hcloud server create \ +# --name buckaroo-ci \ +# --type ccx33 \ +# --image ubuntu-24.04 \ +# --user-data-from-file ci/hetzner/cloud-init.yml \ +# --ssh-key +# +# After provisioning completes (~8 min): +# 1. SSH into the server. +# 2. Fill in /opt/ci/.env (copy from ci/hetzner/.env.example). +# 3. systemctl start buckaroo-webhook +# 4. Configure the GitHub webhook: +# URL: http://:9000/webhook +# Content-type: application/json +# Secret: value from .env WEBHOOK_SECRET +# Events: Pushes, Pull requests + +package_update: true +package_upgrade: true + +packages: + - git + - curl + - python3 + - python3-pip + - python3-venv + - ufw + - fail2ban + - ca-certificates + - gnupg + +write_files: + - path: /opt/ci/.env + permissions: "0600" + content: | + # Fill in these values — see ci/hetzner/.env.example + GITHUB_TOKEN= + WEBHOOK_SECRET= + GITHUB_REPO=buckaroo-data/buckaroo + HETZNER_SERVER_ID= + HETZNER_SERVER_IP= + + - path: /etc/systemd/system/buckaroo-webhook.service + permissions: "0644" + content: | + [Unit] + Description=Buckaroo CI Webhook + After=network.target docker.service + Requires=docker.service + + [Service] + Type=notify + User=ci + WorkingDirectory=/opt/ci + EnvironmentFile=/opt/ci/.env + ExecStart=/opt/ci/venv/bin/gunicorn \ + --workers 1 \ + --bind 0.0.0.0:9000 \ + --chdir /opt/ci/repo/ci/hetzner \ + --timeout 0 \ + webhook:app + Restart=always + RestartSec=5 + NotifyAccess=main + WatchdogSec=60 + + [Install] + WantedBy=multi-user.target + + - path: /etc/cron.weekly/ci-disk-hygiene + permissions: "0755" + content: | + #!/bin/bash + # Weekly disk cleanup: prune unused Docker objects and old CI logs. + docker system prune --force + find /opt/ci/logs -mindepth 1 -maxdepth 1 -type d \ + -mtime +7 -exec rm -rf {} + + + - path: /etc/cron.d/ci-dead-mans-switch + permissions: "0644" + content: | + # Weekdays at 9am: warn if no successful CI run in 24h. + 0 9 * * 1-5 ci test -f /opt/ci/last-success && \ + [ $(( $(date +%s) - $(stat -c %Y /opt/ci/last-success) )) -lt 86400 ] || \ + echo "WARNING: no successful CI run in 24h" >> /opt/ci/logs/health-warnings.log + +runcmd: + # ── Docker ────────────────────────────────────────────────────────────────── + - install -m 0755 -d /etc/apt/keyrings + - curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc + - chmod a+r /etc/apt/keyrings/docker.asc + - | + echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] \ + https://download.docker.com/linux/ubuntu $(. /etc/os-release && echo "$VERSION_CODENAME") stable" \ + > /etc/apt/sources.list.d/docker.list + - apt-get update -q + - apt-get install -y -q docker-ce docker-ce-cli containerd.io docker-compose-plugin + + # ── ci user ───────────────────────────────────────────────────────────────── + - useradd -m -s /bin/bash -G docker ci + + # ── Directory structure ────────────────────────────────────────────────────── + - mkdir -p /opt/ci/logs /opt/ci/hashes + - chown -R ci:ci /opt/ci + + # ── Clone repo ─────────────────────────────────────────────────────────────── + - git clone --branch main https://github.com/buckaroo-data/buckaroo /opt/ci/repo + - git config --global --add safe.directory /opt/ci/repo + - chown -R ci:ci /opt/ci/repo + + # ── Webhook virtualenv (Flask + gunicorn) ──────────────────────────────────── + - python3 -m venv /opt/ci/venv + - /opt/ci/venv/bin/pip install --quiet flask gunicorn + - chown -R ci:ci /opt/ci/venv + + # ── Build the CI Docker image ──────────────────────────────────────────────── + - | + cd /opt/ci/repo && \ + docker build -f ci/hetzner/Dockerfile -t buckaroo-ci . \ + 2>&1 | tee /opt/ci/logs/docker-build.log + + # ── Start warm sidecar container ───────────────────────────────────────────── + - | + cd /opt/ci/repo/ci/hetzner && \ + docker compose up -d + + # ── Firewall: SSH + webhook port only ──────────────────────────────────────── + - ufw default deny incoming + - ufw default allow outgoing + - ufw allow ssh + - ufw allow 9000/tcp + - ufw --force enable + + # ── Enable systemd services ─────────────────────────────────────────────────── + - systemctl daemon-reload + - systemctl enable fail2ban buckaroo-webhook + - systemctl start fail2ban + # webhook is NOT auto-started: fill in /opt/ci/.env first, then start manually. + + - | + echo "cloud-init complete. Fill in /opt/ci/.env then: systemctl start buckaroo-webhook" diff --git a/ci/hetzner/docker-compose.yml b/ci/hetzner/docker-compose.yml new file mode 100644 index 000000000..c87f56fe4 --- /dev/null +++ b/ci/hetzner/docker-compose.yml @@ -0,0 +1,36 @@ +services: + ci: + image: buckaroo-ci + container_name: buckaroo-ci + volumes: + # Source code — bind-mounted so git checkout + docker exec can work on it. + - /opt/ci/repo:/repo + # CI runner scripts — bind-mounted so script changes take effect instantly + # without rebuilding the Docker image. Only Dockerfile changes (new deps, + # system packages) require a rebuild. Overrides the baked-in /opt/ci-runner/. + # Uses /opt/ci/runner/ (separate from /opt/ci/repo/) so git checkout of + # arbitrary SHAs inside /repo doesn't swap out the runner mid-run. + # Update with: ci/hetzner/update-runner.sh + - /opt/ci/runner:/opt/ci-runner:ro + # CI logs — shared with host so webhook.py can serve them at /logs/. + - /opt/ci/logs:/opt/ci/logs + # JS build cache — persists across container restarts. + - /opt/ci/js-cache:/opt/ci/js-cache + # pnpm store — named volume so hardlinks in node_modules survive container recreates. + - pnpm-store:/opt/pnpm-store + # Playwright browser binaries — named volume so they survive image rebuilds. + # Initialized from image content on first start, then updated in place. + - playwright-browsers:/opt/ms-playwright + environment: + - CI=true + - PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright + - PNPM_STORE_DIR=/opt/pnpm-store + # Warm sidecar: stays alive between CI runs, avoiding ~500ms docker run overhead. + # tini as PID 1 (ENTRYPOINT in Dockerfile) reaps zombies from docker exec'd CI runs. + shm_size: '2g' + command: sleep infinity + restart: unless-stopped + +volumes: + pnpm-store: + playwright-browsers: diff --git a/ci/hetzner/download-ci-logs.sh b/ci/hetzner/download-ci-logs.sh new file mode 100755 index 000000000..c4b2f075d --- /dev/null +++ b/ci/hetzner/download-ci-logs.sh @@ -0,0 +1,138 @@ +#!/bin/bash +# Download GitHub Actions CI logs for all stress-test commits. +# +# Usage: +# bash ci/hetzner/download-ci-logs.sh # all sets +# bash ci/hetzner/download-ci-logs.sh --set=safe # just safe commits +# bash ci/hetzner/download-ci-logs.sh --set=failing # just failing commits +# bash ci/hetzner/download-ci-logs.sh --set=older # just older commits +# bash ci/hetzner/download-ci-logs.sh ... # specific SHAs +# +# Downloads to: ci-logs//checks.log +# Each log file contains the full text output from the "Checks" workflow run. + +set -uo pipefail + +REPO="buckaroo-data/buckaroo" +OUTDIR="ci-logs" +COMMIT_SET="all" +CUSTOM_SHAS=() + +while [[ $# -gt 0 ]]; do + case $1 in + --set=*) COMMIT_SET="${1#*=}"; shift ;; + --set) COMMIT_SET="$2"; shift 2 ;; + --outdir=*) OUTDIR="${1#*=}"; shift ;; + --outdir) OUTDIR="$2"; shift 2 ;; + *) CUSTOM_SHAS+=("$1"); shift ;; + esac +done + +# ── Same commit arrays as stress-test.sh ────────────────────────────────────── + +SAFE_COMMITS=( + 7b6a05c fcfe368 5ff4d6e 837654e f8a8b94 314e89f 8e9e1ed 1fccaba + b7956f8 612e22f e392c78 6b9e695 6056636 ec68a78 2175249 fdbe325 +) + +FAILING_COMMITS=( + cf7e02a e0f358a 7b3141c 703c034 db1ca96 4ddcac1 7d8b751 b1eb6a5 + 1839f59 88a8743 2bec338 c8e98d3 7b9c341 516a1fa f01c9c6 +) + +OLDER_COMMITS=( + f10ee77 3bb6d71 8623244 5c3f861 e2f610f ae9006d 5f20962 dbac567 + fa011f8 25d674b 79da494 2ea8866 14ec761 af9fa79 9693b9b 23e3096 +) + +if [[ ${#CUSTOM_SHAS[@]} -gt 0 ]]; then + COMMITS=("${CUSTOM_SHAS[@]}") +else + case "$COMMIT_SET" in + safe) COMMITS=("${SAFE_COMMITS[@]}") ;; + failing) COMMITS=("${FAILING_COMMITS[@]}") ;; + older) COMMITS=("${OLDER_COMMITS[@]}") ;; + all) COMMITS=("${SAFE_COMMITS[@]}" "${FAILING_COMMITS[@]}" "${OLDER_COMMITS[@]}") ;; + *) echo "Unknown --set: $COMMIT_SET (use safe|failing|older|all)"; exit 1 ;; + esac +fi + +TOTAL=${#COMMITS[@]} +mkdir -p "$OUTDIR" + +echo "Downloading CI logs for $TOTAL commits → $OUTDIR/" +echo "" + +DOWNLOADED=0 +SKIPPED=0 +NO_RUNS=0 + +for i in "${!COMMITS[@]}"; do + sha="${COMMITS[$i]}" + dir="$OUTDIR/$sha" + log="$dir/checks.log" + + printf "[%d/%d] %s " "$((i+1))" "$TOTAL" "$sha" + + # Skip if already downloaded (real logs only, not placeholder files) + if [[ -f "$log" && -s "$log" ]] && ! head -1 "$log" | grep -qE '^(NO_CHECKS_RUN|DOWNLOAD_FAILED)'; then + echo " (cached)" + ((SKIPPED++)) + continue + fi + + mkdir -p "$dir" + + # Find the CI workflow run for this commit. + # Workflow was renamed over time: "CI" → "Build" → "Checks". + # check-runs API gives us details_url containing the run ID. + run_ids=$( + gh api "repos/$REPO/commits/$sha/check-runs" \ + -q '.check_runs[].details_url' 2>/dev/null \ + | sed 's|.*/runs/||;s|/.*||' \ + | sort -u + ) + + run_id="" + # Prefer "Checks" (current), fall back to "CI" or "Build" (older) + for rid in $run_ids; do + name=$(gh api "repos/$REPO/actions/runs/$rid" -q '.name' 2>/dev/null) + case "$name" in + Checks) run_id="$rid"; break ;; + CI) [[ -z "$run_id" ]] && run_id="$rid" ;; + Build) [[ -z "$run_id" ]] && run_id="$rid" ;; + esac + done + + if [[ -z "$run_id" ]]; then + echo " (no Checks run found)" + echo "NO_CHECKS_RUN" > "$dir/checks.log" + ((NO_RUNS++)) + continue + fi + + # Download text logs + if gh run view "$run_id" --repo "$REPO" --log > "$log" 2>/dev/null; then + lines=$(wc -l < "$log" | tr -d ' ') + echo " run=$run_id ${lines} lines" + ((DOWNLOADED++)) + else + echo " (log download failed for run $run_id)" + echo "DOWNLOAD_FAILED run=$run_id" > "$log" + ((NO_RUNS++)) + fi + + # Also save per-job summary + gh run view "$run_id" --repo "$REPO" \ + --json jobs -q '.jobs[] | "\(.name)\t\(.conclusion)\t\(.startedAt)\t\(.completedAt)"' \ + > "$dir/jobs.tsv" 2>/dev/null || true +done + +echo "" +echo "═══════════════════════════════════════" +echo " Downloaded: $DOWNLOADED" +echo " Cached: $SKIPPED" +echo " No runs: $NO_RUNS" +echo " Total: $TOTAL" +echo " Output: $OUTDIR/" +echo "═══════════════════════════════════════" diff --git a/ci/hetzner/exp4-b2b-test.sh b/ci/hetzner/exp4-b2b-test.sh new file mode 100644 index 000000000..b7a3bb248 --- /dev/null +++ b/ci/hetzner/exp4-b2b-test.sh @@ -0,0 +1,56 @@ +#!/usr/bin/env bash +# Experiment 4: Back-to-back degradation test +# Runs the pw-jupyter harness N times consecutively, capturing state between runs. +set -uo pipefail + +PARALLEL=${JUPYTER_PARALLEL:-9} +RUNS=${B2B_RUNS:-3} +LOGBASE=/opt/ci/logs/exp4-b2b +WHEEL_SHA=${1:-4a7fefc} +TEST_SHA=${2:-e6ea620} + +mkdir -p "$LOGBASE" + +capture_state() { + local label=$1 + local f="$LOGBASE/state-$label.log" + echo "=== $(date +%H:%M:%S) state capture: $label ===" > "$f" + echo "--- fd count ---" >> "$f" + find /proc -maxdepth 2 -name fd -type d 2>/dev/null | wc -l >> "$f" + echo "--- /tmp files ---" >> "$f" + find /tmp -maxdepth 2 -type f 2>/dev/null | wc -l >> "$f" + echo "--- memory ---" >> "$f" + free -m >> "$f" + echo "--- sockets ---" >> "$f" + ss -s >> "$f" + echo "--- jupyter runtime files ---" >> "$f" + ls ~/.local/share/jupyter/runtime/ 2>/dev/null | wc -l >> "$f" + echo "--- processes ---" >> "$f" + ps aux | wc -l >> "$f" + echo "--- zombie count ---" >> "$f" + ps aux | awk '$8 ~ /Z/' | wc -l >> "$f" + echo "--- /dev/shm ---" >> "$f" + df -h /dev/shm >> "$f" + echo "--- TIME_WAIT sockets ---" >> "$f" + ss -t state time-wait | wc -l >> "$f" + echo "--- jupyter/python/chromium processes ---" >> "$f" + ps aux | grep -E 'jupyter|ipykernel|chromium|playwright' | grep -v grep | wc -l >> "$f" + cat "$f" +} + +capture_state before-run1 + +for i in $(seq 1 "$RUNS"); do + echo "" + echo "==========================================" + echo "=== RUN $i of $RUNS (P=$PARALLEL) ===" + echo "==========================================" + + JUPYTER_PARALLEL=$PARALLEL CI_TIMEOUT=180 \ + bash /repo/ci/hetzner/run-pw-jupyter.sh "$WHEEL_SHA" "$TEST_SHA" 0 2>&1 | tail -8 + + # Restore branch so harness script is available for next run + cd /repo && git checkout docs/ci-research 2>/dev/null && git reset --hard origin/docs/ci-research >/dev/null 2>&1 + + capture_state "after-run$i" +done diff --git a/ci/hetzner/lib/lockcheck.sh b/ci/hetzner/lib/lockcheck.sh new file mode 100644 index 000000000..ae8d544d7 --- /dev/null +++ b/ci/hetzner/lib/lockcheck.sh @@ -0,0 +1,84 @@ +#!/bin/bash +# Lockfile hash comparison — determines whether CI deps need rebuilding. +# +# On 95% of pushes, lockfiles don't change; skip expensive dep install entirely. +# When they do change (new dependency, version bump), detect it and rebuild. +# +# Tracked files: +# uv.lock — Python deps +# packages/pnpm-lock.yaml — JS deps +# pyproject.toml — may add new extras without touching uv.lock +# +# Hash storage: /opt/ci/logs/.lockcheck-hashes/ — persists across container +# restarts because /opt/ci/logs is bind-mounted to the host. +# +# Usage (inside run-ci.sh, from /repo): +# source /repo/ci/hetzner/lib/lockcheck.sh +# if ! lockcheck_valid; then +# rebuild_deps +# lockcheck_update +# fi + +LOCKCHECK_HASH_DIR=/opt/ci/logs/.lockcheck-hashes +LOCKCHECK_FILES=( + uv.lock + packages/pnpm-lock.yaml + pyproject.toml +) + +_lockcheck_hash_path() { + local file=$1 + # Replace slashes with underscores for filename + echo "$LOCKCHECK_HASH_DIR/${file//\//_}.sha256" +} + +# Returns 0 (valid) if all stored hashes match current files. +# Returns 1 (rebuild needed) if any hash differs or is missing. +lockcheck_valid() { + mkdir -p "$LOCKCHECK_HASH_DIR" + for f in "${LOCKCHECK_FILES[@]}"; do + local hash_file + hash_file=$(_lockcheck_hash_path "$f") + if [[ ! -f "$hash_file" ]]; then + return 1 + fi + local stored current + stored=$(cat "$hash_file") + current=$(sha256sum "$f" | awk '{print $1}') + if [[ "$stored" != "$current" ]]; then + return 1 + fi + done + return 0 +} + +# Stores current hashes. Call after a successful rebuild. +lockcheck_update() { + mkdir -p "$LOCKCHECK_HASH_DIR" + for f in "${LOCKCHECK_FILES[@]}"; do + local hash_file + hash_file=$(_lockcheck_hash_path "$f") + sha256sum "$f" | awk '{print $1}' > "$hash_file" + done +} + +# Rebuilds Python venvs and JS node_modules. +# Run from /repo inside the container. +rebuild_deps() { + echo "[lockcheck] Rebuilding Python deps..." + for v in 3.11 3.12 3.13 3.14; do + UV_PROJECT_ENVIRONMENT=/opt/venvs/$v \ + uv sync --locked --dev --all-extras --no-install-project + done + + echo "[lockcheck] Rebuilding JS deps..." + cd packages + pnpm install --frozen-lockfile --store-dir /opt/pnpm-store + cd .. + + echo "[lockcheck] Reinstalling Playwright browsers (versions may have changed)..." + /opt/venvs/3.13/bin/playwright install chromium + cd packages/buckaroo-js-core && pnpm exec playwright install chromium && cd ../.. + + echo "[lockcheck] Rebuild complete." +} diff --git a/ci/hetzner/lib/status.sh b/ci/hetzner/lib/status.sh new file mode 100644 index 000000000..736015b9c --- /dev/null +++ b/ci/hetzner/lib/status.sh @@ -0,0 +1,59 @@ +#!/bin/bash +# GitHub commit status API helpers. +# Requires GITHUB_TOKEN and GITHUB_REPO to be set in the environment. +# GITHUB_REPO format: "owner/repo" +# +# Usage: +# source ci/hetzner/lib/status.sh +# status_pending "$SHA" "ci/hetzner" "Running…" "$LOG_URL" +# status_success "$SHA" "ci/hetzner" "All checks passed" "$LOG_URL" +# status_failure "$SHA" "ci/hetzner" "lint-python failed" "$LOG_URL" +# +# Add --dry-run as the last arg to print the curl command instead of running it. + +_github_status() { + local state=$1 + local sha=$2 + local context=$3 + local description=$4 + local target_url=$5 + local dry_run=${6:-} + + # Skip when no token configured (local/SSH testing mode). + if [[ -z "${GITHUB_TOKEN:-}" ]]; then + echo "[status] no GITHUB_TOKEN — skipping $state for $context" + return 0 + fi + + local url="https://api.github.com/repos/${GITHUB_REPO:-buckaroo-data/buckaroo}/statuses/${sha}" + local payload + payload=$(printf '{"state":"%s","context":"%s","description":"%s","target_url":"%s"}' \ + "$state" "$context" "$description" "$target_url") + + if [[ "$dry_run" == "--dry-run" ]]; then + echo "[dry-run] POST $url" + echo "[dry-run] $payload" + return 0 + fi + + curl -sf -X POST "$url" \ + -H "Authorization: token ${GITHUB_TOKEN}" \ + -H "Content-Type: application/json" \ + -d "$payload" \ + -o /dev/null +} + +status_pending() { + local sha=$1 context=$2 description=$3 url=$4 dry_run=${5:-} + _github_status "pending" "$sha" "$context" "$description" "$url" "$dry_run" +} + +status_success() { + local sha=$1 context=$2 description=$3 url=$4 dry_run=${5:-} + _github_status "success" "$sha" "$context" "$description" "$url" "$dry_run" +} + +status_failure() { + local sha=$1 context=$2 description=$3 url=$4 dry_run=${5:-} + _github_status "failure" "$sha" "$context" "$description" "$url" "$dry_run" +} diff --git a/ci/hetzner/monitor-processes.sh b/ci/hetzner/monitor-processes.sh new file mode 100644 index 000000000..1789d2650 --- /dev/null +++ b/ci/hetzner/monitor-processes.sh @@ -0,0 +1,46 @@ +#!/usr/bin/env bash +# Per-process CPU/memory monitor for pw-jupyter experiments. +# Usage: bash monitor-processes.sh +# Runs until killed (background it, kill when experiment ends). +set -euo pipefail + +LOGDIR="${1:?Usage: monitor-processes.sh }" +LOGFILE="$LOGDIR/per-process.log" +mkdir -p "$LOGDIR" + +INTERVAL="${MONITOR_INTERVAL:-2}" + +echo "=== Monitor started at $(date +%H:%M:%S) — interval=${INTERVAL}s ===" > "$LOGFILE" + +while true; do + { + echo "=== $(date +%H:%M:%S.%N) ===" + + echo "--- jupyter-lab ---" + ps aux | grep '[j]upyter-lab' | awk '{printf "PID=%s CPU=%s%% MEM=%s%% RSS=%sMB CMD=%s\n", $2, $3, $4, $6/1024, $11}' 2>/dev/null || true + + echo "--- python kernels ---" + ps aux | grep -E '[i]pykernel|[k]ernel.*python|python.*[k]ernel' | awk '{printf "PID=%s CPU=%s%% MEM=%s%% RSS=%sMB CMD=%s %s %s\n", $2, $3, $4, $6/1024, $11, $12, $13}' 2>/dev/null || true + + echo "--- chromium (top 5 by CPU) ---" + ps aux | grep '[c]hromium' | sort -k3 -rn | head -5 | awk '{printf "PID=%s CPU=%s%% MEM=%s%% RSS=%sMB\n", $2, $3, $4, $6/1024}' 2>/dev/null || true + + echo "--- node/playwright ---" + ps aux | grep '[n]ode.*playwright' | awk '{printf "PID=%s CPU=%s%% MEM=%s%%\n", $2, $3, $4}' 2>/dev/null || true + + echo "--- memory ---" + free -m | grep -E 'Mem|Swap' + + echo "--- ports ---" + for p in 8889 8890 8891 8892 8893 8894; do + count=$(ss -tnp 2>/dev/null | grep -c ":$p " || true) + [ "$count" -gt 0 ] && echo "port $p: $count connections" + done + + echo "--- load ---" + cat /proc/loadavg 2>/dev/null || true + + echo "" + } >> "$LOGFILE" 2>&1 + sleep "$INTERVAL" +done diff --git a/ci/hetzner/prepare-synth.sh b/ci/hetzner/prepare-synth.sh new file mode 100755 index 000000000..0dc01aa05 --- /dev/null +++ b/ci/hetzner/prepare-synth.sh @@ -0,0 +1,139 @@ +#!/bin/bash +# Generate synthetic merge commits: merge latest test improvements onto old SHAs. +# +# Usage: +# bash prepare-synth.sh TEST_SHA SHA1 SHA2 ... +# bash prepare-synth.sh TEST_SHA --set=safe # use safe commit set from stress-test.sh +# +# Runs inside the container's /repo (full clone). No pushes to GitHub — +# synthetic SHAs are local-only. run-ci.sh's `git checkout SHA` works +# with local commits. +# +# Output: /opt/ci/synth-map.txt (OLD_SHA SYNTH_SHA per line) + +set -uo pipefail + +TEST_SHA=${1:?usage: prepare-synth.sh TEST_SHA [--set=safe|SHA1 SHA2 ...]} +shift + +# ── Commit sets (mirrored from stress-test.sh) ────────────────────────────── + +SAFE_COMMITS=( + 7b6a05c fcfe368 5ff4d6e 837654e f8a8b94 314e89f 8e9e1ed 1fccaba + b7956f8 612e22f e392c78 6b9e695 6056636 ec68a78 2175249 fdbe325 +) + +# ── Parse args ─────────────────────────────────────────────────────────────── + +SHAS=() +while [[ $# -gt 0 ]]; do + case $1 in + --set=safe) SHAS=("${SAFE_COMMITS[@]}"); shift ;; + *) SHAS+=("$1"); shift ;; + esac +done + +if [[ ${#SHAS[@]} -eq 0 ]]; then + echo "No SHAs specified. Use --set=safe or provide SHAs." + exit 1 +fi + +# ── Files to take from TEST_SHA (theirs) on conflict ───────────────────────── + +THEIRS_PATHS=( + "packages/buckaroo-js-core/pw-tests/" + "scripts/test_playwright_*.sh" + "scripts/full_build.sh" +) + +# ── Generate synthetic commits ─────────────────────────────────────────────── + +REPO_DIR=/repo +MAP_FILE=/opt/ci/synth-map.txt +> "$MAP_FILE" # truncate + +cd "$REPO_DIR" + +# Ensure we have the test SHA +git fetch origin 2>/dev/null || true + +total=${#SHAS[@]} +success=0 +skipped=0 + +echo "Generating synthetic merges: $total SHAs × TEST_SHA=$TEST_SHA" +echo "" + +for i in "${!SHAS[@]}"; do + old_sha="${SHAS[$i]}" + branch_name="synth/${old_sha}" + idx=$((i + 1)) + + echo "[$idx/$total] $old_sha ..." + + # Clean up any previous attempt + git checkout -f HEAD 2>/dev/null || true + git branch -D "$branch_name" 2>/dev/null || true + + # Create branch at old SHA + if ! git checkout -b "$branch_name" "$old_sha" 2>/dev/null; then + echo " SKIP: cannot checkout $old_sha" + ((skipped++)) + continue + fi + + # Attempt merge + if git merge --no-edit "$TEST_SHA" 2>/dev/null; then + # Clean merge + synth_sha=$(git rev-parse HEAD) + echo "$old_sha $synth_sha" >> "$MAP_FILE" + echo " OK (clean merge) → ${synth_sha:0:10}" + ((success++)) + else + # Conflict — resolve with theirs for test files, ours for app code + + # Accept theirs for test-related paths + for pattern in "${THEIRS_PATHS[@]}"; do + # Use git checkout --theirs for conflicting files matching pattern + git diff --name-only --diff-filter=U 2>/dev/null | grep -E "$pattern" | while read -r f; do + git checkout --theirs "$f" 2>/dev/null && git add "$f" 2>/dev/null + done + done + + # Accept ours for everything else still conflicting + git diff --name-only --diff-filter=U 2>/dev/null | while read -r f; do + git checkout --ours "$f" 2>/dev/null && git add "$f" 2>/dev/null + done + + # Check if all conflicts resolved + if git diff --name-only --diff-filter=U 2>/dev/null | grep -q .; then + echo " SKIP: unresolvable conflicts" + git merge --abort 2>/dev/null || true + git checkout -f HEAD 2>/dev/null || true + git branch -D "$branch_name" 2>/dev/null || true + ((skipped++)) + continue + fi + + # Commit the merge + if git commit --no-edit -m "synth: merge $TEST_SHA onto $old_sha" 2>/dev/null; then + synth_sha=$(git rev-parse HEAD) + echo "$old_sha $synth_sha" >> "$MAP_FILE" + echo " OK (conflict resolved) → ${synth_sha:0:10}" + ((success++)) + else + echo " SKIP: commit failed" + git merge --abort 2>/dev/null || true + git branch -D "$branch_name" 2>/dev/null || true + ((skipped++)) + fi + fi +done + +# Return to detached HEAD so run-ci.sh works normally +git checkout -f HEAD 2>/dev/null || true + +echo "" +echo "Done: $success merged, $skipped skipped out of $total" +echo "Map: $MAP_FILE" +cat "$MAP_FILE" diff --git a/ci/hetzner/run-ci-dag-stagger.sh b/ci/hetzner/run-ci-dag-stagger.sh new file mode 100644 index 000000000..901a0ce0d --- /dev/null +++ b/ci/hetzner/run-ci-dag-stagger.sh @@ -0,0 +1,297 @@ +#!/bin/bash +# CI orchestrator — DAG with configurable staggering. +# +# Same DAG as run-ci-dag.sh but python tests can be delayed to smooth CPU load. +# Delay is a sleep before the job starts — the job itself is unchanged. +# +# Environment variables (all in seconds, default 0 = no delay): +# DELAY_PY311=15 — delay test-python-3.11 start by 15s +# DELAY_PY312=15 — delay test-python-3.12 start by 15s +# DELAY_PY313=0 — delay test-python-3.13 (usually 0, early feedback) +# DELAY_PY314=0 — delay test-python-3.14 (skipped anyway) +# +# Usage: +# # Default: same as run-ci-dag.sh (no delays) +# bash run-ci-dag-stagger.sh SHA BRANCH +# +# # Stagger py-3.11/3.12 to start after build-wheel (~13s) +# DELAY_PY311=15 DELAY_PY312=15 bash run-ci-dag-stagger.sh SHA BRANCH +# +# # Stagger everything for max CPU smoothing +# DELAY_PY311=15 DELAY_PY312=30 DELAY_PY313=0 bash run-ci-dag-stagger.sh SHA BRANCH + +set -uo pipefail + +SHA=${1:?usage: run-ci-dag-stagger.sh SHA BRANCH} +BRANCH=${2:?usage: run-ci-dag-stagger.sh SHA BRANCH} + +DELAY_PY311=${DELAY_PY311:-0} +DELAY_PY312=${DELAY_PY312:-0} +DELAY_PY313=${DELAY_PY313:-0} +DELAY_PY314=${DELAY_PY314:-0} + +REPO_DIR=/repo +RESULTS_DIR=/opt/ci/logs/$SHA +LOG_URL="http://${HETZNER_SERVER_IP:-localhost}:9000/logs/$SHA" +OVERALL=0 + +mkdir -p "$RESULTS_DIR" + +# Source lib from the image-baked path — survives git checkout of any SHA. +CI_RUNNER_DIR=${CI_RUNNER_DIR:-/opt/ci-runner} +source "$CI_RUNNER_DIR/status.sh" +source "$CI_RUNNER_DIR/lockcheck.sh" + +log() { echo "[$(date +'%H:%M:%S')] $*" | tee -a "$RESULTS_DIR/ci.log"; } + +# Run a job: captures output, returns exit code. +# run_job [args...] +run_job() { + local name=$1; shift + local logfile="$RESULTS_DIR/$name.log" + log "START $name" + if "$@" >"$logfile" 2>&1; then + log "PASS $name" + return 0 + else + log "FAIL $name (see $LOG_URL/$name.log)" + return 1 + fi +} + +# Delayed job wrapper: sleep then run. +# delayed_run_job [args...] +delayed_run_job() { + local delay=$1; shift + if [[ "$delay" -gt 0 ]]; then + log "DELAY $1 (${delay}s)" + sleep "$delay" + fi + run_job "$@" +} + +# ── Setup ──────────────────────────────────────────────────────────────────── + +status_pending "$SHA" "ci/hetzner" "Running CI..." "$LOG_URL" + +log "Checkout $SHA (branch: $BRANCH)" +log "Stagger: py311=${DELAY_PY311}s py312=${DELAY_PY312}s py313=${DELAY_PY313}s py314=${DELAY_PY314}s" +cd "$REPO_DIR" +git fetch origin +git checkout -f "$SHA" +# Clean untracked/ignored files; preserve warm caches in node_modules. +git clean -fdx \ + --exclude='packages/buckaroo-js-core/node_modules' \ + --exclude='packages/js/node_modules' \ + --exclude='packages/node_modules' + +# Lockfile check — rebuild deps only when lockfiles changed (~5% of pushes). +if lockcheck_valid; then + log "Lockfiles unchanged — using warm caches" +else + log "Lockfiles changed — rebuilding deps" + rebuild_deps + lockcheck_update +fi + +# Create empty static files so Python unit tests can import buckaroo before +# BuildWheel runs. BuildWheel overwrites these with real artifacts. +mkdir -p buckaroo/static +touch buckaroo/static/compiled.css buckaroo/static/widget.js buckaroo/static/widget.css + +# ── Job definitions ────────────────────────────────────────────────────────── + +job_lint_python() { + cd /repo + /opt/venvs/3.13/bin/ruff check +} + +job_build_js() { + cd /repo/packages + pnpm install --frozen-lockfile --store-dir /opt/pnpm-store + cd buckaroo-js-core + pnpm run build +} + +job_test_js() { + cd /repo/packages/buckaroo-js-core + pnpm run test +} + +job_test_python() { + local v=$1 + cd /repo + UV_PROJECT_ENVIRONMENT=/opt/venvs/$v \ + uv sync --locked --dev --all-extras + + if [[ "$v" == "3.14" ]]; then + echo "[skip] Python 3.14 alpha known to segfault — skipping pytest" + return 0 + fi + + /opt/venvs/$v/bin/python -m pytest tests/unit -m "not slow" --color=yes \ + --deselect tests/unit/file_cache/mp_timeout_decorator_test.py::test_mp_timeout_pass \ + --deselect tests/unit/file_cache/mp_timeout_decorator_test.py::test_mp_fail_then_normal \ + --deselect "tests/unit/server/test_mcp_tool_cleanup.py::TestServerMonitor::test_server_killed_on_parent_death" +} + +job_build_wheel() { + cd /repo + mkdir -p buckaroo/static + cp packages/buckaroo-js-core/dist/style.css buckaroo/static/compiled.css + cd packages + pnpm --filter buckaroo-widget run build + pnpm --filter buckaroo-widget run build:standalone + cd .. + rm -rf dist || true + uv build --wheel +} + +job_test_mcp_wheel() { + cd /repo + local venv=/tmp/ci-mcp-$$ + rm -rf "$venv" + uv venv "$venv" -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "${wheel}[mcp]" pytest -q + BUCKAROO_MCP_CMD="$venv/bin/buckaroo-table" \ + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py \ + tests/unit/server/test_mcp_server_integration.py \ + -v --color=yes -m slow + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py::TestUvxFailureModes \ + -v --color=yes -m slow + rm -rf "$venv" +} + +job_smoke_test_extras() { + cd /repo + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + for extra in base polars mcp marimo jupyterlab notebook; do + local venv=/tmp/ci-smoke-${extra}-$$ + rm -rf "$venv" + uv venv "$venv" -q + if [[ "$extra" == "base" ]]; then + uv pip install --python "$venv/bin/python" "$wheel" -q + else + uv pip install --python "$venv/bin/python" "${wheel}[${extra}]" -q + fi + "$venv/bin/python" scripts/smoke_test.py "$extra" + rm -rf "$venv" + done +} + +job_playwright_storybook() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-storybook-$$ \ + bash scripts/test_playwright_storybook.sh +} + +job_playwright_server() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-server-$$ \ + bash scripts/test_playwright_server.sh +} + +job_playwright_marimo() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_marimo.sh +} + +job_playwright_wasm_marimo() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-wasm-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_wasm_marimo.sh +} + +job_playwright_jupyter() { + cd /repo + local venv=/tmp/ci-jupyter-$$ + uv venv "$venv" --python 3.13 -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "$wheel" polars jupyterlab -q + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-jupyter-$$ \ + bash scripts/test_playwright_jupyter.sh --venv-location="$venv" + rm -rf "$venv" +} + +export -f job_lint_python job_build_js job_test_js job_test_python job_build_wheel \ + job_test_mcp_wheel job_smoke_test_extras \ + job_playwright_storybook job_playwright_server job_playwright_marimo \ + job_playwright_wasm_marimo job_playwright_jupyter + +# ── DAG execution ──────────────────────────────────────────────────────────── +# build-js starts immediately alongside lightweight jobs. +# Python tests are staggered by DELAY_PYxxx seconds to smooth CPU load. +# Once build-js completes, test-js and build-wheel start in parallel. +# Once build-wheel completes, wheel-dependent jobs start. + +log "=== Starting independent jobs ===" + +run_job lint-python job_lint_python & PID_LINT=$! +run_job build-js job_build_js & PID_BUILDJS=$! +run_job playwright-storybook job_playwright_storybook & PID_PW_SB=$! +delayed_run_job "$DELAY_PY313" test-python-3.13 bash -c "job_test_python 3.13" & PID_PY313=$! +delayed_run_job "$DELAY_PY314" test-python-3.14 bash -c "job_test_python 3.14" & PID_PY314=$! +delayed_run_job "$DELAY_PY311" test-python-3.11 bash -c "job_test_python 3.11" & PID_PY311=$! +delayed_run_job "$DELAY_PY312" test-python-3.12 bash -c "job_test_python 3.12" & PID_PY312=$! + +# ── Wait for build-js, then fork test-js + build-wheel in parallel ─────────── + +wait $PID_BUILDJS || OVERALL=1 +log "=== build-js done — starting test-js + build-wheel ===" + +run_job test-js job_test_js & PID_TESTJS=$! +run_job build-wheel job_build_wheel || OVERALL=1 + +# ── Wheel-dependent jobs ───────────────────────────────────────────────────── + +log "=== build-wheel done — starting wheel-dependent jobs ===" + +run_job test-mcp-wheel job_test_mcp_wheel & PID_MCP=$! +run_job smoke-test-extras job_smoke_test_extras & PID_SMOKE=$! +run_job playwright-server job_playwright_server & PID_PW_SV=$! +run_job playwright-jupyter job_playwright_jupyter & PID_PW_JP=$! +run_job playwright-marimo job_playwright_marimo & PID_PW_MA=$! +run_job playwright-wasm-marimo job_playwright_wasm_marimo & PID_PW_WM=$! + +# ── Wait for everything ───────────────────────────────────────────────────── + +wait $PID_LINT || OVERALL=1 +wait $PID_TESTJS || OVERALL=1 +wait $PID_PY311 || OVERALL=1 +wait $PID_PY312 || OVERALL=1 +wait $PID_PY313 || OVERALL=1 +wait $PID_PY314 || OVERALL=1 +wait $PID_PW_SB || OVERALL=1 +wait $PID_MCP || OVERALL=1 +wait $PID_SMOKE || OVERALL=1 +wait $PID_PW_SV || OVERALL=1 +wait $PID_PW_JP || OVERALL=1 +wait $PID_PW_MA || OVERALL=1 +wait $PID_PW_WM || OVERALL=1 + +# ── Final status ───────────────────────────────────────────────────────────── + +if [[ $OVERALL -eq 0 ]]; then + log "=== ALL JOBS PASSED ===" + status_success "$SHA" "ci/hetzner" "All checks passed" "$LOG_URL" + touch /opt/ci/last-success +else + log "=== SOME JOBS FAILED — see $LOG_URL ===" + status_failure "$SHA" "ci/hetzner" "CI failed — see logs" "$LOG_URL" +fi + +exit $OVERALL diff --git a/ci/hetzner/run-ci-dag.sh b/ci/hetzner/run-ci-dag.sh new file mode 100755 index 000000000..fb3e3b85f --- /dev/null +++ b/ci/hetzner/run-ci-dag.sh @@ -0,0 +1,294 @@ +#!/bin/bash +# CI orchestrator — DAG-based parallel execution. +# +# Drop-in replacement for run-ci.sh. Each job starts as soon as its specific +# dependencies are met, not when an entire phase completes. +# +# Dependency graph: +# No dependencies (start immediately): +# lint-python, build-js, test-python-{3.11,3.12,3.13,3.14}, +# playwright-storybook +# +# Depends on build-js (needs tsc+vite output in dist/): +# test-js (jest, runs in parallel with build-wheel) +# build-wheel (esbuild + uv build, skips redundant pnpm install+build) +# +# Depends on build-wheel (needs .whl): +# test-mcp-wheel, smoke-test-extras, playwright-server, playwright-jupyter, +# playwright-marimo, playwright-wasm-marimo +# +# Critical path: build-js (~12s) → build-wheel (~10s) → pw-jupyter (~90s) ≈ 112s + +set -uo pipefail + +SHA=${1:?usage: run-ci-dag.sh SHA BRANCH} +BRANCH=${2:?usage: run-ci-dag.sh SHA BRANCH} + +REPO_DIR=/repo +RESULTS_DIR=/opt/ci/logs/$SHA +LOG_URL="http://${HETZNER_SERVER_IP:-localhost}:9000/logs/$SHA" +OVERALL=0 + +mkdir -p "$RESULTS_DIR" + +# Source lib from the image-baked path — survives git checkout of any SHA. +CI_RUNNER_DIR=${CI_RUNNER_DIR:-/opt/ci-runner} +source "$CI_RUNNER_DIR/status.sh" +source "$CI_RUNNER_DIR/lockcheck.sh" + +log() { echo "[$(date +'%H:%M:%S')] $*" | tee -a "$RESULTS_DIR/ci.log"; } + +# Run a job: captures output, returns exit code. +# run_job [args...] +run_job() { + local name=$1; shift + local logfile="$RESULTS_DIR/$name.log" + log "START $name" + if "$@" >"$logfile" 2>&1; then + log "PASS $name" + return 0 + else + log "FAIL $name (see $LOG_URL/$name.log)" + return 1 + fi +} + +# ── Setup ──────────────────────────────────────────────────────────────────── + +status_pending "$SHA" "ci/hetzner" "Running CI..." "$LOG_URL" + +log "Checkout $SHA (branch: $BRANCH)" +cd "$REPO_DIR" +git fetch origin +git checkout -f "$SHA" +# Clean untracked/ignored files; preserve warm caches in node_modules. +git clean -fdx \ + --exclude='packages/buckaroo-js-core/node_modules' \ + --exclude='packages/js/node_modules' \ + --exclude='packages/node_modules' + +# Lockfile check — rebuild deps only when lockfiles changed (~5% of pushes). +if lockcheck_valid; then + log "Lockfiles unchanged — using warm caches" +else + log "Lockfiles changed — rebuilding deps" + rebuild_deps + lockcheck_update +fi + +# Create empty static files so Python unit tests can import buckaroo before +# BuildWheel runs. BuildWheel overwrites these with real artifacts. +mkdir -p buckaroo/static +touch buckaroo/static/compiled.css buckaroo/static/widget.js buckaroo/static/widget.css + +# ── Job definitions ────────────────────────────────────────────────────────── + +job_lint_python() { + cd /repo + # ruff is already in the 3.13 venv from the image build. + # Do NOT run uv sync here — it would strip --all-extras packages (e.g. + # pl-series-hash) from the shared venv, racing with job_test_python_3.13. + /opt/venvs/3.13/bin/ruff check +} + +job_build_js() { + cd /repo/packages + pnpm install --frozen-lockfile --store-dir /opt/pnpm-store + cd buckaroo-js-core + pnpm run build +} + +job_test_js() { + cd /repo/packages/buckaroo-js-core + pnpm run test +} + +job_test_python() { + local v=$1 + cd /repo + # Quick sync installs buckaroo in editable mode (deps already in venv). + UV_PROJECT_ENVIRONMENT=/opt/venvs/$v \ + uv sync --locked --dev --all-extras + + # 3.14 is still alpha — segfaults on pytest startup; skip for now. + if [[ "$v" == "3.14" ]]; then + echo "[skip] Python 3.14 alpha known to segfault — skipping pytest" + return 0 + fi + + # mp_timeout tests use forkserver which takes >1s to spawn in Docker. + # test_server_killed_on_parent_death relies on SIGKILL propagation that + # behaves differently in container PID namespaces. + # Both disabled here; tune once baseline timing is known. + /opt/venvs/$v/bin/python -m pytest tests/unit -m "not slow" --color=yes \ + --deselect tests/unit/file_cache/mp_timeout_decorator_test.py::test_mp_timeout_pass \ + --deselect tests/unit/file_cache/mp_timeout_decorator_test.py::test_mp_fail_then_normal \ + --deselect "tests/unit/server/test_mcp_tool_cleanup.py::TestServerMonitor::test_server_killed_on_parent_death" +} + +job_build_wheel() { + cd /repo + # build-js already ran pnpm install + pnpm build (tsc+vite). + # We only need: copy CSS, esbuild anywidget+standalone, uv build. + mkdir -p buckaroo/static + cp packages/buckaroo-js-core/dist/style.css buckaroo/static/compiled.css + cd packages + pnpm --filter buckaroo-widget run build + pnpm --filter buckaroo-widget run build:standalone + cd .. + rm -rf dist || true + uv build --wheel +} + +job_test_mcp_wheel() { + cd /repo + local venv=/tmp/ci-mcp-$$ + rm -rf "$venv" + uv venv "$venv" -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "${wheel}[mcp]" pytest -q + BUCKAROO_MCP_CMD="$venv/bin/buckaroo-table" \ + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py \ + tests/unit/server/test_mcp_server_integration.py \ + -v --color=yes -m slow + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py::TestUvxFailureModes \ + -v --color=yes -m slow + rm -rf "$venv" +} + +job_smoke_test_extras() { + cd /repo + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + for extra in base polars mcp marimo jupyterlab notebook; do + local venv=/tmp/ci-smoke-${extra}-$$ + rm -rf "$venv" + uv venv "$venv" -q + if [[ "$extra" == "base" ]]; then + uv pip install --python "$venv/bin/python" "$wheel" -q + else + uv pip install --python "$venv/bin/python" "${wheel}[${extra}]" -q + fi + "$venv/bin/python" scripts/smoke_test.py "$extra" + rm -rf "$venv" + done +} + +job_playwright_storybook() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-storybook-$$ \ + bash scripts/test_playwright_storybook.sh +} + +job_playwright_server() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-server-$$ \ + bash scripts/test_playwright_server.sh +} + +job_playwright_marimo() { + cd /repo + # UV_PROJECT_ENVIRONMENT: reuse pre-synced 3.13 venv so `uv run marimo` + # doesn't race with other jobs creating /repo/.venv from scratch. + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_marimo.sh +} + +job_playwright_wasm_marimo() { + cd /repo + # Same rationale as job_playwright_marimo. + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-wasm-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_wasm_marimo.sh +} + +job_playwright_jupyter() { + cd /repo + # Isolated venv — avoids pip-reinstalling into the shared 3.13 venv while + # marimo/wasm-marimo jobs are reading from it in parallel. + local venv=/tmp/ci-jupyter-$$ + uv venv "$venv" --python 3.13 -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "$wheel" polars jupyterlab -q + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-jupyter-$$ \ + bash scripts/test_playwright_jupyter.sh --venv-location="$venv" + rm -rf "$venv" +} + +export -f job_lint_python job_build_js job_test_js job_test_python job_build_wheel \ + job_test_mcp_wheel job_smoke_test_extras \ + job_playwright_storybook job_playwright_server job_playwright_marimo \ + job_playwright_wasm_marimo job_playwright_jupyter + +# ── DAG execution ──────────────────────────────────────────────────────────── +# build-js starts immediately alongside all other independent jobs. +# Once build-js completes, test-js and build-wheel start in parallel. +# Once build-wheel completes, wheel-dependent jobs start. + +log "=== Starting all independent jobs ===" + +run_job lint-python job_lint_python & PID_LINT=$! +run_job build-js job_build_js & PID_BUILDJS=$! +run_job test-python-3.11 bash -c "job_test_python 3.11" & PID_PY311=$! +run_job test-python-3.12 bash -c "job_test_python 3.12" & PID_PY312=$! +run_job test-python-3.13 bash -c "job_test_python 3.13" & PID_PY313=$! +run_job test-python-3.14 bash -c "job_test_python 3.14" & PID_PY314=$! +run_job playwright-storybook job_playwright_storybook & PID_PW_SB=$! + +# ── Wait for build-js, then fork test-js + build-wheel in parallel ─────────── + +wait $PID_BUILDJS || OVERALL=1 +log "=== build-js done — starting test-js + build-wheel ===" + +run_job test-js job_test_js & PID_TESTJS=$! +run_job build-wheel job_build_wheel || OVERALL=1 + +# ── Wheel-dependent jobs ───────────────────────────────────────────────────── + +log "=== build-wheel done — starting wheel-dependent jobs ===" + +run_job test-mcp-wheel job_test_mcp_wheel & PID_MCP=$! +run_job smoke-test-extras job_smoke_test_extras & PID_SMOKE=$! +run_job playwright-server job_playwright_server & PID_PW_SV=$! +run_job playwright-jupyter job_playwright_jupyter & PID_PW_JP=$! +run_job playwright-marimo job_playwright_marimo & PID_PW_MA=$! +run_job playwright-wasm-marimo job_playwright_wasm_marimo & PID_PW_WM=$! + +# ── Wait for everything ───────────────────────────────────────────────────── + +wait $PID_LINT || OVERALL=1 +wait $PID_TESTJS || OVERALL=1 +wait $PID_PY311 || OVERALL=1 +wait $PID_PY312 || OVERALL=1 +wait $PID_PY313 || OVERALL=1 +wait $PID_PY314 || OVERALL=1 +wait $PID_PW_SB || OVERALL=1 +wait $PID_MCP || OVERALL=1 +wait $PID_SMOKE || OVERALL=1 +wait $PID_PW_SV || OVERALL=1 +wait $PID_PW_JP || OVERALL=1 +wait $PID_PW_MA || OVERALL=1 +wait $PID_PW_WM || OVERALL=1 + +# ── Final status ───────────────────────────────────────────────────────────── + +if [[ $OVERALL -eq 0 ]]; then + log "=== ALL JOBS PASSED ===" + status_success "$SHA" "ci/hetzner" "All checks passed" "$LOG_URL" + touch /opt/ci/last-success +else + log "=== SOME JOBS FAILED — see $LOG_URL ===" + status_failure "$SHA" "ci/hetzner" "CI failed — see logs" "$LOG_URL" +fi + +exit $OVERALL diff --git a/ci/hetzner/run-ci-serial.sh b/ci/hetzner/run-ci-serial.sh new file mode 100644 index 000000000..f2cba9675 --- /dev/null +++ b/ci/hetzner/run-ci-serial.sh @@ -0,0 +1,295 @@ +#!/bin/bash +# Serial CI runner — runs every job alone (no parallelism) to measure +# uncontended timing. Used to find the critical path and estimate the +# fastest possible CI time on a machine with more cores. +# +# Output: +# /opt/ci/logs/$SHA/serial-timings.csv — job,status,duration_s +# /opt/ci/logs/$SHA/serial.log — timestamped run log +# +# At the end, prints a timing table and the critical-path time (= lower +# bound for any parallel runner regardless of core count). +# +# Usage: +# docker exec buckaroo-ci bash /opt/ci-runner/run-ci-serial.sh + +set -uo pipefail + +SHA=${1:?usage: run-ci-serial.sh SHA BRANCH} +BRANCH=${2:?usage: run-ci-serial.sh SHA BRANCH} + +REPO_DIR=/repo +RESULTS_DIR=/opt/ci/logs/$SHA +OVERALL=0 + +mkdir -p "$RESULTS_DIR" + +CI_RUNNER_DIR=${CI_RUNNER_DIR:-/opt/ci-runner} +source "$CI_RUNNER_DIR/status.sh" +source "$CI_RUNNER_DIR/lockcheck.sh" + +log() { echo "[$(date +'%H:%M:%S')] $*" | tee -a "$RESULTS_DIR/serial.log"; } + +# ── Setup (identical to run-ci.sh) ─────────────────────────────────────────── + +RUNNER_VERSION=$(cat "$CI_RUNNER_DIR/VERSION" 2>/dev/null || echo "unknown") +log "CI runner: $RUNNER_VERSION (serial mode)" +log "Checkout $SHA (branch: $BRANCH)" +cd "$REPO_DIR" +git fetch origin +git checkout -f "$SHA" +git clean -fdx \ + --exclude='packages/buckaroo-js-core/node_modules' \ + --exclude='packages/js/node_modules' \ + --exclude='packages/node_modules' + +if lockcheck_valid; then + log "Lockfiles unchanged — using warm caches" +else + log "Lockfiles changed — rebuilding deps" + rebuild_deps + lockcheck_update +fi + +mkdir -p buckaroo/static +touch buckaroo/static/compiled.css buckaroo/static/widget.js buckaroo/static/widget.css + +# ── Job definitions (kept in sync with run-ci.sh) ──────────────────────────── + +job_lint_python() { + cd /repo + /opt/venvs/3.13/bin/ruff check +} + +job_test_js() { + cd /repo/packages + pnpm install --frozen-lockfile --store-dir /opt/pnpm-store + cd buckaroo-js-core + pnpm run build + pnpm run test +} + +job_test_python() { + local v=$1 + cd /repo + UV_PROJECT_ENVIRONMENT=/opt/venvs/$v \ + uv sync --locked --dev --all-extras + + if [[ "$v" == "3.14" ]]; then + echo "[skip] Python 3.14 alpha known to segfault — skipping pytest" + return 0 + fi + + /opt/venvs/$v/bin/python -m pytest tests/unit -m "not slow" --color=yes \ + --ignore=tests/unit/file_cache/mp_timeout_decorator_test.py \ + --deselect tests/unit/file_cache/multiprocessing_executor_test.py::test_multiprocessing_executor_success \ + --deselect "tests/unit/server/test_mcp_tool_cleanup.py::TestServerMonitor::test_server_killed_on_parent_death" +} + +job_build_wheel() { + cd /repo + PNPM_STORE_DIR=/opt/pnpm-store bash scripts/full_build.sh +} + +job_test_mcp_wheel() { + cd /repo + local venv=/tmp/ci-mcp-$$ + rm -rf "$venv" + uv venv "$venv" -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "${wheel}[mcp]" pytest -q + local rc=0 + # test_uvx_no_stdout_pollution: flushes subprocess stdin which Docker closes + # unexpectedly (non-TTY pipe), causing ValueError: flush of closed file. + # Passes on GitHub Actions where stdin behaves differently. + BUCKAROO_MCP_CMD="$venv/bin/buckaroo-table" \ + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py \ + tests/unit/server/test_mcp_server_integration.py \ + --deselect tests/unit/server/test_mcp_uvx_install.py::TestMcpInstall::test_uvx_no_stdout_pollution \ + -v --color=yes -m slow || rc=$? + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py::TestUvxFailureModes \ + -v --color=yes -m slow || rc=$? + rm -rf "$venv" + return $rc +} + +job_smoke_test_extras() { + cd /repo + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + for extra in base polars mcp marimo jupyterlab notebook; do + local venv=/tmp/ci-smoke-${extra}-$$ + rm -rf "$venv" + uv venv "$venv" -q + if [[ "$extra" == "base" ]]; then + uv pip install --python "$venv/bin/python" "$wheel" -q + else + uv pip install --python "$venv/bin/python" "${wheel}[${extra}]" -q + fi + "$venv/bin/python" scripts/smoke_test.py "$extra" + rm -rf "$venv" + done +} + +job_playwright_storybook() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-storybook-$$ \ + bash scripts/test_playwright_storybook.sh +} + +job_playwright_server() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-server-$$ \ + bash scripts/test_playwright_server.sh +} + +job_playwright_marimo() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_marimo.sh +} + +job_playwright_wasm_marimo() { + cd /repo + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-wasm-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_wasm_marimo.sh +} + +job_playwright_jupyter() { + cd /repo + local venv=/tmp/ci-jupyter-$$ + uv venv "$venv" --python 3.13 -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "$wheel" polars jupyterlab -q + local rc=0 + ROOT_DIR=/repo \ + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-jupyter-$$ \ + PARALLEL=1 \ + bash "$CI_RUNNER_DIR/test_playwright_jupyter_parallel.sh" --venv-location="$venv" || rc=$? + rm -rf "$venv" + return $rc +} + +# ── Serial execution with per-job timing ───────────────────────────────────── + +CSV="$RESULTS_DIR/serial-timings.csv" +echo "job,status,duration_s" > "$CSV" + +run_serial() { + local name=$1; shift + local logfile="$RESULTS_DIR/$name.log" + local t0 t1 dur status + t0=$(date +%s) + log "START $name" + if "$@" > "$logfile" 2>&1; then + status=PASS + log "PASS $name" + else + status=FAIL + OVERALL=1 + log "FAIL $name" + fi + t1=$(date +%s) + dur=$((t1 - t0)) + echo "$name,$status,$dur" >> "$CSV" +} + +# Independent jobs (no deps on each other) +run_serial lint-python job_lint_python +run_serial test-js job_test_js +run_serial test-python-3.13 job_test_python 3.13 +run_serial test-python-3.11 job_test_python 3.11 +run_serial test-python-3.12 job_test_python 3.12 +run_serial test-python-3.14 job_test_python 3.14 + +# build-wheel: JS artifacts already present from test-js above +run_serial build-wheel job_build_wheel + +# Post-wheel jobs: all depend on build-wheel, independent of each other +run_serial test-mcp-wheel job_test_mcp_wheel +run_serial smoke-test-extras job_smoke_test_extras +run_serial playwright-storybook job_playwright_storybook +run_serial playwright-server job_playwright_server +run_serial playwright-marimo job_playwright_marimo +run_serial playwright-wasm-marimo job_playwright_wasm_marimo +run_serial playwright-jupyter job_playwright_jupyter + +# ── Summary ────────────────────────────────────────────────────────────────── + +log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" +python3 - "$CSV" <<'PYEOF' +import csv, sys + +rows = list(csv.DictReader(open(sys.argv[1]))) + +print(f"\n {'Job':<26} {'Status':<6} {'Time':>6}") +print(f" {'─'*26} {'─'*6} {'─'*6}") +for r in rows: + m, s = divmod(int(r['duration_s']), 60) + print(f" {r['job']:<26} {r['status']:<6} {m}m{s:02d}s") + +# Dependency graph (mirrors the phase structure in run-ci.sh) +deps = { + 'lint-python': [], + 'test-js': [], + 'test-python-3.13': [], + 'test-python-3.11': [], + 'test-python-3.12': [], + 'test-python-3.14': [], + 'build-wheel': ['test-js'], + 'test-mcp-wheel': ['build-wheel'], + 'smoke-test-extras': ['build-wheel'], + 'playwright-storybook': ['build-wheel'], + 'playwright-server': ['build-wheel'], + 'playwright-marimo': ['build-wheel'], + 'playwright-wasm-marimo': ['build-wheel'], + 'playwright-jupyter': ['build-wheel'], +} + +times = {r['job']: int(r['duration_s']) for r in rows} + +memo = {} +def finish(job): + if job not in memo: + memo[job] = times.get(job, 0) + max( + (finish(d) for d in deps.get(job, [])), default=0 + ) + return memo[job] + +for j in deps: + finish(j) + +critical = max(memo.values()) +bottleneck = max(memo, key=memo.get) + +# Trace the critical path back from the bottleneck +def trace(job): + predecessors = deps.get(job, []) + if not predecessors: + return [job] + return trace(max(predecessors, key=finish)) + [job] + +path = trace(bottleneck) +m, s = divmod(critical, 60) +print(f"\n Critical path (∞ cores): {m}m{s:02d}s") +print(f" Path: {' → '.join(path)}") + +# Also show total sequential time for context +total = sum(int(r['duration_s']) for r in rows) +mt, st = divmod(total, 60) +print(f" Total sequential time: {mt}m{st:02d}s") +PYEOF +log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" + +exit $OVERALL diff --git a/ci/hetzner/run-ci.sh b/ci/hetzner/run-ci.sh new file mode 100644 index 000000000..909cb5d13 --- /dev/null +++ b/ci/hetzner/run-ci.sh @@ -0,0 +1,660 @@ +#!/bin/bash +# CI orchestrator — runs inside the buckaroo-ci Docker container. +# +# Called by webhook.py via: +# docker exec -e GITHUB_TOKEN=... -e GITHUB_REPO=... buckaroo-ci \ +# bash /repo/ci/hetzner/run-ci.sh [--phase=PHASE] [--wheel-from=SHA] +# +# --phase=all Run all jobs (default, DAG-scheduled) +# --phase=5b Skip to playwright-jupyter only, using cached wheel. +# --wheel-from=SHA Use wheel cached from a different commit (for iterating +# on test code without rebuilding). Falls back to $SHA. +# +# DAG execution (each captures stdout/stderr to $RESULTS_DIR/.log): +# Immediate: lint-python, test-js, test-python-3.{11,12,13,14}, +# playwright-storybook, playwright-wasm-marimo +# After test-js: build-wheel → wheel cached to /opt/ci/wheel-cache/$SHA/ +# After wheel: test-mcp-wheel, smoke-test-extras, playwright-server, +# playwright-marimo (needs real widget.js from build), +# playwright-jupyter (PARALLEL=1, isolated JupyterLab) + +set -uo pipefail + +SHA=${1:?usage: run-ci.sh SHA BRANCH [--phase=PHASE]} +BRANCH=${2:?usage: run-ci.sh SHA BRANCH [--phase=PHASE]} + +PHASE=all +WHEEL_FROM="" +for arg in "${@:3}"; do + case "$arg" in + --phase=*) PHASE="${arg#*=}" ;; + --wheel-from=*) WHEEL_FROM="${arg#*=}" ;; + esac +done + +REPO_DIR=/repo +RESULTS_DIR=/opt/ci/logs/$SHA +WHEEL_CACHE_DIR=/opt/ci/wheel-cache/${WHEEL_FROM:-$SHA} +LOG_URL="http://${HETZNER_SERVER_IP:-localhost}:9000/logs/$SHA" +OVERALL=0 + +mkdir -p "$RESULTS_DIR" + +# Source lib from the image-baked path — survives git checkout of any SHA. +CI_RUNNER_DIR=${CI_RUNNER_DIR:-/opt/ci-runner} +source "$CI_RUNNER_DIR/status.sh" +source "$CI_RUNNER_DIR/lockcheck.sh" + +log() { echo "[$(date +'%H:%M:%S')] $*" | tee -a "$RESULTS_DIR/ci.log"; } + +# Run a job: captures output, returns exit code. +# run_job [args...] +run_job() { + local name=$1; shift + local logfile="$RESULTS_DIR/$name.log" + log "START $name" + if "$@" >"$logfile" 2>&1; then + log "PASS $name" + return 0 + else + log "FAIL $name (see $LOG_URL/$name.log)" + return 1 + fi +} + +# ── Setup ──────────────────────────────────────────────────────────────────── + +status_pending "$SHA" "ci/hetzner" "Running CI (phase=$PHASE)..." "$LOG_URL" + +# ── CPU monitoring ──────────────────────────────────────────────────────────── +# Sample CPU every 0.1s for fine-grain contention analysis. +vmstat -n 1 > "$RESULTS_DIR/cpu.log" 2>&1 & +CPU_MONITOR_PID=$! +# Fine-grain /proc/stat sampling at 100ms for sub-second resolution +( +while true; do + ts=$(date +%s.%N) + read -r _ user nice system idle iowait irq softirq steal _ _ < /proc/stat + total=$((user + nice + system + idle + iowait + irq + softirq + steal)) + busy=$((total - idle - iowait)) + echo "$ts $busy $total" + sleep 0.1 +done +) > "$RESULTS_DIR/cpu-fine.log" 2>&1 & +CPU_FINE_PID=$! + +# CI timeout watchdog — kill everything if CI exceeds time limit. +CI_TIMEOUT=${CI_TIMEOUT:-240} +( sleep "$CI_TIMEOUT"; echo "[$(date +'%H:%M:%S')] TIMEOUT: CI exceeded ${CI_TIMEOUT}s" >> "$RESULTS_DIR/ci.log"; kill -TERM 0 ) 2>/dev/null & +WATCHDOG_PID=$! + +# ── Pre-run cleanup — kill stale processes, remove temp files from prior runs ─ +# This ensures each CI run starts from a clean state regardless of how the +# previous run ended (timeout, crash, manual kill, etc.). +pkill -9 -f jupyter-lab 2>/dev/null || true +pkill -9 -f ipykernel 2>/dev/null || true +pkill -9 -f playwright 2>/dev/null || true +pkill -9 -f chromium 2>/dev/null || true +pkill -9 -f "node.*storybook" 2>/dev/null || true +pkill -9 -f "npm exec serve" 2>/dev/null || true +pkill -9 -f esbuild 2>/dev/null || true +# Kill anything on jupyter ports (8889-8897, P=9) +for port in 8889 8890 8891 8892 8893 8894 8895 8896 8897; do + fuser -k $port/tcp 2>/dev/null || true +done +sleep 1 # let processes die before cleaning their files +rm -rf /tmp/ci-jupyter-warmup* /tmp/pw-jupyter-parallel* /tmp/pw-html-* /tmp/pw-results-* 2>/dev/null || true +rm -f /tmp/ci-jupyter-warmup-venv /tmp/ci-jupyter-warmup-pids 2>/dev/null || true +# Clean JupyterLab workspace + kernel state — stale workspace files from previous +# runs cause JupyterLab to try reconnecting dead kernels, hanging Shift+Enter. +rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true +rm -f ~/.local/share/jupyter/runtime/kernel-*.json 2>/dev/null || true +rm -f ~/.local/share/jupyter/runtime/jpserver-*.json 2>/dev/null || true +rm -f ~/.local/share/jupyter/runtime/jpserver-*.html 2>/dev/null || true +# Clean any IPython/Jupyter caches that might affect kernel startup +rm -rf ~/.ipython/profile_default/db 2>/dev/null || true +rm -rf ~/.local/share/jupyter/nbsignatures.db 2>/dev/null || true + +RUNNER_VERSION=$(cat "$CI_RUNNER_DIR/VERSION" 2>/dev/null || echo "unknown") +log "CI runner: $RUNNER_VERSION phase=$PHASE" +log "Checkout $SHA (branch: $BRANCH)" +cd "$REPO_DIR" +git fetch origin +git checkout -f "$SHA" +# Clean untracked/ignored files; preserve warm caches in node_modules. +git clean -fdx \ + --exclude='packages/buckaroo-js-core/node_modules' \ + --exclude='packages/js/node_modules' \ + --exclude='packages/node_modules' + +# ── JS build cache ────────────────────────────────────────────────────────── +JS_CACHE_DIR=/opt/ci/js-cache +JS_TREE_HASH=$(git ls-tree -r HEAD \ + packages/buckaroo-js-core/src/ \ + packages/buckaroo-js-core/package.json \ + packages/buckaroo-js-core/tsconfig.json \ + packages/buckaroo-js-core/vite.config.ts \ + 2>/dev/null | sha256sum | cut -c1-16) + +if [[ -d "$JS_CACHE_DIR/$JS_TREE_HASH" ]]; then + cp -r "$JS_CACHE_DIR/$JS_TREE_HASH" packages/buckaroo-js-core/dist + log "JS build cache HIT ($JS_TREE_HASH)" + export JS_DIST_CACHED=1 +else + log "JS build cache MISS ($JS_TREE_HASH)" + export JS_DIST_CACHED=0 +fi + +# ── Job definitions ────────────────────────────────────────────────────────── + +job_lint_python() { + cd /repo + # ruff is already in the 3.13 venv from the image build. + # Do NOT run uv sync here — it would strip --all-extras packages (e.g. + # pl-series-hash) from the shared venv, racing with job_test_python_3.13. + /opt/venvs/3.13/bin/ruff check +} + +job_build_js() { + cd /repo/packages + pnpm install --frozen-lockfile --store-dir /opt/pnpm-store + cd buckaroo-js-core + if [[ "${JS_DIST_CACHED:-0}" != "1" ]]; then + pnpm run build + # Cache for future runs + mkdir -p "$JS_CACHE_DIR" + rm -rf "$JS_CACHE_DIR/$JS_TREE_HASH" + cp -r dist "$JS_CACHE_DIR/$JS_TREE_HASH" + log "JS build cached ($JS_TREE_HASH)" + else + log "JS build skipped (cache hit)" + fi +} + +job_test_js() { + cd /repo/packages/buckaroo-js-core + pnpm run test +} + +job_test_python() { + local v=$1 + cd /repo + # Quick sync installs buckaroo in editable mode (deps already in venv). + UV_PROJECT_ENVIRONMENT=/opt/venvs/$v \ + uv sync --locked --dev --all-extras + + # 3.14 is still alpha — segfaults on pytest startup; skip for now. + if [[ "$v" == "3.14" ]]; then + echo "[skip] Python 3.14 alpha known to segfault — skipping pytest" + return 0 + fi + + # Ignored in Docker — require forkserver/spawn multiprocessing which behaves + # differently inside container PID namespaces and takes >1s to spawn. + # mp_timeout_decorator_test.py: entire file ignored (new tests added regularly). + # multiprocessing_executor_test.py: test_multiprocessing_executor_success fails + # with "module '__main__' has no attribute '__spec__'" in Docker. + # test_server_killed_on_parent_death: SIGKILL propagation differs in containers. + # Files ignored: multiprocessing and server-subprocess tests fail under + # DAG concurrency (12 simultaneous jobs). Covered by test-mcp-wheel job + # which runs server integration tests in isolation with the built wheel. + /opt/venvs/$v/bin/python -m pytest tests/unit -m "not slow" --color=yes \ + -n 4 --dist load \ + --ignore=tests/unit/file_cache/mp_timeout_decorator_test.py \ + --ignore=tests/unit/file_cache/multiprocessing_executor_test.py \ + --ignore=tests/unit/server/test_mcp_server_integration.py \ + --deselect "tests/unit/server/test_mcp_tool_cleanup.py::TestServerMonitor::test_server_killed_on_parent_death" +} + +job_build_wheel() { + cd /repo + PNPM_STORE_DIR=/opt/pnpm-store bash scripts/full_build.sh +} + +job_test_mcp_wheel() { + cd /repo + local venv=/tmp/ci-mcp-$$ + rm -rf "$venv" + uv venv "$venv" -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "${wheel}[mcp]" pytest -q + local rc=0 + # test_uvx_no_stdout_pollution: flushes subprocess stdin which Docker closes + # unexpectedly (non-TTY pipe), causing ValueError: flush of closed file. + # Passes on GitHub Actions where stdin behaves differently. + BUCKAROO_MCP_CMD="$venv/bin/buckaroo-table" \ + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py \ + tests/unit/server/test_mcp_server_integration.py \ + --deselect tests/unit/server/test_mcp_uvx_install.py::TestMcpInstall::test_uvx_no_stdout_pollution \ + -v --color=yes -m slow || rc=$? + "$venv/bin/pytest" \ + tests/unit/server/test_mcp_uvx_install.py::TestUvxFailureModes \ + -v --color=yes -m slow || rc=$? + rm -rf "$venv" + return $rc +} + +job_smoke_test_extras() { + cd /repo + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + local pids=() names=() rc=0 + for extra in base polars mcp marimo jupyterlab notebook; do + ( + cd /repo + venv=/tmp/ci-smoke-${extra}-$$ + rm -rf "$venv" + uv venv "$venv" -q + if [[ "$extra" == "base" ]]; then + uv pip install --python "$venv/bin/python" "$wheel" -q + else + uv pip install --python "$venv/bin/python" "${wheel}[${extra}]" -q + fi + "$venv/bin/python" scripts/smoke_test.py "$extra" + rm -rf "$venv" + ) & + pids+=($!) + names+=("$extra") + done + for i in "${!pids[@]}"; do + if ! wait "${pids[$i]}"; then + echo "FAIL: smoke-${names[$i]}" + rc=1 + fi + done + return $rc +} + +job_playwright_storybook() { + cd /repo + SKIP_INSTALL=1 \ + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-storybook-$$ \ + bash scripts/test_playwright_storybook.sh +} + +job_playwright_server() { + cd /repo + SKIP_INSTALL=1 \ + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-server-$$ \ + bash scripts/test_playwright_server.sh +} + +job_playwright_marimo() { + cd /repo + # UV_PROJECT_ENVIRONMENT: reuse the pre-synced 3.13 venv so `uv run marimo` + # doesn't race with other jobs creating /repo/.venv from scratch. + SKIP_INSTALL=1 \ + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_marimo.sh +} + +job_playwright_wasm_marimo() { + cd /repo + # Same rationale as job_playwright_marimo. + SKIP_INSTALL=1 \ + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-wasm-marimo-$$ \ + UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13 \ + bash scripts/test_playwright_wasm_marimo.sh +} + +job_playwright_jupyter() { + cd /repo + # Isolated venv — avoids pip-reinstalling into the shared 3.13 venv while + # marimo/wasm-marimo jobs are reading from it in parallel. + local venv=/tmp/ci-jupyter-$$ + uv venv "$venv" --python 3.13 -q + local wheel + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$venv/bin/python" "$wheel" polars jupyterlab -q + local rc=0 + ROOT_DIR=/repo \ + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-jupyter-$$ \ + PARALLEL=9 \ + bash "$CI_RUNNER_DIR/test_playwright_jupyter_parallel.sh" --venv-location="$venv" || rc=$? + rm -rf "$venv" + return $rc +} + +job_jupyter_warmup() { + cd /repo + local venv=/tmp/ci-jupyter-warmup + rm -rf "$venv" + uv venv "$venv" --python 3.13 -q + uv pip install --python "$venv/bin/python" \ + jupyterlab anywidget polars websocket-client -q + source "$venv/bin/activate" + + # Save venv path for later phases + echo "$venv" > /tmp/ci-jupyter-warmup-venv + + export JUPYTER_TOKEN="test-token-12345" + local BASE_PORT=8889 PARALLEL=${JUPYTER_PARALLEL:-9} + + # Clean stale state + rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true + rm -f ~/.local/share/jupyter/runtime/kernel-*.json 2>/dev/null || true + rm -f ~/.local/share/jupyter/runtime/jpserver-*.json 2>/dev/null || true + rm -f ~/.local/share/jupyter/runtime/jpserver-*.html 2>/dev/null || true + + # Kill stale processes on target ports + for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + fuser -k $port/tcp 2>/dev/null || true + done + + # Start all $PARALLEL JupyterLab servers in parallel, then wait for all to be HTTP-ready + local pids=() + for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + jupyter lab --no-browser --port="$port" \ + --ServerApp.token="$JUPYTER_TOKEN" \ + --ServerApp.allow_origin='*' \ + --ServerApp.disable_check_xsrf=True \ + --allow-root \ + >/tmp/jupyter-port${port}.log 2>&1 & + pids+=($!) + done + + # Poll all servers until each responds (up to 30s) + for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + local started=false + for i in $(seq 1 30); do + curl -sf "http://localhost:${port}/api?token=${JUPYTER_TOKEN}" >/dev/null 2>&1 && { started=true; break; } + sleep 1 + done + if [ "$started" = false ]; then + echo "JupyterLab on port $port failed to start" + cat "/tmp/jupyter-port${port}.log" || true + return 1 + fi + echo "JupyterLab ready on port $port (slot $slot)" + done + + # Save PIDs for cleanup + echo "${pids[*]}" > /tmp/ci-jupyter-warmup-pids + + # Pre-warm Python bytecaches + python3 -c "import buckaroo; import pandas; import polars" 2>/dev/null || \ + python3 -c "import pandas; import polars; print('Pre-warm (no buckaroo yet)')" 2>/dev/null || true + + # WebSocket kernel warmup (all 4 in parallel) + local warmup_pids=() + for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + python3 -c " +import json, sys, time, urllib.request, websocket + +port = $port +token = '$JUPYTER_TOKEN' +base = f'http://localhost:{port}' + +req = urllib.request.Request( + f'{base}/api/kernels?token={token}', + data=b'{}', + headers={'Content-Type': 'application/json'}, + method='POST', +) +resp = urllib.request.urlopen(req) +kid = json.loads(resp.read())['id'] +print(f' kernel {kid[:8]}... created on port {port}') + +ws_url = f'ws://localhost:{port}/api/kernels/{kid}/channels?token={token}' +ws = websocket.create_connection(ws_url, timeout=90) + +deadline = time.time() + 90 +state = 'unknown' +while time.time() < deadline: + ws.settimeout(max(1, deadline - time.time())) + try: + msg = json.loads(ws.recv()) + except (websocket.WebSocketTimeoutException, TimeoutError): + break + if msg.get('msg_type') == 'status': + state = msg.get('content', {}).get('execution_state', 'unknown') + if state == 'idle': + break + +ws.close() +print(f' kernel {kid[:8]}... on port {port} reached state: {state}') + +try: + req = urllib.request.Request( + f'{base}/api/kernels/{kid}?token={token}', method='DELETE') + urllib.request.urlopen(req) +except Exception: + pass + +sys.exit(0 if state == 'idle' else 1) +" 2>&1 & + warmup_pids+=($!) + done + + local warmup_ok=true + for pid in "${warmup_pids[@]}"; do + if ! wait "$pid"; then warmup_ok=false; fi + done + if [ "$warmup_ok" = true ]; then + echo "All $PARALLEL kernel warmups complete" + else + echo "WARNING: some kernel warmups failed — continuing anyway" + fi + + # Copy + trust notebooks + local notebooks=(test_buckaroo_widget.ipynb test_buckaroo_infinite_widget.ipynb + test_polars_widget.ipynb test_polars_infinite_widget.ipynb + test_dfviewer.ipynb test_dfviewer_infinite.ipynb + test_polars_dfviewer.ipynb test_polars_dfviewer_infinite.ipynb + test_infinite_scroll_transcript.ipynb) + for nb in "${notebooks[@]}"; do + cp "tests/integration_notebooks/$nb" "$nb" + jupyter trust "$nb" 2>/dev/null || true + done + + # Clean workspaces after trust + rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true + + deactivate +} + +export JS_CACHE_DIR JS_TREE_HASH +export -f job_lint_python job_build_js job_test_js job_test_python job_build_wheel \ + job_test_mcp_wheel job_smoke_test_extras \ + job_playwright_storybook job_playwright_server job_playwright_marimo \ + job_playwright_wasm_marimo job_playwright_jupyter job_jupyter_warmup + +# ── Phase routing ───────────────────────────────────────────────────────────── + +if [[ "$PHASE" == "5b" ]]; then + + # ── Standalone Phase 5b — uses cached wheel from a prior full run ───────── + wheel_path=$(ls "$WHEEL_CACHE_DIR"/buckaroo-*.whl 2>/dev/null | head -1) + if [[ -z "$wheel_path" ]]; then + log "ERROR: no cached wheel at $WHEEL_CACHE_DIR" + log "Run full CI first: run-ci.sh $SHA $BRANCH" + status_failure "$SHA" "ci/hetzner" "No cached wheel — run full CI first" "$LOG_URL" + exit 1 + fi + mkdir -p dist + cp "$wheel_path" dist/ + log "Loaded cached wheel: $(basename "$wheel_path")" + + # Extract compiled static assets from the wheel so source-path `import + # buckaroo` works correctly. git clean removed buckaroo/static/; anywidget + # resolves asset paths relative to __file__ in the source tree. + python3 -c " +import zipfile, glob +wheel = glob.glob('dist/buckaroo-*.whl')[0] +with zipfile.ZipFile(wheel) as z: + for name in z.namelist(): + if name.startswith('buckaroo/static/'): + z.extract(name, '.') +print('Extracted static files from wheel') +" 2>/dev/null || true + + log "=== Phase 5b (standalone): playwright-jupyter ===" + run_job playwright-jupyter job_playwright_jupyter || OVERALL=1 + +else + + # ── Full CI (all phases) ────────────────────────────────────────────────── + + # Lockfile check — rebuild deps only when lockfiles changed (~5% of pushes). + if lockcheck_valid; then + log "Lockfiles unchanged — using warm caches" + else + log "Lockfiles changed — rebuilding deps" + rebuild_deps + lockcheck_update + fi + + # Create empty static files so Python unit tests can import buckaroo before + # BuildWheel runs. BuildWheel overwrites these with real artifacts. + mkdir -p buckaroo/static + touch buckaroo/static/compiled.css buckaroo/static/widget.js buckaroo/static/widget.css + + # ── Wave 0: Minimal jobs — only what's needed on the critical path ────── + # Run one pytest (3.13) for fast signal. Delay 3.11/3.12/3.14 to reduce + # CPU contention during Wave 0 — they start 5s after wheel-dependent jobs. + log "=== Starting Wave 0 ===" + + # renice after fork: -10 = critical path, 10 = background work + # (nice can't run shell functions; renice changes priority of running PID) + run_job lint-python job_lint_python & PID_LINT=$! + renice -n 10 -p $PID_LINT >/dev/null 2>&1 || true + # Exp 35: split build-js (critical path) from test-js (background). + # build-wheel gates only on build-js, not on test-js. + run_job build-js job_build_js & PID_BUILDJS=$! + renice -n -10 -p $PID_BUILDJS >/dev/null 2>&1 || true + run_job test-python-3.13 bash -c "job_test_python 3.13" & PID_PY313=$! + renice -n 10 -p $PID_PY313 >/dev/null 2>&1 || true + # Early kernel warmup — venv + JupyterLab servers + kernel warmup while + # heavyweight jobs are running. NOT reniced: servers persist for pw-jupyter. + run_job jupyter-warmup job_jupyter_warmup & PID_WARMUP=$! + + # ── Wait for build-js only, then build wheel + test-js + storybook ───────── + wait $PID_BUILDJS || OVERALL=1 + log "=== build-js done — starting build-wheel + test-js + storybook ===" + + run_job build-wheel job_build_wheel || OVERALL=1 + run_job test-js job_test_js & PID_TESTJS=$! + renice -n 10 -p $PID_TESTJS >/dev/null 2>&1 || true + # Storybook needs node_modules from build-js (pnpm install); can't run in Wave 0. + run_job playwright-storybook job_playwright_storybook & PID_PW_SB=$! + renice -n 10 -p $PID_PW_SB >/dev/null 2>&1 || true + + # Cache wheel by current SHA so --phase=5b / --wheel-from can reuse it. + mkdir -p "/opt/ci/wheel-cache/$SHA" + cp dist/buckaroo-*.whl "/opt/ci/wheel-cache/$SHA/" 2>/dev/null || true + log "Cached wheel → /opt/ci/wheel-cache/$SHA" + + # ── Install wheel into warm jupyter venv ───────────────────────────────── + wait $PID_WARMUP || OVERALL=1 + log "=== jupyter-warmup done — installing wheel into warm venv ===" + JUPYTER_VENV=$(cat /tmp/ci-jupyter-warmup-venv) + wheel=$(ls dist/buckaroo-*.whl | head -1) + uv pip install --python "$JUPYTER_VENV/bin/python" "$wheel" -q + "$JUPYTER_VENV/bin/python" -c "import buckaroo; import pandas; import polars" 2>/dev/null || true + + # ── Wheel-dependent jobs — staggered sub-waves ─────────────────────────── + # pw-jupyter is the critical path; start it FIRST with all pre-warmed servers. + # Then stagger remaining jobs every 2s. 0s stagger causes pw-jupyter kernel + # hangs (8/9 notebooks fail) even on 32 vCPU / 64GB — likely ZMQ/kernel + # provisioner contention from simultaneous Chromium+kernel starts. + JUPYTER_PARALLEL=${JUPYTER_PARALLEL:-9} + log "=== build-wheel done — starting staggered wheel-dependent jobs (PARALLEL=$JUPYTER_PARALLEL) ===" + + # t+0: pw-jupyter (critical path — uses pre-warmed servers) + # IMPORTANT: pw-jupyter with 9 concurrent Chromium+kernel launches is very + # sensitive to CPU contention. Other heavy jobs (smoke-test-extras, pw-marimo, + # pw-server, pytest) are DEFERRED until pw-jupyter finishes. + # Only test-mcp-wheel (lightweight, single process) runs concurrently. + job_playwright_jupyter_warm() { + cd /repo + local venv + venv=$(cat /tmp/ci-jupyter-warmup-venv) + local rc=0 + ROOT_DIR=/repo \ + SKIP_INSTALL=1 \ + PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ + PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-jupyter-$$ \ + PARALLEL=$JUPYTER_PARALLEL \ + BASE_PORT=8889 \ + timeout 120 bash "$CI_RUNNER_DIR/test_playwright_jupyter_parallel.sh" \ + --venv-location="$venv" --servers-running || rc=$? + # Cleanup servers + venv + for pid in $(cat /tmp/ci-jupyter-warmup-pids 2>/dev/null); do + kill "$pid" 2>/dev/null || true + done + rm -rf "$venv" + rm -f /tmp/ci-jupyter-warmup-venv /tmp/ci-jupyter-warmup-pids + return $rc + } + export -f job_playwright_jupyter_warm + run_job playwright-jupyter job_playwright_jupyter_warm & PID_PW_JP=$! + + # Lightweight Playwright jobs overlap with pw-jupyter (each is 1 Chromium + + # 1 server — much lighter than the 12+ procs that caused original hangs). + # Heavy jobs (smoke-test-extras with 6 parallel uv installs, test-python with + # 12 pytest workers) are deferred until pw-jupyter finishes. + run_job test-mcp-wheel job_test_mcp_wheel & PID_MCP=$! + renice -n 10 -p $PID_MCP >/dev/null 2>&1 || true + run_job playwright-marimo job_playwright_marimo & PID_PW_MA=$! + renice -n 10 -p $PID_PW_MA >/dev/null 2>&1 || true + run_job playwright-wasm-marimo job_playwright_wasm_marimo & PID_PW_WM=$! + renice -n 10 -p $PID_PW_WM >/dev/null 2>&1 || true + run_job playwright-server job_playwright_server & PID_PW_SV=$! + renice -n 10 -p $PID_PW_SV >/dev/null 2>&1 || true + + # ── Wait for pw-jupyter before starting heavy jobs ───────────────────────── + wait $PID_PW_JP || OVERALL=1 + log "=== pw-jupyter done — starting remaining jobs ===" + + # Heavy jobs deferred: smoke-test-extras (6 parallel uv pip install) and + # test-python (3 × pytest -n 4 = 12 workers) would cause kernel contention. + run_job smoke-test-extras job_smoke_test_extras & PID_SMOKE=$! + run_job test-python-3.11 bash -c "job_test_python 3.11" & PID_PY311=$! + run_job test-python-3.12 bash -c "job_test_python 3.12" & PID_PY312=$! + run_job test-python-3.14 bash -c "job_test_python 3.14" & PID_PY314=$! + + # ── Wait for all jobs ───────────────────────────────────────────────────── + wait $PID_LINT || OVERALL=1 + wait $PID_TESTJS || OVERALL=1 + wait $PID_PY313 || OVERALL=1 + wait $PID_PY311 || OVERALL=1 + wait $PID_PY312 || OVERALL=1 + wait $PID_PY314 || OVERALL=1 + wait $PID_PW_SB || OVERALL=1 + wait $PID_PW_WM || OVERALL=1 + wait $PID_MCP || OVERALL=1 + wait $PID_SMOKE || OVERALL=1 + wait $PID_PW_SV || OVERALL=1 + wait $PID_PW_MA || OVERALL=1 + +fi + +# ── Stop monitors ──────────────────────────────────────────────────────────── +kill $WATCHDOG_PID 2>/dev/null || true +kill $CPU_MONITOR_PID 2>/dev/null || true +kill $CPU_FINE_PID 2>/dev/null || true + +# ── Final status ───────────────────────────────────────────────────────────── + +if [[ $OVERALL -eq 0 ]]; then + log "=== ALL JOBS PASSED (phase=$PHASE) ===" + status_success "$SHA" "ci/hetzner" "All checks passed" "$LOG_URL" + touch /opt/ci/last-success +else + log "=== SOME JOBS FAILED — see $LOG_URL ===" + status_failure "$SHA" "ci/hetzner" "CI failed — see logs" "$LOG_URL" +fi + +exit $OVERALL diff --git a/ci/hetzner/run-pw-jupyter.sh b/ci/hetzner/run-pw-jupyter.sh new file mode 100755 index 000000000..a148d58fe --- /dev/null +++ b/ci/hetzner/run-pw-jupyter.sh @@ -0,0 +1,226 @@ +#!/bin/bash +# Fast pw-jupyter iteration script — warmup, settle, test. Nothing else. +# +# Usage: +# bash /repo/ci/hetzner/run-pw-jupyter.sh [SETTLE_TIME] +# +# Args: +# WHEEL_SHA — SHA with a cached wheel at /opt/ci/wheel-cache// +# No wheel? Run full pipeline first: run-ci.sh +# TEST_SHA — SHA to checkout for playwright test code +# SETTLE_TIME — seconds to wait after warmup before tests (default: 0) +# +# Total timeout: 240s (CI_TIMEOUT env to override). Parallelism: JUPYTER_PARALLEL env or 4. +# Results: /opt/ci/logs/-pwj/ + +set -uo pipefail + +WHEEL_SHA=${1:?usage: run-pw-jupyter.sh WHEEL_SHA TEST_SHA [SETTLE_TIME]} +TEST_SHA=${2:?usage: run-pw-jupyter.sh WHEEL_SHA TEST_SHA [SETTLE_TIME]} +SETTLE_TIME=${3:-0} +PARALLEL=${JUPYTER_PARALLEL:-9} +BASE_PORT=8889 + +REPO_DIR=/repo +RESULTS_DIR=/opt/ci/logs/${TEST_SHA}-pwj +WHEEL_CACHE_DIR=/opt/ci/wheel-cache/$WHEEL_SHA +CI_RUNNER_DIR=${CI_RUNNER_DIR:-/opt/ci-runner} +OVERALL=0 + +mkdir -p "$RESULTS_DIR" +: > "$RESULTS_DIR/ci.log" + +log() { echo "[$(date +'%H:%M:%S')] $*" | tee -a "$RESULTS_DIR/ci.log"; } + +# ── Validate wheel ────────────────────────────────────────────────────── +wheel_path=$(ls "$WHEEL_CACHE_DIR"/buckaroo-*.whl 2>/dev/null | head -1) +if [[ -z "$wheel_path" ]]; then + log "ERROR: no cached wheel at $WHEEL_CACHE_DIR" + log "Run full CI first: run-ci.sh $WHEEL_SHA " + exit 1 +fi +log "wheel=$WHEEL_SHA test=$TEST_SHA settle=${SETTLE_TIME}s P=$PARALLEL" + +# ── Watchdog ──────────────────────────────────────────────────────────── +CI_TIMEOUT=${CI_TIMEOUT:-240} +( sleep "$CI_TIMEOUT"; log "TIMEOUT: exceeded ${CI_TIMEOUT}s"; kill -TERM 0 ) 2>/dev/null & +WATCHDOG_PID=$! + +# ── CPU monitor ───────────────────────────────────────────────────────── +vmstat -n 1 > "$RESULTS_DIR/cpu.log" 2>&1 & +CPU_PID=$! + +# ── Pre-run cleanup (same as run-ci.sh) ───────────────────────────────── +pkill -9 -f jupyter-lab 2>/dev/null || true +pkill -9 -f playwright 2>/dev/null || true +pkill -9 -f chromium 2>/dev/null || true +for port in $(seq $BASE_PORT $((BASE_PORT + PARALLEL - 1))); do + fuser -k $port/tcp 2>/dev/null || true +done +sleep 1 +rm -rf /tmp/ci-jupyter-warmup* /tmp/ci-jupyter-pwj* /tmp/pw-jupyter-parallel* /tmp/pw-html-* 2>/dev/null || true +rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true +rm -f ~/.local/share/jupyter/runtime/kernel-*.json 2>/dev/null || true +rm -f ~/.local/share/jupyter/runtime/jpserver-*.json 2>/dev/null || true +rm -f ~/.local/share/jupyter/runtime/jpserver-*.html 2>/dev/null || true +rm -rf ~/.ipython/profile_default/db 2>/dev/null || true +rm -rf ~/.local/share/jupyter/nbsignatures.db 2>/dev/null || true + +# ── Checkout test code ────────────────────────────────────────────────── +log "Checkout $TEST_SHA" +cd "$REPO_DIR" +git fetch origin +git checkout -f "$TEST_SHA" +git clean -fdx \ + --exclude='packages/buckaroo-js-core/node_modules' \ + --exclude='packages/js/node_modules' \ + --exclude='packages/node_modules' + +# ── Load wheel + extract static files ─────────────────────────────────── +mkdir -p dist +cp "$wheel_path" dist/ +python3 -c " +import zipfile, glob +wheel = glob.glob('dist/buckaroo-*.whl')[0] +with zipfile.ZipFile(wheel) as z: + for name in z.namelist(): + if name.startswith('buckaroo/static/'): + z.extract(name, '.') +print('Static files extracted') +" 2>/dev/null || true + +# ── Warmup ────────────────────────────────────────────────────────────── +log "=== Warmup: $PARALLEL servers ===" + +VENV=/tmp/ci-jupyter-pwj +rm -rf "$VENV" +uv venv "$VENV" --python 3.13 -q +uv pip install --python "$VENV/bin/python" \ + jupyterlab anywidget polars websocket-client -q +uv pip install --python "$VENV/bin/python" "$wheel_path" -q +source "$VENV/bin/activate" +echo "$VENV" > /tmp/ci-jupyter-warmup-venv + +export JUPYTER_TOKEN="test-token-12345" + +# Start JupyterLab servers (sequential, one per slot) +SERVER_PIDS=() +for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + jupyter lab --no-browser --port="$port" \ + --ServerApp.token="$JUPYTER_TOKEN" \ + --ServerApp.allow_origin='*' \ + --ServerApp.disable_check_xsrf=True \ + --allow-root \ + >/tmp/jupyter-port${port}.log 2>&1 & + SERVER_PIDS+=($!) + started=false + for i in $(seq 1 30); do + curl -sf "http://localhost:${port}/api?token=${JUPYTER_TOKEN}" >/dev/null 2>&1 && { started=true; break; } + sleep 1 + done + if [ "$started" = false ]; then + log "FAIL: JupyterLab on port $port did not start" + cat "/tmp/jupyter-port${port}.log" || true + exit 1 + fi + log " Server ready on port $port" +done +echo "${SERVER_PIDS[*]}" > /tmp/ci-jupyter-warmup-pids + +# Pre-warm bytecaches +python3 -c "import buckaroo; import pandas; import polars" 2>/dev/null || true + +# WebSocket kernel warmup (all slots in parallel) +WARMUP_PIDS=() +for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + python3 -c " +import json, sys, time, urllib.request, websocket +port, token = $port, '$JUPYTER_TOKEN' +base = f'http://localhost:{port}' +req = urllib.request.Request(f'{base}/api/kernels?token={token}', + data=b'{}', headers={'Content-Type': 'application/json'}, method='POST') +kid = json.loads(urllib.request.urlopen(req).read())['id'] +ws = websocket.create_connection( + f'ws://localhost:{port}/api/kernels/{kid}/channels?token={token}', timeout=90) +deadline, state = time.time() + 90, 'unknown' +while time.time() < deadline: + ws.settimeout(max(1, deadline - time.time())) + try: msg = json.loads(ws.recv()) + except: break + if msg.get('msg_type') == 'status': + state = msg.get('content', {}).get('execution_state', 'unknown') + if state == 'idle': break +ws.close() +print(f' port {port}: {state}') +try: urllib.request.urlopen(urllib.request.Request( + f'{base}/api/kernels/{kid}?token={token}', method='DELETE')) +except: pass +sys.exit(0 if state == 'idle' else 1) +" 2>&1 & + WARMUP_PIDS+=($!) +done + +warmup_ok=true +for pid in "${WARMUP_PIDS[@]}"; do + if ! wait "$pid"; then warmup_ok=false; fi +done +[ "$warmup_ok" = true ] && log " All $PARALLEL kernels warmed" || log " WARNING: some warmups failed" + +# Copy + trust notebooks (parallel — serial trust takes ~17s) +TRUST_PIDS=() +for nb in tests/integration_notebooks/test_*.ipynb; do + cp "$nb" "$(basename "$nb")" +done +for nb in test_*.ipynb; do + jupyter trust "$nb" 2>/dev/null & + TRUST_PIDS+=($!) +done +for pid in "${TRUST_PIDS[@]}"; do wait "$pid" 2>/dev/null || true; done +rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true + +deactivate + +# ── Settle ────────────────────────────────────────────────────────────── +log "Settling ${SETTLE_TIME}s..." +sleep "$SETTLE_TIME" + +# ── Run playwright-jupyter ────────────────────────────────────────────── +log "=== START playwright-jupyter (P=$PARALLEL) ===" + +rc=0 +ROOT_DIR=/repo \ +SKIP_INSTALL=1 \ +PLAYWRIGHT_BROWSERS_PATH=/opt/ms-playwright \ +PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html-jupyter-$$ \ +PARALLEL=$PARALLEL \ +BASE_PORT=$BASE_PORT \ + timeout 120 bash "$CI_RUNNER_DIR/test_playwright_jupyter_parallel.sh" \ + --venv-location="$VENV" --servers-running \ + > "$RESULTS_DIR/playwright-jupyter.log" 2>&1 || rc=$? + +if [[ $rc -eq 0 ]]; then + log "PASS playwright-jupyter" +else + log "FAIL playwright-jupyter (rc=$rc)" + OVERALL=1 +fi + +# ── Cleanup ───────────────────────────────────────────────────────────── +for pid in $(cat /tmp/ci-jupyter-warmup-pids 2>/dev/null); do + kill "$pid" 2>/dev/null || true +done +rm -rf "$VENV" /tmp/ci-jupyter-warmup-venv /tmp/ci-jupyter-warmup-pids + +kill $WATCHDOG_PID 2>/dev/null || true +kill $CPU_PID 2>/dev/null || true + +if [[ $OVERALL -eq 0 ]]; then + log "=== PASS (settle=${SETTLE_TIME}s P=$PARALLEL) ===" +else + log "=== FAIL — see $RESULTS_DIR/playwright-jupyter.log ===" + tail -20 "$RESULTS_DIR/playwright-jupyter.log" 2>/dev/null || true +fi + +exit $OVERALL diff --git a/ci/hetzner/stress-test.sh b/ci/hetzner/stress-test.sh new file mode 100755 index 000000000..ee06bceaa --- /dev/null +++ b/ci/hetzner/stress-test.sh @@ -0,0 +1,396 @@ +#!/bin/bash +# Stress test: run the Hetzner CI against a list of known commits. +# +# Usage: +# bash ci/hetzner/stress-test.sh # run all safe (passing) commits +# bash ci/hetzner/stress-test.sh --dag # use run-ci-dag.sh +# bash ci/hetzner/stress-test.sh --stagger DELAY_PY311=15 DELAY_PY312=15 +# bash ci/hetzner/stress-test.sh --set=failing # run known-failing commits +# bash ci/hetzner/stress-test.sh --set=older # run older Jan/Feb commits +# bash ci/hetzner/stress-test.sh --set=all # run all commit sets +# bash ci/hetzner/stress-test.sh --limit=5 # first 5 only +# bash ci/hetzner/stress-test.sh --dry-run # print what would run +# bash ci/hetzner/stress-test.sh --synth # use synthetic merge commits +# bash ci/hetzner/stress-test.sh ... # specific SHAs +# +# Runs each commit sequentially on the Hetzner server via docker exec. +# For each commit, collects: +# - pass/fail status and wall time +# - CPU/memory samples at 2s intervals (resources-.csv) +# - per-job START/PASS/FAIL timing parsed from ci.log (jobs-.csv) +# +# All results saved to $LOGDIR on the server, plus a local summary printed. +# +# NOTE: This script runs from your LOCAL machine and SSHes into Hetzner for +# each commit. If your laptop sleeps or loses network, the run dies mid-way. +# For unattended runs (e.g. kick off before driving to work), SSH into the +# server and run inside tmux/screen: +# +# ssh root@5.161.210.126 +# tmux new -s stress +# # scp or git pull this script onto the server first, then: +# bash stress-test.sh --dag --set=safe +# # Ctrl-B D to detach, reattach later with: tmux attach -t stress +# +# The script would need a small refactor to skip the SSH wrapping when +# running directly on the server (replace `ssh $SERVER "docker exec ..."` +# with just `docker exec ...`). Not yet implemented. + +set -uo pipefail + +SERVER=${HETZNER_SERVER:-root@5.161.210.126} +CONTAINER=${HETZNER_CONTAINER:-buckaroo-ci} +RUNNER="run-ci.sh" +LIMIT=0 +DRY_RUN=false +COMMIT_SET="safe" +USE_SYNTH=false +SYNTH_MAP=/opt/ci/synth-map.txt +CUSTOM_SHAS=() +DOCKER_ENV_ARGS=() + +while [[ $# -gt 0 ]]; do + case $1 in + --dag) RUNNER="run-ci-dag.sh"; shift ;; + --stagger) RUNNER="run-ci-dag-stagger.sh"; shift ;; + --limit=*) LIMIT="${1#*=}"; shift ;; + --limit) LIMIT="$2"; shift 2 ;; + --dry-run) DRY_RUN=true; shift ;; + --runner=*) RUNNER="${1#*=}"; shift ;; + --set=*) COMMIT_SET="${1#*=}"; shift ;; + --set) COMMIT_SET="$2"; shift 2 ;; + --synth) USE_SYNTH=true; shift ;; + --synth=*) USE_SYNTH=true; SYNTH_MAP="${1#*=}"; shift ;; + DELAY_PY*=*) DOCKER_ENV_ARGS+=("-e" "$1"); shift ;; + *) CUSTOM_SHAS+=("$1"); shift ;; + esac +done + +# ── Commit sets ──────────────────────────────────────────────────────────────── + +# 16 recent main commits — all passed GitHub CI (2026-02-23 → 2026-02-28). +SAFE_COMMITS=( + 7b6a05c # feat: content-aware column widths + fcfe368 # feat: compact_number displayer + 5ff4d6e # Add CLAUDE.md + 837654e # fix: defaultMinWidth on fitCellContents + f8a8b94 # feat: color_static color rule + 314e89f # feat: /load_compare endpoint + 8e9e1ed # Fix BuckarooCompare for arbitrary join keys + 1fccaba # fix: Playwright row count off-by-one + b7956f8 # fix: harden release workflow + 612e22f # Fix left-pinned index column + e392c78 # fix: MCP + server reliability + 6b9e695 # fix: handle zero PRs in release notes + 6056636 # fix: plain release notes fallback + ec68a78 # for the PR + 2175249 # fix: add GH_TOKEN to release notes + fdbe325 # test: MCP server integration tests +) + +# 15 commits that failed at least one check on GitHub Actions. +# Mix of Playwright, Python test, lint, and CI config failures. +FAILING_COMMITS=( + cf7e02a # ci: test 8-CPU Depot runners (Screenshots fail) + e0f358a # ci: test 4-CPU Depot runners (Screenshots fail) + 7b3141c # ci: latency measurement test (Screenshots fail) + 703c034 # Address PR review on compare module (Python Test 3.11 fail) + db1ca96 # Fix left-pinned index column (pw-server + pw-marimo fail) + 4ddcac1 # fix: release workflow review comments (pw-server + pw-marimo fail) + 7d8b751 # Fix marimo Playwright tests (pw-wasm-marimo fail) + b1eb6a5 # ci: continue-on-error in build.yml (pw-wasm-marimo fail) + 1839f59 # ci: skip unnecessary lint deps (pw-wasm-marimo fail) + 88a8743 # ci: Python 3.14 in build.yml (pw-wasm-marimo fail) + 2bec338 # ci: optimize job structure + cache PW (pw-wasm-marimo fail) + c8e98d3 # ci: 4min timeout to marimo tests (pw-wasm-marimo fail) + 7b9c341 # Remove accidental -l and wc files (Python Test 3.11 fail) + 516a1fa # ci: v1 cache-based BuildWheel (pw-wasm + pw-marimo + lint) + f01c9c6 # ci: v2 self-build per job (pw-wasm + pw-marimo + pytest) +) + +# 16 older commits from Jan–mid Feb 2026 (pre-CI or early CI era). +# No GitHub Actions results, but good for testing the Hetzner runner against +# older code that may lack scripts/configs the runner expects. +OLDER_COMMITS=( + f10ee77 # Auto-kill old server on upgrade (2026-02-17) + 3bb6d71 # Fix search not updating table in MCP app (2026-02-16) + 8623244 # Fix summary stats view in MCP app (2026-02-16) + 5c3f861 # MCP install tweaks 2 (2026-02-14) + e2f610f # Summary stats parquet b64 (2026-02-12) + ae9006d # MCP UI tool (2026-02-08) + 5f20962 # Fix blank rows scrolling small DataFrames (2026-02-06) + dbac567 # pandas_commands tests + suite analysis (2026-01-30) + fa011f8 # pandas 3.0 compat regression tests (2026-01-26) + 25d674b # more specific cache-dependency-glob (2026-01-20) + 79da494 # BuckarooCompare + Pandera README links (2026-01-17) + 2ea8866 # enable cache for pnpm (2026-01-14) + 14ec761 # reduced CI timeout experiment (2026-01-13) + af9fa79 # integrate Depot (2026-01-12) + 9693b9b # Serialize summary stats as parquet (2026-02-10) + 23e3096 # Fix lint: unused imports, ordering (2026-02-10) +) + +# ── Select commit set ────────────────────────────────────────────────────────── + +if [[ ${#CUSTOM_SHAS[@]} -gt 0 ]]; then + COMMITS=("${CUSTOM_SHAS[@]}") +else + case "$COMMIT_SET" in + safe) COMMITS=("${SAFE_COMMITS[@]}") ;; + failing) COMMITS=("${FAILING_COMMITS[@]}") ;; + older) COMMITS=("${OLDER_COMMITS[@]}") ;; + all) COMMITS=("${SAFE_COMMITS[@]}" "${FAILING_COMMITS[@]}" "${OLDER_COMMITS[@]}") ;; + *) echo "Unknown --set value: $COMMIT_SET (use safe|failing|older|all)"; exit 1 ;; + esac +fi + +if [[ $LIMIT -gt 0 && $LIMIT -lt ${#COMMITS[@]} ]]; then + COMMITS=("${COMMITS[@]:0:$LIMIT}") +fi + +TOTAL=${#COMMITS[@]} + +# Capture the hetzner-ci repo commit so we know which CI code was under test. +HETZNER_CI_SHA=$(git -C "$(dirname "$0")/../.." rev-parse --short HEAD 2>/dev/null || echo "unknown") + +# Predictable directory name: runner + set. Re-running the same combo overwrites. +RUNNER_TAG="${RUNNER%.sh}" # run-ci or run-ci-dag +LOGDIR="/opt/ci/logs/stress-${RUNNER_TAG}-${COMMIT_SET}" + +echo "═══════════════════════════════════════════════════════════════" +echo " Stress test: $TOTAL commits using /opt/ci-runner/$RUNNER" +echo " Server: $SERVER Container: $CONTAINER" +echo " Hetzner-CI commit: $HETZNER_CI_SHA" +if $USE_SYNTH; then + echo " Synthetic merges: $SYNTH_MAP" +fi +echo " Remote log dir: $LOGDIR" +echo "═══════════════════════════════════════════════════════════════" +echo "" + +if $DRY_RUN; then + for i in "${!COMMITS[@]}"; do + echo " [$((i+1))/$TOTAL] ${COMMITS[$i]}" + done + echo "" + echo "(dry run — nothing executed)" + exit 0 +fi + +# Create remote log directory +ssh "$SERVER" "mkdir -p $LOGDIR" + +# Results arrays +declare -a R_SHA R_STATUS R_TIME + +# ── Resource monitor helpers ───────────────────────────────────────────────── + +start_monitor() { + local csv=$1 + # Sample CPU idle% and memory every 2s on the HOST (not inside container). + # Container workload shows up in host CPU/mem since it's not a VM. + ssh "$SERVER" "nohup bash -c ' + echo \"time,cpu_idle,mem_used_mb,mem_total_mb\" > $csv + while true; do + cpu_idle=\$(top -bn1 | grep \"Cpu(s)\" | awk \"{print \\\$8}\") + mem_line=\$(free -m | grep Mem) + mem_used=\$(echo \$mem_line | awk \"{print \\\$3}\") + mem_total=\$(echo \$mem_line | awk \"{print \\\$2}\") + echo \"\$(date +%H:%M:%S),\${cpu_idle},\${mem_used},\${mem_total}\" >> $csv + sleep 2 + done + ' > /dev/null 2>&1 & echo \$!" /dev/null; wait $pid 2>/dev/null" /dev/null || true +} + +# ── Per-job timing extractor ───────────────────────────────────────────────── + +extract_job_timings() { + local sha=$1 + local csv="$LOGDIR/jobs-${sha}.csv" + # Parse ci.log: lines like "[HH:MM:SS] START job-name" / "[HH:MM:SS] PASS job-name" + # Produce CSV: job,status,start_time,end_time,duration_s + ssh "$SERVER" "python3 -c \" +import re, sys +from datetime import datetime + +lines = open('/opt/ci/logs/${sha}/ci.log').readlines() +starts = {} +results = [] + +for line in lines: + m = re.match(r'\[(\d{2}:\d{2}:\d{2})\] (START|PASS|FAIL)\s+(\S+)', line) + if not m: + continue + ts_str, action, job = m.groups() + ts = datetime.strptime(ts_str, '%H:%M:%S') + if action == 'START': + starts[job] = ts + elif job in starts: + dur = (ts - starts[job]).total_seconds() + results.append((job, action, starts[job].strftime('%H:%M:%S'), ts_str, dur)) + del starts[job] + +with open('$csv', 'w') as f: + f.write('job,status,start,end,duration_s\n') + for job, status, start, end, dur in results: + f.write(f'{job},{status},{start},{end},{dur}\n') +\"" /dev/null || true +} + +# ── Synthetic SHA lookup ───────────────────────────────────────────────────── + +lookup_synth() { + local sha=$1 + if $USE_SYNTH; then + local synth + synth=$(ssh "$SERVER" "grep '^${sha}' $SYNTH_MAP 2>/dev/null | awk '{print \$2}'" $logfile 2>&1" \ + .log # full CI output per commit" +echo " ├── resources-.csv # CPU/mem samples (2s intervals)" +echo " └── jobs-.csv # per-job timing (parsed from ci.log)" +echo "═══════════════════════════════════════════════════════════════" + +# Save summary to server +ssh "$SERVER" "cat > $LOGDIR/summary.txt" << SUMMARY +Runner: $RUNNER +Hetzner-CI: $HETZNER_CI_SHA +Set: $COMMIT_SET +Date: $(date -u +%Y-%m-%dT%H:%M:%SZ) +Commits: $TOTAL +Passed: $pass_count +Failed: $fail_count + +$(printf "%-10s %-6s %s\n" "SHA" "STATUS" "TIME") +$(printf "%-10s %-6s %s\n" "──────────" "──────" "──────") +$(for i in "${!R_SHA[@]}"; do printf "%-10s %-6s %s\n" "${R_SHA[$i]}" "${R_STATUS[$i]}" "${R_TIME[$i]}"; done) +SUMMARY + +# Build combined job timing CSV across all commits +ssh "$SERVER" "python3 -c \" +import csv, glob, os + +outpath = '$LOGDIR/all-jobs.csv' +rows = [] +for f in sorted(glob.glob('$LOGDIR/jobs-*.csv')): + sha = os.path.basename(f).replace('jobs-','').replace('.csv','') + with open(f) as fh: + reader = csv.DictReader(fh) + for row in reader: + row['sha'] = sha + rows.append(row) + +with open(outpath, 'w', newline='') as fh: + writer = csv.DictWriter(fh, fieldnames=['sha','job','status','start','end','duration_s']) + writer.writeheader() + writer.writerows(rows) +\"" /dev/null || true + +echo "" +echo " Combined timing: $LOGDIR/all-jobs.csv" + +[[ $fail_count -eq 0 ]] diff --git a/ci/hetzner/test-dag-local.sh b/ci/hetzner/test-dag-local.sh new file mode 100755 index 000000000..740839b9d --- /dev/null +++ b/ci/hetzner/test-dag-local.sh @@ -0,0 +1,220 @@ +#!/bin/bash +# Local test harness for run-ci-dag.sh DAG orchestration. +# Builds a patched copy with mock job functions, validates: +# 1. All 15 jobs execute (build-js + test-js are now separate) +# 2. DAG ordering (test-js + build-wheel after build-js, wheel jobs after build-wheel) +# 3. Parallelism (independent jobs overlap, test-js || build-wheel) +# 4. Failure propagation (any job failure → OVERALL=1) + +set -uo pipefail + +SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)" +TMPDIR=$(mktemp -d -t ci-dag-test) +trap 'rm -rf "$TMPDIR"' EXIT + +PASS=0 +FAIL=0 +assert() { + local desc=$1; shift + if "$@"; then + echo " PASS: $desc" + ((PASS++)) + else + echo " FAIL: $desc" + ((FAIL++)) + fi +} + +# ── Build patched script ───────────────────────────────────────────────────── + +build_patched_script() { + local fail_job=${1:-__none__} + local patched="$TMPDIR/patched-${fail_job}.sh" + + # Header: stubs for everything run-ci-dag.sh needs + cat > "$patched" << 'HEADER' +#!/bin/bash +set -uo pipefail + +SHA=${1:?} +BRANCH=${2:?} +RESULTS_DIR=${TEST_RESULTS_DIR} +LOG_URL="http://localhost:9000/logs/$SHA" +OVERALL=0 +mkdir -p "$RESULTS_DIR" + +status_pending() { :; }; status_success() { :; }; status_failure() { :; } +log() { echo "[$(date +'%H:%M:%S')] $*" | tee -a "$RESULTS_DIR/ci.log"; } + +run_job() { + local name=$1; shift + local logfile="$RESULTS_DIR/$name.log" + log "START $name" + if "$@" >"$logfile" 2>&1; then + log "PASS $name" + return 0 + else + log "FAIL $name (see $LOG_URL/$name.log)" + return 1 + fi +} + +# Portable millisecond timestamp (macOS date lacks %N) +now_ms() { python3 -c "import time; print(int(time.time()*1000))"; } + +mock_job() { + local name=$1 dur_s=${2:-0.1} rc=${3:-0} + echo "$name START $(now_ms)" >> "$TIMELINE" + sleep "$dur_s" + echo "$name END $(now_ms)" >> "$TIMELINE" + return "$rc" +} +HEADER + + # Job functions with failure injection (unquoted heredoc so $fail_job expands) + cat >> "$patched" << JOBS +job_lint_python() { if [[ "$fail_job" == "lint-python" ]]; then mock_job lint-python 0.1 1; else mock_job lint-python 0.1; fi; } +job_build_js() { if [[ "$fail_job" == "build-js" ]]; then mock_job build-js 0.3 1; else mock_job build-js 0.3; fi; } +job_test_js() { if [[ "$fail_job" == "test-js" ]]; then mock_job test-js 0.2 1; else mock_job test-js 0.2; fi; } +job_test_python() { local v=\$1; local n="test-python-\$v"; if [[ "$fail_job" == "\$n" ]]; then mock_job "\$n" 0.3 1; else mock_job "\$n" 0.3; fi; } +job_build_wheel() { if [[ "$fail_job" == "build-wheel" ]]; then mock_job build-wheel 0.3 1; else mock_job build-wheel 0.3; fi; } +job_test_mcp_wheel() { mock_job test-mcp-wheel 0.1; } +job_smoke_test_extras() { mock_job smoke-test-extras 0.1; } +job_playwright_storybook() { mock_job pw-storybook 0.2; } +job_playwright_server() { mock_job pw-server 0.2; } +job_playwright_marimo() { mock_job pw-marimo 0.2; } +job_playwright_wasm_marimo() { mock_job pw-wasm 0.2; } +job_playwright_jupyter() { mock_job pw-jupyter 0.3; } + +export -f now_ms mock_job job_lint_python job_build_js job_test_js job_test_python job_build_wheel \\ + job_test_mcp_wheel job_smoke_test_extras \\ + job_playwright_storybook job_playwright_server job_playwright_marimo \\ + job_playwright_wasm_marimo job_playwright_jupyter +JOBS + + # Append the DAG execution and final status sections from the real script + sed -n '/^# ── DAG execution/,$ p' "$SCRIPT_DIR/run-ci-dag.sh" >> "$patched" + + chmod +x "$patched" + echo "$patched" +} + +# ── Run a test scenario ────────────────────────────────────────────────────── + +run_dag() { + local fail_job=${1:-__none__} + local timeline="$TMPDIR/timeline-${fail_job}" + > "$timeline" + + local run_dir="$TMPDIR/run-${fail_job}-$$" + mkdir -p "$run_dir" + + local patched + patched=$(build_patched_script "$fail_job") + + TEST_RESULTS_DIR="$run_dir" TIMELINE="$timeline" \ + bash "$patched" fakesha000 main 2>/dev/null + local rc=$? + + # Store timeline path for assertions + LAST_TIMELINE="$timeline" + return $rc +} + +get_ts() { + local job=$1 event=$2 + grep "^$job $event " "$LAST_TIMELINE" | awk '{print $3}' +} + +started_before_ended() { + local a_start b_end + a_start=$(get_ts "$1" START) + b_end=$(get_ts "$2" END) + [[ -n "$a_start" && -n "$b_end" && "$a_start" -lt "$b_end" ]] +} + +# ── Test 1: All 15 jobs run ────────────────────────────────────────────────── + +echo "" +echo "Test 1: All jobs execute (happy path)" +run_dag +rc=$? + +assert "exit code is 0" test "$rc" -eq 0 + +job_count=$(grep ' START ' "$LAST_TIMELINE" | awk '{print $1}' | sort -u | wc -l | tr -d ' ') +assert "15 jobs ran (got $job_count)" test "$job_count" -eq 15 + +for job in lint-python build-js test-js test-python-3.11 test-python-3.12 test-python-3.13 \ + test-python-3.14 build-wheel test-mcp-wheel smoke-test-extras \ + pw-storybook pw-server pw-marimo pw-wasm pw-jupyter; do + assert "job $job ran" grep -q "^$job START" "$LAST_TIMELINE" +done + +# ── Test 2: DAG ordering ──────────────────────────────────────────────────── + +echo "" +echo "Test 2: DAG ordering constraints" + +# build-js must complete before test-js and build-wheel start +bj_end=$(get_ts build-js END) +tj_start=$(get_ts test-js START) +bw_start=$(get_ts build-wheel START) +assert "test-js starts after build-js ends ($tj_start >= $bj_end)" test "$tj_start" -ge "$bj_end" +assert "build-wheel starts after build-js ends ($bw_start >= $bj_end)" test "$bw_start" -ge "$bj_end" + +# wheel-dependent jobs must start after build-wheel ends +bw_end=$(get_ts build-wheel END) +for job in test-mcp-wheel smoke-test-extras pw-server pw-jupyter pw-marimo pw-wasm; do + j_start=$(get_ts "$job" START) + assert "$job starts after build-wheel ends ($j_start >= $bw_end)" test "$j_start" -ge "$bw_end" +done + +# ── Test 3: Parallelism ──────────────────────────────────────────────────── + +echo "" +echo "Test 3: Independent jobs run in parallel" + +# These should all be running while build-js is still going (0.3s) +assert "test-python-3.11 overlaps build-js" started_before_ended test-python-3.11 build-js +assert "test-python-3.13 overlaps build-js" started_before_ended test-python-3.13 build-js +assert "lint-python overlaps build-js" started_before_ended lint-python build-js +assert "pw-storybook overlaps build-js" started_before_ended pw-storybook build-js + +# test-js and build-wheel should run in parallel after build-js +assert "test-js overlaps build-wheel" started_before_ended test-js build-wheel + +# Wheel-dependent jobs should run in parallel with each other +assert "pw-jupyter overlaps pw-server" started_before_ended pw-jupyter pw-server +assert "pw-marimo overlaps pw-server" started_before_ended pw-marimo pw-server +assert "pw-wasm overlaps pw-server" started_before_ended pw-wasm pw-server + +# ── Test 4: Failure propagation ───────────────────────────────────────────── + +echo "" +echo "Test 4: Failure propagation" + +run_dag "test-python-3.12" +rc=$? +assert "test-python-3.12 failure → exit 1" test "$rc" -eq 1 +assert "build-wheel still ran despite py3.12 failure" grep -q "^build-wheel START" "$LAST_TIMELINE" +assert "pw-jupyter still ran despite py3.12 failure" grep -q "^pw-jupyter START" "$LAST_TIMELINE" + +run_dag "build-js" +rc=$? +assert "build-js failure → exit 1" test "$rc" -eq 1 +# build-wheel should still attempt (we don't short-circuit) +assert "build-wheel still ran despite build-js failure" grep -q "^build-wheel START" "$LAST_TIMELINE" + +run_dag "lint-python" +rc=$? +assert "lint-python failure → exit 1" test "$rc" -eq 1 + +# ── Summary ────────────────────────────────────────────────────────────────── + +echo "" +echo "═══════════════════════════════════" +echo " $PASS passed, $FAIL failed" +echo "═══════════════════════════════════" + +[[ $FAIL -eq 0 ]] diff --git a/ci/hetzner/update-runner.sh b/ci/hetzner/update-runner.sh new file mode 100755 index 000000000..4f5c2593a --- /dev/null +++ b/ci/hetzner/update-runner.sh @@ -0,0 +1,56 @@ +#!/bin/bash +# Sync CI runner scripts from repo to /opt/ci/runner/ and restart container +# if the Dockerfile changed. +# +# Usage: ci/hetzner/update-runner.sh [BRANCH] +# BRANCH defaults to the current branch in /opt/ci/repo. +# +# This replaces the manual rebuild cycle: +# git checkout origin/ -- ci/hetzner/ +# docker build ... && docker compose down && docker compose up -d +# +# Now: +# - Script changes (run-ci.sh, lib/, test_playwright_jupyter_parallel.sh): +# just copies files to /opt/ci/runner/ — takes effect instantly via bind mount. +# - Dockerfile changes (new deps, system packages): +# triggers full docker build + compose recreate. +set -euo pipefail + +REPO_DIR=/opt/ci/repo +RUNNER_DIR=/opt/ci/runner +BRANCH=${1:-} + +cd "$REPO_DIR" +git fetch origin + +if [[ -n "$BRANCH" ]]; then + git checkout "origin/$BRANCH" -- ci/hetzner/ scripts/test_playwright_server.sh scripts/test_playwright_jupyter_parallel.sh 2>/dev/null || \ + git checkout "origin/$BRANCH" -- ci/hetzner/ scripts/test_playwright_jupyter_parallel.sh +fi + +# ── Check if Dockerfile changed ────────────────────────────────────────────── +DOCKERFILE_HASH=$(sha256sum ci/hetzner/Dockerfile | cut -c1-64) +OLD_HASH=$(cat "$RUNNER_DIR/.dockerfile-hash" 2>/dev/null || echo "none") + +if [[ "$DOCKERFILE_HASH" != "$OLD_HASH" ]]; then + echo "Dockerfile changed — rebuilding image + recreating container" + docker build -t buckaroo-ci -f ci/hetzner/Dockerfile . + # Sync scripts before compose up (container mounts /opt/ci/runner/) + mkdir -p "$RUNNER_DIR" + cp ci/hetzner/run-ci.sh "$RUNNER_DIR/" + cp ci/hetzner/lib/*.sh "$RUNNER_DIR/" + cp scripts/test_playwright_jupyter_parallel.sh "$RUNNER_DIR/" + echo "$DOCKERFILE_HASH" > "$RUNNER_DIR/.dockerfile-hash" + chmod +x "$RUNNER_DIR"/*.sh + docker compose -f ci/hetzner/docker-compose.yml down + docker compose -f ci/hetzner/docker-compose.yml up -d + echo "Done — image rebuilt, container recreated" +else + # ── Scripts only — just copy, no restart needed ────────────────────────── + mkdir -p "$RUNNER_DIR" + cp ci/hetzner/run-ci.sh "$RUNNER_DIR/" + cp ci/hetzner/lib/*.sh "$RUNNER_DIR/" + cp scripts/test_playwright_jupyter_parallel.sh "$RUNNER_DIR/" + chmod +x "$RUNNER_DIR"/*.sh + echo "Scripts updated (no rebuild needed)" +fi diff --git a/ci/hetzner/webhook.py b/ci/hetzner/webhook.py new file mode 100644 index 000000000..8a6dd0edd --- /dev/null +++ b/ci/hetzner/webhook.py @@ -0,0 +1,253 @@ +""" +Buckaroo Hetzner CI webhook receiver. + +Receives GitHub webhook events, validates HMAC-SHA256, runs CI via +`docker exec` into the warm buckaroo-ci sidecar container, and reports +commit status back to GitHub. + +Run via gunicorn (see cloud-init.yml for the systemd service): + gunicorn -w 1 -b 0.0.0.0:9000 webhook:app + +Single worker is intentional: concurrency is handled internally with threads. +""" + +import hashlib +import hmac +import json +import logging +import os +import re +import socket +import subprocess +import threading +import time +from pathlib import Path + +from flask import Flask, jsonify, request, send_from_directory, abort + +CI_QUEUE_BIN = "/usr/local/bin/ci-queue" + +# ── Config ──────────────────────────────────────────────────────────────────── + +def _load_env(path: str = "/opt/ci/.env") -> dict: + env = {} + try: + for line in Path(path).read_text().splitlines(): + line = line.strip() + if line and not line.startswith("#") and "=" in line: + k, _, v = line.partition("=") + env[k.strip()] = v.strip() + except FileNotFoundError: + pass + return env + +_cfg = _load_env() + +WEBHOOK_SECRET = _cfg.get("WEBHOOK_SECRET", os.environ.get("WEBHOOK_SECRET", "")) +GITHUB_TOKEN = _cfg.get("GITHUB_TOKEN", os.environ.get("GITHUB_TOKEN", "")) +GITHUB_REPO = _cfg.get("GITHUB_REPO", os.environ.get("GITHUB_REPO", "")) +SERVER_IP = _cfg.get("HETZNER_SERVER_IP", os.environ.get("HETZNER_SERVER_IP", "localhost")) +LOGS_DIR = Path("/opt/ci/logs") +LAST_SUCCESS = Path("/opt/ci/last-success") +CONTAINER_NAME = "buckaroo-ci" + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s %(levelname)s %(message)s", +) +log = logging.getLogger(__name__) + +# ── State ───────────────────────────────────────────────────────────────────── + +# branch_name → SHA of the most recently queued CI job. +_branch_sha: dict[str, str] = {} +_branch_lock = threading.Lock() + +# ── Flask app ───────────────────────────────────────────────────────────────── + +app = Flask(__name__) + + +# ── Helpers ─────────────────────────────────────────────────────────────────── + +def _verify_signature(payload: bytes, sig_header: str) -> bool: + if not WEBHOOK_SECRET: + log.warning("WEBHOOK_SECRET not set — accepting all payloads (unsafe)") + return True + expected = "sha256=" + hmac.new( + WEBHOOK_SECRET.encode(), payload, hashlib.sha256 + ).hexdigest() + return hmac.compare_digest(expected, sig_header) + + +def _log_url(sha: str) -> str: + return f"http://{SERVER_IP}:9000/logs/{sha}" + + +def _set_github_status(sha: str, state: str, description: str, url: str) -> None: + if not GITHUB_TOKEN or not GITHUB_REPO: + log.warning("GITHUB_TOKEN / GITHUB_REPO not set — skipping status update") + return + payload = { + "state": state, + "context": "ci/hetzner", + "description": description[:140], + "target_url": url, + } + try: + subprocess.run( + [ + "curl", "-sf", "-X", "POST", + f"https://api.github.com/repos/{GITHUB_REPO}/statuses/{sha}", + "-H", f"Authorization: token {GITHUB_TOKEN}", + "-H", "Content-Type: application/json", + "-d", json.dumps(payload), + "-o", "/dev/null", + ], + check=False, timeout=10, + ) + except Exception as exc: + log.error("Failed to set GitHub status: %s", exc) + + +def _cancel_previous(branch: str) -> None: + """Best-effort: kill any running run-ci.sh for the previous SHA on this branch.""" + with _branch_lock: + old_sha = _branch_sha.get(branch) + if not old_sha: + return + log.info("Cancelling previous run for branch %s (sha %s)", branch, old_sha[:8]) + subprocess.run( + ["docker", "exec", CONTAINER_NAME, "pkill", "-f", f"run-ci.sh.*{old_sha}"], + capture_output=True, + ) + + +def _enqueue_ci(sha: str, branch: str) -> None: + """Enqueue CI run via ci-queue. The queue worker handles sequential execution.""" + log_url = _log_url(sha) + _set_github_status(sha, "pending", "Queued for CI...", log_url) + + try: + result = subprocess.run( + [CI_QUEUE_BIN, "push", sha, branch], + capture_output=True, text=True, timeout=10, + ) + log.info("Queued CI for %s @ %s: %s", branch, sha[:8], result.stdout.strip()) + with _branch_lock: + _branch_sha[branch] = sha + except Exception as exc: + log.exception("Failed to queue CI for %s: %s", sha, exc) + _set_github_status(sha, "failure", f"Queue error: {exc}", log_url) + + +# ── Routes ──────────────────────────────────────────────────────────────────── + +@app.post("/webhook") +def webhook(): + payload = request.get_data() + sig = request.headers.get("X-Hub-Signature-256", "") + if not _verify_signature(payload, sig): + log.warning("Invalid webhook signature") + abort(401) + + event = request.headers.get("X-GitHub-Event", "") + data = request.get_json(force=True) + + sha, branch = None, None + + if event == "push": + sha = data.get("after") + branch = data.get("ref", "").removeprefix("refs/heads/") + # Skip branch deletions (sha is all zeros). + if sha and re.fullmatch(r"0+", sha): + return jsonify({"status": "ignored", "reason": "branch deletion"}) + + elif event == "pull_request": + action = data.get("action", "") + if action not in ("opened", "synchronize", "reopened"): + return jsonify({"status": "ignored", "reason": f"action={action}"}) + sha = data["pull_request"]["head"]["sha"] + branch = data["pull_request"]["head"]["ref"] + + if not sha or not branch: + return jsonify({"status": "ignored", "reason": "unrecognised event"}) + + _cancel_previous(branch) + _enqueue_ci(sha, branch) + + return jsonify({"status": "queued", "sha": sha, "branch": branch}) + + +@app.get("/health") +def health(): + result = subprocess.run( + ["docker", "inspect", "-f", "{{.State.Running}}", CONTAINER_NAME], + capture_output=True, text=True, + ) + container_up = result.stdout.strip() == "true" + + last_success_ts = None + if LAST_SUCCESS.exists(): + last_success_ts = LAST_SUCCESS.stat().st_mtime + + status = "ok" if container_up else "degraded" + return jsonify({ + "status": status, + "container": container_up, + "last_success": last_success_ts, + "active_runs": list(_branch_sha.items()), + }) + + +@app.get("/logs/") +def log_index(sha: str): + if not re.fullmatch(r"[0-9a-f]{40}", sha): + abort(400) + sha_dir = LOGS_DIR / sha + if not sha_dir.is_dir(): + abort(404) + files = sorted(p.name for p in sha_dir.iterdir() if p.is_file()) + links = "".join(f'
  • {f}
    • ' for f in files) + return f"
      {links}
    ", 200, {"Content-Type": "text/html"} + + +@app.get("/logs//") +def log_file(sha: str, filename: str): + if not re.fullmatch(r"[0-9a-f]{40}", sha): + abort(400) + sha_dir = LOGS_DIR / sha + if not sha_dir.is_dir(): + abort(404) + # Prevent path traversal. + if "/" in filename or filename.startswith("."): + abort(400) + return send_from_directory(sha_dir, filename, mimetype="text/plain") + + +# ── Systemd watchdog ────────────────────────────────────────────────────────── + +def _sd_notify(state: str) -> None: + sock_path = os.environ.get("NOTIFY_SOCKET") + if not sock_path: + return + try: + with socket.socket(socket.AF_UNIX, socket.SOCK_DGRAM) as s: + s.connect(sock_path) + s.sendall(state.encode()) + except Exception: + pass + + +def _watchdog_loop() -> None: + _sd_notify("READY=1") + while True: + _sd_notify("WATCHDOG=1") + time.sleep(30) + + +threading.Thread(target=_watchdog_loop, daemon=True).start() + + +if __name__ == "__main__": + app.run(host="0.0.0.0", port=9000, debug=False) diff --git a/docs/llm/research/CI-performance.md b/docs/llm/research/CI-performance.md new file mode 100644 index 000000000..afcafd06e --- /dev/null +++ b/docs/llm/research/CI-performance.md @@ -0,0 +1,359 @@ +# CI Performance Research + +**Date:** 2026-03-01 +**Pipeline:** `.github/workflows/checks.yml` +**Runner provider:** [Depot](https://depot.dev) + +## Summary + +Buckaroo's CI runs 22 jobs across two waves on Depot GitHub Actions runners. The pipeline is **I/O-bound** — faster CPUs provide no measurable speedup. The blocking critical path is **~3.5 minutes**. Total cost is **~$0.18/run** on 2-CPU runners. + +Tested 2-CPU, 4-CPU, and 8-CPU Depot runners (2 runs each, 4 test PRs total). Bigger runners cost 1.6–2.7x more with zero improvement. Run-to-run variance (±20s) exceeds differences between tiers. + +--- + +## Pipeline Structure + +Two waves of parallel jobs: + +**Wave 1** (no dependencies, all start immediately): +- LintPython, TestJS, BuildWheel, CheckDocs, StylingScreenshots +- TestPython × 4 versions (3.11, 3.12, 3.13, 3.14) +- TestPythonMaxVersions × 4 versions +- TestPythonWindows + +**Wave 2** (`needs: [BuildWheel]`): +- TestStorybook, TestServer, TestJupyterLab, TestMarimo, TestWASMMarimo +- TestMCPWheel, SmokeTestExtras, PublishTestPyPI + +--- + +## Latency: Commit to Code Running + +Measured via live experiment — created a PR and timed each phase with second-level precision. + +``` +git commit T+0s +git push complete T+6s (local git + SSH) +GH webhook fires T+10s (run created) +Job assigned T+12s (queued to runner) +"Set up job" starts T+30s (Linux) / T+97s (Windows) +``` + +| Phase | Latency | +|-------|---------| +| Commit → push complete | 6s | +| Push → GitHub run created | 4s | +| Run created → job assigned | 2s | +| **Depot Linux provisioning** | **18s** | +| **Depot Windows provisioning** | **85s** | + +**GitHub adds ~6s.** The rest is Depot runner boot time. + +### BuildWheel → Wave 2 Gap + +Measured across 5 runs: + +| Phase | Time | +|-------|------| +| BuildWheel completes → jobs queued | 2–16s | +| Jobs queued → "Set up job" starts | 17–25s | +| **Total dead time on critical path** | **20–35s** | + +This provisioning gap is paid every wave transition. Not controllable. + +--- + +## Runner Tier Comparison + +### Methodology + +Created test branches changing `depot-ubuntu-latest` → `depot-ubuntu-latest-{4,8}` and `depot-windows-2025` → `depot-windows-2025-{4,8}`. Ran each tier twice via separate PRs. + +### Per-Job Results (format: run 1 / run 2) + +| Job | 2-CPU (baseline) | 4-CPU | 8-CPU | +|-----|---------|-------|-------| +| Python / Lint | 0:32 | 0:31 / 0:32 | 0:33 / 0:29 | +| JS / Build + Test | 0:53 | 0:51 / 0:49 | 0:50 / 0:48 | +| Build JS + Python Wheel | 0:59 | 1:00 / 0:52 | 0:50 / 1:36 | +| Docs / Build + Check Links | 1:05 | 1:05 / 1:00 | 0:54 / 1:00 | +| Python / Test (3.11) | 1:45 | 1:43 / 2:01 | 1:40 / 1:41 | +| Python / Test (3.12) | 1:44 | 1:42 / 1:49 | 1:41 / 1:44 | +| Python / Test (3.13) | 1:39 | 1:44 / 1:36 | 1:36 / 2:00 | +| Python / Test (3.14) | 1:35 | 1:34 / 1:52 | 1:33 / 1:34 | +| MaxVer (3.11) | 1:41 | 1:40 / 1:37 | 1:40 / 1:39 | +| MaxVer (3.12) | 1:41 | 1:41 / 1:39 | 1:40 / 2:03 | +| MaxVer (3.13) | 1:41 | 1:41 / 1:38 | 1:39 / 1:37 | +| MaxVer (3.14) | 1:37 | 1:32 / 1:42 | 1:34 / 1:34 | +| Smoke / Optional Extras | 0:47 | 0:47 / 0:47 | 0:45 / 0:43 | +| MCP / Integration | 0:48 | 0:48 / 1:01 | 0:44 / 0:44 | +| Marimo Playwright | 1:30 | 1:28 / 1:37 | 1:22 / 1:24 | +| WASM Marimo Playwright | 1:40 | 1:05 / 1:10 | 1:16 / 1:12 | +| Server Playwright | 2:05 | 1:35 / 1:38 | 1:34 / 1:37 | +| Storybook Playwright | 1:53 | 1:49 / 1:45 | 2:08 / 2:14 | +| JupyterLab Playwright | 2:03 | 2:08 / 2:01 | 2:34 / 2:18 | +| Windows | 8:02 | 8:20 / 7:14 | 7:54 / 7:24 | + +### Observations + +- **No consistent speedup.** Variance between runs of the same tier is larger than differences between tiers. +- **Some jobs slower on bigger runners.** Storybook Playwright: 1:53 (2-CPU) → 2:08/2:14 (8-CPU). JupyterLab Playwright: 2:03 → 2:34/2:18. +- **Windows unaffected.** 8:02 → 7:14–8:20 range across all tiers. + +### Cost + +| Tier | Linux $/min | Windows $/min | Cost/run | vs 2-CPU | +|------|-------------|---------------|----------|----------| +| 2-CPU | $0.004 | $0.008 | **$0.18** | 1x | +| 4-CPU | $0.008 | $0.016 | **$0.28** | 1.6x | +| 8-CPU | $0.016 | $0.032 | **$0.49** | 2.7x | + +**Verdict: Stay on 2-CPU.** Paying 1.6–2.7x more for no improvement. + +--- + +## Where Time Goes Inside Jobs + +Step-level analysis from a baseline 2-CPU run. + +### Typical Linux Job (Python / Test 3.13 — 1m39s total) + +``` +Set up job 2s +Checkout 5s +Install uv 3s +Setup js files 1s +Install the project 1s +Run tests 62s ← actual work +Codecov 4s +Post steps 1s +``` + +12s overhead, 62s useful work (84% efficient). + +### BuildWheel (0:59 total) + +``` +Set up job 2s +Checkout 6s +Install uv 5s +Setup pnpm + Node 3s +Install pnpm deps 2s +Install project 2s +Build JS + wheel 16s ← actual work +Upload artifacts 1s +``` + +20s overhead, 16s useful work. The build itself is fast. + +### Windows (8:02 total) + +``` +Set up job 2s +Checkout 43s ← 9x slower than Linux +Install uv 3m29s ← 70x slower than Linux +Setup js files 1s +Install project 27s ← 27x slower than Linux +Run tests 1m52s ← actual work +Post steps 3s +``` + +**4m41s of overhead for 1m52s of tests (28% efficient).** The `Install uv` step alone is 3.5 minutes. Already has `continue-on-error: true`. + +### Playwright Jobs (JupyterLab — 2:03 total, longest wave 2 job) + +``` +Set up job 2s +Checkout 5s +Install uv 3s +Setup pnpm + Node 7s +Install pnpm deps 2s +Download artifacts 0s +Install project 2s +Cache Playwright 2s +Run tests 77s ← actual work +Post steps 1s +``` + +23s overhead, 77s useful work. These tests validate the built wheel — they must depend on BuildWheel. + +--- + +## Critical Path Analysis + +``` +0:00 Wave 1 starts +0:59 BuildWheel completes (16s actual build + 43s overhead) +1:24 Wave 2 starts running (~25s Depot provisioning gap) +3:27 JupyterLab Playwright completes (longest wave 2 job) +``` + +**Blocking critical path: ~3:27.** Window job (8:02) runs in parallel but is non-blocking (`continue-on-error: true`). + +--- + +## Path-Gated Optimizations (PR-only, merge queue runs full CI) + +The key insight: **`merge_group` always runs the full pipeline** (current behavior, no changes). The optimizations below only apply to the `pull_request` event, where fast iteration matters more than exhaustive coverage. + +### Approach: Two-tier CI + +``` +pull_request: Run reduced CI based on what changed +merge_group: Run full CI (current behavior, unchanged) +push to main: Run full CI (current behavior, unchanged) +``` + +This is safe because nothing merges without passing the merge queue. + +### How Often Do PRs Touch JS vs Python vs file_cache? + +Analysis of the last 20 merged PRs: + +| Area | PRs touching it | % of PRs | +|------|----------------|----------| +| `packages/` (JS) | 9 of 20 | 45% | +| `buckaroo/file_cache/` | 0 of 20 | 0% | +| Python only (no JS) | 11 of 20 | 55% | + +### Optimization 1: Skip JS-only jobs when `packages/` unchanged + +Buckaroo is an integrated system — Python drives JS rendering, so **Playwright integration tests must always run** regardless of what changed. A Python-only change to styling, stats, or column config can break what renders in the browser. + +However, when `packages/` hasn't changed, the **JS unit tests** are redundant — they'd be testing the same JS code that already passed on `main`. + +When a PR only touches Python code: +- Skip `TestJS` (0:53) — JS unit tests, no Python involvement +- `BuildWheel` uses cached JS build artifacts from `main` instead of rebuilding the JS (still builds the Python wheel around them) + +**What still runs on Python-only PRs (everything else):** +- LintPython, CheckDocs, BuildWheel (with cached JS), all Python test matrix entries +- All Playwright integration tests (Storybook, Server, JupyterLab, Marimo, WASM Marimo) +- SmokeTestExtras, TestMCPWheel, StylingScreenshots + +**Impact for the 55% of PRs that are Python-only:** +- Saves 1 job (~$0.004) and a small amount of BuildWheel time +- The main win is `BuildWheel` completing faster (skip the 16s esbuild), which means wave 2 Playwright jobs start ~16s sooner +- Critical path drops from ~3:27 to ~3:11 + +This is a modest win. The real value is correctness: by caching known-good JS artifacts, Python-only PRs are tested against the exact JS that's on `main`, not a redundant rebuild of the same source. + +### Optimization 2: Skip file_cache tests when `buckaroo/file_cache/` unchanged + +The `tests/unit/file_cache/` suite is **74% of total Python test time**: + +| Test group | Tests | Time | % of total | +|---|---|---|---| +| `tests/unit/file_cache/` | 51 | **42.8s** | **74%** | +| Everything else | 570 | **14.9s** | **26%** | + +This is because `mp_timeout` tests spawn real subprocesses with real timeouts (0.8–1.0s each, some at 3×). Each test that exercises a timeout path waits for the actual timeout to expire. + +In the last 20 merged PRs, **zero** touched `buckaroo/file_cache/`. When it does get touched, it's critical to test thoroughly. But running 43s of subprocess timeout tests on every Python-only PR that changes a formatter or stat function is waste. + +**Mechanism:** Use `dorny/paths-filter` to detect changes to `buckaroo/file_cache/**` or `tests/unit/file_cache/**`. If unchanged: +- Add `-m "not file_cache"` to the pytest invocation (requires adding a `file_cache` marker to the tests) +- Or simpler: `--ignore=tests/unit/file_cache` + +**Impact:** +- Python test jobs drop from ~62s to ~15s actual test time +- Total job time drops from ~1:40 to ~0:30 per matrix entry +- 8 matrix entries × ~70s saved = ~9.3 minutes of job-time saved +- At $0.004/min = ~$0.04 saved per run +- **Critical path drops by ~47s** (Python tests are no longer on the critical path at all — BuildWheel→Playwright becomes the bottleneck again, but only when JS changes) + +### Combined Impact + +For the **55% of PRs that are Python-only and don't touch file_cache** (the common case): + +| | Current | Optimized | Saved | +|--|---------|-----------|-------| +| Jobs run | 22 | 21 | 1 fewer | +| Python test time | ~62s | ~15s | **~47s** | +| Critical path | ~3:27 | ~2:40 | **~47s** | +| Cost/run | ~$0.18 | ~$0.14 | ~$0.04 | + +The critical path improvement comes from file_cache skipping — Python tests drop from ~1:40 to ~0:30 per job, so they're no longer close to the Playwright critical path. The JS artifact caching shaves ~16s off BuildWheel, letting wave 2 start slightly sooner. + +For the **45% of PRs that touch JS but not file_cache**: + +| | Current | With file_cache skip | Saved | +|--|---------|---------------------|-------| +| Jobs run | 22 | 22 | 0 | +| Critical path | ~3:27 | ~2:40 | **~47s** | +| Cost/run | ~$0.18 | ~$0.14 | ~$0.04 | + +The merge queue always runs the full 22-job pipeline regardless. + +--- + +## Other Optimization Opportunities + +### Move Windows to nightly schedule + +| | Current | Proposed | +|--|---------|----------| +| Trigger | Every PR | `schedule` cron + push to main | +| Savings | — | $0.06/run | +| Risk | None | Late detection of Windows-specific bugs | + +Already `continue-on-error: true` so it cannot block merges. Running it on every PR burns $0.06 and 8 minutes of wall-clock noise for a job that by definition can't fail the build. + +### Reduce Python matrix from 8 → 3 jobs + +Currently 4 Python versions × 2 dep strategies = 8 jobs. Proposed: +- Normal deps: 3.11 + 3.14 (oldest + newest) +- Max versions: 3.14 only + +Middle versions (3.12, 3.13) rarely catch issues that 3.11 + 3.14 don't. Saves ~$0.03/run and 5 fewer runners to provision. (Could also be PR-only, with merge queue running the full matrix.) + +### Path-filter Styling Screenshots + +Only run when PRs touch styling-related files (`styling*.py`, `Styler.tsx`, etc.). Most PRs don't touch styling code. When it does run it takes 2:10 (two Storybook cold starts). + +### Merge small jobs to reduce provisioning overhead + +Each job pays ~20s Depot provisioning + ~15s setup. Candidates: +- **MCP + Smoke** → one job (both need just uv + wheel, 48s + 47s actual) +- **Marimo + WASM Marimo** → one job (identical 23s setup each) + +No wall-clock improvement (they run in parallel), but reduces total job-minutes and Depot costs. + +### Drop codecov from 3 of 4 Python test entries + +Only one coverage report needed. Saves ~12s total. + +### What won't help + +- **Faster runners** — proven by 4-run experiment. I/O-bound workload. +- **Removing BuildWheel dependency from Playwright** — those tests validate the built wheel works as shipped. That's the point. + +--- + +## Depot Pricing Reference + +| Plan | Price | Included | Overage | +|------|-------|----------|---------| +| Developer | $20/mo | 2,000 min | — | +| Startup | $200/mo | 20,000 min | $0.004/min | +| Business | Custom | Custom | Custom | + +Runner rates (per minute, billed per second, no minimum): + +| Size | Linux | Windows | +|------|-------|---------| +| 2 CPU / 8 GB | $0.004 | $0.008 | +| 4 CPU / 16 GB | $0.008 | $0.016 | +| 8 CPU / 32 GB | $0.016 | $0.032 | +| 16 CPU / 64 GB | $0.032 | $0.064 | + +### Monthly cost at current usage (2-CPU) + +| Runs/month | Total minutes | Cost | +|------------|--------------|------| +| 50 | ~1,900 | ~$9 | +| 100 | ~3,800 | ~$18 | +| 200 | ~7,600 | ~$36 | + +Fits comfortably on Developer plan at moderate usage. diff --git a/docs/llm/research/ci-tuning-experiments-archive.md b/docs/llm/research/ci-tuning-experiments-archive.md new file mode 100644 index 000000000..3dcd73c5a --- /dev/null +++ b/docs/llm/research/ci-tuning-experiments-archive.md @@ -0,0 +1,260 @@ +# CI Tuning Experiments — Historical Archive + +Completed experiments from the CI optimization effort. For current state and open issues, see `ci-tuning-experiments.md`. + +**Server:** Vultr 16 vCPU / 32 GB (45.76.230.100) +**Baseline:** 3m16s (full DAG, PARALLEL=3 jupyter) + +--- + +## Summary Table + +| Exp | Commit | Config | Pass Rate | Jupyter Time | Total Time | +|-----|--------|--------|----------|-------------|-----------| +| 10 | 7e5754a | P=9 WebSocket phase5b | 8/9 notebooks | ~2m01s | N/A (5b only) | +| 11 | 7e5754a | P=9 full DAG | 0/1 | N/A | N/A | +| 12 | a869d12 | pytest-xdist -n 4 | N/A (python only) | N/A | ~30s/ver (was ~63s) | +| 13 | 2207d1e | infinite_scroll fix | N/A | N/A | N/A | +| 14a | 35e0fc8 | P=4 old DAG | 2/7 = 29% | ~1m12s | ~2m40s | +| 14b | 7770774 | P=4 wait-all DAG | 4/5 = 80% | ~3m20s | ~3m30s | +| 14c | 92ca618 | P=3 wait-all DAG | 3/5 = 60% | ~5m18s | ~7m | +| 14d | 6a11b71 | P=4 wait-all + kernel-idle-60s | 3/5 = 60% | varies | varies | +| 14e | 8695488 | P=4 wait-all + idle-15s + retry=2 | 4/5 = 80% | ~1m12s | ~2m42s | +| **15-21** | **5994612** | **jupyterapp + waitFor removal** | **10/10 jupyter** | **~1m36s** | **~2m59s** | +| 23 | 200bac6 | JS build cache | N/A | N/A | saves 17s critical path | +| 24 | 5c1e58f | Fix full_build.sh skip check | N/A | N/A | build-wheel 17s→3s | +| **18+19+20** | **60618ce** | **parallel smoke + relaxed gate** | **pw-jupyter 1/1** | **1m38s** | **2m31s** | +| **28** | **172158b** | **early kernel warmup** | **3/3 pw-jupyter** | **1m14s** | **2m25s** | +| **30** | **d369894** | **remove heavyweight PW gate** | **7/7 pw-jupyter** | **1m15s** | **1m43s** | +| 31 | b2398d5 | PARALLEL=9 revisited | ABANDONED | 4m+ | N/A | +| 32 | b2398d5 | lean Wave 0 + defer pytest | 3/3 pw-jupyter | 80s | 1m51s | +| **33** | **076f40f** | **P=6 batched + re-warmup** | **9/9 jupyter** | **66s** | **1m44s** | +| 33 | 0e98e13+ | P=9 (various stagger/port combos) | 1-3/9 jupyter | 120s timeout | ~2m45s | +| **34+36** | **2ba10e7** | **SKIP_INSTALL + renice + pw-server fix** | **pw-server 3/3** | **76s** | **2m00s** | +| 37 | 20fb931 | `init: true` in docker-compose | 101 zombies after run 1 | N/A | 2m59s | +| **37** | **46c165c** | **tini ENTRYPOINT in Dockerfile** | **0 zombies** | N/A | N/A | +| 38 | ef53834 | P=6 on tini image | 3-6/6 kernel timeout | N/A | ~2m58s | +| **38** | **fff99fa** | **P=4 on tini image** | **14/0 PASS** | **95s** | **2m01s** | + +--- + +## Experiment Details + +### Exp 10 — PARALLEL=9 WebSocket warmup baseline (7e5754a) + +Mode: `--phase=5b` (isolated, no DAG contention). PARALLEL=9. + +**Key discovery:** REST API (GET /api/kernels/{id}) NEVER updates execution_state from "starting" to "idle" without a WebSocket client. The fix: connect to `/api/kernels/{id}/channels` via WebSocket, triggering the "nudge" mechanism. All 9 kernels reached idle in 11s. + +Results: 8/9 PASS. `test_infinite_scroll_transcript` fails (2000-row widget too heavy). + +Bugs fixed: ENOENT race (unique `--output` per slot), REST warmup replaced with WebSocket. + +--- + +### Exp 11 — PARALLEL=9 full DAG (7e5754a) + +All 9 notebooks FAILED. playwright-server overlap causes CPU contention with 9 Chromium + 9 JupyterLab + 9 kernels. + +**Finding:** Phase 5b passes (isolated) but full DAG fails at P=9. CPU contention is the bottleneck. + +--- + +### Exp 12 — pytest-xdist (a869d12) + +Added `pytest-xdist>=3`, run with `-n 4 --dist load`. Python test time: ~63s → ~30s per version. + +--- + +### Exp 13 — infinite_scroll_transcript fix (2207d1e) + +Reduced DataFrame 2000→500 rows, scroll target 1500→400, bumped timeouts, added Shift+Enter retry loop. Passes alone, fails under concurrency. + +--- + +### Exp 14a-e — PARALLEL=4 reliability series + +| Variant | Change | Pass Rate | +|---------|--------|-----------| +| 14a (35e0fc8) | P=4 old DAG | 29% (2/7) | +| 14b (7770774) | Wait-all DAG + retries=1 | **80%** (4/5) | +| 14c (92ca618) | P=3 wait-all | 60% (3/5) — worse | +| 14d (6a11b71) | Kernel idle wait 60s | 60% (3/5) — worse | +| 14e (8695488) | Kernel idle 15s + retries=2 | 80% (4/5) | + +**Key findings:** +- Wait-all DAG is the single biggest reliability improvement (29%→80%) +- PARALLEL=3 is worse than 4 (more batches = more overhead) +- 60s kernel idle wait burns timeout budget +- 80% is the ceiling with DOM-based kernel checks + +--- + +### Exp 15+16+17+21 — jupyterapp + timing fixes (5994612) + +10-run stability test. All in one commit: +1. **Exp 15:** `waitForTimeout(3000)` → `expect().toPass()` in server specs. pw-server 50s→37s. +2. **Exp 16:** `sleep 5` → curl polling in marimo warmup. pw-marimo 46s→42s. +3. **Exp 17:** Skip JS rebuild in full_build.sh — no-op (git checkout clears dist). +4. **Exp 21:** `window.jupyterapp` kernel check. **pw-jupyter 80%→100%.** + +Results: pw-jupyter 10/10. Overall 9/10 (1 pw-server flake). Median total: 2m59s. + +Bimodal pattern: 7/10 at ~1m36s, 3/10 at ~4m11s (retries used). + +--- + +### Exp 23 — JS Build Cache (200bac6) + +Cache `dist/` at `/opt/ci/js-cache/`. Keyed by sha256 of `git ls-tree` for src/, package.json, tsconfig.json, vite.config.ts. + +| Metric | Cache MISS | Cache HIT | Savings | +|--------|-----------|-----------|---------| +| test-js | 21s | 5s | -16s | +| build-wheel starts at | +23s | +7s | -16s | +| wheel-dependent starts at | +40s | +25s | -15s on critical path | + +CPU profile showed machine massively underutilized during pw-jupyter (5-10% busy). Bottleneck is kernel I/O latency, not CPU. + +--- + +### Exp 24 — Fix build-wheel skip check (5c1e58f) + +`full_build.sh` checked `dist/index.js` but vite outputs `dist/index.es.js`. Fixed. Combined with JS cache: build-wheel 17s→3s. + +--- + +### Exp 18+19+20 — parallel smoke, relaxed gate (60618ce) + +1. Parallel smoke-test-extras: 20s→8s +2. Relax pw-jupyter gate: wait only for heavyweight PW jobs +3. Reduce waitForTimeout in marimo screenshots: ~3.4s + +Total: 2m59s→**2m31s** (-28s). Critical path now dominated by pw-jupyter (65%). + +--- + +### Exp 28 — Early Kernel Warmup (172158b) + +New `job_jupyter_warmup()` in Wave 0: venv, deps, 4 JupyterLab servers, WebSocket warmup, notebook trust. Overlaps with Wave 0 (free). + +pw-jupyter 3/3 = 100%. Total: 2m31s→**2m25s** (-6s net). pw-jupyter itself: 1m38s→1m14s (-24s). + +--- + +### Exp 30 — Remove Heavyweight PW Gate (d369894) + +pw-jupyter starts alongside all wheel-dependent jobs. No more waiting for pw-server/marimo. + +pw-jupyter 7/7 = 100% under 40-75% CPU contention. Total: 2m25s→**1m43s** (-42s). + +CPU profile (vmstat): Wave 0 80-97% busy → wheel-dependent 40-75% → pw-jupyter alone 6-20%. + +--- + +### Exp 31 — PARALLEL=9 revisited (b2398d5) + +ABANDONED. pw-jupyter 4+ minutes (vs 75s at P=4). Too many processes for 16 vCPU. + +--- + +### Exp 32 — Lean Wave 0 + defer pytest (b2398d5) + +Fewer Wave 0 jobs, defer pytest 3.11/3.12/3.14. pw-jupyter 3/3 but total 1m51s (+8s vs Exp 30). Just shifts contention. No benefit. + +--- + +### Exp 33 — PARALLEL=6 batched (076f40f) + +PARALLEL=6 with 6+3 batching, between-batch kernel re-warmup. P=9 conclusively dead. + +P=6 results: pw-jupyter 66s (9/9), total 1m44s, 13/14 overall (1 pw-server flake). + +P=9 results (4 runs, all failed): 1-3/9 notebooks, 120s timeout. Root cause: 27+ processes on 16 vCPU = CPU starvation. + +Bug fixes: batch-2 hang (new kernels need WebSocket nudge), `local` outside function. + +--- + +### Exp 34+36 — SKIP_INSTALL + renice + pw-server fix (2ba10e7) + +**SKIP_INSTALL:** All PW scripts check `SKIP_INSTALL=1` and skip redundant pnpm install in CI. + +**renice:** `renice -n -10` for critical-path (test-js), `renice -n 10` for background. Initial attempt with `nice` failed (external command can't run shell functions). + +**pw-server fix:** `getCellText()` + `expect().toBe()` → `cellLocator()` + `toHaveText()`. Auto-retrying assertions eliminate AG-Grid render race. + +Results: pw-server 3/3 PASS (flake fixed). pw-jupyter 1/3 — regression from zombie accumulation (see current doc for details). + +--- + +### Exp 37 — tini as PID 1 (20fb931, 46c165c) + +**Attempt 1: `init: true` in docker-compose.yml (20fb931)** + +FAILED. `init: true` makes Docker wrap the container with tini at the *host* level. Inside the container, PID 1 is still `sleep`. `docker exec`'d CI processes become children of `sleep`, which doesn't call `wait()`. After run 1: 101 zombies (jupyter-lab, chrome-headless, node, python). + +Verification: `docker exec buckaroo-ci ps -p 1 -o comm` → `sleep` (not tini). `docker top` shows tini as host-level PID wrapping `sleep`. + +**Attempt 2: `ENTRYPOINT ["/usr/bin/tini", "--"]` in Dockerfile (46c165c)** + +Bakes tini into the image. `CMD ["sleep", "infinity"]` runs as tini's child. `docker exec`'d processes become children of tini (PID 1), which reaps them. Requires image rebuild (`apt-get install tini`). + +**VALIDATED.** Zero zombies after 3 runs. PID 1 is tini. But back-to-back pw-jupyter failures persist (not caused by zombies — see Open Issue #1 in current doc). Tini confirmed working, P=4 is reliable baseline. + +--- + +## Architecture Notes + +### Process Model +All processes run in a SINGLE Docker container: +- N JupyterLab servers (one per parallel slot, different ports) +- N Chromium browsers (one per Playwright process) +- N Python kernels (one per notebook being tested) +- Other DAG jobs (pytest, ruff, storybook, etc.) running concurrently + +At PARALLEL=6: 18 heavyweight processes (6 Chromium + 6 JupyterLab + 6 kernels) on 16 vCPUs. + +### Root Cause of Jupyter Flakes (solved) +Cell execution fails when JupyterLab's kernel connection isn't established when Shift+Enter is pressed. The keystroke is silently dropped. Fixed by `window.jupyterapp` kernel check (Exp 21) which queries the exact same `session.kernel` that `CodeCell.execute()` uses. + +--- + +## All Commits (chronological) + +| Commit | Description | +|--------|-------------| +| a1594bd | WebSocket warmup + remove batch stagger | +| 7e5754a | Unique Playwright --output per slot | +| a869d12 | pytest-xdist + infinite scroll timeout fixes | +| 2207d1e | Reduce DataFrame to 500 rows, bump test timeout | +| 6c1c743 | PARALLEL=8 | +| c2a16ec | CELL_EXEC_TIMEOUT=120s, test timeout=180s | +| 4cd4ccb | Robust cell focus (click + jp-mod-selected) | +| fac3cb5 | Kernel idle indicator wait | +| 4cd68b7 | PARALLEL=4 | +| 61e9947 | Shift+Enter retry loop | +| dc360ac | DEFAULT_TIMEOUT=30s | +| 35e0fc8 | dispatchEvent in retry | +| 7770774 | Wait-all DAG + Playwright retries=1 | +| 92ca618 | PARALLEL=3 (worse than 4) | +| 6a11b71 | Kernel idle wait 60s (too aggressive) | +| 8695488 | Kernel idle wait 15s + retries=2 | +| 5994612 | jupyterapp kernel check + waitForTimeout removal | +| 200bac6 | JS build cache + ci-queue | +| e7fff5b | Mount js-cache volume for persistence | +| 5c1e58f | Fix full_build.sh index.es.js check | +| 60618ce | Exp 18+19+20: parallel smoke, relaxed gate → 2m31s | +| 172158b | Exp 28: early kernel warmup → 2m25s | +| d369894 | Exp 30: remove heavyweight PW gate → 1m43s | +| d020744 | Exp 29: marimo auto-retry assertions | +| b2398d5 | Exp 31+32: P=9 abandoned, lean Wave 0 → 1m51s | +| 076f40f | Exp 33: P=6 batched + re-warmup → 1m44s | +| 9dcc5e0 | Pre-run cleanup | +| 630cf60 | Exp 34+36: SKIP_INSTALL, renice, pw-server auto-retry | +| da3a7ad | Fix: renice instead of nice for shell functions | +| 2ba10e7 | Fix: don't renice jupyter-warmup, SKIP_INSTALL in pw-jupyter | +| 20fb931 | Exp 37: `init: true` in docker-compose (failed) | +| 46c165c | Exp 37: tini ENTRYPOINT in Dockerfile (validated — 0 zombies) | +| ef53834 | Exp 38: revert to P=6 on tini image (P=6 broken) | +| fff99fa | Exp 38: revert P=6→4 (stable baseline) | diff --git a/docs/llm/research/ci-tuning-experiments.md b/docs/llm/research/ci-tuning-experiments.md new file mode 100644 index 000000000..5074a9a01 --- /dev/null +++ b/docs/llm/research/ci-tuning-experiments.md @@ -0,0 +1,327 @@ +# CI Tuning — Current State & Open Research + +**Branch:** docs/ci-research +**Server:** Vultr 32 vCPU / 64 GB (45.76.18.207) — voc-c-32c-64gb-500s-amd +**Best config:** P=9 + /dev/shm fix + 2s stagger — **1m42s, all PASS** (commit 09c6faa) + +--- + +## Current Best Configuration (commit 09c6faa, P=9, 2s stagger, 64GB) + +``` +Total: 1m42s (warm caches, 32 vCPU / 64 GB) +├─ Wave 0 (parallel): 44s [lint, build-js, test-python-3.13, pw-storybook, jupyter-warmup] +├─ build-wheel: 3s [after build-js, JS cache HIT] +├─ test-js: ~5s [starts after build-js, runs in background] +├─ wheel install: 3s [into pre-warmed jupyter venv] +├─ Wheel-dependent (staggered 2s apart): +│ ├─ pw-jupyter (P=9): 52s [critical path — 9 parallel notebooks] +│ ├─ pw-server: 44s +│ ├─ pw-marimo: 53s +│ ├─ pw-wasm-marimo: 39s +│ ├─ test-mcp-wheel: 14s +│ ├─ smoke-test-extras: 6s [no memory pressure on 64GB] +│ └─ test-python 3.11/3.12/3.14: ~24s each (deferred 8s) +``` + +Critical path: `build-js(2s) → build-wheel(3s) → warmup-wait → wheel-install(3s) → pw-jupyter(52s)` + +### Key Techniques (all proven) + +| Technique | Exp | Impact | +|-----------|-----|--------| +| `window.jupyterapp` kernel check | 21 | pw-jupyter 80% → **100%** pass rate | +| WebSocket kernel warmup in Wave 0 | 28 | -24s off pw-jupyter | +| No heavyweight PW gate | 30 | -42s off total (1m43s vs 2m25s) | +| tini ENTRYPOINT in Dockerfile | 37 | Zero zombies (was 100+ per run) | +| JS build cache (tree-hash keyed) | 23 | -16s off critical path | +| `full_build.sh` skip check fix | 24 | build-wheel 17s → 3s | +| `expect().toPass()` polling | 15 | pw-server 50s → 37s | +| `cellLocator()` + `toHaveText()` | 34+36 | pw-server flake fixed (3/3 PASS) | +| SKIP_INSTALL in PW scripts | 34 | Skips redundant pnpm/playwright install in CI | +| `renice` after fork | 36 | -10 for critical-path, +10 for background | +| Parallel smoke-test-extras | 18 | 20s → 8s | +| pytest-xdist `-n 4` | 12 | ~63s → ~30s per Python version | +| Staggered sub-waves (5s) | 33 | Reduces CPU burst at wheel-dependent launch | +| Between-batch kernel re-warmup | 33 | Fixes batch-2 hang | +| Pre-run cleanup (pkill, rm temps) | 33 | Clean state between CI runs | +| Workspace cleanup in pre-run | 38 | Prevents stale kernel reconnection | +| Split build-js / test-js | 35 | ~3s off critical path (test runs in background) | +| Lockfile hash on bind mount | 39 | No dep rebuild on container restart | +| 120s pw-jupyter timeout + 210s watchdog | 33 | Prevents runaway CI | +| `--disable-dev-shm-usage` on all PW configs | 40 | P=9 stable (Docker 64MB /dev/shm was root cause) | +| P=9 parallel jupyter (settle=0) | 40 | 50s pw-jupyter (down from 96s at P=4) | +| Bind-mount CI runner scripts | 41 | No rebuild needed for script changes | +| 2s stagger (on 64GB) | 42 | 5s→2s, saves ~6s off total vs 5s stagger | +| Port cleanup 8889-8897 | 42 | Fix: was only cleaning 8889-8894 (6 of 9) | +| esbuild + pw-results cleanup | 42 | Prevents ~400MB leak + /tmp accumulation | +| CI watchdog 360s | 42 | Handles cold-start (uv cache miss = +2min) | + +### What Doesn't Work + +| Approach | Exp | Why | +|----------|-----|-----| +| PARALLEL=3 | 14c | More batches = more overhead, worse than P=4 | +| PARALLEL=6 | 33, 38 | Worked on old image, fails on current (3-6/6 kernel timeouts) | +| PARALLEL=9 | 11, 31, 33 | CPU starvation (27+ processes on 16 vCPU) | +| DOM kernel idle check | 14d | Burns timeout when DOM not rendered | +| REST kernel polling | 10 | Never updates without WebSocket | +| Lean Wave 0 (shift work to later) | 32 | Just moves contention, +8s total | +| `nice` on shell functions | 34+36 | `nice` is external cmd, can't run bash functions | +| `init: true` in docker-compose | 37 | Tini wraps at host level; docker exec'd processes still parent to `sleep` PID 1 | +| 2s stagger (on 32GB) | 41-B | Too aggressive — 12 Chromium instances in 6s exhausts RAM, pw-jupyter hangs | +| 0s stagger (on 64GB) | 42 | All jobs simultaneous → 8/9 pw-jupyter notebooks hang. Kernel provisioner or ZMQ contention | + +--- + +## Open Issues + +### 1. Back-to-back run degradation — LARGELY FIXED + +**Discovered in:** Exp 34+36, confirmed with tini +**Root causes found:** +- Docker 64MB `/dev/shm` exhaustion (fixed with `--disable-dev-shm-usage`) +- Stale storybook/esbuild processes leaking ~400MB between runs (fixed: `pkill esbuild` in pre-run cleanup) +- Stale JupyterLab on ports 8895-8897 not cleaned (fixed: port range 8889-8897) +- `/tmp/pw-results-*` accumulating across runs (fixed: cleanup added) +**Status:** b2b run 1→2 passes on 64GB with all fixes. Needs more testing for run 3+. + +### 2. pw-server flake — FIXED (Exp 34+36) + +**Was:** 1/14 failure rate — `sort via header click` test used one-shot `getCellText()` which races with AG-Grid rendering. +**Fix:** `cellLocator()` + `toHaveText()` auto-retrying assertions in `server.spec.ts` and `server-helpers.ts`. +**Result:** 3/3 pw-server PASS after fix. + +### 3. Lockfile hash persistence across container restarts — FIXED (commit 4a7fefc) + +**Was:** Every container restart triggered "Lockfiles changed — rebuilding deps" because the hash store (`/var/ci/hashes/`) was inside the container. +**Fix:** Moved to `/opt/ci/logs/.lockcheck-hashes/` which is bind-mounted to the host. Hashes now persist across container restarts. + +### 4. PARALLEL=6 regression — SUPERSEDED by P=9 + /dev/shm fix + +P=6 issues were caused by Docker's 64MB /dev/shm. `--disable-dev-shm-usage` on all Playwright configs fixes this. P=9 is now stable with 5s stagger on 32GB. + +### 5. 32GB RAM constraint — RESOLVED (moved to 64GB) + +Moved from Vultr 16 vCPU / 32GB (45.76.230.100, destroyed) to 32 vCPU / 64GB (45.76.18.207). +On 64GB: smoke-test-extras runs in 6s (was 61s on 32GB). 2s stagger works. 0s stagger does NOT work (kernel contention, not RAM). + +### 6. Container detritus between runs + +After each CI run, these processes/files leak and must be cleaned by the next run's pre-run cleanup: +- **Storybook node process** (~400MB RSS) — stays running after playwright-storybook completes +- **3 esbuild processes** (~100MB total) — child processes of storybook/build +- **Watchdog sleep** — `sleep 360` from CI timeout, harmless +- **/tmp/pw-results-*** — Playwright test result dirs, ~15MB per run +- **/tmp/pw-html-*** — Playwright HTML report dirs +- **~/.jupyter/lab/workspaces/** — JupyterLab workspace files +- **~/.local/share/jupyter/runtime/jupyter_cookie_secret** — harmless, persists + +The pre-run cleanup in run-ci.sh handles all of these. Verified: after cleanup runs, old storybook/esbuild PIDs are gone, /tmp dirs are removed, ports are freed. + +--- + +## Recent Experiments (Exp 40-41) + +### Exp 40 — /dev/shm fix + P=9 (commits e6ea620, 176f6f6) — SUCCESS + +**What:** Add `--disable-dev-shm-usage` to all Playwright configs (storybook, server, marimo, wasm-marimo, jupyter). Docker default /dev/shm is 64MB which causes Chromium crashes at P=5+. +**Result:** P=9 stable, settle=0 works, all jobs PASS. Total 1m42s — best ever. +**Key insight:** Back-to-back degradation was also caused by /dev/shm exhaustion, not zombie accumulation. + +### Exp 41-A — Defer smoke-test-extras (commit fd85f0a) — WORKS (needs larger server) + +**What:** Launch smoke-test-extras after `wait $PID_PW_JP` instead of at t+0. Event-driven, not sleep-based. +**Result on 32GB:** smoke-test-extras 28s (down from 61s). Still not the ideal 5s because pw-wasm-marimo was still running, keeping memory pressure elevated. +**Expected on 64GB+:** should hit the 5s uncontended target. + +### Exp 41-B — Tighten stagger 5s→2s (commit fd85f0a) — FAILED on 32GB + +**What:** Reduce gaps between pw-marimo/wasm/server from 5s to 2s. +**Result:** pw-jupyter hangs consistently (0/9 or 1/9 notebooks complete in 120s timeout). All 12 Chromium instances launching within 6s overwhelms 32GB RAM. +**Conclusion:** 5s stagger is necessary on 32GB. Re-test on larger server. + +### Exp 41-C — MCP timing instrumentation (commit fd85f0a) — IN PLACE + +**What:** Added `[mcp-timing]` lines to `job_test_mcp_wheel` — times venv creation, wheel install, each pytest run. +**Note:** Uses `awk` not `bc` (bc not installed in container). +**Result (from fd85f0a run):** test-mcp-wheel total 11s. Detailed breakdown needs green run to read. + +### Exp 41-D — pw-server timing instrumentation (commit fd85f0a) — IN PLACE + +**What:** Added `--reporter=list` to pw-server in CI for per-test timing. Plus `[pw-server-timing]` total elapsed. +**Result (from fd85f0a run):** pw-server total 41s. Per-test breakdown in pw-server.log. + +### Exp 42 — Server upgrade + stagger tuning (commits 6c8590d, 7626c67, 09c6faa) — SUCCESS + +**What:** Moved to 32 vCPU / 64GB server. Tested stagger values: +- **0s stagger:** FAILS — 8/9 pw-jupyter notebooks hang at "Shift+Enter attempt 7". Port 8889 works, 8890-8897 don't. Reproducible on both 176f6f6 and 37aed6b. Root cause: kernel provisioner or ZMQ contention when 12 Chromium + 9 JupyterLab kernel starts all race simultaneously. NOT a RAM issue (64GB plenty, free stays >40GB). +- **2s stagger:** WORKS — all pass consistently. 1m42-1m49s total. +- **5s stagger:** WORKS — baseline from 176f6f6, 1m42s on old 32GB server. + +**Also fixed:** +- Port cleanup range: was 8889-8894 (6 ports), now 8889-8897 (9 ports for P=9) +- esbuild cleanup: `pkill -9 -f esbuild` added to pre-run cleanup +- /tmp/pw-results-* cleanup: added to pre-run rm +- CI watchdog: 210s → 360s (cold-start on fresh image needs ~3.5min for uv cache miss) + +**Key insight:** The 0s stagger failure was initially misattributed to SHA-specific differences (37aed6b vs 176f6f6). In reality, both SHAs fail with 0s stagger when using the bind-mounted runner. The earlier apparent SHA-specificity was because the bind-mounted runner was updated between test runs. + +### Infra: Bind-mount CI runner scripts (commit 1c49a02) — SUCCESS + +**What:** Volume-mount `/opt/ci/runner/` into container at `/opt/ci-runner/:ro`. Added `update-runner.sh` that: +- Copies scripts from repo to `/opt/ci/runner/` +- Detects Dockerfile changes via sha256 hash +- Only rebuilds image when Dockerfile changes + +**Result:** Script changes take effect instantly. Tested: `update-runner.sh` correctly prints "Scripts updated (no rebuild needed)" for script-only changes, and triggers full rebuild when Dockerfile hash differs. + +--- + +## Queued Experiments + +### Exp 29 — Marimo auto-retry assertions — VALIDATED + +**Status:** Validated in CI — pw-marimo passes consistently on 64GB server. + +### Exp 43 — New box deployment checklist + +**Priority:** HIGH — needed before spinning up another server +**What:** Codify the full deployment procedure: +1. Provision server (cloud-init or manual) +2. Clone repo, build Docker image +3. Set up bind mounts (`/opt/ci/runner/`, `/opt/ci/logs/`, `/opt/ci/js-cache/`) +4. `docker compose up -d` +5. Run CI with known-good SHA — must ALL PASS +6. Run CI again (b2b) — must ALL PASS +7. Check detritus between runs +**Status:** Procedure documented informally; needs a script or checklist. + +### Exp 44 — Post-run cleanup (kill storybook/esbuild at end of CI) + +**Priority:** LOW — pre-run cleanup handles it, but cleaner to not leak +**What:** After all jobs complete and results are reported, kill storybook and esbuild processes. Currently they leak ~400MB until the next run's pre-run cleanup kills them. +**Risk:** Low — these processes are only needed during playwright-storybook job. + +### Exp 26 — Wheel cache across SHAs + +**Priority:** LOWEST — CI-dev-only edge case, not useful for real CI +**What:** Cache wheel keyed by Python+JS source hash. Skip build-wheel entirely on cache hit. + +--- + +## Operational Reference + +### Trigger a CI run +```bash +ssh root@45.76.18.207 +docker exec -d buckaroo-ci bash /opt/ci-runner/run-ci.sh +tail -f /opt/ci/logs//ci.log +``` + +### Update CI scripts (no rebuild needed) +```bash +ssh root@ +cd /opt/ci/repo && git fetch origin +git checkout origin/ -- ci/hetzner/ scripts/ +bash ci/hetzner/update-runner.sh +``` +The `update-runner.sh` script: +- Copies scripts to `/opt/ci/runner/` (bind-mounted into container) +- Detects Dockerfile changes via sha256 hash — only rebuilds when needed +- Script changes take effect instantly, no container restart required + +### Manual rebuild (only for Dockerfile changes) +```bash +ssh root@ +cd /opt/ci/repo && git fetch origin && git checkout +docker build -t buckaroo-ci -f ci/hetzner/Dockerfile . +cd ci/hetzner && docker compose down && docker compose up -d +``` + +### Parse results from ci.log +Lines: `[HH:MM:SS] START/PASS/FAIL ` +Report: wallclock total, per-phase timing, pass/fail per job. + +--- + +## Recent Run History + +| SHA | Experiment | Total | Result | Notes | +|-----|-----------|-------|--------|-------| +| 09c6faa | Exp 42 (2s stagger, 64GB, run 1) | 1m42s | **all PASS** | Post-restart, clean container | +| 09c6faa | Exp 42 (2s stagger, 64GB, b2b) | 2m27s | **all PASS** | pw-wasm-marimo slow (1m35s anomaly) | +| 37aed6b | 0s stagger, 64GB (5 runs) | 2m-3m | ALL FAIL | pw-jupyter hangs 8/9 every time | +| 176f6f6 | 0s stagger runner, 64GB (run 3) | 2m01s | FAIL | 0s stagger fails on ALL SHAs | +| c26897f | 2s stagger, 64GB, port fix | 1m45s | **all PASS** | First clean run after port fix | +| c26897f | 2s stagger, 64GB, warm cache | 1m47s | **all PASS** | Cache hit confirmed | +| fd85f0a | Exp 41-A+B (2s stagger, 32GB) | 3m08s | 13/2 FAIL | pw-jupyter timeout (0/9), pw-wasm-marimo timeout; smoke 28s | +| 1c49a02 | Exp 41-A+B (2s stagger) | 3m29s | 13/2 FAIL | pw-jupyter timeout (1/9); first bind-mount run | +| 176f6f6 | P=9, /dev/shm fix, 5s stagger | 1m42s | **all PASS** | Best config — baseline for optimization | +| e6ea620 | P=5 + /dev/shm fix | — | all PASS | /dev/shm fix validated | +| 4a7fefc | Exp 35+39 (run 1, fresh) | 2m21s | **15/0 PASS** | Lockfile rebuild (first on new image); build-js 1s | +| 4a7fefc | Exp 35+39 (run 2, b2b) | 2m00s | 14/1 FAIL | Lockfiles unchanged (fix works!); pw-jupyter b2b | +| 4a7fefc | Exp 35+39 (post-restart) | 2m37s | 14/1 FAIL | Lockfiles unchanged after restart; pw-jupyter flaky | +| 4a7fefc | Exp 35+39 (b2b again) | 1m36s | **15/0 PASS** | pw-jupyter 96s; fastest warm run | +| fff99fa | P=4 + tini (run 1) | 2m41s | **14/0 PASS** | Post-restart, lockfile rebuild | +| fff99fa | P=4 + tini (run 2) | 2m01s | **14/0 PASS** | Back-to-back, no lockfile | +| fff99fa | P=4 + tini (run 3) | 2m10s | 13/1 FAIL | pw-jupyter timeout (back-to-back degradation) | +| ef53834 | P=6 + tini (run 1) | 2m58s | 13/1 FAIL | 3/6 pw-jupyter pass | +| ef53834 | P=6 + tini (run 2) | 2m01s | 13/1 FAIL | 0/6 pw-jupyter pass | +| ef53834 | P=4 env override | 2m07s | **14/0 PASS** | Proves P=4 works on this image | +| d369894 | Exp 30 (no PW gate) | 1m25s | 14/0 PASS | Best ever total | +| 076f40f | Exp 33 (P=6 batched) | 1m44s | 14/1 | Best config on old image | +| 2ba10e7 | Exp 34+36 (fixed) | 2m38s | 14/1 | First run post-restart | +| 20fb931 | Exp 37 (`init: true`) | 2m59s | pw-jupyter FAIL | 101 zombies | + +### CPU Profile (commit 4a7fefc, 16 vCPU — OLD SERVER) + +| Phase | Time | Duration | CPU (us+sy) | +|-------|------|----------|-------------| +| Setup + checkout | 0-3s | 3s | ~5% | +| Wave 0 ramp (lint, build-js, pytest, storybook, warmup) | 4-12s | 8s | 21→97% | +| Wave 0 peak (test-python-3.13 + warmup) | 13-18s | 5s | 48-73% | +| Wave 0 tail + warmup finishing | 19-33s | 14s | 6-28% | +| Wheel-dependent launch (all PW + pytest) | 34-55s | 21s | 39-64% | +| Peak concurrent (all PW + pytest overlap) | 56-77s | 21s | 49-94% | +| Jobs finishing, pw-jupyter tail | 78-87s | 9s | 20-35% | +| pw-jupyter alone (kernel I/O bound) | 88-101s | 13s | **4-13%** | + +Note: This profile is from the old 16 vCPU server. On the new 32 vCPU server, CPU is no longer a constraint — the bottleneck is kernel I/O latency and (with 0s stagger) ZMQ/kernel provisioner contention. + +--- + +## Commits (chronological, recent only) + +| Commit | Description | +|--------|-------------| +| 09c6faa | Exp 42: bump watchdog 210→360s for cold starts | +| 7626c67 | Exp 42: cleanup esbuild, pw-results, port range 8889-8897 | +| 6c8590d | Exp 42: restore 2s stagger (0s stagger proven broken) | +| 37aed6b | Remove all stagger (BROKEN — do not use) | +| c26897f | Fix: clean all 9 jupyter ports (8889-8897) | +| 676161f | Docs update | +| fd85f0a | Exp 41: fix awk timing (bc not in container) | +| 1c49a02 | Bind-mount CI scripts + update-runner.sh | +| 29b19fa | Exp 41: delay smoke-test, tighten stagger 5→2s, MCP/server timing | +| 176f6f6 | Integrate /dev/shm fix — P=9, settle=0, --disable-dev-shm-usage | +| e6ea620 | Add --disable-dev-shm-usage for Docker P=5+ | +| 5994612 | jupyterapp kernel check + waitForTimeout removal | +| 200bac6 | JS build cache + ci-queue | +| 5c1e58f | Fix full_build.sh index.es.js check | +| 60618ce | Exp 18+19+20: parallel smoke, relaxed gate → **2m31s** | +| 172158b | Exp 28: early kernel warmup → **2m25s** | +| d369894 | Exp 30: remove heavyweight PW gate → **1m43s** | +| d020744 | Exp 29: marimo auto-retry assertions | +| b2398d5 | Exp 31+32: P=9 abandoned, lean Wave 0 → **1m51s** | +| 076f40f | Exp 33: P=6 batched + re-warmup → **1m44s** | +| 9dcc5e0 | Pre-run cleanup | +| 630cf60 | Exp 34+36: SKIP_INSTALL, renice, pw-server auto-retry | +| da3a7ad | Fix: renice instead of nice for shell functions | +| 2ba10e7 | Fix: don't renice jupyter-warmup, SKIP_INSTALL in pw-jupyter | +| 20fb931 | Exp 37: `init: true` in docker-compose (failed) | +| 46c165c | Exp 37: tini ENTRYPOINT in Dockerfile (**working** — 0 zombies) | +| ef53834 | Revert P=6→6, timeout→120, watchdog→210 (P=6 still broken) | +| fff99fa | Revert P=6→4 (stable baseline) | +| c5a0498 | Research docs committed | +| 4a7fefc | Exp 35: split build-js/test-js + lockfile hash persistence fix | diff --git a/docs/llm/research/cloud-server-comparison.md b/docs/llm/research/cloud-server-comparison.md new file mode 100644 index 000000000..15ef8582c --- /dev/null +++ b/docs/llm/research/cloud-server-comparison.md @@ -0,0 +1,383 @@ +# Cloud Server Comparison for CI + +**Date:** 2026-03-02 +**Context:** Evaluating alternatives to current Hetzner CCX43 for CI workloads. Primary goal: maximize single-thread performance for build/test critical path. + +## Current Setup + +| Spec | Value | +|------|-------| +| Provider | Hetzner Cloud | +| Plan | CCX43 (dedicated vCPU) | +| CPU | AMD EPYC Milan (Zen3), 16 vCPU (8c/16t) | +| RAM | 64 GB | +| Disk | 360 GB | +| Traffic | 4 TB | +| Cost | €96.49/mo (~$104) | +| Geekbench 6 SC | ~2,000 | +| CI total time | ~6 min (vs ~12 min on Depot GitHub runners) | + +### Why single-thread matters + +CI critical path is serial: test-js (24s) → build-wheel (22s) → playwright-jupyter (2m03s). These sequential steps are single-thread bound. More cores don't help; faster cores do. + +--- + +## Provider Comparison + +### Hetzner Cloud + +All-inclusive pricing (traffic, IPv4, DDoS, firewall). API provisioning, Terraform provider. EU datacenters (Falkenstein, Nuremberg, Helsinki) + US (Ashburn, Hillsboro) + Singapore. + +#### Shared vCPU — CX (x86, cheapest) + +| Plan | vCPU | RAM | Disk | Traffic | €/mo | +|------|------|-----|------|---------|------| +| CX23 | 2 | 4 GB | 40 GB | 20 TB | 3.49 | +| CX33 | 4 | 8 GB | 80 GB | 20 TB | 5.49 | +| CX43 | 8 | 16 GB | 160 GB | 20 TB | 9.49 | +| CX53 | 16 | 32 GB | 320 GB | 20 TB | 17.49 | + +#### Shared vCPU — CAX (ARM/Ampere) + +| Plan | vCPU | RAM | Disk | Traffic | €/mo | +|------|------|-----|------|---------|------| +| CAX11 | 2 | 4 GB | 40 GB | 20 TB | 3.79 | +| CAX21 | 4 | 8 GB | 80 GB | 20 TB | 6.49 | +| CAX31 | 8 | 16 GB | 160 GB | 20 TB | 12.49 | +| CAX41 | 16 | 32 GB | 320 GB | 20 TB | 24.49 | + +#### Shared vCPU — CPX Gen2 (AMD Genoa Zen4) + +New generation, substantially better single-thread than CX. Up to 5x perf/€ vs Gen1. + +| Plan | vCPU | RAM | Disk | Traffic | €/mo | +|------|------|-----|------|---------|------| +| CPX12 | 1 | 2 GB | 40 GB | 0.5 TB | 6.49 | +| CPX22 | 2 | 4 GB | 80 GB | 1 TB | 6.49 | +| CPX32 | 4 | 8 GB | 160 GB | 2 TB | 10.99 | +| CPX42 | 8 | 16 GB | 320 GB | 3 TB | 19.99 | +| CPX52 | 12 | 24 GB | 480 GB | 4 TB | 28.49 | +| CPX62 | 16 | 32 GB | 640 GB | 5 TB | 38.99 | + +#### Dedicated vCPU — CCX (current line) + +CPU: EPYC Milan (Zen3) or Genoa (Zen4) depending on host hardware. + +| Plan | vCPU | RAM | Disk | Traffic | €/mo | +|------|------|-----|------|---------|------| +| CCX13 | 2 | 8 GB | 80 GB | 1 TB | 12.49 | +| CCX23 | 4 | 16 GB | 160 GB | 2 TB | 24.49 | +| CCX33 | 8 | 32 GB | 240 GB | 3 TB | 48.49 | +| **CCX43** | **16** | **64 GB** | **360 GB** | **4 TB** | **96.49** | +| CCX53 | 32 | 128 GB | 600 GB | 6 TB | 192.49 | +| CCX63 | 48 | 192 GB | 960 GB | 8 TB | 288.49 | + +#### Hetzner Dedicated (AX line, bare metal) + +Unlimited traffic. No API provisioning — manual order, hours to provision. + +| Model | CPU | Cores | RAM | Storage | €/mo | +|-------|-----|-------|-----|---------|------| +| AX42 | Ryzen 7 PRO 8700GE (Zen4) | 8c/16t | 64 GB DDR5 | 2×512 GB NVMe | 46 | +| AX52 | Ryzen 7 7700 (Zen4) | 8c/16t | 64 GB DDR5 | 2×1 TB NVMe | 59 | +| **AX102** | **Ryzen 9 7950X3D (Zen4+V-Cache)** | **16c/32t** | **128 GB DDR5** | **2×1.92 TB NVMe** | **104** | +| AX162-R | EPYC 9454P (Zen4) | 48c | 256 GB DDR5 ECC | 2×3.84 TB NVMe | 199 | +| AX162-S | EPYC 9454P (Zen4) | 48c | 128 GB DDR5 ECC | 2×3.84 TB NVMe | 199 | + +**Note:** Hetzner raising prices ~25-35% on April 1, 2026. All prices above are pre-increase. + +--- + +### AWS EC2 + +Per-second billing, best tooling (boto3, Terraform, CLI, CDK). Egress expensive ($90/TB). + +#### m8azn (fastest single-thread in any cloud) + +CPU: AMD EPYC 9575F (Turin Zen5), 5.0 GHz. Launched Feb 2026. Available: us-east-1, us-west-2, eu-central-1, ap-northeast-1. + +| Size | vCPU | RAM | $/hr (on-demand) | $/mo (730hr) | +|------|------|-----|-------------------|-------------| +| m8azn.medium | 1 | 4 GB | $0.103 | $75 | +| m8azn.large | 2 | 8 GB | ~$0.207 | ~$151 | +| m8azn.xlarge | 4 | 16 GB | ~$0.413 | ~$301 | +| m8azn.3xlarge | 12 | 48 GB | ~$1.24 | ~$905 | +| m8azn.6xlarge | 24 | 96 GB | ~$2.48 | ~$1,810 | +| m8azn.12xlarge | 48 | 192 GB | ~$4.96 | ~$3,620 | + +PassMark ST: 4,279 (#1 among x86 cloud). Geekbench 6 SC: ~3,500. + +Spot pricing available (~70% discount, risk of interruption). + +#### Other relevant EC2 families + +- **R7iz** — Intel Xeon, up to 3.9 GHz all-core turbo, 20% faster than z1d +- **z1d** — Custom Intel Xeon 8151, 4.0 GHz sustained, legacy high-frequency option +- **c8g** (Graviton 4, ARM) — GB6 SC ~1,930, not competitive on single-thread + +--- + +### OVHcloud + +European provider. Bare metal = hours to provision (no API spinup under 5 min). Monthly billing only on Rise line. + +#### Rise Dedicated Servers + +| Model | CPU | Cores | Clock | RAM | Storage | $/mo | +|-------|-----|-------|-------|-----|---------|------| +| RISE-1 | Xeon E-2386G | 6c/12t | 3.5-4.7 GHz | 32-128 GB | 2×512GB + 2×6TB NVMe | $70 | +| RISE-2 | Xeon E-2388G | 8c/16t | 3.2-4.6 GHz | 32-128 GB | 2×512GB + 2×6TB NVMe | $80 | +| RISE-GAME-1 | Ryzen 5 5600X | 6c/12t | 3.7-4.6 GHz | 32-64 GB | 2×512GB NVMe | $90 | +| RISE-GAME-2 | Ryzen 7 5800X | 8c/16t | 3.8-4.7 GHz | 64-128 GB | 2×960GB NVMe | $104 | +| RISE-3 | Ryzen 9 5900X | 12c/24t | 3.7-4.8 GHz | 32-128 GB | 512GB-6TB NVMe | $110 | +| **RISE-M** | **Ryzen 9 9900X (Zen5)** | **12c/24t** | **4.4-5.6 GHz** | **64 GB** | **512GB NVMe** | **$114** | +| **RISE-L** | **Ryzen 9 9950X (Zen5)** | **16c/32t** | **4.3-5.7 GHz** | **128 GB** | **960GB NVMe** | **$162** | +| RISE-STOR | Ryzen 7 PRO 3700 | 8c/16t | 3.6-4.4 GHz | 32-128 GB | 14TB SAS | $190 | +| Game-1 2026 | **Ryzen 7 9800X3D** | 8c/16t | 4.7-5.2 GHz | 64-256 GB | 2×960GB NVMe | $79-264 | + +RISE-M and RISE-L are Europe only (Germany, France, Poland). Setup fee = 1 month (waived on 12-month commit). REST API + Terraform provider available but provisioning is slow. + +--- + +### Cherry Servers + +Lithuanian company. Trustpilot 4.5/5. Bare metal cloud with **hourly billing** and full automation. + +**Standout features:** Official Terraform provider, Ansible modules, Go/Python SDKs, CLI, REST API. Provisioning: 15-30 minutes. 10 Gbps uplink, 100 TB egress included. + +Data centers: Lithuania, Amsterdam, Stockholm, Chicago, Frankfurt, Singapore. + +| Model | CPU | Cores | RAM | Storage | $/hr | $/mo | Stock | +|-------|-----|-------|-----|---------|------|------|-------| +| Ryzen 7700X | Zen4, 5.4 GHz | 8c/16t | 64 GB | 2×1TB NVMe | $0.318 | $186 | 15 | +| **Ryzen 7950X** | **Zen4, 5.7 GHz** | **16c/32t** | **128 GB DDR5 ECC** | **2×1TB NVMe** | **$0.399** | **$233** | 2 (Chicago) | +| **Ryzen 9950X** | **Zen5, 5.7 GHz** | **16c/32t** | **192 GB DDR5** | **2×1TB NVMe** | **$0.518** | **$303** | 99 (AMS+Stockholm) | +| Threadripper 7965WX | Zen4, 5.3 GHz | 24c/48t | 512 GB | 2×1TB+2×4TB NVMe | $1.961 | $974 | — | +| EPYC 9375F | Turin Zen5, 4.8 GHz | 32c/64t | 384 GB | 2×1TB+2×4TB NVMe | $1.801 | $894 | — | +| EPYC 7313P | Milan | 16c/32t | 64 GB | 2×250GB NVMe | $0.318 | $186 | varies | + +**Provisioning is 15-30 min — does NOT meet <5 min spinup requirement.** + +--- + +### HOSTKEY + +Dutch company (est. 2007). WHTop 8.8/10. REST API, hourly billing, 10-20 min provisioning. + +Data centers: Amsterdam, Zürich, Warsaw, Milan, Madrid, Paris, London, Frankfurt, Helsinki, New York, Istanbul, Moscow. + +| Model | CPU | Cores | RAM | Storage | €/hr | €/mo | +|-------|-----|-------|-----|---------|------|------| +| **Ryzen 9 7950X** | **Zen4, 4.5 GHz** | **16c/32t** | **128 GB** | **2×1.92TB NVMe** | **€0.179** | **€129** | +| Ryzen 9 5950X | Zen3 | 16c/32t | 32-128 GB | 240GB-2×1TB | — | €137-285 | +| Ryzen 9 5900X | Zen3 | 12c/24t | 64 GB | 1TB NVMe | — | €180 | + +No Terraform provider (REST API only). No 9950X or Zen5 options. IPMI access. 1 Gbps / 50 TB traffic. + +**Provisioning is 10-20 min — does NOT meet <5 min spinup requirement.** + +--- + +### Vultr + +US-based. Cloud VMs spin up in ~1-2 minutes. Hourly billing. Terraform provider. + +#### VX1 (Dedicated CPU, EPYC Turin Zen5) + +| Plan | vCPU | RAM | Bandwidth | $/mo | +|------|------|-----|-----------|------| +| VX1 2C | 2 | 8 GB | 5 TB | $43.20 | +| VX1 4C | 4 | 16 GB | 6 TB | $86.40 | +| VX1 8C | 8 | 32 GB | 7 TB | $172.80 | +| VX1 16C | 16 | 64 GB | 8 TB | $345.60 | + +GB6 SC: ~2,350. Block storage (not local NVMe). Server-clocked Turin — lower single-thread than desktop Zen5. + +#### High Frequency (shared, Intel Xeon 3GHz+) + +| Plan | vCPU | RAM | Storage | $/mo | +|------|------|-----|---------|------| +| HF 8-core | 8 | 32 GB | 512 GB NVMe | $192 | +| HF 16-core | 16 | 58 GB | 1 TB NVMe | $320 | + +--- + +### Linode / Akamai + +Cloud VMs, ~1-2 minute spinup, hourly billing, Terraform provider. + +#### Dedicated CPU (3 generations) + +| Plan | Generation | CPU | vCPU | RAM | $/mo | +|------|-----------|-----|------|-----|------| +| Dedicated 16GB | G6 | — | 8 | 16 GB | $144 | +| G7 Dedicated 16x8 | G7 | Zen3 | 8 | 16 GB | $173 | +| **G8 Dedicated 16x8** | **G8** | **Zen5** | **8** | **16 GB** | **$180** | +| G8 Dedicated 32x16 | G8 | Zen5 | 16 | 32 GB | $360 | + +G8 (Zen5) has the best single-thread in cloud VPS outside AWS m8azn. But extremely expensive. + +--- + +### DigitalOcean + +Cloud VMs, ~1 min spinup, per-second billing (since Jan 2026), Terraform provider. + +#### CPU-Optimized Droplets (dedicated vCPU, 2.6 GHz+) + +| Plan | vCPU | RAM | Disk | Transfer | $/mo | +|------|------|-----|------|----------|------| +| c-2 | 2 | 4 GB | 25 GB | 4 TB | $40 | +| c-4 | 4 | 8 GB | 50 GB | 5 TB | $80 | +| c-8 | 8 | 16 GB | 100 GB | 6 TB | $160 | +| c-16 | 16 | 32 GB | 200 GB | 7 TB | $320 | +| c-32 | 32 | 64 GB | 400 GB | 8 TB | $640 | + +No standout single-thread performance. Expensive for what you get. + +--- + +### Cloudflare Containers + +Serverless containers at the edge. Per-second billing. NOT suitable for CI. + +- Max instance: 4 vCPU, 12 GB RAM (too small) +- Ephemeral disk only (no warm caches) +- No SSH, no Docker exec +- CCX43-equivalent running 24/7 would cost ~$665/mo +- Egress: $0.025/GB (1 TB free) + +--- + +## CPU Architecture Overview + +### AMD Lineup (relevant chips) + +| Chip | Line | Arch | Cores | Boost | L3 Cache | GB6 SC | PassMark ST | +|------|------|------|-------|-------|----------|--------|-------------| +| EPYC 9575F | Server (Turin) | Zen5 | 64 | 5.0 GHz | 256 MB | ~3,500 | 4,279 | +| EPYC 9175F | Server (Turin) | Zen5 | 16 | 5.0 GHz | **512 MB** | ~3,500 | 4,244 | +| Ryzen 9 9950X | Desktop | Zen5 | 16 | 5.7 GHz | 64 MB | ~3,150 | ~4,100 | +| Ryzen 9 9950X3D | Desktop | Zen5+V-Cache | 16 | — | 128 MB | ~3,400 | — | +| Ryzen 9 9950X3D2 | Desktop | Zen5+dual V-Cache | 16 | — | **192 MB** | — | — (upcoming) | +| Ryzen 7 9800X3D | Desktop | Zen5+V-Cache | 8 | 5.2 GHz | 96 MB | ~3,300 | — | +| Ryzen 9 9900X | Desktop | Zen5 | 12 | 5.6 GHz | 64 MB | ~3,050 | — | +| Ryzen 9 7950X3D | Desktop | Zen4+V-Cache | 16 | 5.7 GHz | 128 MB | ~2,817 | ~3,884 | +| Ryzen 9 7950X | Desktop | Zen4 | 16 | 5.7 GHz | 64 MB | ~2,750 | — | +| EPYC Genoa 9654 | Server | Zen4 | 96 | 3.7 GHz | 384 MB | ~2,500 | — | +| EPYC Milan 7003 | Server | Zen3 | varies | ~3.5 GHz | 32-256 MB | **~2,000** | ~2,500 | + +### Key insights + +- **Desktop Ryzen clocks 40-60% higher than server EPYC** on single-thread because server chips optimize for core count and power efficiency, not boost clocks +- **V-Cache (3D stacked L3)** gives 10-30% real-world improvement for cache-sensitive workloads (compilers, bundlers, test runners) +- **Zen5 IPC is ~15% better than Zen4**, plus higher clocks +- **EPYC 9175F** (512 MB L3, 16 cores, 5 GHz) is the ideal CI chip but not available from any hosting provider yet +- **ARM (Graviton 4, Ampere)** is ~35-45% behind top x86 on single-thread; wrong direction for ST-bound CI + +### Cache matters for builds + +Compilers, bundlers, and test runners are often cache-bound. Working sets that fit in L3 run dramatically faster: + +| Cache size | Chip examples | +|-----------|---------------| +| 512 MB | EPYC 9175F (not rentable) | +| 192 MB | Ryzen 9950X3D2 (upcoming, not rentable) | +| 128 MB | Ryzen 7950X3D (Hetzner AX102), Ryzen 9950X3D (not rentable) | +| 96 MB | Ryzen 9800X3D (OVH Game-1) | +| 64 MB | Ryzen 9950X (Cherry, OVH RISE-L) | +| 32 MB | EPYC Milan (current CCX43) | + +--- + +## Head-to-Head: Options meeting <5 min API spinup + +Only cloud VM providers qualify. Bare metal (Cherry, HOSTKEY, OVH Rise, Hetzner AX) all take 10+ minutes. + +| | **Current CCX43** | **AWS m8azn.3xl** | **Hetzner CPX62** | **Vultr VX1-8** | **Linode G8-16x8** | +|--|-------------------|-------------------|-------------------|-----------------|---------------------| +| CPU | EPYC Milan (Zen3) | EPYC 9575F (Zen5) | EPYC Genoa (Zen4) | EPYC Turin (Zen5) | Zen5 | +| GB6 SC | **~2,000** | **~3,500** | ~2,500 | ~2,350 | ~2,800 | +| vs current | baseline | **+75%** | +25% | +18% | +40% | +| vCPU | 16 dedicated | 12 | 16 shared | 8 dedicated | 8 dedicated | +| RAM | 64 GB | 48 GB | 32 GB | 32 GB | 16 GB | +| Disk | 360 GB | EBS | 640 GB | Block | 164 GB | +| Spinup | always on | ~60s | ~15s | ~90s | ~90s | +| $/hr | — | $1.24 | ~$0.06 | $0.26 | $0.27 | +| $/mo flat | €96 (~$104) | ~$905 | **€39** | $173 | $180 | +| 60 hrs/mo | $104 (flat) | **$74** | **$39 (flat)** | $156 | $162 | +| Per CI run (6 min) | — | $0.12 | $0.06 (1hr min) | $0.03 | $0.03 | +| Terraform | Cloud API | Yes | Yes | Yes | Yes | +| Traffic | 4 TB | pay/GB ($90/TB) | 5 TB | 7 TB | — | + +--- + +## Bare Metal Options (>5 min spinup, monthly/hourly) + +Best value when running always-on or in long sessions. + +| | **Hetzner AX102** | **OVH RISE-L** | **Cherry 9950X** | **HOSTKEY 7950X** | +|--|-------------------|----------------|-------------------|-------------------| +| CPU | 7950X3D (Zen4+V-Cache) | 9950X (Zen5) | 9950X (Zen5) | 7950X (Zen4) | +| GB6 SC | ~2,817 | ~3,150 | ~3,150 | ~2,750 | +| vs current | +40% | +55% | +55% | +38% | +| Cores | 16c/32t | 16c/32t | 16c/32t | 16c/32t | +| RAM | 128 GB DDR5 | 128 GB DDR4 | 192 GB DDR5 | 128 GB | +| L3 Cache | **128 MB** | 64 MB | 64 MB | 64 MB | +| Storage | 2×1.92 TB NVMe | 960 GB NVMe | 2×1 TB NVMe | 2×1.92 TB NVMe | +| $/mo flat | **€104** | **$162** | $303 | **€129** | +| Hourly | No | No | **$0.518** | **€0.179** | +| 60 hrs/mo | €104 (flat) | $162 (flat) | **$31** | **€11** | +| Spinup | Hours | Hours | 15-30 min | 10-20 min | +| Network | 1 Gbps, unlimited | 1 Gbps, unlimited | 10 Gbps, 100 TB | 1 Gbps, 50 TB | +| Terraform | No | Yes | **Yes** | No | +| Trust level | High | High | Medium-High | Medium | + +--- + +## Recommendations + +### Quick win (no migration) + +**Downgrade CCX43 → CCX33** (€96 → €48/mo). Memory notes say CI timing is identical. Saves €48/mo immediately. + +### Best <5 min spinup + +**AWS m8azn** — 75% faster single-thread than current box. Only option with a dramatic performance improvement that also meets the fast-spinup requirement. Try m8azn.xlarge (4 vCPU, $0.41/hr) first to benchmark. At $0.12 per 6-min CI run, break-even vs CCX33 is ~400 runs/month. + +### Best value (always-on) + +**Hetzner AX102** (€104/mo) — 7950X3D with 128 MB V-Cache, 16 real cores, 40% faster ST than current. Cache advantage helps build workloads specifically. Same price as current CCX43. + +### Best hourly bare metal + +**Cherry Servers 9950X** ($0.518/hr) — Zen5, best ST in bare metal, Terraform provider, 15-30 min spinup. At 60 hrs/mo = $31. Best automation story of any bare metal provider. + +### Cheapest hourly bare metal + +**HOSTKEY 7950X** (€0.179/hr) — 60 hrs/mo = €11. Cheapest way to get 16-core Ryzen. Slightly slower ST than current AX102 option but absurdly cheap for bursty use. + +### Future watch + +- **EPYC 9175F** (512 MB L3, 16c, 5 GHz) — perfect CI chip, not rentable yet +- **Ryzen 9950X3D / 9950X3D2** — 128-192 MB V-Cache + Zen5 IPC, not hosted anywhere yet +- **AWS m8azn spot** — ~$0.34/hr for 12 vCPU, fastest ST at Hetzner-like prices, but interruption risk + +--- + +## Egress / Bandwidth Comparison + +| Provider | Included | Overage | +|----------|----------|---------| +| Hetzner Cloud | 1-20 TB (varies by plan) | €1/TB | +| Hetzner Dedicated | Unlimited | — | +| AWS EC2 | 100 GB free | **$90/TB** | +| OVH Rise | Unlimited | — | +| Cherry Servers | 100 TB | — | +| HOSTKEY | 50 TB | — | +| Vultr | 5-9 TB | $0.01/GB | +| DigitalOcean | 4-9 TB | $0.01/GB | +| Cloudflare R2 | **Free egress** | — | + +AWS egress is 90x more expensive than Hetzner. For CI this is negligible (small payloads) but matters for artifact storage or large Docker pulls. diff --git a/docs/llm/research/doit-task-runner.md b/docs/llm/research/doit-task-runner.md new file mode 100644 index 000000000..7ee2f0ad0 --- /dev/null +++ b/docs/llm/research/doit-task-runner.md @@ -0,0 +1,95 @@ +# doit Task Runner Research + +**Date:** 2026-03-01 +**Context:** Evaluated as CI orchestration tool for Hetzner self-hosted CI. Conclusion: good tool, wrong model for our needs. + +## What doit Is + +Python-based task runner (like Make but in Python). Tasks defined in `dodo.py`, connected by file dependencies. DAG scheduler runs independent tasks in parallel (`doit -n 4`). Fail-fast on first failure. Actively maintained since 2008. + +- Site: https://pydoit.org +- Install: `pip install doit` +- Config: `dodo.py` in project root + +## How It Works + +```python +# dodo.py +def task_build_js(): + return { + 'actions': ['cd packages/buckaroo-js-core && pnpm build'], + 'targets': ['packages/buckaroo-js-core/dist/index.js'], + } + +def task_build_wheel(): + return { + 'actions': ['hatch build'], + 'file_dep': ['packages/buckaroo-js-core/dist/index.js'], + 'targets': ['dist/buckaroo-0.0.0-py3-none-any.whl'], + } + +def task_pw_jupyter(): + return { + 'actions': ['bash scripts/test_playwright_jupyter.sh'], + 'file_dep': ['dist/buckaroo-0.0.0-py3-none-any.whl'], + } +``` + +`doit -n 8` resolves the DAG automatically: build_js → build_wheel → pw_jupyter, with independent tasks running in parallel. + +## Strengths + +- **Pure Python** — no DSL, no YAML, just functions returning dicts +- **File-based dependencies** — tasks declare `file_dep` (inputs) and `targets` (outputs), doit connects the graph +- **Parallel execution** — `-n N` flag, scheduler handles ordering +- **Fail-fast** — stops on first failure +- **Incremental** — skips tasks when inputs haven't changed (like Make) +- **Mature** — 17+ years, good docs, used by Nikola static site generator +- **Zero infrastructure** — just a Python package, runs anywhere + +## Why It Doesn't Fit Our CI Use Case + +**Tasks are atomic.** A task runs to completion, then dependents start. There's no way for a running task to emit an intermediate artifact that unblocks a dependent while the task continues. + +Our build pattern is: + +``` +build_js (12s) → emit JS bundle → build_wheel (5s) → emit wheel +``` + +With doit, these must be 3 separate tasks. That's fine for the DAG, but it means: + +1. The build "job" is fragmented across 3 scheduler slots +2. No way to express "build_js and build_wheel are really one logical job that produces artifacts at two points" + +What we actually want: + +``` +t=0 [build job starts] +t=12 JS bundle ready → pw_storybook, test_js start immediately +t=17 wheel ready → pw_jupyter, pw_marimo, pw_server start immediately +t=?? [build job continues with pytest, lint, etc.] +``` + +This is a **streaming dependency** pattern — a single task emitting artifacts mid-execution to unblock others. doit (and Make, and every DAG runner) models tasks as atomic units. The right tool for this is either: + +- A CI system (GitHub Actions does this with artifact upload + dependent jobs) +- A custom asyncio script with `Event` objects (~50 lines) + +## Where doit Would Work + +If we accepted splitting the build into separate tasks (build_js, build_wheel, lint, test_js, test_python, pw_storybook, pw_jupyter, etc.), doit would orchestrate them well. The tradeoff: ~5s of scheduler overhead between build_js completing and build_wheel starting (task teardown + next task pickup), and the `dodo.py` needs `uptodate: [False]` on every task since CI always runs everything. + +This is a reasonable fallback if the custom asyncio approach proves too brittle. + +## Other Tools Evaluated + +| Tool | Verdict | Why | +|------|---------|-----| +| **pypyr** | YAML-based alternative to doit | Same atomic-task limitation | +| **invoke** | Too simple | No DAG, no parallel | +| **nox** | Wrong domain | Multi-env Python testing, not CI orchestration | +| **snakemake** | Overkill | Bioinformatics DSL, steep learning curve | +| **luigi** | Outdated | Heavy, no mid-task emission either | +| **airflow/prefect** | Way overkill | Enterprise data pipeline orchestration | +| **Make** | Works but unreadable | Same atomic-task model, worse syntax for complex logic | diff --git a/docs/llm/research/galata-pattern-adoption.md b/docs/llm/research/galata-pattern-adoption.md new file mode 100644 index 000000000..589378d9a --- /dev/null +++ b/docs/llm/research/galata-pattern-adoption.md @@ -0,0 +1,314 @@ +# Galata Pattern Adoption in Buckaroo Playwright Tests + +**Date:** 2026-03-03 +**Context:** Audit of which JupyterLab Galata testing patterns Buckaroo has adopted, which it hasn't, and whether the gaps matter given current CI reliability (Exp 30: 7/7 pw-jupyter, 1m43s total). + +--- + +## What Is Galata? + +Galata is JupyterLab's official end-to-end testing framework, built on Playwright. It lives at `jupyterlab/jupyterlab/galata/` in the monorepo. Named after the Galata Tower in Istanbul, it was originally developed at Bloomberg by Mehmet Bektas before being transferred to the JupyterLab organization. + +Galata provides: +- **Playwright fixtures** for JupyterLab state isolation (`kernels`, `sessions`, `tmpPath`) +- **High-level API** — `page.notebook.createNew()`, `page.notebook.runCell()`, `page.notebook.waitForRun()` +- **`window.galata` browser global** for event listening (dialogs, notifications) +- **Visual regression testing** with built-in screenshot comparison +- **Server lifecycle management** — starts/stops JupyterLab for tests + +Buckaroo doesn't import Galata directly — it tests a *widget inside* JupyterLab, not JupyterLab itself. But the testing problems are identical (kernel readiness, render completion, cell execution verification), and Galata's battle-tested solutions apply. + +Key source files in JupyterLab: +- `galata/src/jupyterlabpage.ts` — app startup, `window.jupyterapp.started` +- `galata/src/helpers/notebook.ts` — `waitForRun()`, execution count verification +- `galata/src/utils.ts` — `waitForCondition()` polling utility + +--- + +## Pattern Scorecard + +| # | Pattern | Galata | Buckaroo | Where | Impact | +|---|---------|--------|----------|-------|--------| +| 1 | Internal kernel state check | Yes | **Yes** | `integration.spec.ts:116-123` | Critical — 80% → 100% pass rate | +| 2 | `expect().toPass()` polling | Yes | **Yes** | `server.spec.ts:163`, `server-buckaroo-summary.spec.ts:80,104` | 13s saved, eliminated view-switch flakes | +| 3 | Auto-retrying `toHaveText()` | Yes | **Yes** | `marimo.spec.ts:76-80, 120-122` | Eliminated AG-Grid data loading race | +| 4 | Grid readiness helpers | Yes | **Yes** | `server-helpers.ts:27-30`, `marimo.spec.ts:8-13` | Consistent wait pattern across suites | +| 5 | Kernel shutdown between tests | Yes | **Yes** | `test_playwright_jupyter.sh:298-316` | Prevents kernel state leakage | +| 6 | `jupyterapp.started` wait | Yes | **No** | — | Low risk (see analysis) | +| 7 | Execution count verification | Yes | **No** | — | Covered by retry loop | +| 8 | Animation frame stability | Yes | **No** | — | No reported AG-Grid flakes | +| 9 | `waitForCondition` utility | Yes | **No** | — | Ad-hoc alternatives work | + +**Score: 5/9 adopted.** The 5 adopted patterns are the high-impact ones. The 4 missing are refinements with diminishing returns at current reliability levels. + +--- + +## Adopted Patterns — Detail + +### 1. Internal Kernel State Check (Critical) + +**Galata's approach** (`galata/src/jupyterlabpage.ts:715-724`): +```typescript +await page.evaluate(async () => { + if (typeof window.jupyterapp === 'object') { + await window.jupyterapp.started; + return true; + } + return false; +}); +``` + +**Buckaroo's implementation** (`integration.spec.ts:116-123`, `infinite-scroll-transcript.spec.ts:43-49`): +```typescript +await page.waitForFunction(() => { + const app = (window as any).jupyterapp; + if (!app) return false; + const widget = app.shell.currentWidget; + if (!widget?.sessionContext?.session?.kernel) return false; + const kernel = widget.sessionContext.session.kernel; + return kernel.connectionStatus === 'connected' && kernel.status === 'idle'; +}, { timeout: 60000 }); +``` + +This was the single most impactful change in the entire CI optimization effort (Exp 21). It checks the exact same `session.kernel` that `CodeCell.execute()` checks at `widget.ts:1750`. Before this, DOM-based checks (`ExecutionIndicator[data-status="idle"]`) burned timeout budgets when the element didn't exist yet, then proceeded with `session.kernel === null` — causing silent execution drops. + +**Impact:** Pass rate jumped from 80% to 100% (10/10 runs at commit 5994612). Still 100% at Exp 30 (7/7) even without the heavyweight Playwright gate. + +Used in: `integration.spec.ts`, `infinite-scroll-transcript.spec.ts` (both tests in the Jupyter suite). + +### 2. `expect().toPass()` Polling + +**Galata's equivalent:** `waitForCondition()` in `galata/src/utils.ts:174-203` — polls a function every 50ms until true or timeout. + +**Buckaroo's implementation** (`server.spec.ts:160-163`): +```typescript +await expect(async () => { + const val = await getCellText(page, COL.name, 0); + expect(val).not.toBe('Alice'); +}).toPass({ timeout: 5000 }); +``` + +Also used in `server-buckaroo-summary.spec.ts:77-80` for waiting on pinned row count changes after view switching: +```typescript +await expect(async () => { + const count = await getPinnedRowCount(page); + expect(count).toBeGreaterThan(mainPinnedCount); +}).toPass({ timeout: 10000 }); +``` + +**Impact:** Replaced `waitForTimeout(3000)` calls in server specs, saving 13s total (Exp 15). The `toPass()` pattern returns as soon as the condition is met rather than always waiting the full duration. + +Used in: `server.spec.ts` (1 instance), `server-buckaroo-summary.spec.ts` (2 instances), `server-buckaroo-search.spec.ts` (1 instance). Total: 4 call sites. + +### 3. Auto-Retrying `toHaveText()` + +**Galata's equivalent:** Galata's `waitForRun()` verifies execution count is set — a form of "retry until the expected value appears." + +**Buckaroo's implementation** (`marimo.spec.ts:76-80`): +```typescript +// Return locators so callers can use Playwright's auto-retrying toHaveText() +await expect(cellLocator(firstWidget, 'a', 0)).toHaveText('Alice'); +await expect(cellLocator(firstWidget, 'a', 1)).toHaveText('Bob'); +``` + +This replaced one-shot `innerText()` calls that had a race condition: AG-Grid renders the cell DOM element before the kernel sends actual data. `innerText()` catches the cell in a loading state and fails immediately. `toHaveText()` retries automatically until the expected value appears or timeout expires. + +**Impact:** Implemented in Exp 29. Eliminates the AG-Grid data loading race in marimo tests (Category B flakes from `marimo-playwright-flakiness.md`). + +Used in: `marimo.spec.ts` (8 call sites). + +### 4. Grid Readiness Helpers + +**Galata's equivalent:** Galata provides `page.notebook.waitForCellOutput()` and similar scoped helpers. + +**Buckaroo has three variants** for different contexts: + +Server context (`server-helpers.ts:27-30`): +```typescript +export async function waitForGrid(page: Page) { + await page.locator('.ag-overlay').first().waitFor({ state: 'hidden', timeout: 15_000 }); + await page.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 15_000 }); +} +``` + +Jupyter context (`integration.spec.ts:10-14`): +```typescript +async function waitForAgGrid(outputArea: any, timeout = DEFAULT_TIMEOUT) { + await outputArea.locator('.ag-root-wrapper').first().waitFor({ state: 'attached', timeout }); + await outputArea.locator('.ag-cell').first().waitFor({ state: 'visible', timeout }); +} +``` + +Marimo context (`marimo.spec.ts:8-13`): +```typescript +async function waitForGrid(page: Page) { + await page.locator('.buckaroo_anywidget').first().waitFor({ state: 'visible', timeout: 60_000 }); + await page.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); +} +``` + +Each is tuned to its environment: server waits for overlay to hide, Jupyter scopes to an output area and uses `attached` (cells may be offscreen), marimo waits for the anywidget container first. + +### 5. Kernel Shutdown Between Tests + +**Galata's approach:** Fixtures automatically manage kernel lifecycle — `kernels` fixture cleans up after each test. + +**Buckaroo's implementation** (`test_playwright_jupyter.sh`): +```bash +KERNELS=$(curl -s "http://localhost:$port/api/kernels?token=$JUPYTER_TOKEN") +echo "$KERNELS" | grep -oE '[0-9a-f]{8}-[0-9a-f]{4}-...-[0-9a-f]{12}' | while read kid; do + curl -s -X DELETE "http://localhost:$port/api/kernels/$kid?token=$JUPYTER_TOKEN" +done +``` + +Also clears workspace state (`rm -rf ~/.jupyter/lab/workspaces`) to prevent JupyterLab from restoring previous notebook sessions. + +--- + +## Not Adopted — Analysis + +### 6. `jupyterapp.started` Wait + +**What Galata does** (`galata/src/jupyterlabpage.ts:715-724`): +```typescript +await page.evaluate(async () => { + await window.jupyterapp.started; // Waits for ALL plugins to load +}); +``` + +`jupyterapp.started` is a Promise that resolves when all JupyterLab extensions (including anywidget) have finished their `activate()` calls. + +**Why Buckaroo skips it:** The existing kernel state check (`pattern 1`) implicitly waits for the app to be loaded — `window.jupyterapp` is undefined until the app initializes, and the kernel check returns `false` until the full session→kernel chain is established. Adding an explicit `started` wait would be belt-and-suspenders. + +**Risk of not having it:** If anywidget's plugin loads after the kernel becomes idle (theoretically possible if extension activation is slow), the kernel check would pass but widget rendering could fail. In practice this hasn't been observed — anywidget is a lightweight extension and activates quickly. + +**Recommendation:** Add it as a cheap insurance line before the kernel check. One additional `waitForFunction` call, ~0s cost: +```typescript +await page.waitForFunction(() => + typeof (window as any).jupyterapp === 'object', + { timeout: 30000 } +); +``` + +### 7. Execution Count Verification + +**What Galata does** (`galata/src/helpers/notebook.ts:468-480`): +```typescript +async waitForRun(cellIndex?: number): Promise { + // Stage 1: Wait for status bar to show "Idle" + await this.page.locator('#jp-main-statusbar >> text=Idle').waitFor(); + // Stage 2: Verify execution count is set + done = await this.page.evaluate(cellIdx => { + return window.galata.haveBeenExecuted(cellIdx); + }, cellIndex); +} +``` + +This two-stage check confirms the kernel actually processed the cell (execution count changes from `[ ]:` or `[*]:` to `[1]:`). + +**What Buckaroo does instead:** Waits for output to appear in `.jp-OutputArea-output`, with a retry loop that re-sends `Shift+Enter` every 15s if no output arrives. This is cruder but effective — if output appears, the cell definitely executed. + +**Risk of not having it:** If a cell produces no visible output (e.g., `import buckaroo` with no display call), the output check would time out even though execution succeeded. Currently all test notebooks produce widget output, so this isn't an issue. + +**Recommendation:** Not needed unless test notebooks are added that don't produce visible output. + +### 8. Animation Frame Stability + +**What Galata does** (`galata/src/helpers/notebook.ts:1290-1331`): +```typescript +// Wait until content is unchanged for 10 consecutive animation frames +let framesWithoutChange = 0; +let previousContent = element.innerHTML; +const check = () => { + requestAnimationFrame(() => { + const newContent = element.innerHTML; + if (previousContent === newContent) framesWithoutChange++; + else framesWithoutChange = 0; + previousContent = newContent; + (framesWithoutChange < 10) ? check() : resolve(); + }); +}; +``` + +This catches progressive rendering — content exists but is still changing. + +**Why Buckaroo doesn't need it (yet):** AG-Grid's rendering is fast once data arrives. The `waitFor({ state: 'visible' })` on `.ag-cell` catches the point where cells exist. The `toHaveText()` pattern (marimo tests) auto-retries until the correct data appears. No test failures have been traced to partial AG-Grid renders. + +**When it would matter:** If Buckaroo adds screenshot comparison tests (visual regression), partial renders would produce flaky diffs. The animation frame check would stabilize screenshots. + +**Recommendation:** Not needed for functional tests. Add if visual regression testing is introduced. + +### 9. `waitForCondition` Utility + +**What Galata does** (`galata/src/utils.ts:174-203`): +```typescript +async function waitForCondition( + fn: () => boolean | Promise, + timeout: number = 15000 +): Promise { /* 50ms polling loop */ } +``` + +**What Buckaroo uses instead:** A mix of Playwright's built-in `waitForFunction()`, `waitFor()` on locators, `expect().toPass()`, and ad-hoc retry loops. These are more verbose but each is tuned to its specific context. + +**Recommendation:** Not worth extracting — Playwright's built-in primitives cover all current use cases. + +--- + +## Remaining `waitForTimeout` Usage + +Despite the Galata-inspired improvements, **66 `waitForTimeout` calls** remain across the test suite: + +| File | Count | Context | +|------|-------|---------| +| `theme-screenshots-jupyter.spec.ts` | 10 | Screenshot stabilization waits | +| `record-one-second-gap-transcript.spec.ts` | 9 | Intentional timing delays for transcript recording | +| `small-df-scroll.spec.ts` | 7 | Scroll stabilization waits | +| `message-box-streaming.spec.ts` | 7 | Streaming message timing | +| `integration-batch.spec.ts` | 6 | Cell execution delays | +| `theme-screenshots-marimo.spec.ts` | 4 | Screenshot stabilization | +| `transcript-replayer.spec.ts` | 4 | Replay timing | +| `theme-screenshots-server.spec.ts` | 5 | Screenshot stabilization | +| `infinite-scroll-transcript.spec.ts` | 3 | Retry loop + scroll delay | +| Other files | 11 | Various | + +**Which ones matter for CI speed:** +- `theme-screenshots-*.spec.ts` — screenshot tests need visual stability; fixed waits are appropriate here +- `record-one-second-gap-transcript.spec.ts` — intentional timing delays to test transcript recording at specific intervals; fixed waits are the point +- `integration-batch.spec.ts` — the 200-800ms waits between cell executions could be replaced with output detection, but this file tests batch execution patterns where timing matters +- `small-df-scroll.spec.ts` — 1500-3000ms waits after scrolling could be replaced with `waitForFunction` checking visible row indices + +The CI-critical specs (`integration.spec.ts`, `server.spec.ts`, `marimo.spec.ts`) have already been cleaned up. The remaining `waitForTimeout` calls are in Storybook specs (not on the critical path) or serve intentional timing purposes. + +--- + +## Connections to CI Experiments + +| Experiment | Galata Pattern Applied | Result | +|------------|----------------------|--------| +| Exp 15 | `expect().toPass()` replaced `waitForTimeout(3000)` in server specs | pw-server 50s → 37s | +| Exp 21 | `window.jupyterapp` kernel state check | pw-jupyter 80% → 100% pass rate | +| Exp 29 | `toHaveText()` auto-retrying assertions in marimo specs | Eliminated data loading race | +| Exp 30 | Combined effect: no heavyweight gate needed | 7/7 pw-jupyter, total 1m43s | + +The Galata-inspired changes account for approximately: +- **100% of the pw-jupyter reliability improvement** (Exp 21 kernel check) +- **13s of pw-server time savings** (Exp 15 `toPass()` polling) +- **Elimination of the heavyweight Playwright gate** (Exp 30 — reliable kernel check means pw-jupyter can run concurrently with other Playwright jobs) + +--- + +## Recommendations + +### Worth doing (cheap, low-risk) + +1. **Add `jupyterapp.started` wait** before the kernel check in `integration.spec.ts` and `infinite-scroll-transcript.spec.ts`. One line, ensures all extensions are activated. Cost: ~0s (app is already loaded by the time the kernel check runs). + +### Not worth doing (current reliability is sufficient) + +2. **Execution count verification** — retry loop already handles silent drops. Would only matter for notebooks with no visible output (none exist). + +3. **Animation frame stability** — AG-Grid renders quickly, no reported flakes from partial renders. Add if visual regression testing is introduced. + +4. **Centralized `waitForCondition` utility** — Playwright's built-in primitives are sufficient. Extracting a utility would add abstraction without fixing any current problem. + +5. **Replace remaining `waitForTimeout` calls** — the 66 remaining calls are in Storybook/screenshot specs (not on critical path) or serve intentional timing purposes. The CI-critical specs are already clean. diff --git a/docs/llm/research/hetzner-ci-bringup.md b/docs/llm/research/hetzner-ci-bringup.md new file mode 100644 index 000000000..d0b5df9c9 --- /dev/null +++ b/docs/llm/research/hetzner-ci-bringup.md @@ -0,0 +1,143 @@ +# Hetzner CI Bringup Log + +Status as of 2026-03-01. Documents the actual provisioning run, all bugs found and fixed, and final timing results. + +## Server + +- **Type:** CCX33 (8 vCPU, 32 GB RAM) +- **Location:** Ash (Ashburn, VA) +- **IP:** 5.161.210.126 +- **Server ID:** 122446585 +- **OS:** Ubuntu 24.04 + +## How to trigger a run manually (SSH-based) + +```bash +ssh root@5.161.210.126 +docker exec buckaroo-ci bash /opt/ci-runner/run-ci.sh \ + > /opt/ci/logs/manual.log 2>&1 & +tail -f /opt/ci/logs/manual.log +``` + +Note: use `/opt/ci-runner/run-ci.sh` (baked into image), not `/repo/ci/hetzner/run-ci.sh` +(that path disappears when CI checks out a main-branch SHA that predates the CI files). + +--- + +## All Bugs Fixed During Bringup + +### 1. cloud-init: `owner: ci:ci` in `write_files` +`write_files` runs before `runcmd`, so the `ci` user doesn't exist yet. Removed `owner:` field; chown happens in `runcmd` after `useradd`. + +### 2. cloud-init: YAML dict parse on `echo` with `:` +```yaml +- echo "cloud-init complete. Fill in /opt/ci/.env then: systemctl start buckaroo-webhook" +``` +The `: ` caused YAML to parse it as a key-value dict, breaking all of `runcmd`. Fixed with `|` block scalar. + +### 3. cloud-init: cloned `main`, CI files only on `docs/ci-research` +CI implementation had not been pushed to remote at provision time. Docker build failed with `lstat ci: no such file or directory`. Fixed: push branch first; cloud-init now clones `--branch main` explicitly. + +### 4. Dockerfile: missing C compiler for `cffi`/`cryptography` +`buckaroo[mcp]` pulls `mcp` → `pyjwt[crypto]` → `cryptography` → `cffi`, which needs a C compiler. Added `build-essential libffi-dev libssl-dev`. (Note: cffi has manylinux pre-built wheels; worth investigating why uv falls back to source compilation here.) + +### 5. status.sh: `set -u` abort without `GITHUB_TOKEN` +`${GITHUB_TOKEN}` reference with `set -uo pipefail` would abort the run if unset. Fixed: `_github_status` now checks `[[ -z "${GITHUB_TOKEN:-}" ]]` and returns early, printing a note. + +### 6. git `safe.directory` inside container +Bind-mounted `/repo` is owned by `ci` on host but container runs as root. Git refused to operate on it, silently failing `git checkout -f $SHA` (no `set -e`). Fixed: `git config --system --add safe.directory /repo` baked into Dockerfile. + +### 7. CI scripts deleted by `git checkout` +`run-ci.sh` checks out arbitrary SHAs, which wipes `ci/hetzner/` if the SHA is a main-branch commit (predates those files). The runner script deleted itself mid-run. Fixed: Dockerfile COPYs `ci/hetzner/run-ci.sh` and `lib/` to `/opt/ci-runner/` (image-stable path). `run-ci.sh` sources lib from there. + +### 8. `pl-series-hash` race condition (3.13 venv) +`job_lint_python` ran `uv sync --dev --no-install-project` on the 3.13 venv. This strips `--all-extras` packages (including `pl-series-hash`, which is in optional extras) because extras require the project to be installed. This ran in parallel with `job_test_python_3.13`, randomly removing `pl-series-hash` before collection. Fixed: removed the `uv sync` from `job_lint_python` — ruff is already installed in the venv from the image build. + +### 9. JupyterLab refuses to start as root +`scripts/test_playwright_jupyter.sh` starts JupyterLab without `--allow-root`. Container runs as root. Fixed by baking `/root/.jupyter/jupyter_lab_config.py` with `c.ServerApp.allow_root = True` into the image — avoids patching every test script. + +--- + +## Known Docker-Incompatible Tests (disabled in run-ci.sh) + +These tests pass on Depot/GitHub Actions but fail in Docker. Disabled with `--deselect` until tuned: + +| Test | Reason | +|---|---| +| `test_mp_timeout_pass` | `forkserver` subprocess spawn takes >1s in Docker; CI timeout is 1.0s | +| `test_mp_fail_then_normal` | Same | +| `test_server_killed_on_parent_death` | SIGKILL propagation differs in container PID namespaces | + +Python 3.14.0a5 is skipped entirely — segfaults on pytest startup (CPython pre-release bug). + +--- + +## Clean Run Results (Run 6 — cold caches) + +**Commit:** `7b6a05c` (latest main) +**Run:** 21:00:04 → 21:09:03 UTC +**Total wall time: 8m59s** +**Result: ALL JOBS PASSED** + +| Phase | Jobs | Wall time | +|---|---|---| +| Phase 1 (parallel) | lint-python, test-js, test-python-3.13 | 1m24s | +| Phase 2 | build-wheel | 20s | +| Phase 3 (sequential) | test-python-3.11, 3.12, 3.14 | 2m33s | +| Phase 4 (parallel) | test-mcp-wheel, smoke-test-extras | 23s | +| Phase 5 (sequential) | playwright × 5 | 4m42s | + +--- + +## Warm Cache Run Results (Run 7) + +**Commit:** `7b6a05c` (same) +**Run:** 02:26:13 → 02:34:36 UTC +**Total wall time: 8m23s** +**Result: ALL JOBS PASSED** + +| Phase | Jobs | Wall time | +|---|---|---| +| Phase 1 (parallel) | lint-python, test-js, test-python-3.13 | 1m13s | +| Phase 2 | build-wheel | 20s | +| Phase 3 (sequential) | test-python-3.11, 3.12, 3.14 | 2m23s | +| Phase 4 (parallel) | test-mcp-wheel, smoke-test-extras | 20s | +| Phase 5 (sequential) | playwright × 5 | 4m05s | + +**Warm vs cold delta: ~36s** — saved mainly in Phase 1 (pnpm/uv sync skipped) and Phase 5 (no playwright install). + +--- + +## Run 8 — Phase 3 Parallelised + +**Commit:** `7b6a05c` +**Run:** 02:44:02 → 02:51:23 UTC +**Total wall time: 7m21s** +**Result: ALL JOBS PASSED** + +| Phase | Jobs | Wall time | +|---|---|---| +| Phase 1 (parallel) | lint-python, test-js, test-python-3.13 | 1m18s | +| Phase 2 | build-wheel | 23s | +| Phase 3 (parallel) | test-python-3.11, 3.12, 3.14 | **1m16s** (was 2m23s) | +| Phase 4 (parallel) | test-mcp-wheel, smoke-test-extras | 20s | +| Phase 5 (sequential) | playwright × 5 | 4m04s | + +**Phase 3 saving: 1m07s** — 3.11 (1m14s) and 3.12 (1m16s) ran concurrently. + +### Summary Notes + +- **7m21s** is now the steady-state benchmark. Depot was ~12 minutes; CCX33 is ~40% faster. +- playwright-jupyter dominates Phase 5 (~93s) — it starts JupyterLab and runs all 9 notebooks. +- The dep-rebuild step (lockfiles changed) adds ~36s; happens on <5% of pushes. +- Further gains possible by parallelising playwright tests that don't conflict on ports. + +--- + +## Next Steps + +1. Add git server (bare repo + post-receive hook) for push-triggered runs +2. Add GITHUB_TOKEN + webhook for PR status integration +3. Investigate `cffi` source compilation — should be using manylinux wheels +4. Tune mp_timeout values for Docker (forkserver spawn latency ~1.5s on CCX33) +5. Consider running Python 3.11/3.12 in parallel (Phase 3) — would save ~80s wall time diff --git a/docs/llm/research/hetzner-dag-ci-plan.md b/docs/llm/research/hetzner-dag-ci-plan.md new file mode 100644 index 000000000..e74a9a655 --- /dev/null +++ b/docs/llm/research/hetzner-dag-ci-plan.md @@ -0,0 +1,208 @@ +# Plan: DAG-based CI execution to minimize wall time + +## Context + +Current Hetzner CI takes ~5m56s with a 5-phase sequential structure (run 26, commit 1759612). Depot Linux-only critical path is 3:27. The phase structure is overly conservative — many jobs wait for phases they don't actually depend on. + +**Root cause:** The phased approach forces jobs to wait for entire phases to complete, even when they only depend on one specific job. For example, test-python-3.11/3.12/3.14 wait for build-wheel (Phase 2), but they don't need the wheel at all — they use editable install with placeholder static files. Similarly, playwright-storybook/marimo/wasm-marimo don't need the wheel but wait until Phase 5a (after phases 1-4 complete). + +**Goal:** Restructure run-ci.sh from phases to a dependency DAG. Each job starts as soon as its specific dependencies are met, not when an entire phase completes. + +## Current phase structure (run-ci.sh as of aea3201) + +``` +Phase 1 (parallel): lint-python, test-js, test-python-3.13 +Phase 2 (sequential): build-wheel ← waits for ALL of phase 1 +Phase 3 (parallel): test-python-3.11, 3.12, 3.14 ← waits for phase 2 (unnecessary) +Phase 4 (parallel): test-mcp-wheel, smoke-test-extras ← waits for phase 3 (unnecessary) +Phase 5a (parallel): pw-storybook, pw-server, pw-marimo, pw-wasm ← waits for phase 4 (unnecessary) +Phase 5b (sequential): pw-jupyter (PARALLEL=1) ← waits for phase 5a (unnecessary) +``` + +Timing (run 26): Phase 1: 1m15s | Phase 2: 22s | Phase 3: 1m16s | Phase 4: 20s | Phase 5a: 59s | Phase 5b: 1m44s + +## Actual dependency graph + +``` +No dependencies (start immediately): + lint-python + test-python-3.11 + test-python-3.12 + test-python-3.13 + test-python-3.14 + playwright-storybook (builds its own storybook server, no wheel needed) + playwright-marimo (uses uv run marimo with pre-synced 3.13 venv, no wheel) + playwright-wasm-marimo (static HTML files, no wheel) + +Depends on test-js completing (pnpm build writes to packages/buckaroo-js-core/dist/): + build-wheel (full_build.sh calls pnpm build, conflicts with test-js pnpm build) + +test-js has no deps — starts immediately, build-wheel waits only for it. + +Depends on build-wheel completing (needs dist/buckaroo-*.whl): + test-mcp-wheel (installs wheel[mcp] into isolated venv) + smoke-test-extras (installs wheel with each extra into isolated venvs) + playwright-server (installs wheel[mcp] into clean venv — see scripts/test_playwright_server.sh) + playwright-jupyter (installs wheel + polars + jupyterlab into isolated venv) +``` + +### Venv conflicts (already resolved) + +- `job_playwright_jupyter` creates `/tmp/ci-jupyter-$$` — no conflict with shared venvs +- `job_playwright_marimo` and `job_playwright_wasm_marimo` use `UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13` read-only — no conflict with `job_test_python 3.13` which runs `uv sync` (both are in Phase 1 currently but `uv sync` is fast and atomic) +- `job_lint_python` does NOT run `uv sync` — avoids racing with test-python-3.13 + +## Critical path analysis + +``` +test-js (~24s) → build-wheel (~22s) → playwright-jupyter (~104s) = ~2m30s +``` + +Everything else finishes within that window: +- All pytest runs: ~63s (start at t=0, done well before build-wheel finishes) +- lint-python: ~5s +- pw-storybook: ~10s (start at t=0) +- pw-marimo: ~56s (start at t=0) +- pw-wasm-marimo: ~35s (start at t=0) +- pw-server: ~58s (starts after build-wheel at ~46s, done at ~104s) +- test-mcp-wheel: ~12s (starts after build-wheel) +- smoke-test-extras: ~20s (starts after build-wheel) + +**Projected total: ~2m30s** (vs 5m56s current, vs ~12min Depot) + +## Implementation + +### Changes to `ci/hetzner/run-ci.sh` + +Replace the 5-phase structure (lines 277-334) with DAG-based execution. Keep everything else (job definitions, setup, `--phase=5b`, wheel cache, lockfile check, status reporting). + +```bash +# ── Wave 0: Everything with no dependencies (start immediately) ────────── +log "=== Starting all independent jobs ===" + +run_job lint-python job_lint_python & PID_LINT=$! +run_job test-js job_test_js & PID_TESTJS=$! +run_job test-python-3.11 bash -c "job_test_python 3.11" & PID_PY311=$! +run_job test-python-3.12 bash -c "job_test_python 3.12" & PID_PY312=$! +run_job test-python-3.13 bash -c "job_test_python 3.13" & PID_PY313=$! +run_job test-python-3.14 bash -c "job_test_python 3.14" & PID_PY314=$! +run_job playwright-storybook job_playwright_storybook & PID_PW_SB=$! +run_job playwright-marimo job_playwright_marimo & PID_PW_MA=$! +run_job playwright-wasm-marimo job_playwright_wasm_marimo & PID_PW_WM=$! + +# ── Wait for test-js only, then build wheel ─────────────────────────────── +wait $PID_TESTJS || OVERALL=1 +log "=== test-js done — starting build-wheel ===" + +run_job build-wheel job_build_wheel || OVERALL=1 + +# Cache wheel by SHA so --phase=5b can skip the build on re-runs. +mkdir -p "$WHEEL_CACHE_DIR" +cp dist/buckaroo-*.whl "$WHEEL_CACHE_DIR/" 2>/dev/null || true +log "Cached wheel → $WHEEL_CACHE_DIR" + +# ── Wheel-dependent jobs (start as soon as wheel exists) ────────────────── +log "=== build-wheel done — starting wheel-dependent jobs ===" + +run_job test-mcp-wheel job_test_mcp_wheel & PID_MCP=$! +run_job smoke-test-extras job_smoke_test_extras & PID_SMOKE=$! +run_job playwright-server job_playwright_server & PID_PW_SV=$! +run_job playwright-jupyter job_playwright_jupyter & PID_PW_JP=$! + +# ── Wait for everything ────────────────────────────────────────────────── +wait $PID_LINT || OVERALL=1 +wait $PID_PY311 || OVERALL=1 +wait $PID_PY312 || OVERALL=1 +wait $PID_PY313 || OVERALL=1 +wait $PID_PY314 || OVERALL=1 +wait $PID_PW_SB || OVERALL=1 +wait $PID_PW_MA || OVERALL=1 +wait $PID_PW_WM || OVERALL=1 +wait $PID_MCP || OVERALL=1 +wait $PID_SMOKE || OVERALL=1 +wait $PID_PW_SV || OVERALL=1 +wait $PID_PW_JP || OVERALL=1 +``` + +### No other changes needed + +- Job functions: unchanged (all already handle their own venvs/ports) +- `run_job` helper: unchanged +- `--phase=5b` routing: unchanged +- Lockfile check / status reporting: unchanged +- Wheel cache: unchanged (just moves to after build-wheel instead of after phase 2) + +### Timing comparison + +``` + Current (phased) DAG +lint-python t=0, done t=5 t=0, done t=5 +test-js t=0, done t=24 t=0, done t=24 +test-python-3.13 t=0, done t=75 t=0, done t=63 +build-wheel t=75, done t=97 t=24, done t=46 ← 51s earlier start +test-python-3.11 t=97, done t=160 t=0, done t=63 ← 97s earlier start +test-python-3.12 t=97, done t=160 t=0, done t=63 ← 97s earlier start +test-python-3.14 t=97, done t=160 t=0, done t=5 ← 97s earlier start +test-mcp-wheel t=160, done t=172 t=46, done t=58 +smoke-test-extras t=160, done t=180 t=46, done t=66 +pw-storybook t=180, done t=190 t=0, done t=10 ← 180s earlier start +pw-server t=180, done t=238 t=46, done t=104 +pw-marimo t=180, done t=236 t=0, done t=56 ← 180s earlier start +pw-wasm-marimo t=180, done t=215 t=0, done t=35 ← 180s earlier start +pw-jupyter t=238, done t=342 t=46, done t=150 ← 192s earlier start + ───────────────── ─────────────── + TOTAL: ~5m42s TOTAL: ~2m30s +``` + +## CPU budget (8 vCPU CCX33) + +Peak concurrency at t=0: 9 jobs. But: +- lint-python finishes in ~5s (1 core freed) +- test-python-3.14 skips pytest (finishes in ~5s) +- pw-storybook finishes in ~10s +- pw-wasm-marimo finishes in ~35s +- By the time wheel-dependent jobs start (~46s), only pw-marimo and possibly test-python 3.11/3.12/3.13 are still running + +Most jobs are single-threaded or I/O-bound (Playwright waits on Chromium). 8 vCPU is sufficient. Some jobs may run ~10-20% slower from contention in the first 30s, but the parallelism gain far outweighs it. + +## Risk: pw-jupyter CPU contention + +playwright-jupyter (PARALLEL=1, 104s) is the critical path. At t=46 when it starts, these may still be running: +- test-python-3.13 (usually done by t=63) +- pw-marimo (usually done by t=56) + +By t=63, only pw-jupyter and pw-server remain. Minimal contention for the bulk of pw-jupyter's runtime. + +If pw-jupyter proves flaky under DAG concurrency, add a `wait` for pw-marimo before starting it: +```bash +wait $PID_PW_MA || OVERALL=1 # ensure marimo done before jupyter starts +``` + +## Verification + +1. Rebuild Docker image (run-ci.sh is baked at `/opt/ci-runner/`): + ```bash + ssh root@5.161.210.126 + cd /opt/ci/repo && git pull + docker build -f ci/hetzner/Dockerfile -t buckaroo-ci . + docker compose -f ci/hetzner/docker-compose.yml up -d --force-recreate + ``` + +2. Run CI and compare timing: + ```bash + docker exec buckaroo-ci bash /opt/ci-runner/run-ci.sh main \ + > /opt/ci/logs/dag-test.log 2>&1 & + tail -f /opt/ci/logs/dag-test.log + ``` + +3. Verify all 14 jobs pass +4. Compare wall time against 5m56s (phased) baseline +5. Run 3x to confirm stability + +## Files to modify + +- `ci/hetzner/run-ci.sh` — replace phases 1-5b (~lines 277-334) with DAG execution block above + +## Future: parallel jupyter + +playwright-jupyter currently runs PARALLEL=1 (104s). See `docs/llm/research/parallel-jupyter-plan.md` for findings from 20 experiments attempting PARALLEL=3. Summary: the overhead required for batch-1 reliability exceeds parallelism savings at 9 notebooks. Revisit when notebook count grows to 15+, using the pre-started persistent server approach (9 JupyterLab servers running in container, ~16s test time). diff --git a/docs/llm/research/hetzner-implementation-plan.md b/docs/llm/research/hetzner-implementation-plan.md new file mode 100644 index 000000000..537c89cff --- /dev/null +++ b/docs/llm/research/hetzner-implementation-plan.md @@ -0,0 +1,210 @@ +# Hetzner Self-Hosted CI Implementation Plan + +## Context + +Current CI runs 22 jobs on Depot cloud runners with a ~3:27 critical path. Most time is overhead (provisioning, dep install), not tests. A persistent Hetzner CCX33 with warm Docker containers eliminates that overhead, targeting ~60-70s critical path. + +**Approach**: Bare GitHub webhook → Python receiver on Hetzner → `docker exec` into warm sidecar container → run tests → report status back to GitHub via commit status API. No CI framework. + +## What Moves to Hetzner vs Stays on GitHub Actions + +**Hetzner (fast feedback):** +- LintPython, TestJS, BuildWheel +- TestPython (3.11, 3.12, 3.13, 3.14) +- All Playwright: Storybook, Server, Marimo, WASMMarimo, JupyterLab +- TestMCPWheel, SmokeTestExtras + +**Stays on GitHub Actions:** +- TestPythonWindows (can't run on Linux) +- TestPythonMaxVersions (low-priority edge-case testing) +- PublishTestPyPI (needs GitHub OIDC trusted publishing) +- StylingScreenshots (complex baseline git checkout workflow) +- CheckDocs (low value for fast feedback) + +## File Structure + +``` +ci/hetzner/ + Dockerfile # Multi-layer image: OS → uv → Python 3.11-3.14 → Node/pnpm → deps → Playwright + docker-compose.yml # Sidecar container (sleep infinity) with volume-mounted caches + webhook.py # Flask webhook receiver (~120 lines) + run-ci.sh # Main CI orchestrator (git fetch → build → parallel tests → status) + lib/ + status.sh # GitHub commit status API helpers + lockcheck.sh # Lockfile hash comparison → triggers docker rebuild + cloud-init.yml # CCX33 provisioning (Docker, webhook systemd service, firewall) + .env.example # Template: GITHUB_TOKEN, WEBHOOK_SECRET, GITHUB_REPO +``` + +## Implementation Steps + +### Step 1: Dockerfile + +Multi-layer, ordered from least to most frequently changing: + +1. **OS + system deps** — Ubuntu 24.04, Playwright system libs (libnss3, libatk, etc.), curl, git +2. **uv** — `COPY --from=ghcr.io/astral-sh/uv:0.6.6` (pin a specific version). We don't need to track uv releases proactively — uv is a build tool, not a runtime dependency. When something breaks or we want a new feature, we bump the pin. The Docker image rebuild is fast either way. +3. **Python 3.11-3.14 via uv** — `uv python install 3.11 3.12 3.13 3.14` (no deadsnakes PPA needed) +4. **Node 22 LTS + pnpm@9.10.0** — Node installed via nodesource, pnpm via `corepack enable && corepack prepare pnpm@9.10.0`. Both pinned to specific versions in the Dockerfile. Same philosophy as uv: pin, don't track. Bump when needed. Node 22 is current LTS (supported through April 2027), no reason to stay on 20. +5. **JS deps from lockfile** — COPY `pnpm-lock.yaml` + `package.json` files, `pnpm install --frozen-lockfile` +6. **Python deps from lockfile** — COPY `pyproject.toml` + `uv.lock`, create venvs for each Python version with `uv sync` +7. **Playwright chromium** — `playwright install chromium` + +Source code is NOT baked in — mounted at runtime. Image rebuilds only when lockfiles change. + +### Step 2: docker-compose.yml + +Single `ci` service running `sleep infinity` (warm sidecar). Volumes: +- Source code bind-mounted read-only +- Named volumes for pnpm store, uv cache, Playwright browsers +- `/opt/ci/logs` for CI output + +The webhook runs directly on the host via systemd (avoids Docker-in-Docker complexity). + +### Step 3: webhook.py + +Minimal Flask app running on port 9000: +- Validates GitHub webhook secret (HMAC-SHA256) +- Handles `push` and `pull_request` (opened/synchronize/reopened) events +- Sets GitHub commit status to "pending" immediately +- Runs CI in background thread via `docker exec buckaroo-ci bash run-ci.sh ` +- **Concurrency**: Same branch → kill previous run (only latest commit matters). Different branches → run concurrently (max 2 via semaphore) +- On completion: sets commit status to "success" or "failure" + +Deployed as systemd service (`buckaroo-webhook.service`) running under gunicorn. + +### Step 4: run-ci.sh + +Runs inside the Docker container. Orchestrates: + +1. `git fetch` + `checkout` the specific SHA +2. `git clean -fdx` excluding `node_modules`, `.venv-*` (warm caches) +3. Lockfile hash check — skip dep install if unchanged (95% of pushes) +4. **Wave 1 (parallel)**: lint-python, test-js (build+jest), build-wheel (`full_build.sh`), test-python-3.13 +5. Wait for build-wheel, then run test-python 3.11/3.12/3.14 sequentially +6. **Wave 2 (sequential)**: Playwright tests — storybook, server, marimo, jupyter, wasm-marimo. Run sequentially because they bind to specific ports (6006, 8889, 2718, 8701, 8765) +7. **Wave 2 (parallel with Playwright)**: mcp-wheel test, smoke tests (no ports needed) +8. Collect results, exit 0 or 1 + +Each job's stdout/stderr captured to `$RESULTS_DIR/.log` for debugging. + +### Step 5: lib/status.sh + lib/lockcheck.sh + +**status.sh**: Shell functions wrapping `curl` calls to GitHub's commit status API (`POST /repos/:owner/:repo/statuses/:sha`). Functions: `status_pending`, `status_success`, `status_failure`. + +**lockcheck.sh**: Compares SHA256 hashes of `uv.lock`, `pnpm-lock.yaml`, `pyproject.toml`, `packages/buckaroo-js-core/package.json` against stored hashes in `/opt/ci/hashes/`. Returns 0 if caches valid, 1 if rebuild needed. `--update` flag stores current hashes. + +### Step 6: cloud-init.yml + +Provisions CCX33 from zero: +- Creates `ci` user with Docker group access +- Installs Docker, git, python3, ufw, fail2ban +- Clones repo to `/opt/ci/repo` +- Creates webhook venv, installs flask + gunicorn +- Builds CI Docker image, starts sidecar container +- Configures firewall (SSH + port 9000 only) +- Installs systemd service for webhook + +**Post-cloud-init manual steps**: Fill in `/opt/ci/.env` (GITHUB_TOKEN, WEBHOOK_SECRET), start webhook service, configure GitHub webhook in repo settings. + +### Step 7: .env.example + +Template with required secrets and infrastructure state: +- `GITHUB_TOKEN` — fine-grained PAT with `repo:status` write scope on `buckaroo-data/buckaroo` +- `WEBHOOK_SECRET` — shared secret for HMAC validation +- `GITHUB_REPO` — `buckaroo-data/buckaroo` +- `HETZNER_SERVER_ID` — numeric ID of the CCX33 (from `hcloud server list`), used by any scripts that manage the server +- `HETZNER_SERVER_IP` — public IP, used for SSH and webhook URL configuration + +## Key Design Decisions + +| Decision | Choice | Why | +|----------|--------|-----| +| Webhook vs CI framework | Bare webhook | Least infrastructure, ~120 lines of Python | +| Flask vs netcat | Flask | Needs concurrent handling, HMAC validation, threading | +| Webhook in Docker vs host | Host (systemd) | Avoids Docker-in-Docker complexity | +| Container per run vs sidecar | Sidecar (`docker exec`) | ~50ms overhead vs ~500ms for `docker run` | +| Playwright parallel vs sequential | Sequential | Port conflicts (6006, 8889, 2718, etc.) | +| Python tests parallel vs sequential | 3.13 parallel, rest sequential | Stay within 8-vCPU budget | +| Log viewing | `/logs/` endpoint on webhook | Click-through from GitHub commit status | + +## Expected Performance + +| Scenario | Time | +|----------|------| +| Warm push (no lockfile change) | ~60-75s | +| Cold push (lockfiles changed) | ~100-140s | +| Full wipe + reprovision (cloud-init) | ~5-8 min | + +## Files to Create + +All new files in `ci/hetzner/`: +- `ci/hetzner/Dockerfile` +- `ci/hetzner/docker-compose.yml` +- `ci/hetzner/webhook.py` +- `ci/hetzner/run-ci.sh` +- `ci/hetzner/lib/status.sh` +- `ci/hetzner/lib/lockcheck.sh` +- `ci/hetzner/cloud-init.yml` +- `ci/hetzner/.env.example` + +Existing scripts (`scripts/test_playwright_*.sh`, `scripts/full_build.sh`) are reused as-is. The existing `pnpm install` and `playwright install chromium` calls in those scripts become no-ops in the warm container (deps already installed). + +No changes to `.github/workflows/checks.yml` — Depot CI continues running in parallel. The Hetzner CI is additive (shows as a separate commit status context `ci/hetzner`). + +## Development Verification (how Claude develops this autonomously) + +Every script is built to be testable locally without a Hetzner server or live GitHub webhooks. The goal is: Claude can write, run, verify, and iterate without asking the user. + +**Dockerfile** — Build it locally (`docker build`). Verify: image builds, `docker exec` into it and confirm `uv`, `python3.11-3.14`, `node`, `pnpm`, `playwright` are all on PATH. Run `pnpm install --frozen-lockfile` and `uv sync` inside to confirm deps install correctly. + +**run-ci.sh** — Run locally inside the Docker container against the repo's current HEAD. Every test job already has a known-good baseline (what Depot CI produces). Compare: same tests pass, same tests fail. The script is pure shell — no external dependencies beyond what's in the container. + +**lockcheck.sh** — Unit-testable with temp directories. Create fake lockfiles, run `--update` to store hashes, verify return code 0. Modify a lockfile, verify return code 1. All locally. + +**status.sh** — Add a `--dry-run` flag that prints the curl command instead of executing it. Verify the correct URL, SHA, and status are in the output. For live testing, use a throwaway commit on a test branch. + +**webhook.py** — Test with `curl` against localhost: +- Send a valid payload with correct HMAC → verify 200 + CI triggered +- Send invalid HMAC → verify 401 +- Send irrelevant event type → verify 200 + ignored +- Flask has a built-in test client, so these can be pytest tests in the same file or a small test script. + +**cloud-init.yml** — This one can't be tested locally. Verify by provisioning a real CCX33 and SSH-ing in to check each step completed. Since cloud-init is idempotent and only runs once, the blast radius is low (worst case: delete server, fix script, reprovision). + +**Integration test sequence** (run by Claude after all scripts are written): +1. `docker build` → `docker-compose up -d` → `docker exec buckaroo-ci bash run-ci.sh HEAD main` → all tests pass +2. Modify a lockfile → rerun → verify lockcheck detects change and reinstalls +3. Run webhook.py locally → send test payloads with curl → verify status.sh dry-run output +4. Push to a test branch → verify Depot and Hetzner both report status + +## Monitoring & Alerting + +**Depot as canary** — Both Depot and Hetzner run on every push. Missing or disagreeing `ci/hetzner` status when Depot is green = something is wrong with the Hetzner setup. This is the primary detection mechanism and requires zero extra infrastructure. + +**Health endpoint** — `GET /health` on the webhook returns JSON with: webhook process up, Docker container running (`docker inspect`), disk usage %, last successful CI run timestamp. One `curl` tells you the full system status. + +**Systemd watchdog** — `WatchdogSec=60` in the service file. `webhook.py` pings systemd every 30s via `sd_notify`. If the process hangs (not just crashes), systemd restarts it automatically. + +**Disk hygiene** — Weekly cron: `docker system prune --force`, rotate CI logs older than 7 days. Disk filling up is the most likely silent failure mode. + +**Dead man's switch** — After each successful CI run, touch `/opt/ci/last-success`. A daily cron on weekdays checks if this file is older than 24 hours. If so, post a warning to the webhook's `/health` endpoint (health check goes from "ok" to "stale"). You'd see this next time you check, or could optionally wire it to a Slack/email notification later. + +## Testing & Ongoing Verification + +### Initial Verification + +1. **Local Docker test**: Build the image locally, `docker exec` into it, run `run-ci.sh` against current HEAD. All tests must pass and match what GitHub Actions produces. +2. **Webhook smoke test**: Run `webhook.py` locally behind ngrok, configure a test webhook on GitHub, push a commit, verify pending/success status appears on the commit. +3. **Hetzner deploy**: Provision CCX33 with cloud-init, configure secrets, push a PR, verify end-to-end green status. +4. **Concurrency test**: Push two commits rapidly on same branch, verify first run is cancelled and only second reports status. +5. **Lockfile change test**: Bump a dep, push, verify the container detects the lockfile change and reinstalls. + +### Ongoing Verification (keeping it working as we change things) + +**Depot CI stays on as the source of truth.** Both Depot and Hetzner run on every push. If Hetzner disagrees with Depot, Hetzner is wrong. This gives us a permanent regression check with zero extra effort — we never have to wonder if Hetzner is silently broken because Depot is always there to compare against. + +**When to investigate**: If Hetzner reports failure but Depot is green (environment drift, stale cache, port conflict). If Hetzner reports success but Depot is red (shouldn't happen — means Hetzner is skipping something). + +**Deprecating Depot**: Only after Hetzner has been green and agreeing with Depot for 2+ weeks of active development. At that point, flip the GitHub branch protection to require `ci/hetzner` instead of the Depot check, then disable the Depot workflow. Keep the workflow file around (commented out) so it's easy to re-enable if Hetzner has issues. + diff --git a/docs/llm/research/hetzner-plan-review.md b/docs/llm/research/hetzner-plan-review.md new file mode 100644 index 000000000..9448b4443 --- /dev/null +++ b/docs/llm/research/hetzner-plan-review.md @@ -0,0 +1,126 @@ +# Adversarial Review: Hetzner CI Implementation Plan + +**Date:** 2026-03-01 +**Status:** Review of plan that is already being executed. These are notes for future iterations, not blockers. + +--- + +## Critical Issues + +### 1. The 60-75s estimate is wrong + +The plan targets 60-75s warm critical path. But it specifies **sequential Playwright** in a single sidecar container due to "port conflicts." Five sequential Playwright suites at ~30-45s each = **150-225s just for Playwright**. + +**However, the port conflict premise is false.** All 5 suites bind to different ports: + +| Suite | Port | +|-------|------| +| Storybook | 6006 | +| JupyterLab | 8889 | +| Marimo | 2718 | +| Buckaroo Server | 8701 | +| WASM Marimo | 8765 | + +The only conflict (Storybook vs Screenshots on 6006) doesn't apply — Screenshots stays on GitHub Actions. + +**Fix:** Run all 5 Playwright suites in parallel. Critical path becomes ~45s (longest single suite, JupyterLab). Combined with build overhead (~17s) and dep verification (~2s), warm critical path is realistically **~65-75s** — which actually matches the plan's target, just for different reasons than stated. + +### 2. Concurrent runs in shared container will corrupt state + +The plan says "different branches → run concurrently (max 2 via semaphore)." But both runs share one container filesystem. Two concurrent `git checkout` calls clobber each other. `git clean -fdx` in run A nukes run B's working state. + +**Resolution (agreed):** Run only 1 build at a time. Kill previous run on same branch, queue or reject different-branch runs. This is simpler and avoids the entire class of problems. + +### 3. Bash orchestrator is under-scoped + +`run-ci.sh` needs to handle: parallel execution with background processes, per-job timeouts, structured error collection, wave dependencies, process cleanup on failure. This is exactly what CI frameworks solve. + +The "~120 lines of Python" pitch describes the webhook, not the orchestrator. The orchestrator is the hard part. + +**Options evaluated:** +- **doit** — Python DAG runner, good parallel + fail-fast, but tasks are atomic (no mid-task artifact emission). See `doit-task-runner.md`. +- **Custom asyncio** — ~50-80 lines, `asyncio.Event` per artifact, `gather` for fail-fast. Matches the desired pattern exactly but is bespoke. +- **Bash with discipline** — Workable if kept simple (no waves, just parallel backgrounded jobs with `wait`). Fragile at scale. + +No recommendation yet. The plan can start with bash and migrate if it gets painful. + +--- + +## Moderate Issues + +### 4. Webhook is an unauthenticated attack surface + +Port 9000 open to the internet, HMAC as only defense. This is standard for GitHub webhooks, but: + +- **No TLS** — webhook payloads (commit SHAs, branch names) sent in plaintext +- **No rate limiting** — endpoint can be spammed +- **Injection risk** — `docker exec ... bash run-ci.sh ` is vulnerable if `sha` isn't validated as hex. A payload with `sha="; rm -rf /"` would be catastrophic + +**Mitigations:** +- Validate SHA is `/^[0-9a-f]{40}$/` before passing to shell +- Put nginx or caddy in front for TLS (Let's Encrypt) and rate limiting +- Or restrict port 9000 to GitHub's webhook IP ranges (documented at `api.github.com/meta`) + +### 5. No per-job GitHub commit status + +On Depot, each job reports independently — you see which specific test failed. The plan reports a single `ci/hetzner` commit status. One flaky Playwright test fails the entire run with no granularity. + +**Fix:** Report multiple commit status contexts: `ci/hetzner/lint`, `ci/hetzner/test-js`, `ci/hetzner/pw-storybook`, etc. Each job calls `status_success` or `status_failure` independently. More `status.sh` calls but much better UX. + +### 6. 240GB disk might be tight + +Estimated usage: +- Docker image: 8-12GB +- Docker build cache: 5-10GB +- Named volumes (pnpm store, uv cache, Playwright browsers): 5-10GB +- Git repo: 1-2GB +- OS + Docker overhead: 5-10GB +- CI logs (7 day retention): 1-2GB + +**Total: ~25-46GB steady state.** 240GB is fine. This is less of a concern than initially flagged — the weekly `docker system prune` cron handles growth. + +### 7. No rollback story after Depot deprecation + +The plan says deprecate Depot after 2+ weeks of agreement. But after deprecation, there's no canary. Re-enabling Depot requires active credentials and runner access. + +**Recommendation:** Keep Depot running indefinitely as a read-only canary. At ~$9/month for 50 runs, it's cheap insurance. Don't make it a branch protection requirement — just let it run and alert if it disagrees with Hetzner. + +--- + +## Minor Issues + +### 8. Research doc / plan contradictions + +| Topic | Research doc | Implementation plan | Notes | +|-------|-------------|-------------------|-------| +| Python install | deadsnakes PPA | `uv python install` | Plan is better | +| Node version | Node 20 | Node 22 LTS | Plan is better | +| Playwright | Parallel (separate containers) | Sequential (single container) | Both wrong — should be parallel in single container | +| CI trigger | Forgejo or GH self-hosted runner recommended | Bare webhook chosen | Intentional, but research recommendation was ignored without justification | +| Container command | `tail -f /dev/null` | `sleep infinity` | Doesn't matter | + +### 9. `sleep infinity` sidecar has no health check + +If the container's main process dies or the container enters a bad state (OOM, zombie processes), nothing detects it. The webhook's `/health` endpoint checks `docker inspect` but that only tells you the container exists, not that it's functional. + +**Fix:** Add a lightweight health check to docker-compose: +```yaml +healthcheck: + test: ["CMD", "python3", "-c", "import sys; sys.exit(0)"] + interval: 30s +``` + +### 10. Systemd watchdog adds complexity for little benefit + +`sd_notify` integration in Python requires the `systemd` Python bindings or manual socket handling. For a Flask app behind gunicorn, gunicorn's own `--timeout` flag handles hung workers. The systemd watchdog is solving a problem gunicorn already solves. + +--- + +## What the Plan Gets Right + +- **CCX33 cloud over dedicated** — simpler automation, easy wipe, adequate CPU for Playwright-bound workload +- **Depot as parallel canary during rollout** — exactly the right approach +- **Source mounted, not baked in** — image rebuilds only on lockfile changes +- **Lockfile hash check** — skipping dep install on 95% of pushes is the key optimization +- **Reusing existing scripts** — `test_playwright_*.sh` and `full_build.sh` already work, no rewrite needed +- **Development verification plan** — every component testable locally before deploying diff --git a/docs/llm/research/implementation-notes.md b/docs/llm/research/implementation-notes.md new file mode 100644 index 000000000..6bb4638f9 --- /dev/null +++ b/docs/llm/research/implementation-notes.md @@ -0,0 +1,314 @@ +# Hetzner CI — Implementation Notes + +Lessons learned across all runs. Companion to `hetzner-ci-bringup.md`. + +--- + +## Architecture Decisions That Worked + +### Warm sidecar container +Running `docker exec` into an always-on container is dramatically better than +`docker run` per CI job. The venvs and pnpm store persist in the container for +the lifetime of the deployment; no layer caching needed. + +### Bake CI scripts into the image at `/opt/ci-runner/` +`run-ci.sh` checks out arbitrary SHAs with `git checkout -f $SHA`. Any file that +lives only in `/repo/ci/hetzner/` will be wiped when the checked-out SHA predates +the CI branch. Copying scripts to `/opt/ci-runner/` at image build time gives +them a stable path that survives the checkout. + +Rule: **any file called from within `run-ci.sh` must live in `/opt/ci-runner/`**, +not in `/repo/scripts/`. This burned us three times (run-ci.sh itself, lib/, +and test_playwright_jupyter_parallel.sh). + +### One venv per Python version at `/opt/venvs/3.11-3.14/` +Pre-populated with all deps at image build time. `uv sync` at runtime only +installs the project itself (editable), which is nearly instant. This is the +main reason Phase 1/3 are fast. + +### `UV_PROJECT_ENVIRONMENT` to prevent `.venv` creation races +When two jobs both call `uv run` or `uv sync` without this env var set, they +race to create/modify `/repo/.venv`. Set `UV_PROJECT_ENVIRONMENT=/opt/venvs/3.13` +for any job that needs to use the shared venv. + +### Per-job `PLAYWRIGHT_HTML_OUTPUT_DIR` +All playwright configs default to writing HTML reports to `playwright-report/` +in the working dir. When playwright jobs run in parallel they stomp each other. +Set `PLAYWRIGHT_HTML_OUTPUT_DIR=/tmp/pw-html--$$` per job. + +### Isolated venv for playwright-jupyter +`job_playwright_jupyter` creates `/tmp/ci-jupyter-$$` and installs +`buckaroo + polars + jupyterlab` there. This avoids pip-reinstalling into the +shared 3.13 venv while marimo/wasm-marimo are reading from it in parallel. + +--- + +## Parallelisation Wins + +| Change | Saved | Total after | +|--------|-------|-------------| +| Baseline (cold, sequential) | — | 8m59s | +| Warm caches | ~36s | 8m23s | +| Phase 3 parallel (3.11/3.12/3.14) | ~1m07s | 7m21s | +| Phase 5 parallel (5× playwright) | ~2m20s | 4m58s | +| Phase 5 split + parallel jupyter (PARALLEL=1) | ~1m04s | **3m56s** | +| Phase 5b PARALLEL=3 (tested, fails) | — | worse | + +Run 26 (commit 1759612, warm caches): +- Phase 1: 1m15s | Phase 2: 22s | Phase 3: 1m16s | Phase 4: 20s +- Phase 5a: 59s | Phase 5b: 1m44s (9 notebooks, PARALLEL=1) +- **Total: 5m56s** + +**Critical path** after all parallelisation: +`test-js (~24s) → build-wheel (~22s) → playwright-jupyter (~104s) ≈ 2m30s` + +Nothing else can beat this without shortening playwright-jupyter or decoupling +build-wheel from test-js. Next opportunity: PARALLEL=3 for Phase 5b (requires +CPU headroom after Phase 5a completes — currently untested but likely viable). + +### Why CCX43 didn't help +Upgrading from CCX33 (8 vCPU) to CCX43 (16 vCPU) gave identical timing +(~5m05s vs ~4m58s). The bottleneck is the sequential critical path, not CPU +core count. More cores only help if there's parallelisable work waiting on them. + +### Why PARALLEL=3 fails even after Phase 5a (batch-1 timing) +PARALLEL=3 launches 3 notebooks in batch 1: 3 browsers + 3 fresh kernels + a +freshly-started JupyterLab all compete for CPU simultaneously. The Playwright +spec's 1.3s static wait (`waitForTimeout(800)` + `waitForTimeout(500)`) fires +before widgets render → 6/9 failures. The first batch is the dangerous one +because JupyterLab itself is still initialising. Batches 2+ would likely be +fine, but we can't skip batch 1. PARALLEL=1 is the only safe value until the +Playwright spec is updated to use proper `waitFor` instead of fixed timeouts. + +### Why high Jupyter parallelism fails (when 5a is concurrent) +Running 9 (or even 3) Jupyter notebooks in parallel while the other 4 playwright +jobs are also running causes `tornado.iostream.StreamClosedError` — JupyterLab's +WebSocket connections drop under CPU load. The widget comm channels never +establish, giving "Comm not found" and "Widget failed to render: 0 elements." +Fix: run the 4 non-Jupyter playwright tests first (Phase 5a, ~60s), then run +Jupyter with PARALLEL=1+ after CPU is free (Phase 5b). PARALLEL=3 expected to +be viable since the system is idle during Phase 5b. + +### Why the DAG approach failed +Running all independent jobs simultaneously (9 concurrent on 8 vCPUs) caused: +- CPU saturation → forkserver tests hit hardcoded 1s timeouts +- playwright-marimo server too slow to start → 6-minute hang +The phased approach (P1→P2→P3→P4→P5) naturally throttles concurrency. + +--- + +## Bugs That Will Bite You Again + +### `((x++))` with `set -e` exits on zero result +`(( expression ))` returns exit code 1 when the expression evaluates to 0. +With `set -e`, `((NEXT++))` when `NEXT=0` kills the script after the first +background job launches. This burned us: one notebook started, cleanup trap +fired, JupyterLab was killed. Fix: `((NEXT++)) || true` for all arithmetic +that can evaluate to 0. + +### `cd "$(dirname "$0")/.."` breaks when called from `/opt/ci-runner/` +Already documented above — same pattern also hit `test_playwright_jupyter_parallel.sh`. + +### Linux `mktemp` needs explicit X's +`mktemp -d -t prefix` fails on Linux ("too few X's"). Use `mktemp -d -t prefixXXXXXX`. + +### `rm -rf` masking exit codes +```bash +job_foo() { + local venv=/tmp/foo-$$ + uv venv "$venv" + run_tests "$venv" # ← if this fails... + rm -rf "$venv" # ← ...this succeeds, and job returns 0 +} +``` +Always capture the exit code explicitly before cleanup: +```bash + local rc=0 + run_tests "$venv" || rc=$? + rm -rf "$venv" + return $rc +``` + +### `cd "$(dirname "$0")/.."` breaks when called from `/opt/ci-runner/` +Scripts that use this pattern to find the repo root will navigate to `/opt` +when called as `bash /opt/ci-runner/script.sh`. Fix: respect `ROOT_DIR` if set: +```bash +if [ -z "${ROOT_DIR:-}" ]; then + cd "$(dirname "$0")/.." + ROOT_DIR="$(pwd)" +fi +cd "$ROOT_DIR" +``` +Then callers set `ROOT_DIR=/repo`. + +### Linux `mktemp -d -t` requires explicit X's +`mktemp -d -t pw-jupyter-parallel` fails on Linux with "too few X's". +macOS silently appends the random suffix. Use: +```bash +mktemp -d -t pw-jupyter-parallelXXXXXX +``` + +### JupyterLab 4.x blocks widget rendering for untrusted notebooks +Freshly copied `.ipynb` files have no trust signature. JupyterLab 4.x +refuses to render widget JavaScript (anywidget's embedded `_esm`) for +untrusted notebooks — even for newly-executed live outputs. All 9 +notebooks fail with "Widget failed to render: 0 elements". + +Fix: run `jupyter trust "$nb"` for every notebook after copying it, before +starting Playwright tests. This adds the notebook's hash to +`~/.local/share/jupyter/nbsignatures.db`, which JupyterLab checks when +opening the notebook. + +### `shutdown_kernels` JSON parsing — `"id":"uuid"` vs `"id": "uuid"` +`grep -o '"id":"[^"]*"'` requires no space between the colon and the +opening quote. JupyterLab's `/api/kernels` response returns +`"id": "uuid"` (with a space), so the grep never matches. Result: every +batch call to `shutdown_kernels` silently does nothing — kernels +accumulate throughout the test run, consuming memory and causing +JupyterLab to reconnect old sessions on each new Playwright test. + +Fix: extract UUIDs with the UUID pattern instead: +```bash +grep -oE '[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}' +``` + +### JupyterLab workspace state restored across Playwright sessions +Even in Playwright's `--incognito` mode, JupyterLab stores workspace +state (which notebooks are open) server-side in +`~/.jupyter/lab/workspaces/`. When a new Playwright test opens JupyterLab, +it restores the previous workspace, causing old notebook sessions to +reconnect to stale kernels. The old kernel for notebook N reconnects +briefly, flooding the server log and potentially interfering with notebook +N+1's widget communication. + +Fix: add `rm -rf ~/.jupyter/lab/workspaces` to `shutdown_kernels` so each +batch starts with a fresh workspace, and run the same cleanup once before +the first batch. + +### `uv sync` in a parallel job strips extras from a shared venv +`uv sync --dev --no-install-project` removes packages not in the lock file for +the current sync scope. If job A syncs the shared 3.13 venv and job B is +running tests that require an extras package (e.g. `pl-series-hash`), job B +fails non-deterministically. Either: don't sync in the parallel job, or use +`UV_PROJECT_ENVIRONMENT` pointing to a job-private venv. + +### Stale kernel runtime files cause batch-1 timing failures across runs +`~/.local/share/jupyter/runtime/kernel-*.json` and `jpserver-*.json` files +accumulate without cleanup — each 9-notebook CI run adds 9 kernel JSON files. +When JupyterLab starts, it scans the runtime directory and attempts ZMQ +heartbeat connections to every kernel JSON it finds. Dead kernels cause a +connection timeout for each file. With 100+ stale files, this delays JupyterLab +initialization by 1-2 seconds. + +The first notebook (test_buckaroo_widget.ipynb) runs while JupyterLab is still +processing these stale connections. The Playwright test's 1.3s static wait after +Shift+Enter isn't enough time for the widget to render, so it fails. Batches 2-9 +pass because JupyterLab finishes the scan before they run. + +This produced an alternating PASS/FAIL pattern in stress tests: runs after a +full 9-notebook pass added more files, pushing the next run over the threshold. + +Fix: add to `test_playwright_jupyter_parallel.sh` startup: +```bash +rm -f ~/.local/share/jupyter/runtime/kernel-*.json +rm -f ~/.local/share/jupyter/runtime/jpserver-*.json +rm -f ~/.local/share/jupyter/runtime/jpserver-*.html +``` + +### Double-run contamination from SSH heredocs +Running `ssh host << 'EOF' ... EOF` can spawn two processes if the connection +is slow. Always use `nohup bash -c "..." /opt/ci-runner/VERSION' +echo "deployed VERSION=$SHA" +``` + +The VERSION file is read by `run-ci.sh` at startup and logged as +`CI runner: `, so every run log identifies which script version ran it. + +--- + +## Resource Usage (CCX43, parallel Phase 5) + +Peak memory: **11.8 GB** (38% of 31 GB) — driven by wasm-marimo loading a +large WASM bundle while 4 other browser processes are alive. +Peak CPU: briefly 100%, average 44% across the run. +Headroom is comfortable; CCX43 is not over-provisioned for this workload. + +--- + +## Purpose and Design Intent + +This CI system is built for **manual and agent-driven use before pushing to GitHub** — +not for PR status automation. Think of it as syntax highlighting for LLMs: fast, +low-friction feedback on a commit while still on the local branch. The webhook and +GITHUB_TOKEN integration are explicitly out of scope; the trigger is always a direct +`docker exec` call by a human or agent. + +Implications for prioritisation: +- Speed and reliability matter most — false positives waste agent iteration cycles +- Webhook/PR-status integration is not a goal +- The runner should be usable with a single SSH command or script call, no GitHub setup required + +--- + +## What's Left + +### Speed — critical path is 2m49s + +The entire suite currently runs in ~6min on CCX43. The theoretical minimum +(critical path with ∞ cores) is **2m49s**: `test-js(24s) → build-wheel(22s) → playwright-jupyter(2m03s)`. +Nothing else can beat this without shortening the playwright-jupyter leg. + +| Item | Expected saving | Notes | +|------|----------------|-------| +| PARALLEL=3 for Phase 5b | ~45s off total | Batch-1 timing flake is now fixed (kernel warmup). Ready to retry. | +| Fix Playwright static waits (`waitForTimeout`) | Reduces playwright-jupyter from 2m03s; unblocks PARALLEL=4+ | The spec uses hardcoded 800ms+500ms waits instead of `waitFor` conditions. This is the main critical-path bottleneck and the prerequisite for any further parallelism gains. | +| Downgrade CCX43 → CCX33 | Cost only, no speed change | Benchmarked identical timing on 8 vs 16 vCPU — bottleneck is the sequential critical path, not cores. CCX43 is paying for unused capacity. | + +### Reliability + +| Item | Notes | +|------|-------| +| Flaky `test_lazy_widget_status_and_messages` | Timing-sensitive async widget tests that occasionally fail under parallel Phase 3 CPU load. Rerunning reliably passes. Root fix is in the test spec (proper async assertions). | +| `cffi` source compilation | `uv` falls back to building cffi from source instead of manylinux wheels on dep-change runs. Investigate wheel availability for the target platform. | +| `mp_timeout` Docker tuning | forkserver spawn is ~1.5s on CCX43; tests hardcoded to 1.0s — requires code changes, deferred. | + +### Uncontended job timings (fcfe368, serial run) + +Measured with `run-ci-serial.sh` — each job runs alone with no parallel contention: + +| Job | Time | +|-----|------| +| lint-python | 0s | +| test-js | 24s | +| test-python-3.11/3.12/3.13 | ~63s each | +| test-python-3.14 | 0s (skipped) | +| build-wheel | 22s | +| test-mcp-wheel | 12s | +| smoke-test-extras | 20s | +| playwright-storybook | 10s | +| playwright-server | 58s | +| playwright-marimo | 56s | +| playwright-wasm-marimo | 35s | +| playwright-jupyter | 2m03s | + +These are the numbers to optimise against. The Python test jobs each take ~63s +uncontended but only ~75s even when three run in parallel — good CPU efficiency. +playwright-jupyter dominates; fixing its static waits is the highest-leverage change. diff --git a/docs/llm/research/jupyter-kernel-rest-api-execution-state.md b/docs/llm/research/jupyter-kernel-rest-api-execution-state.md new file mode 100644 index 000000000..305d13210 --- /dev/null +++ b/docs/llm/research/jupyter-kernel-rest-api-execution-state.md @@ -0,0 +1,207 @@ +# Why JupyterLab Kernels Stay "starting" via REST API + +**Date:** 2026-03-03 +**Context:** CI warmup creates kernels via POST /api/kernels, polls GET /api/kernels/{id} for execution_state. With PARALLEL=1, kernels reach "idle" in ~70s. With PARALLEL=9, all kernels stay "starting" for 90+ seconds and never transition. + +## Root Cause: No Messages Reach the Kernel, So No IOPub Status Updates Occur + +The REST API endpoint `GET /api/kernels/{id}` returns `kernel.execution_state` from the `MappingKernelManager`'s in-memory model. This value starts as `"starting"` and is only updated by a `record_activity` callback listening on the kernel's ZMQ iopub channel. **The callback can correctly transition `"starting"` to `"idle"`, but only if iopub messages actually arrive. With a pure REST-only workflow (no WebSocket connection, no code execution), nobody sends the kernel any requests, so the kernel never publishes any iopub messages, and `execution_state` stays `"starting"` forever.** + +There are two layers to this problem: + +1. **Primary: No one talks to the kernel.** POST /api/kernels starts the kernel process and returns. The `KernelManager.ready` future resolves when the subprocess launches -- it does NOT send a `kernel_info_request` or any other message. The kernel sits idle on its ZMQ channels waiting for a request that never comes. + +2. **Secondary: ZMQ SUB socket subscription race.** Even if someone did send a request, the server's `_activity_stream` (ZMQ SUB socket created by `start_watching_activity`) might miss early iopub messages due to the well-known SUB subscription propagation delay ([jupyter/jupyter_client#593](https://github.com/jupyter/jupyter_client/issues/593)). + +### Detailed Code Trace + +Source: [`jupyter_server/services/kernels/kernelmanager.py`](https://github.com/jupyter-server/jupyter_server/blob/main/jupyter_server/services/kernels/kernelmanager.py) + +**Step 1: `_async_start_kernel` sets `execution_state = "starting"` and creates a task for `_finish_kernel_start`:** + +```python +kernel.execution_state = "starting" +# ... +task = asyncio.create_task(self._finish_kernel_start(kernel_id)) +``` + +**Step 2: `_finish_kernel_start` awaits `km.ready` (process launch), then calls `start_watching_activity`:** + +```python +async def _finish_kernel_start(self, kernel_id): + km = self.get_kernel(kernel_id) + if hasattr(km, "ready"): + await km.ready # Waits for subprocess to start (NOT for kernel to be responsive) + self._kernel_ports[kernel_id] = km.ports + self.start_watching_activity(kernel_id) # Creates ZMQ SUB on iopub +``` + +The `KernelManager.ready` future resolves when the kernel subprocess starts. It does NOT send `kernel_info_request` or verify the kernel is responsive. Source: [`jupyter_client/manager.py`](https://github.com/jupyter/jupyter_client/blob/main/jupyter_client/manager.py) + +**Step 3: `start_watching_activity` creates a ZMQ SUB socket and registers `record_activity`:** + +```python +def start_watching_activity(self, kernel_id): + kernel = self._kernels[kernel_id] + kernel._activity_stream = kernel.connect_iopub() + # ... + def record_activity(msg_list): + # ... + if msg_type == "status": + execution_state = msg["content"]["execution_state"] + if self.track_message_type(parent_msg_type): + kernel.execution_state = execution_state + elif kernel.execution_state == "starting" and execution_state != "starting": + kernel.execution_state = "idle" + kernel._activity_stream.on_recv(record_activity) +``` + +Note: the `if msg_type == "status"` block is **not** gated by the `track_message_type` check on `msg_type`. The `execution_state` update logic runs for ALL status messages, not just tracked ones. The `elif` branch correctly handles `starting -> idle` for any parent message type. + +**Step 4: Nothing happens.** The kernel process is running. The iopub SUB socket is listening. But no one sends the kernel a `kernel_info_request`, `execute_request`, or any other message. The kernel publishes exactly one `status: starting` message at process startup (from [`ipykernel/kernelbase.py`](https://github.com/ipython/ipykernel/blob/main/ipykernel/kernelbase.py): + +```python +# In ipykernel's start(): +self._publish_status("starting", "shell") +``` + +This message is likely **missed** by `record_activity` because the SUB socket is created AFTER the kernel process starts (the `km.ready` await completes, THEN `connect_iopub()` is called). The kernel's `status: starting` message was already published before the SUB subscription propagated. + +After that single message, **the kernel goes quiet.** It has nothing to do. No iopub messages flow. `record_activity` is never called. `execution_state` stays `"starting"` on the server. + +### What the `record_activity` callback CAN do (if messages arrive) + +The callback IS properly coded to handle the transition. If someone sends a `kernel_info_request`: +- The kernel publishes `status: busy` with `parent_header.msg_type = "kernel_info_request"` +- `"kernel_info_request"` is in the untracked list, so `track_message_type("kernel_info_request")` = False +- But `kernel.execution_state == "starting"` and `"busy" != "starting"`, so the `elif` fires: `kernel.execution_state = "idle"` + +The problem is not the callback logic. The problem is that **no messages ever arrive at the callback** because nobody sends the kernel any requests via the REST API path. + +### What DOES work: WebSocket "nudge" mechanism + +When a WebSocket client connects (`KernelWebsocketHandler.open()`), it calls `connection.prepare()` which calls `nudge()`. The nudge mechanism ([source](https://github.com/jupyter-server/jupyter_server/blob/main/jupyter_server/services/kernels/connection/channels.py)): +1. Opens transient shell/control channels +2. Sends `kernel_info_request` repeatedly +3. Monitors iopub directly, waiting for both the shell reply AND at least one iopub message +4. Confirms ZMQ subscriptions are active and kernel is responsive + +This is the ONLY code path in jupyter_server that actively verifies kernel readiness. It is triggered exclusively by WebSocket connections. The `kernel_info_request` messages it sends also cause iopub status messages that `record_activity` receives, transitioning `execution_state` from "starting" to "idle" as a side effect. + +### The ZMQ SUB socket subscription race + +Even when messages are being sent, the `_activity_stream` SUB socket can miss early iopub messages because ZMQ SUB subscriptions take time to propagate. The kernel may publish `status: busy` and `status: idle` before the SUB socket receives them. This is the issue documented in [jupyter/jupyter_client#593](https://github.com/jupyter/jupyter_client/issues/593) and fixed for the WebSocket path via the nudge retry mechanism, but NOT fixed for the `record_activity` path. + +## Why PARALLEL=1 Works But PARALLEL=9 Doesn't + +With PARALLEL=1, the warmup creates a kernel and polls. We observed it reaching "idle" after ~70s. Most likely explanation: something else on the JupyterLab server (perhaps a session manager, extension, or internal heartbeat) eventually sends a message that triggers iopub activity. With only one server, system load is low, and the kernel starts quickly enough that some internal mechanism triggers the transition. + +With PARALLEL=9, nine servers start simultaneously on a 16-vCPU machine. CPU contention from 9 simultaneous Python startups (each kernel imports numpy, pandas, etc.) delays kernel initialization. But more fundamentally, the pure REST polling loop (POST kernel -> poll GET -> wait for idle -> DELETE) never sends the kernel any ZMQ messages and never opens a WebSocket. The `execution_state` has no mechanism to transition. + +CPU contention amplifies the problem but is NOT the root cause. Even with infinite CPU, `execution_state` would stay "starting" in the pure REST path unless something else sends the kernel a tracked message. + +## Confirmed Upstream Issues + +- [jupyter-server/enterprise_gateway#1138](https://github.com/jupyter-server/enterprise_gateway/issues/1138): "The /api/kernels call shows the kernel in starting state even when the kernel is busy." Kevin Bates confirms: **"the kernel status will remain in the 'starting' state until the websocket is created."** +- [jupyter-server/jupyter_server#900](https://github.com/jupyter-server/jupyter_server/issues/900): Proposal for a new kernels REST API with proper state tracking via an event system. Still open. +- [jupyter-server/jupyter_server#1395](https://github.com/jupyter-server/jupyter_server/issues/1395): Kernel execution_state not updated after crash with no open notebook (no WebSocket = no status updates flowing). +- [jupyter/jupyter_client#593](https://github.com/jupyter/jupyter_client/issues/593): ZMQ SUB socket subscription race -- messages lost during subscription propagation window. +- [jupyter-server/jupyter_server#361](https://github.com/jupyter-server/jupyter_server/pull/361): PR that added the nudge mechanism -- "nudge kernel with info request until we receive IOPub messages." WebSocket-only fix. + +## Solutions + +### Option A: Open a WebSocket connection to trigger nudge (CORRECT FIX) + +Use `websocat` or a Python websocket client to connect to `/api/kernels/{id}/channels`, triggering the nudge mechanism that properly verifies kernel readiness: + +```bash +# Create kernel +KID=$(curl -s -X POST "http://localhost:$PORT/api/kernels" \ + -H "Content-Type: application/json" -d '{"name":"python3"}' \ + | python3 -c "import sys,json; print(json.load(sys.stdin)['id'])") + +# Open WebSocket to trigger nudge (kernel_info_request loop until iopub responds) +# websocat will connect, nudge fires server-side, kernel transitions to idle +timeout 30 websocat --one-message "ws://localhost:$PORT/api/kernels/$KID/channels" < /dev/null & +WS_PID=$! + +# Poll REST API for execution_state (now it WILL transition because nudge sent messages) +for i in $(seq 1 60); do + STATE=$(curl -s "http://localhost:$PORT/api/kernels/$KID" \ + | python3 -c "import sys,json; print(json.load(sys.stdin)['execution_state'])") + [ "$STATE" = "idle" ] && break + sleep 1 +done +kill $WS_PID 2>/dev/null + +# Delete warmup kernel +curl -s -X DELETE "http://localhost:$PORT/api/kernels/$KID" +``` + +Or with Python's `websocket-client` library: + +```python +import websocket, json, threading, time +ws = websocket.WebSocket() +ws.connect(f"ws://localhost:{port}/api/kernels/{kid}/channels") +# Nudge happens server-side on connect; wait briefly then close +time.sleep(5) +ws.close() +``` + +### Option B: Use jupyter_client directly (bypass REST API entirely) + +Instead of the REST API, use `jupyter_client.BlockingKernelClient` which has a proper `wait_for_ready()` method that sends `kernel_info_request` and waits for shell reply + iopub idle: + +```python +from jupyter_client import KernelManager +km = KernelManager(kernel_name='python3') +km.start_kernel() +kc = km.client() +kc.start_channels() +kc.wait_for_ready(timeout=60) # Sends kernel_info_request, waits for reply + iopub idle +print("Kernel ready") +kc.stop_channels() +km.shutdown_kernel() +``` + +This completely bypasses the broken REST polling path. + +### Option C: Don't check execution_state at all -- use fixed delay + +```bash +# Create kernel (blocks until subprocess launches) +KID=$(curl -s -X POST "http://localhost:$PORT/api/kernels" \ + -H "Content-Type: application/json" -d '{"name":"python3"}' \ + | python3 -c "import sys,json; print(json.load(sys.stdin)['id'])") + +# Wait fixed time for kernel to initialize (kernel IS starting regardless of execution_state) +sleep 10 + +# Delete warmup kernel +curl -s -X DELETE "http://localhost:$PORT/api/kernels/$KID" +``` + +Crude but avoids the fundamentally broken polling loop. The kernel process IS running and initializing; `execution_state` just doesn't reflect that. + +### Option D: Skip kernel warmup entirely + +The kernel warmup was added because "HTTP ready != kernel provisioner ready." But Playwright tests open notebooks which create WebSocket connections which trigger the nudge mechanism. The first notebook's kernel startup happens within Playwright's test timeouts anyway. + +```bash +# Just check JupyterLab is serving HTTP +for i in $(seq 1 30); do + curl -sf "http://localhost:$PORT/api/status" && break + sleep 1 +done +``` + +## Recommendation + +**Option D (skip kernel warmup)** is simplest. The warmup was a workaround for a problem that Playwright's own `waitForSelector` timeouts handle. Each Playwright test opens a notebook, which creates a WebSocket, which triggers the nudge, which properly waits for the kernel. The REST warmup kernel adds overhead and its state polling is fundamentally broken. + +If kernel warmup is still desired for first-notebook latency reduction, **Option A (WebSocket connection)** is the most correct approach. It exercises the exact code path that JupyterLab uses internally and is the only path in jupyter_server that properly verifies kernel readiness. + +## Key Takeaway + +**The jupyter_server REST API `GET /api/kernels/{id}` reports stale `execution_state` because the server's iopub activity monitor only updates when messages flow, and no messages flow without a WebSocket connection or direct ZMQ client.** This is by design -- the REST API was built for kernel lifecycle management (create/list/delete), not for kernel readiness checking. Kernel readiness has always been a WebSocket-layer concern in Jupyter's architecture. diff --git a/docs/llm/research/jupyterlab-codebase-notes-for-buckaroo.md b/docs/llm/research/jupyterlab-codebase-notes-for-buckaroo.md new file mode 100644 index 000000000..281c843cb --- /dev/null +++ b/docs/llm/research/jupyterlab-codebase-notes-for-buckaroo.md @@ -0,0 +1,436 @@ +# JupyterLab Codebase Notes for Buckaroo + +**Date:** 2026-03-03 +**Source:** Deep dive into `jupyterlab/jupyterlab` codebase + Galata test framework +**Purpose:** Patterns, APIs, and fixes buckaroo should adopt + +--- + +## 1. The Kernel Readiness Fix (Critical — Do This First) + +**Problem:** Current DOM-based kernel check (`integration.spec.ts:112-127`) uses +`.jp-Notebook-ExecutionIndicator[data-status="idle"]` which fails when: +- The ExecutionIndicator isn't in DOM yet (JupyterLab still loading) → `querySelector` returns `null` → function returns `false` → burns 15s timeout +- data-status attribute lags behind internal kernel state + +**Fix:** Query JupyterLab's internal kernel state directly: + +```typescript +await page.waitForFunction(() => { + const app = (window as any).jupyterapp; + if (!app) return false; + const widget = app.shell.currentWidget; + if (!widget?.sessionContext?.session?.kernel) return false; + const kernel = widget.sessionContext.session.kernel; + return kernel.connectionStatus === 'connected' && kernel.status === 'idle'; +}, { timeout: 60000 }); +``` + +**Why this works:** This checks the exact same condition JupyterLab checks before +allowing execution. `CodeCell.execute()` at `packages/cells/src/widget.ts:1750` +silently returns void if `!sessionContext.session?.kernel`. Our check ensures the +kernel object exists AND is connected AND is idle before we fire Shift+Enter. + +**Expected impact:** 80% → ~98%+ pass rate. + +--- + +## 2. Galata Patterns We Should Adopt + +Galata is JupyterLab's official Playwright testing framework (`galata/`). It has +years of battle-tested patterns for the exact problems we're solving. + +### 2a. Wait for App Started — Not Just DOM + +Galata waits for `window.jupyterapp.started` before doing anything: + +```typescript +// From galata/src/jupyterlabpage.ts:715-724 +await page.evaluate(async () => { + if (typeof window.jupyterapp === 'object') { + await window.jupyterapp.started; // Waits for ALL plugins to load + return true; + } + return false; +}); +``` + +**We should add this** before our notebook load check. It ensures all extensions +(including anywidget support) are initialized before we interact with the notebook. + +### 2b. Double-Check Cell Execution (Status Bar + Execution Count) + +Galata's `waitForRun()` uses a two-stage check: + +```typescript +// From galata/src/helpers/notebook.ts:468-480 +async waitForRun(cellIndex?: number): Promise { + // Stage 1: Wait for status bar to show "Idle" + const idleLocator = this.page.locator('#jp-main-statusbar >> text=Idle'); + await idleLocator.waitFor(); + + // Stage 2: Verify execution count is set + let done = false; + do { + await this.page.waitForTimeout(20); + done = await this.page.evaluate(cellIdx => { + return window.galata.haveBeenExecuted(cellIdx); + }, cellIndex); + } while (!done); +} +``` + +**Key insight:** Status bar showing "Idle" alone isn't enough. Must also verify the +cell's execution count was set (proving the kernel actually processed the request). + +### 2c. Animation Frame Stability for Rendering + +Galata checks that rendered content is stable across multiple animation frames: + +```typescript +// From galata/src/helpers/notebook.ts:1290-1331 +// Wait until content is unchanged for 10 consecutive animation frames +let framesWithoutChange = 0; +let previousContent = element.innerHTML; + +const check = () => { + window.requestAnimationFrame(() => { + const newContent = element.innerHTML; + if (previousContent === newContent) { + framesWithoutChange++; + } else { + framesWithoutChange = 0; // Reset on change + } + previousContent = newContent; + if (framesWithoutChange < 10) { + check(); + } else { + resolve(); // Stable! + } + }); +}; +``` + +**We should use this** for AG-Grid rendering. Currently we `waitFor({ state: 'visible' })` +on `.ag-cell` but AG-Grid renders progressively. 10 stable frames would catch the +point where rows are fully populated. + +### 2d. `waitForCondition` Utility + +Galata's core polling utility (50ms intervals, 15s default): + +```typescript +// From galata/src/utils.ts:174-203 +async function waitForCondition( + fn: () => boolean | Promise, + timeout: number = 15000 +): Promise { + return new Promise((resolve, reject) => { + const check = async () => { + if (await Promise.resolve(fn())) { + resolve(); + } else { + setTimeout(check, 50); + } + }; + check(); + setTimeout(() => reject(new Error('Timed out')), timeout); + }); +} +``` + +This is simpler and more reliable than our retry loops. Consider extracting a +similar utility for buckaroo tests. + +--- + +## 3. How Anywidget Rendering Works in JupyterLab + +Understanding this helps diagnose widget rendering failures. + +### Output Rendering Pipeline + +``` +Kernel execute_reply (IOPub) + ↓ +OutputArea._onIOPub() — packages/outputarea/src/widget.ts:732 + ↓ +OutputAreaModel.add() — adds to model, emits changed signal + ↓ +OutputArea.onModelChanged() — receives signal + ↓ +RenderMimeRegistry.preferredMimeType() — selects best MIME renderer + ↓ +RenderMimeRegistry.createRenderer() — instantiates renderer widget + ↓ +renderer.renderModel(model) — async, fire-and-forget (!) + ↓ +Widget attached to DOM +``` + +### Fire-and-Forget Render Issue + +At `packages/outputarea/src/widget.ts:594-611`, when an output is updated: + +```typescript +void renderer.renderModel(model); // Fire and forget! +``` + +If multiple updates arrive rapidly, the renderer may render stale data. +Anywidget's React rendering should handle this via state diffing, but it means +our test shouldn't assume the first paint is the final paint. + +### Comm Message Handling + +Anywidget uses the Jupyter comm protocol, NOT the MIME renderer pipeline, for +ongoing widget-kernel communication. The comm messages flow through: + +``` +KernelConnection._handleMessage() — default.ts:1595 + ↓ +_handleCommMsg / _handleCommOpen — handles comm_open, comm_msg, comm_close + ↓ +anywidget model.on('msg:custom') — frontend receives custom messages + ↓ +SmartRowCache processes infinite_resp — buckaroo-specific handling +``` + +This means our `infinite_request`/`infinite_resp` messages go through the same +WebSocket connection as execution. If the WebSocket drops, comm messages are +also lost (they're not queued like execute_request). + +--- + +## 4. Key JupyterLab Constants That Affect CI + +| Constant | Value | Impact | Location | +|----------|-------|--------|----------| +| `KERNEL_INFO_TIMEOUT` | 3000ms | Failsafe: sends pending messages even if kernel_info_reply not received. Under contention, kernel may not be ready. | `services/kernel/default.ts:33` | +| `_reconnectLimit` | 7 | After 7 failed WebSocket reconnection attempts (~120s total), kernel is permanently `disconnected` | `services/kernel/default.ts:1840` | +| `enableKernelInitNotification` | `false` | When true, shows notification instead of silently dropping execution during init. Consider enabling in test notebooks. | `notebook-extension/schema/tracker.json:689` | + +### Reconnection Backoff Schedule + +| Attempt | Max delay | Cumulative | +|---------|-----------|------------| +| 1 | 0s | 0s | +| 2 | 1s | 1s | +| 3 | 3s | 4s | +| 4 | 7s | 11s | +| 5 | 15s | 26s | +| 6 | 31s | 57s | +| 7 | 63s | 120s | +| 8+ | gives up | `disconnected` | + +With P=4 on 16 vCPU, if a WebSocket drops during contention, it has ~120s +to reconnect before permanent failure. + +--- + +## 5. Silent Execution Drop Scenarios (Full List) + +Every way Shift+Enter can be silently swallowed in JupyterLab: + +| # | Check | Condition | Result | +|---|-------|-----------|--------| +| 1 | Keybinding selector | Not in `.jp-mod-editMode` | Keystroke ignored | +| 2 | `actions.tsx:2546` | `kernelDisplayStatus === 'initializing'` AND `enableKernelInitNotification` | Shows notification, `return false` | +| 3 | `cellexecutor.ts:54` | `sessionContext.isTerminating` | Shows dialog, drops | +| 4 | `cellexecutor.ts:62` | `sessionContext.pendingInput` | Shows dialog, `return false` | +| 5 | `cellexecutor.ts:74` | `hasNoKernel` after start attempt | Clears execution, `return true` (!) | +| **6** | **`widget.ts:1750`** | **`!sessionContext.session?.kernel`** | **Returns `void`, NO error** | + +**#6 is our primary failure mode.** The kernel object doesn't exist yet when +Shift+Enter fires. The code path returns cleanly with no error, no notification, +and no queuing. + +--- + +## 6. Message Queueing — What's Safe and What's Not + +### Safe: Messages queued while WebSocket is down + +`packages/services/src/kernel/default.ts:489-507` — if `connectionStatus !== 'connected'` +or kernel is restarting, messages are pushed to `_pendingMessages[]` and sent when +connection recovers. + +### Unsafe: `_clearKernelState()` drops the queue + +`default.ts:1302-1304`: +```typescript +private _clearKernelState(): void { + this._kernelSession = ''; + this._pendingMessages = []; // ALL QUEUED MESSAGES LOST + this._futures.forEach(future => { future.dispose(); }); +} +``` + +Called during: +- Kernel restarts (autorestarting status received) +- `reconnect()` method +- `dispose()` + +**For buckaroo:** If the kernel auto-restarts during a test (OOM, crash), any +pending `execute_request` or `comm_msg` (infinite_request) messages are silently +dropped. Our retry loop handles this for execution, but infinite scroll requests +via SmartRowCache would need their own retry logic. + +--- + +## 7. Notebook Windowing (Virtual Scrolling) + +JupyterLab virtualizes cells in large notebooks. Not all cells are in the DOM. + +```typescript +// Galata uses data-windowed-list-index to find cells +const firstIndex = parseInt( + (await cells.first().getAttribute('data-windowed-list-index')) ?? '', 10 +); +``` + +**For buckaroo:** Our test notebooks are small (1-2 cells) so this doesn't matter +today. But if we ever test multi-cell notebooks, we can't assume all cells are in +DOM. Use `data-windowed-list-index` attribute instead of `.jp-Cell:nth-child(n)`. + +--- + +## 8. `window.jupyterapp` API Surface for Tests + +Available globals in the browser context during JupyterLab tests: + +```typescript +// Application object +window.jupyterapp: JupyterFrontEnd + +// Key properties +window.jupyterapp.started // Promise: resolves when plugins loaded +window.jupyterapp.shell.currentWidget // Current active widget (NotebookPanel) +window.jupyterapp.serviceManager // Sessions, kernels, contents APIs + +// Kernel state (via currentWidget) +const panel = window.jupyterapp.shell.currentWidget; +panel.sessionContext // ISessionContext +panel.sessionContext.session // Session.ISessionConnection +panel.sessionContext.session.kernel // Kernel.IKernelConnection +panel.sessionContext.session.kernel.status // 'idle'|'busy'|'starting'|... +panel.sessionContext.session.kernel.connectionStatus // 'connected'|'connecting'|'disconnected' +panel.sessionContext.session.kernel.info // Promise +panel.sessionContext.kernelDisplayStatus // Combined display status +panel.sessionContext.isReady // Boolean +panel.sessionContext.hasNoKernel // Boolean +``` + +**`kernel.info`** is a Promise that resolves when the kernel_info_reply arrives +(the nudge completed). This is the definitive "kernel is fully ready" signal: + +```typescript +// Most reliable way to wait for kernel readiness +await page.evaluate(async () => { + const panel = window.jupyterapp.shell.currentWidget; + await panel.sessionContext.session.kernel.info; +}); +``` + +--- + +## 9. Recommended Test Helper Improvements + +### Replace current kernel wait (integration.spec.ts:112-127) + +```typescript +// NEW: Wait for app + kernel ready +async function waitForKernelReady(page: Page, timeout = 60000) { + // Stage 1: Wait for JupyterLab app to finish loading + await page.waitForFunction(() => { + return typeof (window as any).jupyterapp === 'object'; + }, { timeout: 30000 }); + + // Stage 2: Wait for kernel to be connected and idle + await page.waitForFunction(() => { + const app = (window as any).jupyterapp; + const widget = app.shell.currentWidget; + if (!widget?.sessionContext?.session?.kernel) return false; + const kernel = widget.sessionContext.session.kernel; + return kernel.connectionStatus === 'connected' && kernel.status === 'idle'; + }, { timeout }); +} +``` + +### Add AG-Grid rendering stability check + +```typescript +async function waitForGridStable(page: Page, timeout = 15000) { + await page.locator('.ag-overlay').first().waitFor({ state: 'hidden', timeout }); + await page.locator('.ag-cell').first().waitFor({ state: 'visible', timeout }); + + // Wait for AG-Grid to stop re-rendering (10 stable animation frames) + await page.evaluate(() => new Promise(resolve => { + const grid = document.querySelector('.ag-root-wrapper')!; + let stableFrames = 0; + let prev = grid.innerHTML; + const check = () => { + requestAnimationFrame(() => { + const cur = grid.innerHTML; + stableFrames = (cur === prev) ? stableFrames + 1 : 0; + prev = cur; + (stableFrames >= 10) ? resolve() : check(); + }); + }; + check(); + })); +} +``` + +### Add execution verification after Shift+Enter + +```typescript +async function verifyExecution(page: Page, timeout = 15000) { + // Check that execution count was set (kernel actually ran the cell) + await page.waitForFunction(() => { + const cell = document.querySelector('.jp-CodeCell'); + if (!cell) return false; + const prompt = cell.querySelector('.jp-InputArea-prompt'); + // Execution count shows "[N]:" not "[*]:" or "[ ]:" + return prompt?.textContent?.match(/\[\d+\]:/) !== null; + }, { timeout }); +} +``` + +--- + +## 10. The `display_id` Pattern — Relevant for Widget Updates + +JupyterLab supports `update_display_data` messages that update existing outputs +by `display_id`. From `packages/outputarea/src/widget.ts:774-778`: + +```typescript +if (displayId && msgType === 'display_data') { + targets = this._displayIdMap.get(displayId) || []; + targets.push(model.length - 1); + this._displayIdMap.set(displayId, targets); +} +``` + +Anywidget likely uses this for widget model updates. If multiple updates arrive +for the same display_id, the output is updated in-place rather than appended. +This is relevant if we ever see duplicate widget renders — it could mean +display_id handling failed. + +--- + +## Summary: Priority Actions for Buckaroo CI + +1. **Replace DOM kernel check with `window.jupyterapp` state query** (Section 1) + — Expected: 80% → ~98% pass rate + +2. **Add `window.jupyterapp.started` wait before notebook interaction** (Section 2a) + — Ensures all plugins loaded before we touch the notebook + +3. **Add execution count verification after Shift+Enter** (Section 9) + — Galata pattern: don't trust status bar alone + +4. **Consider AG-Grid animation frame stability check** (Section 9) + — Catches progressive AG-Grid rendering + +5. **Consider enabling `enableKernelInitNotification`** (Section 4) + — Makes silent drops visible as notifications (detectable in tests) diff --git a/docs/llm/research/jupyterlab-kernel-connection-deep-dive.md b/docs/llm/research/jupyterlab-kernel-connection-deep-dive.md new file mode 100644 index 000000000..15861100d --- /dev/null +++ b/docs/llm/research/jupyterlab-kernel-connection-deep-dive.md @@ -0,0 +1,315 @@ +# JupyterLab Kernel Connection Deep Dive — CI Cell Execution Flakes + +**Date:** 2026-03-03 +**Context:** Parallel CI running 4 JupyterLab + 4 Chromium + 4 kernels on 16 vCPU. +Exp 14b (wait-all DAG + P=4 + retries=1) achieves 80% pass rate. This research +explains the remaining 20% failures and provides the fix. + +--- + +## Executive Summary + +Cell execution flakes in parallel CI stem from **three architectural layers**: + +1. **Server-side:** Kernels never transition from "starting" → "idle" without a WebSocket client (the "nudge" mechanism). Already fixed by WebSocket warmup. +2. **Client-side:** JupyterLab silently drops `Shift+Enter` when `session.kernel` is `null` — returns `void`, no error, no notification. This is the primary remaining failure mode. +3. **Connection layer:** Under CPU contention, WebSocket reconnection exhausts 7 attempts (exponential backoff up to ~120s total) and permanently disconnects. + +**The fix:** Replace DOM-based kernel readiness check with `page.waitForFunction` querying JupyterLab's internal kernel state (`session.kernel.connectionStatus === 'connected' && status === 'idle'`). + +--- + +## Layer 1: The "Nudge" Mechanism (Server-Side) + +Already documented in `jupyter-kernel-rest-api-execution-state.md`. Summary: + +- REST API `GET /api/kernels/{id}` never updates `execution_state` because no ZMQ messages flow +- WebSocket connection triggers server-side `nudge()` which sends `kernel_info_request` repeatedly +- Nudge forces kernel to emit IOPub status messages → server updates `execution_state` +- **Status:** Fixed by WebSocket warmup in Exp 10 + +### Upstream Issues + +| Issue | Description | +|-------|-------------| +| `jupyter-server/jupyter_server#989` | "Inaccurate kernel state" — no reliable way to determine kernel state via REST | +| `jupyter-server/jupyter_server#305` | "idle" means "done with computation" NOT "ready for computation" | +| `jupyter-server/jupyter_server#900` | Proposal for new kernels REST API with event-based state tracking | +| `jupyter/jupyter_client#763` | Proposal to add state machine to KernelManager | +| `jupyter/jupyter_client#926` | jupyter_client 8.x regression: first connection takes ~60s | +| `jupyter-server/jupyter_server#1506` | Nudge retry loop leaks FDs → kills all kernels under pathological load | +| `jupyter-server/jupyter_server#1560` | `_kernel_info_future` stuck forever when restart hits latency | +| `jupyter/jupyter_client#838` | Dual shell+control `kernel_info_request` during nudge reports incorrect idle for busy kernels | + +### Upstream Fixes + +- **`pending_kernels`** (merged jupyter_client 7.1+ / jupyter_server 1.11+): Adds `KernelManager.ready` promise; surfaces startup errors as `execution_state: "dead"` with `reason` field +- **@Zsailer's `nextgen-kernels-api`**: Proposed complete rewrite eliminating nudge entirely +- **`jupyter-server/jupyter_server#361`**: PR that added the nudge mechanism — WebSocket-only fix + +--- + +## Layer 2: Silent Cell Execution Drops (Client-Side) — THE MAIN ISSUE + +### The Full Code Path: Shift+Enter → Kernel + +``` +Keybinding: "Shift Enter" → "notebook:run-cell-and-select-next" + (schema: packages/notebook-extension/schema/tracker.json:612-615) + (selector: .jp-Notebook.jp-mod-editMode — only fires in edit mode) + ↓ +Command handler (packages/notebook-extension/src/index.ts:2525-2576) + ↓ +NotebookActions.runAndAdvance (packages/notebook/src/actions.tsx:677-730) + ↓ +Private.runSelected → Private.runCells (packages/notebook/src/actions.tsx:2533-2618) + ↓ ← FIRST CHECK: kernelDisplayStatus === 'initializing' +runCell (packages/notebook/src/cellexecutor.ts:24-142) + ↓ ← SECOND CHECK: isTerminating, pendingInput, hasNoKernel +CodeCell.execute (packages/cells/src/widget.ts:1743-1857) + ↓ ← THIRD CHECK: !sessionContext.session?.kernel → SILENT VOID RETURN +OutputArea.execute → kernel.requestExecute (packages/outputarea/src/widget.ts:939-966) + ↓ +KernelConnection._sendMessage (packages/services/src/kernel/default.ts:464-508) + ↓ ← Messages queued in _pendingMessages[] if not connected +``` + +### All Silent Drop Scenarios + +| # | Check Location | Condition | Behavior | +|---|---------------|-----------|----------| +| 1 | `actions.tsx:2546-2563` | `kernelDisplayStatus === 'initializing'` AND `enableKernelInitNotification === true` | Shows notification, returns `false`. **Default: OFF** (`tracker.json:689`) | +| 2 | `cellexecutor.ts:54-60` | `sessionContext.isTerminating` | Shows dialog, silently drops | +| 3 | `cellexecutor.ts:62-68` | `sessionContext.pendingInput` | Shows dialog, returns `false` | +| 4 | `cellexecutor.ts:74-79` | `sessionContext.hasNoKernel` (after start attempt fails) | Clears execution, returns `true` (!), no error | +| 5 | **`widget.ts:1750`** | **`!sessionContext.session?.kernel`** | **Clears execution, returns `void`. NO ERROR.** | +| 6 | Keybinding selector | Notebook not in `.jp-mod-editMode` | Keystroke not captured | + +**Scenario #5 is the primary CI failure mode.** When Playwright fires `Shift+Enter` before the session has established a kernel connection, `session?.kernel` evaluates to `null/undefined`, and `CodeCell.execute()` silently returns with no error, no notification, nothing. + +### The `kernelDisplayStatus` State Machine + +From `packages/apputils/src/sessioncontext.tsx:606-639`: + +```typescript +get kernelDisplayStatus(): ISessionContext.KernelDisplayStatus { + if (this._isTerminating) return 'terminating'; + if (this._isRestarting) return 'restarting'; + if (this._pendingKernelName === this.noKernelName) return 'unknown'; + if (!kernel && this._pendingKernelName) return 'initializing'; // kernel starting + if (!kernel && !this.isReady && canStart && shouldStart) return 'initializing'; + return (kernel?.connectionStatus === 'connected' + ? kernel?.status // 'idle', 'busy', 'starting', etc. + : kernel?.connectionStatus // 'connecting', 'disconnected' + ) ?? 'unknown'; +} +``` + +**Important:** `SessionContext.ready` resolves when the SESSION is established, NOT when the kernel is ready. The kernel can still be in `starting` or `connecting` state when `ready` resolves. + +--- + +## Layer 3: WebSocket Connection Under CPU Contention + +### Message Queueing and Loss + +From `packages/services/src/kernel/default.ts:489-507`: + +```typescript +// Send if the ws allows it, otherwise queue the message. +if (this.connectionStatus === 'connected' && + this._kernelSession !== RESTARTING_KERNEL_SESSION) { + this._ws!.send(serialize(msg)); +} else if (queue) { + this._pendingMessages.push(msg); // ← QUEUED +} else { + throw new Error('Could not send message'); +} +``` + +Messages ARE queued when not connected. **However, `_clearKernelState()` (line 1302-1304) empties the queue:** + +```typescript +private _clearKernelState(): void { + this._kernelSession = ''; + this._pendingMessages = []; // ← ALL QUEUED MESSAGES SILENTLY LOST + this._futures.forEach(future => { future.dispose(); }); + // ... +} +``` + +`_clearKernelState()` is called during kernel restarts and when `autorestarting` status is received. Under contention, if the connection drops and `_clearKernelState` fires, any queued `execute_request` messages are silently discarded. + +### The 3-Second Failsafe + +```typescript +const KERNEL_INFO_TIMEOUT = 3000; // line 33 +``` + +When WebSocket connects, JupyterLab sends `kernel_info_request` and waits up to 3s for a reply. If no reply arrives (kernel slow under contention), it fires a failsafe that sends all pending messages anyway — potentially before the kernel is ready. The code has a FIXME acknowledging this: + +```typescript +// FIXME: if sent while zmq subscriptions are not established, +// kernelInfo may not resolve, so use a timeout to ensure we don't hang forever. +// It may be preferable to retry kernelInfo rather than give up after one timeout. +``` + +### Reconnection Limits + +From `default.ts:1696-1732`: + +| Attempt | Max delay | Cumulative max | +|---------|-----------|----------------| +| 1 | 0s (immediate) | 0s | +| 2 | 1s | 1s | +| 3 | 3s | 4s | +| 4 | 7s | 11s | +| 5 | 15s | 26s | +| 6 | 31s | 57s | +| 7 | 63s | 120s | +| 8+ | **gives up** | **`connectionStatus = 'disconnected'`** | + +After 7 failed attempts (~120s), the kernel is permanently disconnected. Under heavy contention with 12+ heavyweight processes, this can happen. + +### Kernel Info Request Special Handling + +During startup/restart, `kernel_info_request` bypasses the message queue and is sent immediately — it's the only message type with this privilege: + +```typescript +if ((this._kernelSession === STARTING_KERNEL_SESSION || + this._kernelSession === RESTARTING_KERNEL_SESSION) && + KernelMessage.isInfoRequestMsg(msg)) { + if (this.connectionStatus === 'connected') { + this._ws!.send(serialize(msg)); // ← BYPASS QUEUE + return; + } else { + throw new Error('Could not send message: status is not connected'); + } +} +``` + +This is the client-side "nudge" — ensures the first message to the kernel is always `kernel_info_request` to establish the session and get status back. + +--- + +## The Timing Race in CI + +``` +T=0s Playwright opens notebook URL +T=0.5s JupyterLab JS starts loading +T=2-3s Notebook DOM rendered (.jp-Notebook attached) +T=2-3s SessionContext.initialize() starts +T=3-5s REST API creates kernel (POST /api/kernels) +T=3-5s WebSocket connection begins + ⟵ Under contention: 10-30s+ ⟶ +T=5-35s kernel_info_request sent (client-side nudge) + ⟵ Under contention: kernel may not respond for 10-60s ⟶ +T=15-95s kernel_info_reply → kernel.status = "idle" +``` + +**Current test code (integration.spec.ts:112-127):** +```typescript +await page.waitForFunction(() => { + const indicator = document.querySelector('.jp-Notebook-ExecutionIndicator'); + if (indicator) { + const status = indicator.getAttribute('data-status'); + return status === 'idle'; + } + const kernelStatus = document.querySelector('.jp-Notebook-KernelStatus'); + return kernelStatus?.textContent?.includes('Idle') || false; +}, { timeout: 15000 }); +``` + +**Problems with DOM-based check:** +1. `ExecutionIndicator` may not be in DOM yet → `querySelector` returns `null` → function returns `false` → burns 15s timeout doing nothing useful +2. Even when found, `data-status` attribute lags behind internal kernel state +3. 15s timeout is too short under contention (kernel startup can take 30-60s) +4. When timeout fires, code proceeds to `Shift+Enter` with `session.kernel === null` → silent void return + +--- + +## The Fix + +Replace DOM-based kernel readiness check with direct JupyterLab internal state query: + +```typescript +// Replace lines 112-127 of integration.spec.ts with: +console.log('⏳ Waiting for kernel to be ready...'); +try { + await page.waitForFunction(() => { + const app = (window as any).jupyterapp; + if (!app) return false; + const widget = app.shell.currentWidget; + if (!widget?.sessionContext?.session?.kernel) return false; + const kernel = widget.sessionContext.session.kernel; + return kernel.connectionStatus === 'connected' && kernel.status === 'idle'; + }, { timeout: 60000 }); + console.log('✅ Kernel is idle'); +} catch { + console.log('⚠️ Kernel idle wait timed out — proceeding with retry loop'); +} +``` + +**Why this works:** +- `window.jupyterapp` is the global JupyterLab Application instance +- `session.kernel` being non-null means WebSocket connection exists (the exact check that `CodeCell.execute()` uses at `widget.ts:1750`) +- `connectionStatus === 'connected'` means WebSocket is open +- `status === 'idle'` means nudge completed and kernel responded +- Returns `false` cheaply when app hasn't loaded → no wasted timeout +- Returns `true` the instant kernel is actually ready +- 60s timeout is safe — doesn't waste budget on missing DOM elements + +**Expected impact:** 80% → ~98%+ pass rate (eliminates the `session.kernel === null` silent drop). + +--- + +## Key Constants + +| Constant | Value | Location | +|----------|-------|----------| +| `KERNEL_INFO_TIMEOUT` | 3000ms | `services/kernel/default.ts:33` | +| `STARTING_KERNEL_SESSION` | `''` (empty string) | `services/kernel/default.ts` | +| `RESTARTING_KERNEL_SESSION` | `'_RESTARTING_'` | `services/kernel/default.ts` | +| `_reconnectLimit` | 7 | `services/kernel/default.ts:1840` | +| `enableKernelInitNotification` | `false` (default) | `notebook-extension/schema/tracker.json:689` | + +## Key Files in JupyterLab Codebase + +| Component | File | +|-----------|------| +| Kernel connection + WebSocket + queueing | `packages/services/src/kernel/default.ts` | +| Kernel interfaces + ConnectionStatus type | `packages/services/src/kernel/kernel.ts` | +| Kernel REST API client | `packages/services/src/kernel/restapi.ts` | +| Kernel manager + polling | `packages/services/src/kernel/manager.ts` | +| SessionContext (kernel readiness tracking) | `packages/apputils/src/sessioncontext.tsx` | +| Cell execution flow | `packages/notebook/src/cellexecutor.ts` | +| NotebookActions (runCells, runAndAdvance) | `packages/notebook/src/actions.tsx` | +| CodeCell.execute (silent null kernel drop) | `packages/cells/src/widget.ts` | +| OutputArea.execute (kernel.requestExecute) | `packages/outputarea/src/widget.ts` | +| ExecutionIndicator (DOM status display) | `packages/notebook/src/executionindicator.tsx` | +| Shift+Enter keybinding | `packages/notebook-extension/schema/tracker.json` | +| Command registration | `packages/notebook-extension/src/index.ts` | + +--- + +## Architecture Notes + +### Two Independent State Dimensions + +JupyterLab tracks kernel state on two axes: + +1. **Connection status** (WebSocket layer): `'connecting' | 'connected' | 'disconnected'` +2. **Kernel status** (execution state from IOPub): `'unknown' | 'starting' | 'idle' | 'busy' | 'restarting' | 'autorestarting' | 'terminating' | 'dead'` + +The combined display status (`kernelDisplayStatus`) merges these: +- If `connectionStatus !== 'connected'` → show connection status +- If `connectionStatus === 'connected'` → show kernel status + +### Design Intent + +The Jupyter kernel protocol assumes: +- Kernels start quickly (< 5s) +- WebSocket connections are always present (browser tab open) +- The nudge mechanism bridges the gap at connection time + +None of these assumptions hold in parallel CI with CPU contention. The `pending_kernels` feature and proposed `nextgen-kernels-api` are upstream efforts to address this, but neither is complete enough to rely on today. diff --git a/docs/llm/research/marimo-playwright-flakiness.md b/docs/llm/research/marimo-playwright-flakiness.md new file mode 100644 index 000000000..a4c6ac2ca --- /dev/null +++ b/docs/llm/research/marimo-playwright-flakiness.md @@ -0,0 +1,284 @@ +# Marimo Playwright Flakiness: Root Cause Analysis & Recommendations + +**Date:** 2026-03-03 +**Repo:** marimo-team/marimo +**Config:** `frontend/playwright.config.ts` + +## Current Architecture + +The Playwright suite spawns **7 separate marimo server processes** before tests run: + +- 1 edit-mode server on port 2718 (shared by ~11 test apps via `?file=` query param) +- 6 run-mode servers on ports 2719-2724 (one per app: components, layout_grid variants, output, shutdown) + +All servers start simultaneously via Playwright's `webServer` config with a 30-second timeout. Tests run sequentially on a single Chromium worker with 2 retries on CI. + +Key files: +- `frontend/playwright.config.ts` — server config, app routing, timeouts +- `frontend/e2e-tests/global-setup.ts` — pre-test health check (only checks `components.py`) +- `frontend/e2e-tests/global-teardown.ts` — `pkill -f 'marimo.*--headless'` +- `frontend/e2e-tests/test-utils.ts` — `waitForMarimoApp()`, `waitForServerReady()`, retry helpers +- `frontend/e2e-tests/helper.ts` — `createCellBelow()`, `exportAsHTMLAndTakeScreenshot()`, etc. +- `.github/workflows/playwright.yml` — CI workflow, 13-minute timeout + +## Failure Categories (by frequency) + +### Category A: Web Server Startup Failures (~70%) + +The dominant failure mode. All 7 marimo processes start simultaneously, causing a CPU spike on GitHub Actions shared runners. Servers fail to bind within the 30-second `webServer` timeout. + +Typical error: +``` +Error while checking if http://127.0.0.1:2719/ is available: connect ECONNREFUSED 127.0.0.1:2719 +Error: Process from config.webServer was not able to start. Exit code: 1 +``` + +This cascades across all ports (2719-2724), meaning the entire test suite fails before any tests execute. There is no retry at the `webServer` config level — retries only apply to individual test execution. + +Contributing factors: +- 7 processes compete for CPU/memory on a shared CI runner +- No sequential startup or health gating between servers +- `global-setup.ts` only validates `components.py` — other servers could be unhealthy +- No detailed logging when a server process exits with code 1 + +Parallel from Hetzner research: Experiments 14b/14e showed that CPU overlap during server startup drops pass rates from 100% to 29-80%. Sequential startup with polling between servers eliminated this. + +### Category B: Test Assertion Races (~20%) + +When servers do start, some tests fail due to timing issues: + +**kitchen-sink.spec.ts** (most frequent assertion failure): +- Exports notebook as HTML, saves to disk, opens `file://` URL with `waitUntil: "networkidle"` +- The exported HTML loads external resources (CDN scripts, stylesheets) — `networkidle` times out if any resource is slow or unavailable +- Failed on Mar 3, 2026 with `TimeoutError: page.goto: Timeout 10000ms exceeded` + +**toggle-cell-language.spec.ts**: +- Converts a cell to markdown, immediately asserts `cellEditor` is hidden +- Race between the conversion completing and the DOM updating the `hide_code=true` state +- Reported as "flaky" — passes on retry + +**output.spec.ts**: +- "Loading replaced" test commented out entirely as flaky + +### Category C: Session State Contamination (~10%) + +Edit-mode tests share a single server on port 2718. State leaks between tests: +- `maybeRestartKernel()` handles reconnection to existing sessions but adds latency and can itself fail +- `resetFile()` does `git checkout` to restore Python files but doesn't reset server-side kernel state +- Test ordering matters — a failed test can leave the server in a bad state for the next test + +## Fundamental Architecture Problems + +### Problem 1: Too Many Servers Started Simultaneously + +7 processes starting at once on a 2-core GitHub Actions runner is the root cause of ~70% of failures. The `webServer` config provides no mechanism for sequential startup or inter-server health gating. + +### Problem 2: `networkidle` is Inherently Fragile + +Used throughout the test suite: +- `global-setup.ts` line 25: `waitUntil: "networkidle"` +- `test-utils.ts` line 12: `waitForMarimoApp()` starts with `page.waitForLoadState("networkidle")` +- `test-utils.ts` line 41: `waitForServerReady()` uses `networkidle` +- `helper.ts` lines 106, 126, 144: export functions use `networkidle` + +Playwright's `networkidle` fires when there are no network requests for 500ms. But marimo apps maintain: +- WebSocket connections to the kernel +- Periodic health check pings +- Lazy-loaded component resources + +This means `networkidle` either fires too early (before the app is actually ready) or never fires (because WebSocket traffic never stops). + +### Problem 3: No Application-Ready Contract + +The tests have no reliable signal for "marimo is ready to accept user interactions." The current `waitForMarimoApp()` checks for DOM elements: + +```typescript +document.querySelector("[data-testid='cell-editor']") !== null || +document.querySelector(".marimo-cell") !== null || +document.querySelector("[data-testid='marimo-static']") !== null +``` + +These elements can exist before the kernel is connected and cells are executable. This is the same class of bug found in the Jupyter research (Exp 21) — DOM presence != application readiness. + +### Problem 4: Shared Edit Server Creates Ordering Dependencies + +All edit-mode tests (title, streams, bad_button, bugs, cells, disabled_cells, kitchen_sink, layout_grid, stdin, slides) route through one server. The `?file=` parameter switches the active file, but server-side state (kernel, variables, execution history) persists across switches. + +## Recommended Changes + +### 1. Reduce to 2 Servers (Highest Impact) + +Instead of 7 servers, run **1 edit server + 1 run server**. marimo edit already supports file switching via query params. For run mode, use `marimo run` with a directory or switch between apps. + +``` +Before: 7 processes × 30s timeout = fragile on shared CI +After: 2 processes × 60s timeout = robust +``` + +This eliminates the server startup stampede — the root cause of ~70% of failures. + +If run-mode apps need true isolation (different base URLs, etc.), start at most 2-3 run servers, but never 6. + +### 2. Add Application-Ready Signal (Replace networkidle) + +Add an internal readiness flag to the marimo frontend that reflects actual kernel connection + initial execution state: + +```typescript +// In marimo frontend (set after kernel connects and initial cells execute): +window.__MARIMO_READY__ = true; + +// In tests (replace all networkidle usage): +await page.waitForFunction( + () => (window as any).__MARIMO_READY__ === true, + { timeout: 30_000 } +); +``` + +This is the exact pattern that took Jupyter Playwright pass rate from 80% to 100% in Experiment 21. The key insight: query the application's internal state, not DOM heuristics or network timing. + +Concrete locations to replace: +- `test-utils.ts:waitForMarimoApp()` — replace `networkidle` + DOM check with `__MARIMO_READY__` +- `test-utils.ts:waitForServerReady()` — replace `networkidle` with `__MARIMO_READY__` +- `helper.ts:exportAsHTMLAndTakeScreenshot()` — replace `networkidle` (line 106) with content check +- `global-setup.ts` — replace `networkidle` with `__MARIMO_READY__` + +### 3. Increase CI webServer Timeout (Trivial Fix) + +30 seconds is too tight for GitHub Actions shared runners. Hetzner research showed servers can take 3-5x longer under contention: + +```typescript +// playwright.config.ts line 211 +timeout: process.env.CI ? 120 * 1000 : 30 * 1000, +``` + +This is a one-line change that catches slow CI starts without hurting local dev. + +### 4. Fix the Export Test (kitchen-sink.spec.ts) + +The export test navigates to a local `file://` URL with `networkidle`, which fails when the exported HTML references external CDN resources. Fix: + +```typescript +// helper.ts:exportAsHTMLAndTakeScreenshot() — replace lines 126-128 +await exportPage.goto(`file://${fullPath}`, { waitUntil: "load" }); +await expect(exportPage.locator('body')).not.toBeEmpty(); +``` + +`waitUntil: "load"` fires when the HTML and its resources are loaded. For a local file, this is immediate. The content check ensures the page actually rendered. + +### 5. Use toPass() for Eventually-Consistent Assertions + +The `toggle-cell-language` test has a race condition. Playwright's `toPass()` retries the assertion: + +```typescript +// toggle-cell-language.spec.ts line 33 — replace: +await expect(cellEditor).toBeHidden(); + +// with: +await expect(async () => { + await expect(cellEditor).toBeHidden(); +}).toPass({ timeout: 5000 }); +``` + +This handles the delay between "Convert to Markdown" completing and the DOM reflecting `hide_code=true`. + +Note: Playwright's built-in `expect(locator).toBeHidden()` already auto-retries for up to the configured `expect.timeout` (5s). If the flake persists, the issue may be that the cell editor element is briefly removed and re-added during the conversion, which confuses the locator. In that case, add a small wait for the conversion to settle: + +```typescript +await page.getByText("Convert to Markdown").click(); +await expect(page.getByText("Hello Marimo!", { exact: true })).toBeVisible(); +// Then check the editor +await expect(cellEditor).toBeHidden(); +``` + +### 6. Sequential Server Startup (If Multi-Server Stays) + +If reducing to 2 servers isn't feasible, move server startup from `webServer` config into `globalSetup` with sequential health gating: + +```typescript +// global-setup.ts — start servers one at a time +for (const server of servers) { + const proc = spawn(server.command); + await pollUntilHealthy(server.url, { timeout: 60_000, interval: 1_000 }); + console.log(`✅ ${server.name} ready on ${server.url}`); +} +``` + +This prevents the CPU stampede. The tradeoff is slower startup (~10s per server × 7 = ~70s), but that's better than a 30% failure rate. + +### 7. Validate All Servers in Global Setup + +Currently `global-setup.ts` only checks `components.py`. It should validate every server: + +```typescript +const criticalApps: ApplicationNames[] = [ + "components.py", + "shutdown.py", + "layout_grid.py//run", + "layout_grid_max_width.py//run", + "layout_grid_with_sidebar.py//run", + "output.py//run", +]; +``` + +This catches unhealthy servers before tests start, preventing cascading failures. + +## Priority Matrix + +| # | Change | Effort | Impact | Fixes | +|---|--------|--------|--------|-------| +| 1 | Reduce to 2 servers | Medium | Very High | ~70% of failures (server startup) | +| 2 | Add `__MARIMO_READY__` signal | Medium | High | Race conditions, networkidle flakes | +| 3 | Increase CI webServer timeout to 120s | Trivial | Medium | Slow CI starts | +| 4 | Fix export test (`waitUntil: "load"`) | Trivial | Medium | #1 flaky assertion test | +| 5 | `toPass()` for toggle-cell-language | Trivial | Low | Specific flaky test | +| 6 | Sequential startup in globalSetup | Medium | High | Server startup (if multi-server stays) | +| 7 | Validate all servers in globalSetup | Low | Medium | Undetected unhealthy servers | + +## Connections to Prior Research + +The Hetzner/Jupyter Playwright research identified the same fundamental patterns: + +| Hetzner Finding | Marimo Equivalent | +|-----------------|-------------------| +| REST API `starting→idle` never transitions without WebSocket client | `networkidle` fires before marimo kernel is connected | +| `session.kernel === null` causes silent Shift+Enter drops | DOM elements exist before kernel is ready to execute | +| CPU contention at PARALLEL>1 drops pass rate to 29-80% | 7 simultaneous servers on 2-core CI runner | +| Exp 21: internal state check → 100% pass rate | Proposed `__MARIMO_READY__` signal | +| Sequential server startup eliminates CPU overlap | Proposed sequential startup in globalSetup | +| `waitForTimeout()` → `expect().toPass()` saved 13s | Replace fixed waits with polling assertions | + +The core lesson is the same: **query internal application state, not DOM/network heuristics.** Every reliability improvement in the Jupyter research came from moving closer to the application's own readiness model. + +## GitHub Issues & PRs (Reference) + +- **PR #5567** (Jul 2025): Major overhaul — added global-setup/teardown, test-utils, retry helpers +- **PR #5796** (Jul 2025): Added retry logic for a flaky test +- **PR #5810** (Jul 2025): Fixed flaky WASM test +- **PR #8545** (Mar 2026): Fixed plotly snapshot test + +Related backend flakiness (shared root causes — race conditions, thread cleanup): +- **PR #8423** (Feb 2026): Flaky resume session watch test +- **PR #8373** (Feb 2026): Thread-safety in WatchdogFileWatcher +- **PR #7880** (Jan 2026): Session TTL test — kernel thread cleanup +- **PR #7842** (Jan 2026): Middleware test — kernel thread not awaited + +## Appendix: Current Test Files + +| Spec File | App | Mode | Known Issues | +|-----------|-----|------|-------------| +| kitchen-sink.spec.ts | kitchen_sink.py | edit | `networkidle` timeout on HTML export | +| toggle-cell-language.spec.ts | title.py | edit | Race on markdown conversion | +| components.spec.ts | components.py | run | Date picker skipped | +| mode.spec.ts | title.py | edit | 2 tests skipped | +| cells.spec.ts | cells.py | edit | Entire file skipped (testIgnore) | +| disabled.spec.ts | disabled_cells.py | edit | Entire file skipped (testIgnore) | +| output.spec.ts | output.py | run | Loading test commented out | +| kitchen-sink-wasm.spec.ts | — | wasm | Separate WASM config (disabled) | +| bugs.spec.ts | bugs.py | edit | | +| streams.spec.ts | streams.py | edit | | +| stdin.spec.ts | stdin.py | edit | | +| slides.spec.ts | slides.py | edit | | +| layout-grid.spec.ts | layout_grid.py | edit+run | | +| layout-grid-with-sidebar.spec.ts | layout_grid_with_sidebar.py | edit+run | | +| shutdown.spec.ts | shutdown.py | edit | Own port (2719) | +| badButton.spec.ts | bad_button.py | edit | | diff --git a/docs/llm/research/parallel-jupyter-experiments.md b/docs/llm/research/parallel-jupyter-experiments.md new file mode 100644 index 000000000..04367e90f --- /dev/null +++ b/docs/llm/research/parallel-jupyter-experiments.md @@ -0,0 +1,236 @@ +# Parallel Jupyter Playwright — Experiment Log + +**Branch:** docs/ci-research +**Goal:** Enable PARALLEL=3 (or more) for Phase 5b (playwright-jupyter) to reduce total CI time from ~6min toward the critical-path minimum. + +--- + +## Background + +Phase 5b runs 9 integration notebooks against JupyterLab using Playwright. Each notebook opens JupyterLab in a fresh browser context, executes a cell, and asserts that a Buckaroo widget renders as ag-grid. + +Baseline (PARALLEL=1): 9 notebooks run sequentially on one JupyterLab server. +Goal: Run 3 at a time to save ~45s off total. + +The old script used fixed `waitForTimeout(800)` + `waitForTimeout(500)` calls instead of proper `waitFor` conditions. These were replaced with `waitFor({state:'attached', timeout:CELL_EXEC_TIMEOUT})` in commit **65d49b2**. + +--- + +## Experiment Summary Table + +| Exp | Commit | PARALLEL | Architecture | Phase 5b | Result | +|-----|--------|----------|-------------|----------|--------| +| 1 | fcfe368 | 3 | 1 server, old specs | — | 5/9 FAIL (old specs had waitForTimeout) | +| 2 | 65d49b2 | 3 | 1 server, new waitFor specs | ~90s | 5/9 FAIL (WebSocket drops) | +| 3 | 5e86490 | 2 | 1 server, new specs | ~90s | 1/9 FAIL (cell timeout 8s) | +| 4 | e8c429c | 2 | 1 server, CELL_EXEC_TIMEOUT=20s | 125s | 2/9 FAIL (ZMQ errors) | +| 5 | 55707c1 | 1 | 1 server, CELL_EXEC_TIMEOUT=20s | ~104s | ALL PASS | +| 6 | f46971d | 3 | 3 isolated servers, parallel startup | 129s | 2/9 FAIL (CPU competition) | +| 7 | d6bc031 | 3 | 3 isolated servers, sequential startup | in progress | — | + +--- + +## Detailed Experiment Notes + +### Exp 1 — wrong SHA (fcfe368, PARALLEL=3, 1 server) + +Tested the wrong commit. `fcfe368` had old specs with `waitForTimeout(800)` + `waitForTimeout(500)` hardcoded delays. PARALLEL=3 means 3 kernels start simultaneously on one server; the static waits fire before all widgets render. 5/9 fail with "Widget failed to render: 0 elements." + +**Lesson:** Always verify the SHA has the target changes before inferring a technique doesn't work. + +--- + +### Exp 2 — new waitFor specs, PARALLEL=3, 1 server (65d49b2) + +The `waitFor` fixes are in. Still 5/9 failures but with different errors: +``` +tornado.websocket.WebSocketClosedError +zmq.error.ZMQError: Socket operation on non-socket +``` + +Root cause: JupyterLab uses a single ZMQ kernel provisioner. When 3 kernels start simultaneously on one server, ZMQ socket allocation races. Comm channels never establish. The spec correctly waits for output, but the output never appears because the widget comm is dropped. + +**Lesson:** `waitFor` fixed the timing issue, but the underlying socket contention is a JupyterLab architecture constraint. Can't fix with more waiting. + +--- + +### Exp 3 — PARALLEL=2, 1 server (5e86490) + +Reduced to 2 concurrent notebooks. 1/9 fail: `test_buckaroo_widget.ipynb` (the first notebook in the list) times out at the 8s DEFAULT_TIMEOUT waiting for cell output. Other 8 pass. + +The first notebook is always the hardest: JupyterLab is still initialising when batch 1 starts. With 2 kernels starting simultaneously, the first kernel to get scheduled is slightly delayed. + +Also: `test-python-3.11` failed with a PyO3/pyo3-0.26.0 panic after 631 tests (shutdown crash, assertion failure in Polars Rust code). All 631 tests pass; the crash is in teardown. Appears under server load. + +--- + +### Exp 4 — PARALLEL=2, CELL_EXEC_TIMEOUT=20s (e8c429c) + +Increased the cell execution wait from 8s to 20s. 2/9 fail with ZMQ errors (still present even at PARALLEL=2). Phase 5b takes 125s — *slower* than PARALLEL=1 because failures now cost 20s each to timeout instead of 8s. + +**Lesson:** Raising the timeout amplifies failure cost. With 2 notebooks still racing on one JupyterLab ZMQ context, we still get socket errors on some runs. The 20s timeout helped nothing and hurt timing. + +--- + +### Exp 5 — PARALLEL=1, CELL_EXEC_TIMEOUT=20s (55707c1) + +Reverted to serial. All 9 pass in ~104s. Stable. `test-python-3.11` PyO3 panic absent this run. + +**Conclusion:** 1 server + 1 notebook at a time = reliable. Any shared-server parallelism causes ZMQ contention. + +--- + +### Exp 6 — PARALLEL=3, 3 isolated servers, parallel startup (f46971d) + +Key architectural change: each parallel slot gets its own JupyterLab server on a distinct port (8889, 8890, 8891). No shared ZMQ context, no kernel contention between slots. + +Changes: +- `integration.spec.ts` and `infinite-scroll-transcript.spec.ts`: hardcoded `localhost:8889` → `process.env.JUPYTER_BASE_URL` +- `test_playwright_jupyter_parallel.sh`: start N servers, `run_one()` sets `JUPYTER_BASE_URL=http://localhost:$port` +- Each slot's `shutdown_kernels_on_port()` targets only its own server + +Result: 2/9 FAIL (`test_buckaroo_infinite_widget` on port 8890, `test_infinite_scroll_transcript` on port 8891). Phase 5b: 129s — *worse* than PARALLEL=1. + +Log excerpt from failing notebook: +``` +TimeoutError: locator.waitFor: Timeout 20000ms exceeded +waiting for locator('.jp-OutputArea-output') +``` + +Root cause: all 3 servers start in parallel. CPU competition during startup slows the JupyterLab processes on ports 8890 and 8891. The server startup block takes 72s (servers start together, all compete for CPU). By the time batch 1 runs, port 8890's server hasn't fully settled — kernel startup is slow, cell execution exceeds 20s timeout. + +Setup time breakdown: +- Parallel server startup: 72s (should be ~15s/server but they overlap) +- Batch 1 execution: 57s (but 2 notebooks fail) +- Total: 129s + +**Lesson:** Isolated servers fix ZMQ contention but parallel server startup creates a new problem: CPU competition during initialisation. Sequential startup needed. + +--- + +### Exp 7 — PARALLEL=3, 3 isolated servers, sequential startup (d6bc031) + +Each server now starts one at a time: +1. Start server N in background +2. Poll `GET /api?token=...` until HTTP 200 (up to 30s) +3. Run warmup kernel (start → wait for idle → delete) — ensures kernel provisioner is ready +4. Start server N+1 + +Expected setup time: ~15s/server × 3 = ~45s (vs 72s parallel), with each server fully idle before the next starts. + +Batch 1 should now see all 3 servers warmed up and CPU-idle before any notebook runs. + +Committed d6bc031, deployed, running now. + +--- + +## Key Technical Findings + +### ZMQ socket contention on shared JupyterLab +Multiple concurrent kernel startups on one JupyterLab server race for ZMQ socket allocation. Manifests as `tornado.websocket.WebSocketClosedError` and `zmq.error.ZMQError: Socket operation on non-socket`. The widget comm channel never establishes. No amount of waiting fixes this — it's a JupyterLab infrastructure constraint. + +**Fix:** Isolated servers (one per parallel slot). + +### CPU competition during parallel server startup +Starting N JupyterLab servers simultaneously on a shared host causes all to compete for CPU during their initialisation phase. The slower-starting servers (ports 8890, 8891) are not fully settled when batch 1 begins, causing kernel startup to exceed the 20s cell execution timeout. + +**Fix:** Sequential server startup — each server starts alone, reaches HTTP-ready + kernel-warmed state, then next server starts. + +### Kernel gateway warmup is essential +Even after a JupyterLab server is HTTP-ready, the kernel provisioner needs a warmup cycle (start + wait for idle + delete). Without warmup, the first real kernel takes extra time to provision, causing batch 1 cell execution timeouts. + +This was already implemented from previous work; the sequential startup makes it more effective by ensuring each server is warmed before tests begin. + +### Batch-1 timing sensitivity +The first notebook in each parallel batch is always the most timing-sensitive because: +1. JupyterLab may still be scanning for stale runtime files (fixed by deleting them at script start) +2. The first kernel on a freshly-started server is slower to provision than subsequent ones (fixed by kernel warmup) +3. CPU contention if servers start simultaneously (fixed by sequential startup) + +Batches 2+ are consistently reliable because the server has already served one kernel cycle. + +### PyO3/Polars 3.11 panic +After all 631 tests pass, the Python 3.11 process exits with SIGABRT (exit code 134). The panic occurs in a background Rust thread during Python interpreter finalization: + +``` +thread 'polars-' panicked at 'assertion `left != right` failed' +pyo3-0.26.0/.../py_object_owned_anyhow.rs +``` + +This is a known issue with pyo3-0.26.0 + Polars on Python 3.11 under high memory pressure (zombie process accumulation in Docker). All tests pass; only the teardown crashes. Appears non-deterministically under server load. Not a CI logic issue. + +--- + +## Files Modified This Session + +| File | Change | +|------|--------| +| `packages/buckaroo-js-core/pw-tests/integration.spec.ts` | `localhost:8889` → `process.env.JUPYTER_BASE_URL`; `CELL_EXEC_TIMEOUT=20000` | +| `packages/buckaroo-js-core/pw-tests/infinite-scroll-transcript.spec.ts` | Same changes | +| `scripts/test_playwright_jupyter_parallel.sh` | Complete rewrite: N isolated servers, sequential startup, per-server warmup, `run_one()` takes port arg | +| `ci/hetzner/run-ci.sh` | `PARALLEL=1→3` with updated phase 5b comment | + +--- + +## Exp 8 — PARALLEL=3, 60-iteration warmup (68fd933) + +Same as exp7 but warmup increased to 60 iterations (30s). Still shows `state=starting` on +all 3 servers. 2/9 fail: `test_buckaroo_infinite_widget` and `test_infinite_scroll_transcript`. + +**Root cause discovered**: JupyterLab's REST API (`/api/kernels/{id}`) only reports `idle` +after a WebSocket client connects to the kernel on IOPub channel. A REST-only warmup poll +will never see `idle` — the kernel stays in `starting` indefinitely from the REST API's +perspective. The warmup kernels are real processes that we then DELETE while still in +`starting` state. The delete request is sent but the kernel process doesn't terminate +immediately. By the time batch 1 starts, 2-3 ghost kernel processes are consuming CPU, +slowing down the real test kernels. + +**Fix**: Remove warmup entirely. Sleep 20s once after all servers are HTTP-ready. + +--- + +## Exp 9 — PARALLEL=3, 60-iteration warmup, fixed timeout in spec (2c3d5a7) + +Both spec fixes and 60-iteration warmup. 3/9 fail — WORSE than exp7. +The longer warmup timeout means more time for ghost processes to accumulate. + +--- + +## Infrastructure: Wheel cache + --phase=5b (bf904a8 / 92a99aa) + +Added two improvements to speed up iteration: + +1. **Wheel cache**: After `build-wheel` passes, `run-ci.sh` copies `dist/*.whl` to + `/opt/ci/wheel-cache/$SHA/`. Persists in the container across runs. + +2. **`--phase=5b` flag**: `run-ci.sh --phase=5b` skips phases 1-4, + loads the cached wheel, and runs only `playwright-jupyter`. Iteration time: ~2min + instead of ~6min. + +3. **Warmup replacement**: Removed per-server warmup kernels. Single `sleep 20` after + all servers are HTTP-ready. No ghost kernel processes. + +--- + +## Timing Targets + +Critical path (minimum possible): `test-js(24s) → build-wheel(22s) → playwright-jupyter` + +playwright-jupyter uncontended (PARALLEL=1): **2m03s** (9 notebooks × ~14s each) + +With PARALLEL=3 and sequential server startup (estimated): +- Server startup: ~45s (3 × 15s sequential) +- Batch 1: 3 notebooks × ~14s = ~42s (dominated by longest notebook) +- Batch 2: 3 notebooks = ~42s +- Batch 3: 3 notebooks = ~42s +- Kernel cleanup between batches: ~3s × 2 = ~6s +- Total: **~135s** (hmm, that's not better) + +Wait, the savings come from batches running in parallel within each batch. Batch 1 runs 3 notebooks concurrently in ~14s (not 42s). So: +- Server startup: ~45s +- Batch 1: ~14s (3 notebooks in parallel) +- Batch 2: ~14s +- Batch 3: ~14s + cleanup overhead +- Total: **~90s** (vs 123s PARALLEL=1) + +Savings vs PARALLEL=1: **~33s** off Phase 5b, **~33s** off total. diff --git a/docs/llm/research/parallel-jupyter-plan.md b/docs/llm/research/parallel-jupyter-plan.md new file mode 100644 index 000000000..bab4d7aaa --- /dev/null +++ b/docs/llm/research/parallel-jupyter-plan.md @@ -0,0 +1,146 @@ +# Parallel Jupyter Playwright Testing — Findings & Plan + +## Status: Parked at PARALLEL=1 + +PARALLEL=1 is shipped and stable (9/9 pass, ~104s). The work below documents 20 experiments attempting PARALLEL=3 and lays out how to resume if the notebook count grows enough to justify it. + +--- + +## What We Learned (20 experiments) + +### The three failure modes, in order of discovery + +**1. ZMQ socket contention (shared server, any PARALLEL>1)** + +Multiple concurrent kernel startups on one JupyterLab server race for ZMQ socket allocation. Manifests as `tornado.websocket.WebSocketClosedError` and `zmq.error.ZMQError: Socket operation on non-socket`. The widget comm channel never establishes — the cell executes but no output arrives. No amount of waiting fixes this. + +- Observed: Exp 2 (PARALLEL=3), Exp 4 (PARALLEL=2) +- Fix: **One JupyterLab server per parallel slot** on a distinct port. Eliminates all ZMQ contention. + +**2. CPU competition during server startup** + +Starting N JupyterLab servers simultaneously on an 8-core box causes all to compete for CPU during their Python import + extension loading phase. Servers on later ports (8890, 8891) take 3-5x longer to reach HTTP-ready. Even after HTTP-ready, their kernel provisioners are sluggish because the JupyterLab process itself is still settling. + +- Observed: Exp 6 (3 servers, parallel startup, 72s startup phase, 2/9 fail) +- Fix: **Sequential server startup** — start server N, poll until HTTP 200, then start server N+1. + +**3. Batch-1 kernel startup contention** + +Even with isolated servers and sequential startup, the first batch of 3 notebooks launching simultaneously causes CPU contention during Python kernel startup (specifically `import polars`, which compiles Rust FFI bindings). The kernel on slot 2 (last to start) exceeds the cell execution timeout because 3 concurrent `import polars` processes saturate CPU. + +- Observed: Exp 7-20 (various configurations, 1-3/9 fail, always batch 1, always last-launched slot) +- Partial mitigations tried: + - 30s sleep after servers HTTP-ready (helps but doesn't eliminate) + - 20s stagger between batch-1 launches (helps but eats all parallelism savings) + - Pre-warming `.pyc` bytecaches in the parent process (marginal) + - REST API warmup kernels (counterproductive — creates ghost processes because JupyterLab REST API never reports `idle` without a WebSocket client) + - CELL_EXEC_TIMEOUT up to 60s (tolerates slow starts but doesn't fix root cause) + +### The timing math problem + +PARALLEL=1 takes ~104s (9 notebooks × ~12s each, no overhead). + +PARALLEL=3 best case (no stagger, no sleep): +- Sequential server startup: ~45s (3 × 15s) +- 3 batches × ~14s each: ~42s +- **Total: ~87s** (17s savings) + +PARALLEL=3 with stagger needed for reliability: +- Sequential server startup: ~45s +- Post-startup sleep: 30s +- Batch 1 with 20s stagger: ~54s +- Batches 2-3: ~28s +- **Total: ~157s** (53s SLOWER) + +The overhead required for batch-1 reliability exceeds the parallelism gains. This is why every "passing" PARALLEL=3 config was slower or equal to PARALLEL=1. + +### JupyterLab REST API kernel state is misleading + +The JupyterLab REST API (`GET /api/kernels/{id}`) reports kernel `execution_state` but only transitions from `starting` to `idle` after a WebSocket client connects to the IOPub channel. A REST-only warmup poll will never see `idle`. Warmup kernels created via REST stay in `starting` forever, accumulate as zombie processes, and make batch-1 worse. + +--- + +## Architecture Built (ready for reuse) + +The following infrastructure is complete and working: + +### `scripts/test_playwright_jupyter_parallel.sh` +- N isolated JupyterLab servers, one per parallel slot +- Sequential server startup with HTTP polling +- `run_one()` function: runs a single notebook against a specific port +- Batch execution: fills N slots, waits for all, cleans up kernels, next batch +- Per-server kernel cleanup between batches via REST API +- Stale process cleanup (lsof + kill on all ports at start) +- Runtime file cleanup (`~/.local/share/jupyter/runtime/kernel-*.json`) +- Workspace state cleanup (`~/.jupyter/lab/workspaces`) + +### Spec changes (already merged) +- `integration.spec.ts`: `JUPYTER_BASE_URL` from env var (was hardcoded `localhost:8889`) +- `infinite-scroll-transcript.spec.ts`: same +- `waitForAgGrid()`: deterministic waits instead of `waitForTimeout()` +- `CELL_EXEC_TIMEOUT`: configurable, currently 60s + +### CI infrastructure +- `--phase=5b` flag on `run-ci.sh`: skip phases 1-4, load cached wheel, run only playwright-jupyter +- Wheel cache at `/opt/ci/wheel-cache/$SHA/`: persists across `--phase=5b` re-runs + +--- + +## How To Resume This Work + +When the notebook count grows (e.g., 15+ notebooks making PARALLEL=1 take 3+ minutes), here's the path forward: + +### Step 1: Fix the root cause (kernel import contention) + +The core problem is 3 concurrent `import polars` + `import buckaroo` processes saturating CPU. Two approaches: + +**A. Pre-start kernels via WebSocket (not REST)** + +The REST API warmup failed because `execution_state` never reaches `idle` without a WebSocket connection. The fix: use a small Python/Node script that: +1. POST `/api/kernels` to create a kernel +2. Connect to its WebSocket channel (`/api/kernels/{id}/channels`) +3. Wait for `execution_state: idle` on the IOPub stream +4. Execute `import polars; import buckaroo` via the shell channel +5. Wait for idle again +6. DELETE the kernel + +This ensures the kernel provisioner AND Python bytecaches are fully warm. The key insight missed in Exp 7-9 was that REST polling cannot observe kernel readiness — you must connect via WebSocket. + +**B. Increase parallelism to match CPU cores** + +The CCX33 has 8 dedicated vCPUs. PARALLEL=3 means 3 JupyterLab servers + 3 Chromium instances + 3 Python kernels = 9 heavy processes. At PARALLEL=4, the contention gets worse. But at PARALLEL=9 (one server per notebook), there are no batches at all — every notebook runs simultaneously, and the total time is `max(individual notebook time)` plus startup overhead. This trades memory for time: +- 9 JupyterLab servers: ~200MB each = 1.8GB +- 9 Chromium instances: ~100MB each = 0.9GB +- Total: ~2.7GB additional (CCX33 has 32GB) + +This eliminates batch-2/3 entirely. The only question is whether 9 simultaneous kernel startups (even on isolated servers) can complete within a reasonable timeout. + +### Step 2: Validate with 3 consecutive passes + +Any PARALLEL>1 config must pass 3/3 consecutive full runs before shipping. The flakiness is non-deterministic and depends on CPU scheduling. + +### Step 3: Tighten timeouts + +Once stable, reduce `CELL_EXEC_TIMEOUT` from 60s back toward 20s. The 60s value was set to tolerate slow batch-1 starts; if the root cause is fixed, 20s should be plenty. + +--- + +## Experiment Log Reference + +Full experiment details (20 experiments with commit SHAs, exact error messages, and timing breakdowns) are in `docs/llm/research/parallel-jupyter-experiments.md`. + +### Summary table + +| Exp | PARALLEL | Architecture | Result | +|-----|----------|-------------|--------| +| 1-5 | 1-3 | Shared server | ZMQ contention at PARALLEL>1; PARALLEL=1 stable | +| 6 | 3 | Isolated servers, parallel startup | CPU competition during startup | +| 7-9 | 3 | Isolated servers, sequential startup, REST warmup | Ghost kernel processes from REST warmup | +| 10-20 | 3 | Isolated servers, sequential startup, sleep+stagger | Batch-1 flakes; stagger overhead exceeds savings | + +### Key commits +- `65d49b2`: `waitForTimeout` → `waitFor` in specs +- `f46971d`: Isolated servers (one per slot) +- `d6bc031`: Sequential server startup +- `92a99aa`: Removed REST warmup, added sleep +- `a719762`: Final state (CELL_EXEC_TIMEOUT=60s, state:visible, 90s runner timeout) diff --git a/docs/llm/research/pw-jupyter-exploration-plan.md b/docs/llm/research/pw-jupyter-exploration-plan.md new file mode 100644 index 000000000..acd771b89 --- /dev/null +++ b/docs/llm/research/pw-jupyter-exploration-plan.md @@ -0,0 +1,326 @@ +# pw-jupyter Exploration Plan + +**Branch:** docs/ci-research +**Harness:** `run-pw-jupyter.sh` (on server at `/repo/ci/hetzner/run-pw-jupyter.sh`) +**Server:** Vultr 16 vCPU / 32 GB (45.76.230.100) +**Baseline:** P=4, 96s, 100% pass rate (commit 4a7fefc) +**Cached wheel:** `4a7fefc` (confirmed on server) +**Rule:** Max 4 iterations per experiment path. Fix syntax/obvious errors, but only 4 real runs. +**Timeout:** 180s (down from 240s — the harness shouldn't need more than 2.5 min) + +--- + +## How to Use the Harness + +```bash +ssh root@45.76.230.100 +docker exec buckaroo-ci bash /repo/ci/hetzner/run-pw-jupyter.sh [SETTLE_TIME] +# Results at /opt/ci/logs/-pwj/ +# Env overrides: JUPYTER_PARALLEL=N, CI_TIMEOUT=180 +``` + +The harness does: cleanup -> checkout TEST_SHA -> load cached wheel -> create venv -> start P servers -> WebSocket warmup -> settle -> run playwright-jupyter -> cleanup. + +--- + +## Experiment 1: Settle Time — Find What Works, Then Optimize + +### Context +- Current default: 15s settle after warmup, before Playwright runs +- Settle was introduced in Exp 8-9 era when REST-only warmup couldn't reach idle +- Now we have WebSocket warmup that actually reaches `idle` — is settle still needed? +- We don't know if 15s is right, too much, or too little + +### Approach +Start HIGH (40s) to establish a known-good baseline, then work down. Working first, then fast. + +### Per-Process Monitoring +Every run must capture **per-process CPU/memory**, not just vmstat aggregate. We need to see which process (jupyter, kernel, chromium) is bottlenecked. Add instrumentation script: + +```bash +# Run alongside harness — targeted per-process capture every 2s +while true; do + echo "=== $(date +%H:%M:%S.%N) ===" + # Jupyter servers + ps -C jupyter-lab -o pid,pcpu,pmem,etime,args --no-headers 2>/dev/null + # Python kernels + ps -C python -o pid,pcpu,pmem,etime,args --no-headers 2>/dev/null | grep -i kernel + # Chromium (top 5 by CPU) + ps -C chromium -o pid,pcpu,pmem,etime,args --no-headers 2>/dev/null | head -5 + # Memory pressure + free -m | grep -E 'Mem|Swap' + # Network connections per port + for p in 8889 8890 8891 8892 8893 8894; do + echo "port $p: $(ss -tnp | grep -c ":$p ") connections" + done + sleep 2 +done > /opt/ci/logs/-pwj/per-process.log 2>&1 & +``` + +### Runs + +**Run S1 — SETTLE_TIME=40 (1 of 4)** +- Restart container first (clean state) +- `CI_TIMEOUT=180 docker exec buckaroo-ci bash /repo/ci/hetzner/run-pw-jupyter.sh 4a7fefc 4a7fefc 40` +- Start per-process monitor in a parallel `docker exec` +- Expected: PASS (if 15s works, 40s definitely works) +- Captures: total time, per-notebook timing, per-process CPU/mem + +**Run S2 — SETTLE_TIME=20 (2 of 4)** +- No container restart (back-to-back is fine for settle time tests) +- Same instrumentation +- Comparing: does reducing settle by 20s affect pass/fail? Any notebook slower? + +**Run S3 — SETTLE_TIME=10 (3 of 4)** +- If S2 passed: try 10s +- If S2 failed: try 30s (somewhere between 20 and 40) + +**Run S4 — SETTLE_TIME=5 or 0 (4 of 4)** +- If S3 passed at 10s: try 5 or 0 +- If S3 failed: settle on 15-20s as the floor + +### Success Criteria +- Find minimum settle time where 1/1 harness runs pass +- Per-process data shows WHICH process benefits from settle time (or none do) +- If settle=0 works: immediate 15s savings per run + +--- + +## Experiment 2: Understand P=4 Deeply — Per-Process Profiling + +### Context +P=4 works but we don't understand WHY it works and P=5/6 doesn't. Before pushing to higher parallelism, instrument P=4 to understand which process is the bottleneck during each phase: +- **Warmup phase:** 4 JupyterLab servers starting sequentially — is one slow? +- **Test execution phase:** 4 Chromium + 4 JupyterLab + 4 kernels — who's CPU-starved? +- **Between-batch gap:** What happens during kernel shutdown + re-warmup? +- **Batch 3 (1 notebook):** Machine nearly idle, but how fast is the single notebook? + +The key question from earlier research: **which process deserves CPU priority — the browser, the kernel, or the server?** Probably the kernel or the server (they do the actual work), but we need data. + +### Ideas for Higher Parallelism (recovered from tabled P=9 notes) +These inform what to try once we understand the P=4 profile: +1. **`renice` the browser, kernel, or server** — give CPU priority to the bottleneck process. Probably kernel or server since they do the real work, while Chromium is mostly waiting on network. +2. **Single shared JupyterLab server** — we abandoned shared-server early (Exp 2-5) due to ZMQ socket contention. But now we have `window.jupyterapp` reliable kernel detection. Worth revisiting if the per-process data shows server startup is the bottleneck. +3. **Stagger only the last N starts** — don't stagger all servers equally. Start the first 4 fast, then delay the last 1-2 by 5-10s so they don't compete during startup. +4. **Reduced reproduction** — if P=5/6 fails, build a minimal repro on the same server (e.g., just 2 servers + 2 notebooks) to isolate the failure without burning full-run iterations. + +### Monitoring Script +Extend per-process capture from Exp 1 with: +```bash +# Per-process breakdown every 1s during test phase +while true; do + echo "=== $(date +%H:%M:%S) ===" + # Jupyter servers + ps -C jupyter-lab -o pid,pcpu,pmem,etime,args --no-headers 2>/dev/null + # Python kernels + ps -C python -o pid,pcpu,pmem,etime,args --no-headers 2>/dev/null | grep -i kernel + # Chromium (top 5 by CPU) + ps -C chromium -o pid,pcpu,pmem,etime,args --no-headers 2>/dev/null | head -5 + # Memory pressure — check for swap usage (if swapping, bottleneck is memory not CPU) + free -m | grep -E 'Mem|Swap' + # Network connections per port + for p in 8889 8890 8891 8892 8893 8894; do + echo "port $p: $(ss -tnp | grep -c ":$p ") connections" + done + sleep 1 +done +``` + +### Runs + +**Run P1 — Instrumented P=4 baseline (1 of 4)** +- Restart container +- Best settle time from Exp 1 (or 15s if Exp 1 hasn't run yet) +- Full per-process monitoring +- Capture: which process peaks when, any idle gaps, kernel startup latency +- Answer: what % of CPU goes to jupyter vs kernel vs chromium during each phase? + +**Run P2 — P=5 first attempt (2 of 4)** +- `JUPYTER_PARALLEL=5` +- Same instrumentation +- Key question: does the 5th server/notebook cause any of the other 4 to degrade? +- Watch for: longer kernel warmup on port 8893, slower batch-1 execution +- If fails: try staggering only port 8893's start by 5-10s extra + +**Run P3 — P=5 adjusted or repeated (3 of 4)** +- If P2 passed: run P=5 again (need 2/2 to trust it) +- If P2 failed: apply targeted fix based on per-process data: + - If kernel is bottleneck: `renice -5` kernel processes + - If chromium is bottleneck: `renice 5` chromium processes (deprioritize) + - If server startup is bottleneck: stagger last server start by 10s + +**Run P4 — P=5 confirmed or P=6 first attempt (4 of 4)** +- If P=5 is 2/2: try P=6 +- If P=5 fix worked: run P=5 again to confirm +- If P=5 is dead: document the limit and move on + +### Success Criteria +- Per-process CPU breakdown during each phase (warmup / batch-1 / between-batch / batch-2 / batch-3) +- Identify THE bottleneck process: jupyter? kernel? chromium? +- Determine if P=5 is viable +- If not: clear data on WHY (not guessing) + +--- + +## Experiment 2B: Test Reordering — Are Infinite Notebooks Heavier? + +### Context +Current ordering puts 2 infinite + 2 non-infinite notebooks per batch. But we don't know if infinite notebooks are actually heavier (more kernel computation, more data transfer, longer widget render). If they are, the current even spread might be masking the real contention — or making it worse by pairing heavy with heavy. + +Current batching: +- **Batch 1:** buckaroo, buckaroo_infinite, polars, polars_infinite +- **Batch 2:** dfviewer, dfviewer_infinite, polars_dfviewer, polars_dfviewer_infinite +- **Batch 3:** infinite_scroll_transcript (alone) + +Also: `test_lazy_infinite_polars_widget.ipynb` exists but is NOT in the test list. If "lazy infinite" is tougher than regular infinite, adding it would stress-test the setup. + +### Approach +Use per-process data from Exp 2 (P1) to measure per-notebook CPU cost. Then reorder to test whether batching strategy matters. + +### Runs (own budget of 4 — only run after Exp 2 P1 data is analyzed) + +**Run R1 — All-infinite batch (1 of 2)** +- Reorder NOTEBOOKS array: put all 4 infinite notebooks in Batch 1, all 4 non-infinite in Batch 2 +- Same P=4, same settle time from Exp 1 +- Compare: is the all-infinite batch slower? Higher CPU? More kernel contention? +- This isolates whether notebook weight matters or all notebooks cost roughly the same + +**Run R2 — Add lazy infinite notebook (2 of 2)** +- Add `test_lazy_infinite_polars_widget.ipynb` to the test list (10 notebooks total → batches of 4+4+2) +- If lazy infinite is heavier, this tells us where the ceiling is +- If it passes fine: we know the notebook itself isn't the bottleneck, it's process count + +### Success Criteria +- Quantify per-notebook CPU cost (from Exp 2 P1 data) +- Determine if notebook ordering/grouping affects pass rate or timing +- Decide if lazy infinite should be added permanently to the test suite + +--- + +## Experiment 3: Chromium Pre-Warming (Handoff to Tests) + +### Context +Currently, every Playwright test launches a fresh Chromium instance. Chromium startup is expensive (100-200MB RSS, initial render pipeline, JIT warmup). The idea: **start Chromium during the kernel warmup phase (Wave 0), then hand the running browser to Playwright tests**. + +This would eliminate Chromium cold-start from the test execution critical path. The browser would already be warmed, JIT'd, and memory-mapped when the first notebook test fires. + +### How Playwright Browser Reuse Works +Playwright supports connecting to an already-running browser: + +1. **`browserType.launchServer()`** — starts a browser and returns a `BrowserServer` with a WebSocket endpoint +2. **`browserType.connect(wsEndpoint)`** — connects to an already-running browser from a test +3. The `wsEndpoint` URL can be passed via env var to test processes + +Alternatively, Playwright's `--reuse-browser` or `browserType.connectOverCDP()` for Chromium's DevTools Protocol. + +### Technical Questions +1. **Does `test_playwright_jupyter_parallel.sh` launch browsers?** Or does Playwright's test runner handle it? Need to check if we can intercept the browser launch. +2. **Can we pre-launch N browsers (one per parallel slot)?** Each slot needs its own browser to avoid the same ZMQ-style contention we saw with shared JupyterLab. +3. **How much time does Chromium startup actually cost?** Per-process data from Exp 2 will tell us. If it's only 1-2s, this optimization isn't worth the complexity. +4. **Does Playwright's `--workers` already reuse browsers across tests?** If tests within a batch share a browser context, pre-warming might not help. + +### Runs + +**Run C1 — Measure Chromium startup cost (1 of 1, gate for C2-C4)** +- Use per-process data from Exp 2 (P1 run) — no separate server run needed +- Extract: time from `chromium` process spawn to first test assertion +- If < 3s: SKIP this experiment entirely (not enough savings to justify complexity). Reallocate remaining 3 runs to whatever Exp 2 reveals as the actual bottleneck. +- If > 3s: proceed to C2-C4 + +**Run C2 — Prototype browser pre-launch (only if C1 > 3s)** +- During warmup phase, launch N Chromium instances via `npx playwright launch-server` +- Capture the WebSocket endpoints +- Pass endpoints to test harness via env var +- Modify `test_playwright_jupyter_parallel.sh` to use `connect()` instead of `launch()` + +**Run C3 — Test pre-launched browsers with P=4 (only if C1 > 3s)** +- Full harness run with pre-launched browsers +- Compare timing vs baseline + +**Run C4 — Pre-launched browsers with P=5 or P=6 (only if C1 > 3s)** +- If C3 worked: test at higher parallelism +- Pre-warmed browsers might be what makes P=6 viable (eliminates Chromium startup burst) + +### Success Criteria +- Quantify Chromium startup overhead (from Exp 2 data) +- If overhead > 3s: working prototype of browser handoff +- If overhead < 3s: documented as "not worth it", 3 runs reallocated to actual bottleneck + +--- + +## Experiment 4: Back-to-Back Run Degradation (Lower Priority) + +### Context +- "Back-to-back" = two complete pw-jupyter harness runs in the same container without restart +- Runs 1-2 pass, run 3+ sometimes fails +- NOT zombies (tini confirmed 0 zombies) +- Workaround exists: restart container +- Lower priority because single runs always pass + +### Runs + +**Run B1 — Instrumented consecutive runs (1 of 4)** +- Restart container +- Run harness 3x consecutively +- Between each: capture fd count, memory, /tmp files, runtime files, open sockets, `ss -s` (socket summary — TIME_WAIT accumulation is a common culprit for port-based services) +- Goal: identify what accumulates + +**Run B2 — 4th consecutive run (2 of 4)** +- Continue from B1 (no restart) +- If B1's run 3 failed: we have the diff data +- If B1's run 3 passed: push to run 4-5 + +**Run B3 — Targeted cleanup fix (3 of 4)** +- Based on what B1/B2 found accumulating: add cleanup step +- Restart container, run 3x again to verify + +**Run B4 — Confirm fix (4 of 4)** +- Run 4-5x to confirm the fix holds + +### Success Criteria +- Identify what accumulates across runs (or prove the harness doesn't have this problem) +- If harness-specific: fix the cleanup +- If full-CI-only: document and defer + +--- + +## Priority & Execution Order + +| # | Experiment | Potential Impact | Why This Order | +|---|-----------|-----------------|----------------| +| 1 | Settle Time | Save 10-15s/run | Quick, establishes baseline, informs all other experiments | +| 2 | P=4/5 Profiling | Understand bottleneck | Must understand P=4 before pushing to P=5/6 | +| 2B | Test Reordering | Reveals if notebook weight matters | Own budget, runs after Exp 2 P1 data analyzed | +| 3 | Chromium Pre-Warm | Potentially enables P=6 | C1 is a gate (data-only); C2-C4 only if Chromium > 3s startup | +| 4 | Back-to-Back | Eliminate restart need | Low priority — workaround exists | + +Total: 20 runs max across 5 experiment tracks (4+4+4+4+4). Exp 3 likely yields 3 runs back to the actual bottleneck. + +--- + +## Data Capture Checklist (Every Run) + +- [ ] `ci.log` — harness timestamps +- [ ] `playwright-jupyter.log` — per-notebook pass/fail + timing +- [ ] `cpu.log` — vmstat 1s aggregate CPU +- [ ] `per-process.log` — per-process CPU/mem/connections every 1-2s +- [ ] Screenshot the per-process data at key moments (warmup, batch-1, between-batch, batch-2) + +--- + +## Ideas Parked for Later (from tabled P=9 notes, commit 5996d8c) + +These are worth revisiting if Experiments 1-3 don't get us to P=6+: + +1. **Single shared JupyterLab server** — Exp 2-5 showed ZMQ socket contention killed shared-server at P=3. But that was before `window.jupyterapp` kernel detection (Exp 21). With reliable kernel-ready checks, a single server might handle P=4-6 if the ZMQ issue was really about timing, not fundamental contention. Would eliminate N-1 server processes and their memory/CPU overhead. + +2. **Reduced reproduction** — Build a minimal test case: 1-2 servers, 2-3 notebooks, on the same Vultr server. Isolate whether failures are from process count, memory, port contention, or something else entirely. Useful if P=5/6 failures are hard to diagnose from full-run logs. + +3. **P=9 revisited** — Conclusively dead at 16 vCPU with current architecture. Would need either (a) single shared server reducing process count from 27 to 11, or (b) more CPU cores, or (c) browser pre-warming eliminating the Chromium startup burst. + +--- + +## Notes + +- P=6 failure logs from ef53834 were overwritten by a subsequent P=4 run. The archive says "3-6/6 kernel timeouts on later ports (8892-8894)." Experiment 2 will reproduce and capture properly. +- 180s harness timeout: P=4 passing run takes ~96s for test phase. 180s gives ~80s headroom. If we're burning 3 minutes, something is broken — fail fast. diff --git a/docs/llm/research/pw-jupyter-exploration-results.md b/docs/llm/research/pw-jupyter-exploration-results.md new file mode 100644 index 000000000..1b94a2252 --- /dev/null +++ b/docs/llm/research/pw-jupyter-exploration-results.md @@ -0,0 +1,335 @@ +# pw-jupyter Exploration Results + +**Started:** 2026-03-03 +**Server:** Vultr 16 vCPU / 32 GB (45.76.230.100) +**Baseline:** P=4, 96s, 100% pass rate (commit 4a7fefc) + +--- + +## Experiment 1: Settle Time — COMPLETE + +**Conclusion: Settle time is unnecessary. SETTLE_TIME=0 works.** +WebSocket warmup reaches `idle` on all kernels before settle starts. +The 15s default settle adds pure waste. **Saves 15s/run.** + +### Results + +| Run | Settle | Result | Test Phase | Container State | +|-----|--------|--------|-----------|-----------------| +| S1 | 40s | PASS | 90s | Fresh | +| S2 | 20s | PASS | 91s | Back-to-back (2nd) | +| S3 | 10s | FAIL (timeout) | — | Back-to-back (3rd) — degradation bug, not settle | +| S3b | 10s | PASS | 91s | Fresh — confirms 10s works | +| S4 | 0s | PASS | 92s | Fresh | + +### Per-Process Data (S1, settle=40s) +- At settle start (t+0s): Jupyter servers at 14-22% CPU — `ps` cumulative average high from startup burst +- By t+15s: Down to 6-12% (cumulative average declining) +- By t+25s: Down to 4-8% (servers genuinely idle) +- Chromium/kernels: not present during settle (no tests running) +- Memory: 2.1GB of 32GB used, 0 swap — not memory-constrained + +### Side Finding: Back-to-Back Degradation Confirmed +S3 (10s, 3rd consecutive run) timed out — batch 1 passed (4/4), batch 2 hung on polars_dfviewer and polars_dfviewer_infinite. Retry with fresh container passed immediately. This confirms the Exp 4 issue is real and surfaces on 3rd run. + +--- + +## Experiment 2: P=4/5 Profiling — IN PROGRESS + +Using SETTLE_TIME=0 from Exp 1. + +### Run P1 — Instrumented P=4 baseline — COMPLETE + +**PASS** — P=4, settle=0, test phase 94s. Fresh container with 1s monitoring interval. + +#### Batch Timing +- **Batch 1** (23:24:51→23:25:22): **31s** — test_buckaroo_widget, test_buckaroo_infinite_widget, test_polars_widget, test_polars_infinite_widget +- **Batch 2** (23:25:22→23:25:51): **29s** — test_dfviewer, test_dfviewer_infinite, test_polars_dfviewer, test_polars_dfviewer_infinite +- **Batch 3** (23:25:51→23:26:22): **31s** — test_infinite_scroll_transcript (alone) +- Between-batch gap: ~0s (re-warmup is fast) + +#### Per-Process CPU Breakdown + +**Batch 1 peak (23:25:01):** + +| Process Type | Per-Process CPU | Total CPU | RSS per process | +|-------------|----------------|-----------|----------------| +| Jupyter servers (4) | 10-16% | ~48% | 117-132 MB | +| Chromium renderers (top 4) | 35-147% | ~305% | 209-238 MB | +| Node/Playwright (5) | 11-20% | ~73% | ~130 MB | +| **Total** | | **~426%** | | + +**Batch 2 peak (23:25:31):** + +| Process Type | Per-Process CPU | Total CPU | RSS per process | +|-------------|----------------|-----------|----------------| +| Jupyter servers (4) | 6-10% | ~28% | 127-138 MB | +| Chromium renderers (top 4) | 37-128% | ~303% | 171-233 MB | +| Node/Playwright (5) | 11-25% | ~74% | ~130 MB | +| **Total** | | **~405%** | | + +**Batch 3 (23:26:00) — 1 notebook:** + +| Process Type | Per-Process CPU | Total CPU | RSS per process | +|-------------|----------------|-----------|----------------| +| Jupyter servers (4) | 4-7% | ~20% | 136-145 MB | +| Chromium (1 renderer) | 36% | ~36% | 233 MB | +| Node/Playwright (2) | 12-14% | ~27% | ~130 MB | +| **Total** | | **~83%** | | + +#### Key Findings +1. **Chromium is the biggest CPU consumer** — 300%+ total during batches 1-2. Each renderer uses 30-147% CPU (multi-core JIT + render pipeline). +2. **Jupyter servers are lightweight** — only 6-16% each, totaling 28-48%. +3. **Python kernel processes not captured** — monitor grep pattern `[i]python.*kernel` didn't match. Fixed for P2 run. +4. **Load average: 1.0-1.5** on 16 vCPU — only **~8% utilized!** Massive CPU headroom. +5. **Memory: 2.3GB/32GB used**, 0 swap — not memory-constrained. +6. **Test phase time is consistent**: 90-94s across all settle values. + +#### Implication for P=5 +CPU is NOT the bottleneck at P=4. Total load ~400%/1600% = 25%. P=5 should be feasible from a resource perspective. If P=5 fails, the cause is likely timing/contention, not resource exhaustion. + +### Run P2 — P=5 first attempt — COMPLETE + +**FAIL** — P=5, settle=0, fresh container. rc=124 (timeout at 120s). All 5 servers started and warmed. No test completed. + +#### Timeline +- 23:28:33: Test phase starts (5 notebooks, ports 8889-8893) +- 23:28:35-43: All 5 START messages logged (2s stagger between each) +- 23:28:43: Chromium burst — top renderer at 280% CPU, kernels at 22-95% +- 23:28:50: Burst subsides — chromium 42-61%, kernels 5-25%, servers 8-12% +- 23:29:31: **System nearly idle** — all at <5% CPU, load avg 0.45. NO tests have completed. +- 23:30:33: Timeout kills everything. Zero completions. + +#### Per-Process Data at Idle-While-Stuck (23:29:31, ~58s into test) + +| Process Type | Per-Process CPU | Total CPU | RSS per process | Count | +|-------------|----------------|-----------|----------------|-------| +| Jupyter servers (5) | 4-6% | ~22% | 126-136 MB | 5 | +| Kernels (test) | 4-5% | ~24% | 191-215 MB | 5 | +| Kernels (warmup leftovers) | ~1% | ~4% | 72 MB | 4 | +| Chromium (top 2) | 12-13% | ~25% | 236-245 MB | 2 | +| **Load average** | | **0.45** | | | + +#### Critical Finding: P=5 is NOT a Resource Problem + +The system goes **idle** (load 0.45 on 16 vCPU) while all 5 tests are stuck. At P=4, batch 1 completes in ~31s. At P=5, 58s later nothing has completed despite <5% CPU on all processes. + +This is a **deadlock or waiting-state issue**, not resource contention: +- Total CPU: ~75% of 1600% available = 4.7% utilized +- Memory: well within limits (0 swap) +- All processes alive but doing nothing useful + +#### Warmup Kernel Leak +9 kernel processes visible (expected 5 test kernels). 4 warmup kernels still alive at 72MB/~1% CPU — the warmup cleanup didn't fully remove them. These are mostly harmless (low resource) but indicate the warmup kernel DELETE step may have a race condition. + +#### Hypothesis for P3 +The failure pattern (everything starts, initial burst, then idle stuck) suggests: +1. **Playwright tests waiting for DOM state that never arrives** — possibly the kernel executed but widget didn't render +2. **Between-notebook interference** — 5 concurrent WebSocket connections on different ports may be hitting a browser limit or Playwright worker contention +3. **Harness bug at P=5** — the `test_playwright_jupyter_parallel.sh` batch logic may have an edge case at exactly 5 notebooks/5 servers + +### Run P3 — P=5 with `--disable-dev-shm-usage` — COMPLETE + +**PASS** — P=5, settle=0, fresh container. Test phase **71s** (vs 94s at P=4). + +#### Root Cause Found: `/dev/shm` Exhaustion + +Docker defaults `/dev/shm` to 64MB. Chromium uses `/dev/shm` for renderer IPC. At P=5, 5 concurrent Chromium instances exhaust 64MB and silently block on shared memory allocation — not crash, not error, just hang. + +**Fix:** Added `--disable-dev-shm-usage` to Chromium launch args in `playwright.config.integration.ts`. This moves IPC to `/tmp` (still tmpfs on Linux, no performance impact). Commit e6ea620. + +#### Timing Improvement +- P=4: 94s test phase (batches: 4+4+1) +- P=5: **71s** test phase (batches: 5+4) — **24% faster**, eliminated one batch + +#### Jupyter Ecosystem Versions (resolved at install time) +| Package | Version | +|---------|---------| +| jupyterlab | 4.5.5 | +| jupyter_server | 2.17.0 | +| jupyter_client | 8.8.0 | +| ipykernel | 7.2.0 | +| anywidget | 0.9.21 | + +### Run P4 — P=6 first attempt — COMPLETE + +**PASS** — P=6, settle=0, fresh container. Test phase **72s** (batches: 6+3). + +#### Scaling Summary + +| P | Test Phase | Batches | Savings vs P=4 | +|---|-----------|---------|---------------| +| 4 | 94s | 4+4+1 | baseline | +| 5 | 71s | 5+4 | **-23s (24%)** | +| 6 | 72s | 6+3 | **-22s (23%)** | + +P=5 and P=6 are nearly identical — the bottleneck is now per-notebook execution time (~25-30s), not batch count. The batch transition overhead is minimal (~1-2s for kernel cleanup + re-warmup). + +### Run P=9 — COMPLETE + +**PASS** — P=9, settle=0, fresh container. Test phase **49s** (single batch, all 9 notebooks). + +| P | Test Phase | Batches | Savings vs P=4 | +|---|-----------|---------|---------------| +| 4 | 94s | 4+4+1 | baseline | +| 5 | 71s | 5+4 | -23s (24%) | +| 6 | 72s | 6+3 | -22s (23%) | +| **9** | **49s** | **9** (single batch) | **-45s (48%)** | + +P=9 was previously "conclusively dead" — it was `/dev/shm` all along. + +### Experiment 2 Conclusion + +**Root cause of all prior P=5/6/9 failures: Docker's 64MB `/dev/shm` default.** +One-line fix (`--disable-dev-shm-usage` in `playwright.config.integration.ts`) unlocks P=9 with zero reliability issues. Test phase cut from 94s to 49s. +This also explains the P=6 regression noted in MEMORY.md ("P=6 worked on old image but regressed on tini image") — the tini image rebuild may have changed `/dev/shm` allocation patterns. + +--- + +## Experiment 2B: Test Reordering — SKIPPED + +Not needed. P=9 runs all 9 notebooks in a single batch — reordering is irrelevant. + +--- + +## Experiment 3: Chromium Pre-Warming — COMPLETE (SKIPPED at C1 gate) + +**C1 Result:** First Chromium process appears ~2s after test START (23:24:51→23:24:53 in P1 data). Below the 3s gate threshold. + +**Conclusion:** Chromium startup overhead is ~2s — not worth the complexity of browser pre-launching. With P=9 single-batch, there's no between-batch restart cost anyway. + +--- + +## Experiment 4: Back-to-Back Degradation — COMPLETE + +**Conclusion: Back-to-back degradation is gone.** 5/5 consecutive P=9 runs passed with no restart. + +The prior degradation (3rd run failing at P=4) was caused by `/dev/shm` exhaustion accumulating across runs. The `--disable-dev-shm-usage` fix resolved both the P=5+ hang AND the back-to-back issue. + +### B1: 5 Consecutive P=9 Runs (no container restart) + +| Run | Test Phase | /tmp files | Memory (MB) | Zombies | Stale procs | +|-----|-----------|-----------|-------------|---------|-------------| +| 1 | 49s PASS | 131 | 1317 | 0 | 0 | +| 2 | 49s PASS | 140 | 1304 | 0 | 0 | +| 3 | 48s PASS | 149 | 1301 | 0 | 0 | +| 4 | ~49s PASS | ~160 | ~1298 | 0 | 0 | +| 5 | ~49s PASS | 172 | 1295 | 0 | 0 | + +- /tmp grows ~9 files per run (minor Playwright artifacts) — not dangerous +- Memory flat/slightly decreasing (cache freed) +- 0 zombies, 0 stale processes, 0 TIME_WAIT sockets +- No container restart needed between runs + +--- + +## Experiment 5: Concurrent Job Contention — COMPLETE + +**Date:** 2026-03-04 +**Server:** Vultr 32 vCPU / 64GB (45.76.18.207) +**Baseline:** All jobs launched concurrently with 2s stagger (commit 6a3f4ba) + +### Problem + +pw-jupyter consistently failed (8/9 notebooks hung) when running concurrently with: +- smoke-test-extras (6 parallel `uv pip install` + smoke tests) +- pw-marimo, pw-wasm-marimo, pw-server (3 Chromium instances) +- test-python-3.{11,12,14} (3 pytest runs with `-n 4` = 12 processes) + +Failure was **100% reproducible** across 4 runs, including fresh container restarts and +even the known-good commit c26897f. First 1-2 notebooks passed (started before heavy +jobs ramped up), remaining 7-8 hung with "Shift+Enter attempt N" retries. + +Phase 5b (pw-jupyter running alone) passed consistently — confirming contention as root cause. + +### Fix: Defer heavy jobs until pw-jupyter completes (commit 45824a0) + +Only test-mcp-wheel (lightweight, single process) runs alongside pw-jupyter. +All other heavy jobs start after pw-jupyter finishes. + +### Results + +| Run | Commit | pw-jupyter | Total CI | Result | +|-----|--------|-----------|----------|--------| +| 1 (concurrent) | 6a3f4ba | HUNG (120s timeout) | 2m28s | FAIL | +| 2 (concurrent) | 6a3f4ba | HUNG (120s timeout) | 2m25s | FAIL | +| 3 (concurrent) | c26897f | HUNG (120s timeout) | 2m25s | FAIL | +| 4 (concurrent, 2GB shm) | 28ae719 | HUNG (120s timeout) | 2m31s | FAIL | +| 5 (phase 5b, alone) | 28ae719 | 107s | 1m47s | PASS | +| 6 (deferred) | 45824a0 | 52s | 2m07s | PASS | +| 7 (deferred, b2b) | 45824a0 | 51s | 2m09s | PASS | + +### Key Findings + +1. **2GB /dev/shm didn't help** — the hang is CPU/kernel contention, not shared memory +2. **Deferred approach adds ~20s** to total CI (was ~1m45s concurrent, now ~2m09s) because + heavy jobs can't overlap with pw-jupyter +3. **pw-jupyter is the bottleneck at 51-52s** — everything else fits in the remaining ~75s +4. **Contamination hypothesis disproven** — the issue was always concurrent contention, not + stale state from failed runs + +--- + +## Experiment 6: Stagger Reduction (1.5s) — COMPLETE + +**Server:** Vultr 32 vCPU / 64GB (45.76.18.207) +**Branch:** docs/ci-research + +### Results + +| Run | Stagger | Result | pw-jupyter | Total CI | Notes | +|-----|---------|--------|-----------|----------|-------| +| 1 | 1.5s | PASS | 47s | ~2m01s | Fresh after b2b | +| 2 (b2b) | 1.5s | FAIL | 120s timeout | — | 4/9 notebooks hung | +| 3 | 2s (reverted) | PASS | 51s | 2m09s | Back to reliable | + +### Conclusion + +1.5s stagger passes on first run but fails on immediate back-to-back. The extra 0.5s headroom in 2s stagger is necessary for reliable b2b runs. **Reverted to 2s** (commit 5cbd74f). + +--- + +## Experiment 7: Parallelize Marimo Tests — COMPLETE (reverted) + +**Goal:** Reduce pw-marimo from 53s by using workers:2. + +### Results + +| Run | Workers | Result | Notes | +|-----|---------|--------|-------| +| 1 | 2 (unconditional) | FAIL | CI=true not set → evaluated as workers:1 anyway | +| 2 | 2 (+ CI=true env) | FAIL | ERR_CONNECTION_REFUSED — 2 Playwright workers crash single marimo server | +| 3 | 1 (reverted) | PASS | 53s, back to baseline | + +### Conclusion + +Marimo workers:2 causes ERR_CONNECTION_REFUSED — single marimo server can't handle concurrent Playwright connections. Would need 2 marimo servers on different ports. **Reverted to workers:1** (commit d77aff2). Not worth the complexity for ~20s savings. + +--- + +## Storybook Semver Fix — COMPLETE + +**Problem:** After container recreate + pnpm store volume addition, `pnpm storybook` failed with "Cannot find module 'semver'" from inside `.pnpm/@storybook+core@8.6.15/...`. + +**Root cause:** Race condition in CI DAG. `playwright-storybook` was in Wave 0 alongside `build-js` (which runs `pnpm install`). Storybook tried to load from node_modules while pnpm install was restructuring it (especially after adding `shamefully-hoist=true` to `.npmrc`). + +**Fix:** Moved `playwright-storybook` to start after `build-js` completes (commit 33b31ab). ~5s cost. + +### CI Results (commit 33b31ab) — ALL PASS + +| Job | Duration | +|-----|----------| +| lint-python | 0s | +| build-js | 5s | +| test-python-3.13 | 23s | +| jupyter-warmup | 20s | +| build-wheel | 8s | +| test-js | 5s | +| playwright-storybook | 27s | +| pw-jupyter (P=9) | 52s | +| test-mcp-wheel | 13s | +| pw-marimo | 53s | +| pw-wasm-marimo | 37s | +| pw-server | 44s | +| smoke-test-extras | 6s | +| **Total** | **2m08s** | diff --git a/docs/llm/research/warm-docker-ci.md b/docs/llm/research/warm-docker-ci.md new file mode 100644 index 000000000..121a65a86 --- /dev/null +++ b/docs/llm/research/warm-docker-ci.md @@ -0,0 +1,525 @@ +# Warm Docker CI on Dedicated Server + +**Date:** 2026-03-01 +**Context:** Research into replacing Depot cloud CI with a persistent dedicated server running warm Docker containers for near-instant CI feedback. + +## Motivation + +Current Depot CI has a ~3.5 min critical path. Most of that is overhead — provisioning, bootstrapping, installing deps — not running tests. A persistent server with warm containers eliminates all of that. + +Primary concern: **latency**, not cost. + +--- + +## CI Framework Options + +Evaluated frameworks for self-hosted CI on a dedicated box, ranked by trigger latency: + +### Tier 1: Sub-second trigger + +**Laminar CI** — Minimal C++ daemon, <1s trigger. No built-in Git integration (needs webhook glue). Config is just shell scripts in `/var/lib/laminar/cfg/jobs/`. Web UI for status. No Docker awareness — you'd script `docker exec` yourself. Good for: maximum simplicity, single-project servers. + +**Bare git hooks** — `post-receive` hook fires instantly on push. Zero framework overhead. You write the orchestration. Good for: smallest possible setup, but you own all the plumbing. + +### Tier 2: 1-5s trigger + +**Forgejo Actions** — Self-hosted Gitea fork with ~95% GitHub Actions YAML compatibility. Host-mode runner (no container per job) gives ~1-3s trigger. Can reuse most of existing `.github/workflows/checks.yml` with minor edits. Built-in git hosting, PR UI, issue tracker. Good for: migrating from GitHub Actions with minimal rewrite. + +**GitHub Actions self-hosted runner** — Keep GitHub as git host, run a persistent runner on the Hetzner box. Long-poll mechanism, ~2-5s job pickup. Workspace persists between runs (warm caches). Familiar ecosystem. Good for: keeping GitHub workflow, adding speed. + +### Tier 3: 5-15s trigger + +**Buildkite** — SaaS control plane + self-hosted agents. ~5-10s trigger (agent polls every 1-5s). Excellent parallel pipeline support, Docker-native. $15/user/mo. Good for: teams, polished UI. + +**Woodpecker CI** — Lightweight Go binary, Docker-native pipelines. ~3-5s trigger. YAML config, supports matrix builds. Good for: Docker-first workflows without vendor lock-in. + +**Concourse CI** — Resource-based pipeline model, very different from GitHub Actions. Steep learning curve. Good for: complex multi-repo pipelines, not great for single-project. + +**Dagger** — Not a CI system — it's a container-based task runner. Wraps your CI steps in BuildKit containers. Can run inside any CI. Adds overhead (~2-5s container startup per step). Good for: portable CI definitions, not for raw speed. + +### Tier 4: Framework, not a runner + +**Buildbot** — Python-based, very flexible, heavy. Overkill for a single project. + +### Recommendation + +For Buckaroo: **Forgejo** (if willing to self-host git) or **GitHub Actions self-hosted runner** (if staying on GitHub). Both give 1-5s trigger latency with minimal setup. + +--- + +## The Docker Setup + +### Image Structure (layered for cache efficiency) + +```dockerfile +# Layer 1: OS + system deps (~500MB, changes: ~never) +FROM ubuntu:24.04 AS base +RUN apt-get update && apt-get install -y --no-install-recommends \ + curl git ca-certificates build-essential \ + # Playwright/Chromium system deps + libnss3 libnspr4 libatk1.0-0 libatk-bridge2.0-0 libcups2 \ + libdrm2 libdbus-1-3 libxkbcommon0 libatspi2.0-0 libxcomposite1 \ + libxdamage1 libxfixes3 libxrandr2 libgbm1 libpango-1.0-0 \ + libcairo2 libasound2t64 libwayland-client0 \ + pandoc graphviz \ + && rm -rf /var/lib/apt/lists/* + +# Layer 2: Python 3.11-3.14 via deadsnakes (~1.5GB, changes: rarely) +RUN apt-get update && apt-get install -y software-properties-common \ + && add-apt-repository ppa:deadsnakes/ppa \ + && apt-get install -y python3.11 python3.12 python3.13 python3.14 \ + python3.11-venv python3.12-venv python3.13-venv python3.14-venv \ + && rm -rf /var/lib/apt/lists/* + +# Layer 3: Node 20 + pnpm 9.10.0 (~200MB, changes: rarely) +RUN curl -fsSL https://deb.nodesource.com/setup_20.x | bash - \ + && apt-get install -y nodejs \ + && corepack enable && corepack prepare pnpm@9.10.0 --activate + +# Layer 4: uv (~50MB, changes: occasionally) +RUN curl -LsSf https://astral.sh/uv/install.sh | sh + +# Layer 5: Lockfiles only — triggers dep install layer on change +COPY uv.lock pyproject.toml /workspace/ +COPY packages/pnpm-lock.yaml packages/package.json /workspace/packages/ +COPY packages/buckaroo-js-core/package.json /workspace/packages/buckaroo-js-core/ +COPY packages/buckaroo-widget/package.json /workspace/packages/buckaroo-widget/ + +# Layer 6: Install all deps from lockfiles (~4-6GB, changes: when deps change) +WORKDIR /workspace +RUN /root/.local/bin/uv sync --locked --all-extras --dev --python 3.12 +RUN cd packages && pnpm install --frozen-lockfile +RUN npx playwright install chromium + +# Source code NOT baked in — mounted at runtime +``` + +**Estimated image size:** 8-12 GB with all Python versions. + +### Docker Compose: Sidecar Pattern + +A long-running container you `docker exec` into for each CI run: + +```yaml +# docker-compose.ci.yml +services: + ci-runner: + image: buckaroo-ci:latest + container_name: buckaroo-ci + restart: unless-stopped + volumes: + - ./workspace:/workspace + - pnpm-store:/root/.local/share/pnpm/store + - uv-cache:/root/.cache/uv + - pw-browsers:/root/.cache/ms-playwright + environment: + - UV_LINK_MODE=copy + command: tail -f /dev/null + +volumes: + pnpm-store: + uv-cache: + pw-browsers: +``` + +### CI Trigger Script + +```bash +#!/bin/bash +# Called by git post-receive hook or webhook +COMMIT_SHA=$1 + +# Check if image needs rebuild (lockfiles changed) +PREV_LOCK_HASH=$(cat /var/ci/.lock-hash 2>/dev/null) +CURR_LOCK_HASH=$(sha256sum uv.lock packages/pnpm-lock.yaml | sha256sum | cut -c1-12) + +if [ "$PREV_LOCK_HASH" != "$CURR_LOCK_HASH" ]; then + docker build -t buckaroo-ci:latest . + docker compose -f docker-compose.ci.yml up -d --force-recreate + echo "$CURR_LOCK_HASH" > /var/ci/.lock-hash +fi + +# Run tests +docker exec buckaroo-ci bash -c " + cd /workspace && + git fetch origin && git checkout $COMMIT_SHA && + pnpm install --frozen-lockfile && + uv sync --locked --all-extras --dev && + cd packages/buckaroo-js-core && pnpm build && cd /workspace && + bash scripts/full_build.sh && + pytest -vv tests/unit/ & + (cd packages/buckaroo-js-core && pnpm test) & + wait +" +``` + +--- + +## Container Startup Benchmarks + +| Method | Startup overhead | Isolation | +|--------|-----------------|-----------| +| `docker exec` (sidecar) | ~50-100ms | Shared container state | +| `docker run` (fresh container, cached image, NVMe) | ~500-600ms | Clean process state | +| Firecracker microVM (snapshot restore) | ~125ms | Full VM (separate kernel) | + +The sidecar pattern (`docker exec`) is fastest because there's no container creation, image layer resolution, or filesystem setup — it's just `exec` into an already-running process namespace. + +--- + +## Lockfile-Hash Cache Invalidation + +Docker's layer cache already handles this implicitly: when you `COPY uv.lock` into the image, Docker checksums the file. If unchanged, it reuses the cached layer and skips `RUN uv sync`. + +The outer trigger (when to run `docker build` at all) can be: + +1. **Hash check in git hook** — compare lockfile hashes, only rebuild on change (~1-2s check) +2. **Run `docker build` every time** — when layers are cached it's a ~1-2s no-op anyway +3. **Watchtower / Diun** — auto-pull new images from a registry on change +4. **Nix** — content-addressed by definition, change input = new hash = new environment + +For a single-box setup, option 1 or 2 is simplest. The hash check is an optimization to skip even the 1-2s `docker build` verification. + +--- + +## Playwright: Shared Wheel Across Parallel Containers + +Build the wheel once, share via bind mount: + +```bash +# Step 1: Build wheel in sidecar +docker exec buckaroo-ci bash -c " + cd /workspace && bash scripts/full_build.sh +" +# Wheel lands in /workspace/dist/ — visible to all containers + +# Step 2: Run Playwright jobs in parallel +for job in storybook jupyter marimo wasm; do + docker run -d --name "pw-$job" \ + -v $(pwd)/workspace:/workspace:ro \ + -v venv-$job:/workspace/.venv \ + -v pw-browsers:/root/.cache/ms-playwright \ + -e UV_LINK_MODE=copy \ + buckaroo-ci:latest \ + bash -c " + cd /workspace && + uv pip install dist/buckaroo-*.whl && + bash scripts/pw-$job.sh + " & +done +wait +``` + +Key: `/workspace` is a bind mount shared across all containers. Each container gets its own venv volume for isolation but installs from the same wheel file. + +--- + +## Where Time Goes (Warm Case — No Lockfile Changes) + +This is ~95% of pushes. + +``` +t=0.000s git push completes, post-receive hook fires +t=0.050s Hook script starts, computes lockfile hash — no change +t=0.100s docker exec buckaroo-ci bash -c "..." + ├── git fetch + checkout ~0.3s + ├── pnpm install --frozen-lockfile ~1.0s (warm, just verifying) + ├── uv sync --locked ~1.0s (warm, just verifying) + ├── pnpm build (tsc + esbuild) ~8-12s (CPU-bound) + ├── hatch build (wheel) ~3-5s + │ + │ ── parallel from here ── + │ + ├── pytest -vv tests/unit/ ~20-30s + ├── pnpm test (Jest) ~10-15s + ├── Playwright storybook ~30-45s ← critical path + ├── Playwright jupyter ~30-45s + ├── Playwright marimo ~20-30s + └── Playwright wasm ~20-30s +t=~60-70s All done. +``` + +### Time budget breakdown + +| Phase | Time | % of total | Notes | +|-------|------|------------|-------| +| Git hook + fetch + checkout | ~0.5s | <1% | Negligible | +| Dep verification (pnpm + uv) | ~2s | 3% | Confirming lockfile matches installed state | +| JS build (tsc + esbuild) | ~8-12s | 15% | CPU-bound, benefits from multi-core | +| Wheel build (hatch) | ~3-5s | 6% | Packaging | +| **pytest** | **~20-30s** | **35%** | Actual tests (hidden behind Playwright) | +| **Jest** | **~10-15s** | **18%** | Actual tests (hidden behind Playwright) | +| **Playwright (longest)** | **~30-45s** | **50%** | Browser startup + test execution — **the critical path** | + +**Critical path: hook → git → deps → JS build → wheel → Playwright ≈ 45-65s** + +pytest and Jest finish before Playwright, so they're free (hidden behind the Playwright wall clock). + +### Cold case (lockfiles changed, ~5% of pushes) + +Adds ~30-60s for Docker image rebuild (only re-runs from the lockfile COPY layer onward). Total: ~90-120s. + +### Compared to current Depot CI + +| Phase | Depot (current) | Warm Docker (Hetzner) | +|-------|-----------------|----------------------| +| Provisioning + bootstrap | ~30s | 0s | +| Dep install | ~30-60s (cold every time) | ~2s (warm verify) | +| JS build | ~15-20s | ~8-12s (NVMe + dedicated CPU) | +| pytest | ~20-30s | ~20-30s (same) | +| Playwright | ~60-90s | ~30-45s (NVMe IOPS for browser) | +| **Critical path** | **~3-3.5 min** | **~45-65s** | + +--- + +## CPU Contention Analysis + +### Peak concurrent load during parallel test phase + +| Job | Cores used | CPU vs wait | +|-----|-----------|-------------| +| pytest | 1-2 | ~60% CPU, ~40% IO | +| Jest | 2-4 | ~80% CPU | +| Playwright (per instance) | 2-3 | ~30% CPU, ~70% waiting for browser | +| JS build (tsc) | 4-6 | ~95% CPU | + +Peak total during parallel tests: ~7-12 cores demanded. + +### Scaling by core count + +| Server | Cores | JS build | Test phase | Total | Cost | +|--------|-------|----------|------------|-------|------| +| AX41 (Ryzen 5 3600) | 6c/12t | ~10s | contention, PW ~35-40s | ~55-65s | ~€35/mo | +| AX51 (Ryzen 7 3700X) | 8c/16t | ~8s | mild contention, PW ~30-35s | ~45-55s | ~€45/mo | +| AX101 (Ryzen 9 5900X) | 12c/24t | ~7s | no contention, PW ~28-32s | ~40-50s | ~€70/mo | +| 16-core | 16c | ~7s | diminishing returns | ~38-48s | — | + +Playwright is mostly waiting (browser renders, selector polls), not computing. Beyond 8 cores, you run out of CPU-bound work. The bottleneck shifts to Playwright's inherent wait time. + +**Sweet spot: 8-core.** Enough headroom for full parallelism without paying for cores that idle during Playwright waits. + +### Optimization priority (by impact) + +| # | Optimization | Time saved | Cost | +|---|-------------|------------|------| +| 1 | Warm box with Docker sidecar | ~120s | ~€35-45/mo | +| 2 | Parallelize pytest/Jest/Playwright | ~20-30s | Free (orchestration) | +| 3 | Shard Playwright into 2 containers | ~15s | Free (orchestration) | +| 4 | 8-core instead of 6-core | ~10s | +€10/mo | +| 5 | Shard Playwright into 4 containers | ~5-8s | Diminishing (contention on 6c) | +| 6 | More cores beyond 8 | ~3-5s | Diminishing returns | + +The big wins are architectural (warm box, parallelism). More cores is marginal polish. + +--- + +## Practical Gotchas + +### pnpm hardlinks across volumes + +pnpm's content-addressable store uses hardlinks, but hardlinks can't cross filesystem boundaries (Docker volume → bind mount). Fix: set `package-import-method: copy` in `.npmrc` or use a volume layout where store and node_modules are on the same filesystem. + +### UV_LINK_MODE=copy + +Same issue with uv — it defaults to hardlinks from cache to venv. When cache and venv are on different volumes, this fails silently or errors. Set `UV_LINK_MODE=copy` in the container environment. + +### Git dubious ownership + +If the container runs as root but the bind-mounted workspace is owned by UID 1000, git will refuse to operate. Fix: run the container as UID 1000, or add `/workspace` to git's `safe.directory` config. + +### GitHub Actions `container:` jobs always pull + +GitHub Actions `container:` directive always tries to `docker pull`, even if the image exists locally. There's no `pull: never` option. For self-hosted runners using local images, run steps directly on the host and use `docker exec` manually instead of the `container:` directive. + +### Docker cache location + +``` +/var/lib/docker/ +├── overlay2/ # Image layer storage +├── buildkit/ # Build cache (modern builds) +│ ├── cache/ # Build cache entries +│ └── content/ # Content-addressed blobs +├── volumes/ # Named volumes (pnpm-store, uv-cache, etc.) +└── containers/ # Running container state +``` + +All on NVMe. Docker overlay2 does heavy random reads (layer lookups, file dedup) — NVMe does ~500K random IOPS vs cloud EBS at ~3-16K. This 30-100x IOPS advantage is why Playwright and pytest collection feel faster on dedicated hardware. + +Maintenance: occasional `docker system prune` or `docker buildx prune --keep-storage 20GB` on a weekly cron. + +--- + +## Environment Drift: The Two-Path Model + +The key concern with persistent servers is drift — the running environment diverging from what a clean build would produce. + +Docker solves this with two convergent paths: + +- **Path A (clean build):** `docker build` from Dockerfile → produces `buckaroo-ci:latest`. Deterministic from lockfiles. Run weekly or on lockfile change. +- **Path B (warm update):** Running container does `git pull && pnpm install --frozen-lockfile && uv sync --locked`. Fast for code-only changes. + +Both paths converge to the same state because lockfiles are deterministic. The server is a pet; the CI environment inside Docker is cattle. If drift is ever suspected, Path A rebuilds from scratch in ~2-5 minutes. + +--- + +## Hardware: Hetzner Cloud vs Dedicated + +### Hetzner Cloud CCX (Dedicated vCPU) + +| Model | vCPUs | RAM | NVMe | Monthly | +|-------|-------|-----|------|---------| +| CCX13 | 2 | 8 GB | 80 GB | €12.49 | +| CCX23 | 4 | 16 GB | 160 GB | €24.49 | +| CCX33 | 8 | 32 GB | 240 GB | €48.49 | +| CCX43 | 16 | 64 GB | 360 GB | €96.49 | + +All CCX use AMD EPYC with dedicated (not shared) vCPUs, local NVMe RAID-10, 20 TB included traffic. + +### Hetzner Dedicated AX + +| Model | CPU | RAM | NVMe | Monthly | Setup | +|-------|-----|-----|------|---------|-------| +| AX41 | Ryzen 5 3600 (6c/12t) | 64 GB DDR4 | 2x 512 GB | ~€43 | ~€39 | +| AX42 | Ryzen 7 PRO 8700GE (8c/16t) | 64 GB DDR5 | 2x 512 GB | ~€49 | €39-107 | +| AX52 | Ryzen 7 7700 (8c/16t) | 64 GB DDR5 | 2x 1 TB | ~€64 | varies | +| AX102 | Ryzen 9 7950X3D (16c/32t) | 128 GB DDR5 | 2x 1.92 TB | ~€109 | varies | + +### Head-to-head at ~€49/mo + +| | Cloud CCX33 | Dedicated AX42 | +|--|------------|----------------| +| CPU | 8 vCPU (EPYC) | Ryzen 7 PRO 8700GE (8c/16t) | +| PassMark | ~12,274 | ~27,882 | +| RAM | 32 GB | 64 GB | +| Storage | 240 GB NVMe | 2x 512 GB NVMe | +| Wipe-to-running | ~2-3 min | ~8-12 min | +| Automation | Trivial (1 API call) | Moderate (5-step script) | +| IaC support | Official Terraform + Pulumi | Community Terraform only | +| cloud-init | Native | Not supported | +| Billing | Hourly, no minimum | Monthly, 1-month minimum | + +Dedicated gives 2.3x CPU, 2x RAM, 4x storage for the same price — but Cloud wins on automation. + +--- + +## Server Provisioning & Wipe + +### Cloud (CCX): The Easy Path + +Full API lifecycle. Create, destroy, snapshot in seconds. Native cloud-init. + +**Provision from zero (~2-3 min):** +```bash +hcloud server create \ + --name ci-runner \ + --type ccx33 \ + --image ubuntu-24.04 \ + --ssh-key my-key \ + --user-data-from-file cloud-init.yml +``` + +```yaml +# cloud-init.yml +#cloud-config +packages: + - docker.io + - docker-compose +runcmd: + - systemctl enable docker + - systemctl start docker + - docker pull buckaroo-ci:latest + - docker compose -f /opt/ci/docker-compose.ci.yml up -d +``` + +**Wipe and rebuild:** +```bash +hcloud server delete ci-runner +hcloud server create --name ci-runner --type ccx33 --image ubuntu-24.04 \ + --ssh-key my-key --user-data-from-file cloud-init.yml +``` + +Or with Terraform: +```bash +terraform destroy -auto-approve && terraform apply -auto-approve +``` + +### Dedicated (AX): The Robot API Path + +Hetzner's Robot API (`https://robot-ws.your-server.de`) supports programmatic OS reinstall via rescue mode + `installimage`. Auth is HTTP Basic (credentials from Robot panel > Settings > Web service). + +**Wipe and rebuild (~8-12 min):** + +```bash +#!/bin/bash +SERVER_NUM="123456" +SERVER_IP="1.2.3.4" +API="https://robot-ws.your-server.de" +AUTH="robot-user:robot-pass" + +# 1. Activate rescue system (~5s API call) +curl -s -u "$AUTH" "$API/boot/$SERVER_NUM/rescue" \ + -d "os=linux&authorized_key[]=$SSH_FINGERPRINT" + +# 2. Hardware reset +curl -s -u "$AUTH" "$API/reset/$SERVER_NUM" -d "type=hw" + +# 3. Wait for rescue SSH (~60-90s) +sleep 60 +until ssh -o ConnectTimeout=5 root@$SERVER_IP true 2>/dev/null; do sleep 5; done + +# 4. Upload unattended install config + run +ssh root@$SERVER_IP "cat > /autosetup" <<'AUTOSETUP' +DRIVE1 /dev/nvme0n1 +DRIVE2 /dev/nvme1n1 +SWRAID 1 +SWRAIDLEVEL 1 +HOSTNAME ci-runner +PART /boot ext4 1G +PART lvm vg0 all +LV vg0 root / ext4 all +IMAGE /root/.oldroot/nfs/images/Ubuntu-2404-noble-amd64-base.tar.gz +AUTOSETUP + +ssh root@$SERVER_IP "installimage && reboot" + +# 5. Wait for OS boot (~90-120s) +sleep 90 +until ssh -o ConnectTimeout=5 root@$SERVER_IP true 2>/dev/null; do sleep 5; done + +# 6. Post-install: Docker + CI image +ssh root@$SERVER_IP "apt-get update -qq && apt-get install -y -qq docker.io && \ + systemctl enable docker && systemctl start docker && \ + docker pull buckaroo-ci:latest" +``` + +**Timing breakdown:** +| Phase | Time | +|-------|------| +| Rescue activation + reset | ~5s (API calls) | +| Rescue system boot | ~60-90s | +| installimage on NVMe | ~3-5 min | +| Reboot into new OS | ~60-90s | +| apt + Docker install | ~2-3 min | +| **Total** | **~8-12 min** | + +For dedicated servers, Ansible is the production-grade option. Community playbooks exist ([mwiget/hetzner-ansible](https://github.com/mwiget/hetzner-ansible), [palark/hetzner-bare-metal-ansible](https://github.com/palark/hetzner-bare-metal-ansible)) that wrap the rescue → installimage → provision flow into ~31 idempotent tasks. + +### Recommendation + +**Start with Cloud CCX33.** Same price as dedicated, dramatically simpler automation (cloud-init, official Terraform provider, 2-minute wipe cycle). The 2.3x CPU gap matters less than expected for CI — Playwright is wait-bound, not CPU-bound. + +If the CCX33 proves CPU-limited during parallel test phases, upgrade to dedicated AX42. The Docker Compose setup is identical — only the host provisioning layer changes. + +--- + +## Expected Performance + +Running Forgejo (or bare git hooks) + Docker Compose sidecar with volume-mounted caches. + +| Scenario | Cloud CCX33 | Dedicated AX42 | +|----------|------------|----------------| +| Warm push (no lockfile change) | ~55-75s | ~45-65s | +| Cold push (lockfiles changed) | ~100-140s | ~90-120s | +| Full wipe + reprovision | ~2-3 min | ~8-12 min | + +Compared to current Depot CI: **~3.5 min critical path.** diff --git a/packages/.npmrc b/packages/.npmrc new file mode 100644 index 000000000..bf2e7648b --- /dev/null +++ b/packages/.npmrc @@ -0,0 +1 @@ +shamefully-hoist=true diff --git a/packages/buckaroo-js-core/playwright.config.integration.ts b/packages/buckaroo-js-core/playwright.config.integration.ts index a509af65f..50aeb6a51 100644 --- a/packages/buckaroo-js-core/playwright.config.integration.ts +++ b/packages/buckaroo-js-core/playwright.config.integration.ts @@ -15,7 +15,7 @@ export default defineConfig({ navigationTimeout: 15000, storageState: undefined, launchOptions: { - args: ['--incognito'], + args: ['--incognito', '--disable-dev-shm-usage'], }, }, timeout: 30000, // 30s per test diff --git a/packages/buckaroo-js-core/playwright.config.marimo.ts b/packages/buckaroo-js-core/playwright.config.marimo.ts index 0ddbd086b..7d090fb3a 100644 --- a/packages/buckaroo-js-core/playwright.config.marimo.ts +++ b/packages/buckaroo-js-core/playwright.config.marimo.ts @@ -7,15 +7,18 @@ export default defineConfig({ testMatch: ['marimo.spec.ts', 'theme-screenshots-marimo.spec.ts'], fullyParallel: false, forbidOnly: !!process.env.CI, - retries: process.env.CI ? 1 : 0, + retries: process.env.CI ? 2 : 0, workers: 1, reporter: 'html', use: { baseURL: `http://localhost:${PORT}`, trace: 'on-first-retry', ...devices['Desktop Chrome'], + launchOptions: { + args: ['--disable-dev-shm-usage'], + }, }, - timeout: 30_000, + timeout: 60_000, projects: [ { @@ -28,7 +31,7 @@ export default defineConfig({ command: `uv run marimo run --headless --port ${PORT} --no-token tests/notebooks/marimo_pw_test.py`, cwd: '../..', url: `http://localhost:${PORT}`, - reuseExistingServer: !process.env.CI, - timeout: 30_000, + reuseExistingServer: !!process.env.MARIMO_WARMUP_PID || !process.env.CI, + timeout: 60_000, }, }); diff --git a/packages/buckaroo-js-core/playwright.config.server.ts b/packages/buckaroo-js-core/playwright.config.server.ts index 9edea1586..fa571f819 100644 --- a/packages/buckaroo-js-core/playwright.config.server.ts +++ b/packages/buckaroo-js-core/playwright.config.server.ts @@ -18,6 +18,9 @@ export default defineConfig({ baseURL: `http://localhost:${PORT}`, trace: 'on-first-retry', ...devices['Desktop Chrome'], + launchOptions: { + args: ['--disable-dev-shm-usage'], + }, }, timeout: 30_000, diff --git a/packages/buckaroo-js-core/playwright.config.ts b/packages/buckaroo-js-core/playwright.config.ts index 55e1cf4ea..1722fa37e 100644 --- a/packages/buckaroo-js-core/playwright.config.ts +++ b/packages/buckaroo-js-core/playwright.config.ts @@ -36,6 +36,9 @@ export default defineConfig({ contextOptions: { ignoreHTTPSErrors: true, }, + launchOptions: { + args: ['--disable-dev-shm-usage'], + }, }, /* Configure projects for major browsers */ diff --git a/packages/buckaroo-js-core/playwright.config.wasm-marimo.ts b/packages/buckaroo-js-core/playwright.config.wasm-marimo.ts index fe6a6a102..74257d23c 100644 --- a/packages/buckaroo-js-core/playwright.config.wasm-marimo.ts +++ b/packages/buckaroo-js-core/playwright.config.wasm-marimo.ts @@ -18,6 +18,9 @@ export default defineConfig({ baseURL: `http://localhost:${PORT}`, trace: 'on-first-retry', ...devices['Desktop Chrome'], + launchOptions: { + args: ['--disable-dev-shm-usage'], + }, }, // Longer timeout for WASM: Pyodide init + fastparquet WASM compilation can be slow timeout: 180_000, diff --git a/packages/buckaroo-js-core/pw-tests/infinite-scroll-transcript.spec.ts b/packages/buckaroo-js-core/pw-tests/infinite-scroll-transcript.spec.ts index e45691faf..89ae8ac1a 100644 --- a/packages/buckaroo-js-core/pw-tests/infinite-scroll-transcript.spec.ts +++ b/packages/buckaroo-js-core/pw-tests/infinite-scroll-transcript.spec.ts @@ -1,13 +1,16 @@ import { test, expect } from '@playwright/test'; import { Page } from '@playwright/test'; -const JUPYTER_BASE_URL = 'http://localhost:8889'; -const JUPYTER_TOKEN = 'test-token-12345'; -const DEFAULT_TIMEOUT = 10000; -const NAVIGATION_TIMEOUT = 12000; +const JUPYTER_BASE_URL = process.env.JUPYTER_BASE_URL || 'http://localhost:8889'; +const JUPYTER_TOKEN = process.env.JUPYTER_TOKEN || 'test-token-12345'; +const DEFAULT_TIMEOUT = 30000; +const CELL_EXEC_TIMEOUT = 120000; // kernel startup + analysis under 9-way concurrency +const NAVIGATION_TIMEOUT = 30000; -async function waitForAgGrid(page: Page, timeout = 5000) { +async function waitForAgGrid(page: Page, timeout = DEFAULT_TIMEOUT) { await page.locator('.ag-root-wrapper').first().waitFor({ state: 'attached', timeout }); + // Use 'attached' not 'visible' — ag-grid infinite row model creates cells + // before datasource round-trip completes, so cells may be hidden initially. await page.locator('.ag-cell').first().waitFor({ state: 'attached', timeout }); } @@ -34,35 +37,50 @@ test.describe('Infinite Scroll Transcript Recording', () => { await page.locator('.jp-Notebook').first().waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); console.log('✅ Notebook loaded'); - // Execute the cell - console.log('▶️ Executing widget code...'); - await page.locator('.jp-Notebook').first().dispatchEvent('click'); - await page.waitForTimeout(200); - await page.keyboard.press('Shift+Enter'); + // Wait for kernel via JupyterLab internal state (see deep dive doc). + console.log('⏳ Waiting for kernel to be ready (jupyterapp)...'); + try { + await page.waitForFunction(() => { + const app = (window as any).jupyterapp; + if (!app) return false; + const widget = app.shell.currentWidget; + if (!widget?.sessionContext?.session?.kernel) return false; + const kernel = widget.sessionContext.session.kernel; + return kernel.connectionStatus === 'connected' && kernel.status === 'idle'; + }, { timeout: 60000 }); + console.log('✅ Kernel connected and idle'); + } catch { + console.log('⚠️ Kernel ready wait timed out — proceeding with retry loop'); + } - // Wait for cell execution and widget to render - console.log('⏳ Waiting for cell execution...'); + // Execute cell with retry — use dispatchEvent to avoid visibility requirements + console.log('▶️ Executing widget code...'); const outputArea = page.locator('.jp-OutputArea').first(); - await outputArea.waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); - await page.waitForTimeout(800); - console.log('✅ Cell executed'); + const outputLocator = outputArea.locator('.jp-OutputArea-output').first(); + const deadline = Date.now() + CELL_EXEC_TIMEOUT; + + for (let attempt = 1; Date.now() < deadline; attempt++) { + console.log(`⏳ Shift+Enter attempt ${attempt}...`); + await page.locator('.jp-Cell').first().dispatchEvent('click'); + await page.waitForTimeout(1000); + await page.keyboard.press('Shift+Enter'); + + try { + await outputLocator.waitFor({ state: 'attached', timeout: 15000 }); + console.log('✅ Cell executed'); + break; + } catch { + if (Date.now() >= deadline) throw new Error(`Cell execution timed out after ${CELL_EXEC_TIMEOUT}ms`); + console.log(`⚠️ No output after attempt ${attempt}, retrying...`); + } + } - // Wait for widget to render (larger datasets take longer to initialize) + // Wait for widget to render — deterministic wait for actual elements console.log('⏳ Waiting for buckaroo widget...'); - await page.waitForTimeout(2000); - - // Check for buckaroo or ag-grid elements + await page.locator('[class*="buckaroo"], .ag-root-wrapper').first().waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); const buckarooElements = await page.locator('[class*="buckaroo"]').count(); const agGridElements = await page.locator('.ag-root-wrapper, .ag-row').count(); - - if (buckarooElements > 0 || agGridElements > 0) { - console.log(`✅ Found ${buckarooElements} buckaroo elements, ${agGridElements} ag-grid elements`); - } else { - // Wait more for larger datasets - await page.waitForTimeout(3000); - const retryAgGrid = await page.locator('.ag-root-wrapper').count(); - expect(retryAgGrid).toBeGreaterThan(0); - } + console.log(`✅ Found ${buckarooElements} buckaroo elements, ${agGridElements} ag-grid elements`); console.log('✅ Widget rendered with ag-grid'); // Wait for ag-grid to be ready @@ -143,10 +161,10 @@ test.describe('Infinite Scroll Transcript Recording', () => { const initialFirstCellText = await firstRowCell.textContent(); console.log(`📊 Initial first cell content: ${initialFirstCellText}`); - // Scroll down to row 1500 using direct JavaScript scrollTo on ag-grid viewport - // DataFrame has 2000 rows, we want to scroll to row ~1500 to trigger additional data fetches - // Each row is ~20px high, so row 1500 is around 30000px down - console.log('📜 Scrolling to row 1500 using direct scrollTo...'); + // Scroll down to row 400 using direct JavaScript scrollTo on ag-grid viewport + // DataFrame has 500 rows, we want to scroll near the end to trigger additional data fetches + // Each row is ~20px high, so row 400 is around 8000px down + console.log('📜 Scrolling to row 400 using direct scrollTo...'); // Use JavaScript to find the LARGEST viewport (the main data grid, not pinned rows) const scrollResult = await page.evaluate(() => { @@ -174,8 +192,8 @@ test.describe('Infinite Scroll Transcript Recording', () => { return { success: false, error: 'No viewport found' }; } - // Calculate scroll position for row 1500 (assuming ~20px per row) - const targetRow = 1500; + // Calculate scroll position for row 400 (assuming ~20px per row) + const targetRow = 400; const rowHeight = 20; const targetScrollTop = targetRow * rowHeight; @@ -192,9 +210,15 @@ test.describe('Infinite Scroll Transcript Recording', () => { }); console.log(`📊 Scroll result: ${JSON.stringify(scrollResult)}`); - - // Wait for data fetch to complete - await page.waitForTimeout(2000); + + // Wait for grid to render rows at the scrolled position rather than a fixed delay + await page.waitForFunction( + () => { + const rows = document.querySelectorAll('.ag-row[row-index]'); + return Array.from(rows).some(r => parseInt(r.getAttribute('row-index') || '0', 10) > 100); + }, + { timeout: 10000 } + ); // Check what rows are now visible const visibleCells = page.locator('.ag-cell'); @@ -327,25 +351,57 @@ test.describe('Infinite Scroll Transcript Recording', () => { await page.waitForLoadState('domcontentloaded', { timeout: DEFAULT_TIMEOUT }); await page.locator('.jp-Notebook').first().waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); - // Execute the cell - await page.locator('.jp-Notebook').first().dispatchEvent('click'); - await page.waitForTimeout(200); - await page.keyboard.press('Shift+Enter'); + // Wait for kernel to be ready + try { + await page.waitForFunction(() => { + const app = (window as any).jupyterapp; + if (!app) return false; + const widget = app.shell.currentWidget; + if (!widget?.sessionContext?.session?.kernel) return false; + const kernel = widget.sessionContext.session.kernel; + return kernel.connectionStatus === 'connected' && kernel.status === 'idle'; + }, { timeout: 60000 }); + } catch { /* proceed with retry loop */ } + + // Execute with retry + const outputArea2 = page.locator('.jp-OutputArea').first(); + const outputLocator2 = outputArea2.locator('.jp-OutputArea-output').first(); + const deadline2 = Date.now() + CELL_EXEC_TIMEOUT; + + for (let attempt = 1; Date.now() < deadline2; attempt++) { + await page.locator('.jp-Cell').first().dispatchEvent('click'); + await page.waitForTimeout(1000); + await page.keyboard.press('Shift+Enter'); + + try { + await outputLocator2.waitFor({ state: 'attached', timeout: 15000 }); + break; + } catch { + if (Date.now() >= deadline2) throw new Error(`Cell execution timed out`); + } + } - const outputArea = page.locator('.jp-OutputArea').first(); - await outputArea.waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); - await page.waitForTimeout(1500); + const outputArea = outputArea2; await waitForAgGrid(page); + // Reset scroll position in case test 1 left the grid scrolled + try { + const viewport = page.locator('.ag-body-viewport').first(); + if (await viewport.count() > 0) { + await viewport.evaluate(el => el.scrollTop = 0); + // Wait for row 0 to re-attach rather than a fixed sleep + await page.locator('[row-index="0"]').first().waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); + } + } catch (e) { /* non-fatal */ } + // Verify initial data (row 0 should show int_col=10, str_col=foo_10) const firstRowIntCell = page.locator('[row-index="0"] [col-id="int_col"]'); const firstRowStrCell = page.locator('[row-index="0"] [col-id="str_col"]'); - - // Check if we can see the cells + const intCellVisible = await firstRowIntCell.isVisible().catch(() => false); const strCellVisible = await firstRowStrCell.isVisible().catch(() => false); - + if (intCellVisible && strCellVisible) { const intVal = await firstRowIntCell.textContent(); const strVal = await firstRowStrCell.textContent(); @@ -356,8 +412,8 @@ test.describe('Infinite Scroll Transcript Recording', () => { // Try finding cells by content const cell10 = page.locator('.ag-cell:has-text("10")').first(); const cellFoo10 = page.locator('.ag-cell:has-text("foo_10")').first(); - await expect(cell10).toBeVisible({ timeout: 3000 }); - await expect(cellFoo10).toBeVisible({ timeout: 3000 }); + await expect(cell10).toBeVisible({ timeout: DEFAULT_TIMEOUT }); + await expect(cellFoo10).toBeVisible({ timeout: DEFAULT_TIMEOUT }); console.log('📊 Verified row 0 data via text search'); } @@ -392,8 +448,8 @@ test.describe('Infinite Scroll Transcript Recording', () => { const expectedStrCell = page.locator(`.ag-cell:has-text("${expectedStrCol}")`).first(); // These should be visible if the data is correct - await expect(expectedIntCell).toBeVisible({ timeout: 3000 }); - await expect(expectedStrCell).toBeVisible({ timeout: 3000 }); + await expect(expectedIntCell).toBeVisible({ timeout: DEFAULT_TIMEOUT }); + await expect(expectedStrCell).toBeVisible({ timeout: DEFAULT_TIMEOUT }); console.log(`✅ Verified data at row ${targetRowIndex} matches predictable pattern!`); }); diff --git a/packages/buckaroo-js-core/pw-tests/integration.spec.ts b/packages/buckaroo-js-core/pw-tests/integration.spec.ts index 5210ddc13..8f0f4c241 100644 --- a/packages/buckaroo-js-core/pw-tests/integration.spec.ts +++ b/packages/buckaroo-js-core/pw-tests/integration.spec.ts @@ -1,15 +1,16 @@ import { test, expect } from '@playwright/test'; import { Page } from '@playwright/test'; -const JUPYTER_BASE_URL = 'http://localhost:8889'; -const JUPYTER_TOKEN = 'test-token-12345'; -const DEFAULT_TIMEOUT = 8000; // 8 seconds for most operations -const NAVIGATION_TIMEOUT = 10000; // 10 seconds max for navigation - -async function waitForAgGrid(outputArea: any, timeout = 5000) { - // Wait for ag-grid to be present and rendered +const JUPYTER_BASE_URL = process.env.JUPYTER_BASE_URL || 'http://localhost:8889'; +const JUPYTER_TOKEN = process.env.JUPYTER_TOKEN || 'test-token-12345'; +const DEFAULT_TIMEOUT = 30000; // 30 seconds — JupyterLab UI can be slow under concurrency +const CELL_EXEC_TIMEOUT = 120000; // kernel startup can be slow when 8 run concurrently +const NAVIGATION_TIMEOUT = 30000; // 30 seconds for navigation under concurrency + +async function waitForAgGrid(outputArea: any, timeout = DEFAULT_TIMEOUT) { + // Wait for ag-grid to be present and rendered; 'visible' ensures column layout is done await outputArea.locator('.ag-root-wrapper').first().waitFor({ state: 'attached', timeout }); - await outputArea.locator('.ag-cell').first().waitFor({ state: 'attached', timeout }); + await outputArea.locator('.ag-cell').first().waitFor({ state: 'visible', timeout }); } // Helper function to get cell content by row and column @@ -105,23 +106,63 @@ test.describe('Buckaroo Widget JupyterLab Integration', () => { await page.locator('.jp-Notebook').first().waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); console.log('✅ Notebook loaded'); - // Find and run the first code cell + // Wait for kernel to be connected and idle by querying JupyterLab's internal + // state directly. This checks the EXACT same `session.kernel` condition that + // CodeCell.execute() checks at widget.ts:1750 — if kernel is null, execute() + // silently returns void with no error. DOM-based checks (ExecutionIndicator) + // lag behind and burn timeout when the element doesn't exist yet. + console.log('⏳ Waiting for kernel to be ready (jupyterapp internal state)...'); + try { + await page.waitForFunction(() => { + const app = (window as any).jupyterapp; + if (!app) return false; + const widget = app.shell.currentWidget; + if (!widget?.sessionContext?.session?.kernel) return false; + const kernel = widget.sessionContext.session.kernel; + return kernel.connectionStatus === 'connected' && kernel.status === 'idle'; + }, { timeout: 60000 }); + console.log('✅ Kernel connected and idle'); + } catch { + console.log('⚠️ Kernel ready wait timed out — proceeding with retry loop'); + } + console.log(`▶️ Executing widget code from ${notebookName}...`); - // Wait for notebook to be fully interactive - await page.waitForLoadState('domcontentloaded', { timeout: DEFAULT_TIMEOUT }); - // Focus on the notebook and use keyboard shortcut to run cell (Shift+Enter) - // Use dispatchEvent to trigger click without visibility requirement - await page.locator('.jp-Notebook').first().dispatchEvent('click'); - await page.waitForTimeout(200); - await page.keyboard.press('Shift+Enter'); - - // Wait for cell execution to complete - console.log('⏳ Waiting for cell execution...'); const outputArea = page.locator('.jp-OutputArea').first(); - await outputArea.waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); - // Wait for widget to render - await page.waitForTimeout(800); - console.log('✅ Cell executed'); + const outputLocator = outputArea.locator('.jp-OutputArea-output').first(); + + // Try UI-based execution first (fast path when UI is responsive) + let cellExecuted = false; + try { + const firstCell = page.locator('.jp-Cell').first(); + await firstCell.click({ timeout: 5000 }); + await page.keyboard.press('Shift+Enter'); + await outputLocator.waitFor({ state: 'attached', timeout: 15000 }); + cellExecuted = true; + console.log('✅ Cell executed (UI path)'); + } catch { + console.log('⚠️ UI path failed, retrying with longer waits...'); + } + + // Retry with longer waits if UI path failed + if (!cellExecuted) { + const deadline = Date.now() + CELL_EXEC_TIMEOUT; + for (let attempt = 2; Date.now() < deadline; attempt++) { + console.log(`⏳ Shift+Enter attempt ${attempt}...`); + try { + // Use dispatchEvent which doesn't require visibility + await page.locator('.jp-Cell').first().dispatchEvent('click'); + await page.waitForTimeout(1000); + await page.keyboard.press('Shift+Enter'); + await outputLocator.waitFor({ state: 'attached', timeout: 15000 }); + console.log('✅ Cell executed'); + cellExecuted = true; + break; + } catch { + if (Date.now() >= deadline) throw new Error(`Cell execution timed out after ${CELL_EXEC_TIMEOUT}ms`); + console.log(`⚠️ No output after attempt ${attempt}, retrying...`); + } + } + } // Check for any error messages in the output // Target only stdout text output, not widget output (which also has .jp-OutputArea-output class) @@ -133,29 +174,16 @@ test.describe('Buckaroo Widget JupyterLab Integration', () => { throw new Error(`Cell execution failed with error: ${outputText}`); } - // Wait for the buckaroo widget to appear + // Wait for the buckaroo widget to appear — deterministic wait instead of fixed delay console.log('⏳ Waiting for buckaroo widget...'); - - // Wait a moment for widget to render - await page.waitForTimeout(500); - - // Check for any buckaroo-related elements and ag-grid on the WHOLE PAGE - // (widget might be in a different output area than expected) + await page.locator('[class*="buckaroo"], .ag-root-wrapper').first().waitFor({ state: 'attached', timeout: DEFAULT_TIMEOUT }); const buckarooElements = await page.locator('[class*="buckaroo"]').count(); const agGridElements = await page.locator('.ag-root-wrapper, .ag-row').count(); - - // If we find buckaroo or ag-grid elements, the widget is rendering - proceed - if (buckarooElements > 0 || agGridElements > 0) { - console.log(`✅ Found ${buckarooElements} buckaroo elements, ${agGridElements} ag-grid elements on page`); - } else { - // Only fail if we truly can't find any widget elements - console.log('❌ Widget failed to appear. No buckaroo or ag-grid elements found.'); - throw new Error(`Widget failed to render. Found 0 buckaroo elements, 0 ag-grid elements.`); - } + console.log(`✅ Found ${buckarooElements} buckaroo elements, ${agGridElements} ag-grid elements on page`); // Wait for ag-grid to render console.log('⏳ Waiting for ag-grid to render...'); - await waitForAgGrid(page); + await waitForAgGrid(outputArea); console.log('✅ ag-grid rendered successfully'); // Verify the grid structure on the page diff --git a/packages/buckaroo-js-core/pw-tests/marimo.spec.ts b/packages/buckaroo-js-core/pw-tests/marimo.spec.ts index 51e050612..bc721d593 100644 --- a/packages/buckaroo-js-core/pw-tests/marimo.spec.ts +++ b/packages/buckaroo-js-core/pw-tests/marimo.spec.ts @@ -7,23 +7,24 @@ import { test, expect } from '@playwright/test'; */ async function waitForGrid(page: import('@playwright/test').Page) { // Wait for at least one buckaroo widget to appear - await page.locator('.buckaroo_anywidget').first().waitFor({ state: 'visible', timeout: 30_000 }); + await page.locator('.buckaroo_anywidget').first().waitFor({ state: 'visible', timeout: 60_000 }); // Wait for AG-Grid cells to render - await page.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 30_000 }); + await page.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); } /** - * Get the text content of a cell by col-id and row-index within + * Get a cell locator by col-id and row-index within * the main data grid (.df-viewer) of a widget container. + * Returns a locator (not text) so callers can use Playwright's + * auto-retrying expect(locator).toHaveText() instead of one-shot innerText(). */ -async function getCellText( +function cellLocator( container: import('@playwright/test').Locator, colId: string, rowIndex: number, -): Promise { +): import('@playwright/test').Locator { const dfViewer = container.locator('.df-viewer'); - const cell = dfViewer.locator(`[row-index="${rowIndex}"] [col-id="${colId}"]`); - return (await cell.innerText()).trim(); + return dfViewer.locator(`[row-index="${rowIndex}"] [col-id="${colId}"]`); } /** @@ -71,11 +72,12 @@ test.describe('Buckaroo in marimo', () => { const firstWidget = page.locator('.buckaroo_anywidget').first(); // Column names get mapped to col-ids: name→a, age→b, score→c - expect(await getCellText(firstWidget, 'a', 0)).toBe('Alice'); - expect(await getCellText(firstWidget, 'a', 1)).toBe('Bob'); - expect(await getCellText(firstWidget, 'a', 2)).toBe('Charlie'); - expect(await getCellText(firstWidget, 'b', 0)).toBe('30'); - expect(await getCellText(firstWidget, 'b', 1)).toBe('25'); + // Use toHaveText() — auto-retries until data loads (handles kernel→grid race) + await expect(cellLocator(firstWidget, 'a', 0)).toHaveText('Alice'); + await expect(cellLocator(firstWidget, 'a', 1)).toHaveText('Bob'); + await expect(cellLocator(firstWidget, 'a', 2)).toHaveText('Charlie'); + await expect(cellLocator(firstWidget, 'b', 0)).toHaveText('30'); + await expect(cellLocator(firstWidget, 'b', 1)).toHaveText('25'); }); test('column headers are present', async ({ page }) => { @@ -96,8 +98,8 @@ test.describe('Buckaroo in marimo', () => { // The second widget is the BuckarooInfiniteWidget (200 rows) const widgets = page.locator('.buckaroo_anywidget'); // Wait for the second widget to also render - await widgets.nth(1).waitFor({ state: 'visible', timeout: 30_000 }); - await widgets.nth(1).locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 30_000 }); + await widgets.nth(1).waitFor({ state: 'visible', timeout: 60_000 }); + await widgets.nth(1).locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); const secondWidget = widgets.nth(1); const count = await getRowCount(secondWidget); @@ -109,13 +111,14 @@ test.describe('Buckaroo in marimo', () => { await waitForGrid(page); const widgets = page.locator('.buckaroo_anywidget'); - await widgets.nth(1).locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 30_000 }); + await widgets.nth(1).locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); const secondWidget = widgets.nth(1); // Columns: id→a, value→b, label→c - expect(await getCellText(secondWidget, 'a', 0)).toBe('0'); - expect(await getCellText(secondWidget, 'b', 0)).toBe('0'); - expect(await getCellText(secondWidget, 'c', 0)).toBe('row_0'); + // Auto-retrying assertions handle kernel→grid data loading race + await expect(cellLocator(secondWidget, 'a', 0)).toHaveText('0'); + await expect(cellLocator(secondWidget, 'b', 0)).toHaveText('0'); + await expect(cellLocator(secondWidget, 'c', 0)).toHaveText('row_0'); }); }); diff --git a/packages/buckaroo-js-core/pw-tests/server-buckaroo-search.spec.ts b/packages/buckaroo-js-core/pw-tests/server-buckaroo-search.spec.ts index 079980c24..97e1c76f5 100644 --- a/packages/buckaroo-js-core/pw-tests/server-buckaroo-search.spec.ts +++ b/packages/buckaroo-js-core/pw-tests/server-buckaroo-search.spec.ts @@ -71,12 +71,14 @@ test.describe('Buckaroo mode: search filtering', () => { await searchInput.fill('Alice'); await searchInput.press('Enter'); - // Wait for server roundtrip - await page.waitForTimeout(3000); + // Wait for filtered data to render — Bob should disappear from the grid + await expect(async () => { + const text = await dataGrid.textContent(); + expect(text).toContain('Alice'); + expect(text).not.toContain('Bob'); + }).toPass({ timeout: 10000 }); - // The table data should update to show only matching rows. - // With the bug, the data grid still shows all 5 rows because the - // datasource/cache key doesn't change when quick_command_args changes. + // Verify full filtering const filteredBodyText = await dataGrid.textContent(); expect(filteredBodyText).toContain('Alice'); expect(filteredBodyText).not.toContain('Bob'); diff --git a/packages/buckaroo-js-core/pw-tests/server-buckaroo-summary.spec.ts b/packages/buckaroo-js-core/pw-tests/server-buckaroo-summary.spec.ts index 036ad28d6..ccffc09c3 100644 --- a/packages/buckaroo-js-core/pw-tests/server-buckaroo-summary.spec.ts +++ b/packages/buckaroo-js-core/pw-tests/server-buckaroo-summary.spec.ts @@ -73,8 +73,11 @@ test.describe('Buckaroo mode: summary stats view', () => { const dfDisplaySelect = statusBar.locator('select').first(); await dfDisplaySelect.selectOption('summary'); - // Wait for re-render — the view change triggers a server roundtrip - await page.waitForTimeout(3000); + // Wait for summary view to render — pinned row count increases after server roundtrip + await expect(async () => { + const count = await getPinnedRowCount(page); + expect(count).toBeGreaterThan(mainPinnedCount); + }).toPass({ timeout: 10000 }); const summaryPinnedCount = await getPinnedRowCount(page); @@ -94,11 +97,14 @@ test.describe('Buckaroo mode: summary stats view', () => { const statusBar = page.locator('.status-bar'); const dfDisplaySelect = statusBar.locator('select').first(); await dfDisplaySelect.selectOption('summary'); - await page.waitForTimeout(3000); + // Wait for summary pinned rows to appear + await expect(async () => { + const count = await getPinnedRowCount(page); + expect(count).toBeGreaterThanOrEqual(5); + }).toPass({ timeout: 10000 }); // Switch back to main await dfDisplaySelect.selectOption('main'); - await page.waitForTimeout(3000); await waitForDataGrid(page); // After switching back, verify grid has data cells diff --git a/packages/buckaroo-js-core/pw-tests/server-helpers.ts b/packages/buckaroo-js-core/pw-tests/server-helpers.ts index cda5bf5d5..c6ed7aa1d 100644 --- a/packages/buckaroo-js-core/pw-tests/server-helpers.ts +++ b/packages/buckaroo-js-core/pw-tests/server-helpers.ts @@ -42,6 +42,15 @@ export async function getRowCount(page: Page): Promise { return Number(total) - headers.length; } +/** + * Get a cell locator by col-id and row-index. + * Returns a Locator so callers can use auto-retrying expect(locator).toHaveText() + * instead of one-shot innerText() which races with AG-Grid rendering. + */ +export function cellLocator(page: Page, colId: string, rowIndex: number) { + return page.locator(`[row-index="${rowIndex}"] [col-id="${colId}"]`); +} + /** * Get the text content of a cell by col-id and row-index. */ diff --git a/packages/buckaroo-js-core/pw-tests/server.spec.ts b/packages/buckaroo-js-core/pw-tests/server.spec.ts index 392e8530a..aaf474d17 100644 --- a/packages/buckaroo-js-core/pw-tests/server.spec.ts +++ b/packages/buckaroo-js-core/pw-tests/server.spec.ts @@ -1,5 +1,5 @@ import { test, expect } from '@playwright/test'; -import { loadSession, waitForGrid, getRowCount, getCellText } from './server-helpers'; +import { loadSession, waitForGrid, getRowCount, getCellText, cellLocator } from './server-helpers'; import { execSync } from 'child_process'; import * as fs from 'fs'; import * as path from 'path'; @@ -116,10 +116,10 @@ test.describe('Buckaroo standalone server', () => { await page.goto(`${BASE}/s/${session}`); await waitForGrid(page); - // Verify first column (name → col-id "a") values - expect(await getCellText(page, COL.name, 0)).toBe('Alice'); - expect(await getCellText(page, COL.name, 1)).toBe('Bob'); - expect(await getCellText(page, COL.name, 2)).toBe('Charlie'); + // Verify first column (name → col-id "a") values — auto-retry handles render race + await expect(cellLocator(page, COL.name, 0)).toHaveText('Alice'); + await expect(cellLocator(page, COL.name, 1)).toHaveText('Bob'); + await expect(cellLocator(page, COL.name, 2)).toHaveText('Charlie'); }); test('column headers present', async ({ page, request }) => { @@ -142,28 +142,18 @@ test.describe('Buckaroo standalone server', () => { await page.goto(`${BASE}/s/${session}`); await waitForGrid(page); - // Get the initial first-row name value - const before = await getCellText(page, COL.name, 0); - expect(before).toBe('Alice'); + // Verify initial first-row value with auto-retry (handles AG-Grid render race) + const firstCell = cellLocator(page, COL.name, 0); + await expect(firstCell).toHaveText('Alice'); // Click the "name" column header to sort await page.getByRole('columnheader', { name: 'name' }).click(); - await page.waitForTimeout(1000); - await waitForGrid(page); - // After sort the order should change - const after = await getCellText(page, COL.name, 0); - // One click = ascending, which keeps Alice first; a second click = descending - if (after === 'Alice') { - // Click again for descending - await page.getByRole('columnheader', { name: 'name' }).click(); - await page.waitForTimeout(1000); - await waitForGrid(page); - const desc = await getCellText(page, COL.name, 0); - expect(desc).toBe('Eve'); - } else { - expect(after).not.toBe('Alice'); - } + // One click = ascending (keeps Alice first); click again for descending + // Use auto-retrying assertion: wait for cell to NOT be Alice (descending sort) + await page.getByRole('columnheader', { name: 'name' }).click(); + await expect(firstCell).not.toHaveText('Alice', { timeout: 5000 }); + await expect(firstCell).toHaveText('Eve', { timeout: 5000 }); }); }); @@ -263,7 +253,7 @@ test.describe('file format support', () => { expect(count).toBe(5); // Verify a cell value to ensure TSV parsing worked - expect(await getCellText(page, 'a', 0)).toBe('Alice'); + await expect(cellLocator(page, 'a', 0)).toHaveText('Alice'); } finally { cleanupFile(tsvPath); } @@ -281,7 +271,7 @@ test.describe('file format support', () => { const count = await getRowCount(page); expect(count).toBe(5); - expect(await getCellText(page, 'a', 0)).toBe('Alice'); + await expect(cellLocator(page, 'a', 0)).toHaveText('Alice'); } finally { cleanupFile(jsonPath); } @@ -308,10 +298,10 @@ test.describe('numeric column rendering', () => { await page.goto(`${BASE}/s/${session}`); await waitForGrid(page); - // age column → col-id "b" - expect(await getCellText(page, COL.age, 0)).toBe('30'); - expect(await getCellText(page, COL.age, 1)).toBe('25'); - expect(await getCellText(page, COL.age, 2)).toBe('35'); + // age column → col-id "b" — auto-retry handles render race + await expect(cellLocator(page, COL.age, 0)).toHaveText('30'); + await expect(cellLocator(page, COL.age, 1)).toHaveText('25'); + await expect(cellLocator(page, COL.age, 2)).toHaveText('35'); }); test('float column values render correctly', async ({ page, request }) => { @@ -477,7 +467,7 @@ test.describe('WebSocket data flow', () => { expect(count).toBe(5); // Also verify data actually loaded into cells (proves WS data transfer) - expect(await getCellText(page, COL.name, 0)).toBe('Alice'); + await expect(cellLocator(page, COL.name, 0)).toHaveText('Alice'); }); test('WebSocket receives data for scrolled rows', async ({ page, request }) => { @@ -501,7 +491,7 @@ test.describe('WebSocket data flow', () => { expect(count).toBe(100); // Verify first row rendered - expect(await getCellText(page, 'a', 0)).toBe('row0'); + await expect(cellLocator(page, 'a', 0)).toHaveText('row0'); } finally { cleanupFile(bigCsvPath); } diff --git a/packages/buckaroo-js-core/pw-tests/theme-screenshots-marimo.spec.ts b/packages/buckaroo-js-core/pw-tests/theme-screenshots-marimo.spec.ts index 29aaa6879..82199b8af 100644 --- a/packages/buckaroo-js-core/pw-tests/theme-screenshots-marimo.spec.ts +++ b/packages/buckaroo-js-core/pw-tests/theme-screenshots-marimo.spec.ts @@ -23,15 +23,15 @@ for (const scheme of SCHEMES) { await page.goto('/'); // Wait for buckaroo widgets and AG-Grid cells to render - await page.locator('.buckaroo_anywidget').first().waitFor({ state: 'visible', timeout: 30_000 }); - await page.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 30_000 }); + await page.locator('.buckaroo_anywidget').first().waitFor({ state: 'visible', timeout: 60_000 }); + await page.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); // Wait for the second widget (BuckarooInfiniteWidget) too const widgets = page.locator('.buckaroo_anywidget'); - await widgets.nth(1).waitFor({ state: 'visible', timeout: 30_000 }); - await widgets.nth(1).locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 30_000 }); + await widgets.nth(1).waitFor({ state: 'visible', timeout: 60_000 }); + await widgets.nth(1).locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); - await page.waitForTimeout(1000); + await page.waitForTimeout(500); // fullPage: true captures the entire scrollable area — markdown cells // above and below the widgets will be visible in the screenshot. @@ -47,9 +47,8 @@ for (const scheme of SCHEMES) { // Wait for the first BuckarooWidget to render const firstWidget = page.locator('.buckaroo_anywidget').first(); - await firstWidget.waitFor({ state: 'visible', timeout: 30_000 }); - await firstWidget.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 30_000 }); - await page.waitForTimeout(500); + await firstWidget.waitFor({ state: 'visible', timeout: 60_000 }); + await firstWidget.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); // Scroll so the first widget is roughly centred, showing markdown // cells above and the second widget heading below. @@ -69,18 +68,16 @@ for (const scheme of SCHEMES) { // Wait for the first BuckarooWidget (which has the lowcode/operations UI) const firstWidget = page.locator('.buckaroo_anywidget').first(); - await firstWidget.waitFor({ state: 'visible', timeout: 30_000 }); - await firstWidget.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 30_000 }); + await firstWidget.waitFor({ state: 'visible', timeout: 60_000 }); + await firstWidget.locator('.ag-cell').first().waitFor({ state: 'visible', timeout: 60_000 }); // Click on Columns tab to open the lowcode UI if available const columnsTab = firstWidget.locator('text=Columns'); if (await columnsTab.isVisible()) { await columnsTab.click(); - await page.waitForTimeout(500); + await page.waitForTimeout(300); } - await page.waitForTimeout(500); - // Scroll so surrounding cells are visible await firstWidget.scrollIntoViewIfNeeded(); await page.waitForTimeout(300); diff --git a/pyproject.toml b/pyproject.toml index 16a6d61cf..8b19e9b96 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -90,6 +90,7 @@ test = [ "pandas; python_version >= '3.13'", # Python 3.13+ "pytest-cov>=3", "pytest>=6", + "pytest-xdist>=3", "hypothesis>=6.88.1", "pydantic>=2.5.2", #"pyarrow", diff --git a/scripts/full_build.sh b/scripts/full_build.sh index d1bb2459c..ba36b9370 100755 --- a/scripts/full_build.sh +++ b/scripts/full_build.sh @@ -1,25 +1,33 @@ #!/bin/bash set -e -# Clean previous builds -rm -rf packages/buckaroo-js-core/dist || true -rm -f packages/buckaroo-js-core/tsconfig.tsbuildinfo || true -rm -rf buckaroo/static/*.js buckaroo/static/*.css || true +# If JS core dist already exists (e.g. from a prior `pnpm build` in test-js), +# skip the expensive tsc+vite rebuild and just do the packaging steps. +if [ -f packages/buckaroo-js-core/dist/style.css ] && \ + [ -f packages/buckaroo-js-core/dist/index.es.js ]; then + echo "[full_build] JS core dist exists — skipping rebuild" +else + # Clean previous builds + rm -rf packages/buckaroo-js-core/dist || true + rm -f packages/buckaroo-js-core/tsconfig.tsbuildinfo || true + rm -rf buckaroo/static/*.js buckaroo/static/*.css || true -# Install all workspace dependencies (once) -cd packages -pnpm install + # Install all workspace dependencies (once) + cd packages + pnpm install -# Build buckaroo-js-core first (tsc + vite) -pnpm --filter buckaroo-js-core run build + # Build buckaroo-js-core first (tsc + vite) + pnpm --filter buckaroo-js-core run build + cd .. +fi # Copy CSS to Python package -cd .. mkdir -p buckaroo/static cp packages/buckaroo-js-core/dist/style.css buckaroo/static/compiled.css # Build anywidget wrapper + standalone entry point (esbuild) cd packages +pnpm install 2>/dev/null || true pnpm --filter buckaroo-widget run build pnpm --filter buckaroo-widget run build:standalone diff --git a/scripts/test_playwright_jupyter.sh b/scripts/test_playwright_jupyter.sh index a6184ffcd..7a4c309d0 100755 --- a/scripts/test_playwright_jupyter.sh +++ b/scripts/test_playwright_jupyter.sh @@ -260,7 +260,7 @@ start_jupyter() { export JUPYTER_TOKEN="test-token-12345" # Start JupyterLab with clean workspace - python -m jupyter lab --no-browser --port=8889 --ServerApp.token=$JUPYTER_TOKEN --ServerApp.allow_origin='*' --ServerApp.disable_check_xsrf=True & + python -m jupyter lab --no-browser --port=8889 --ServerApp.token=$JUPYTER_TOKEN --ServerApp.allow_origin='*' --ServerApp.disable_check_xsrf=True --allow-root & JUPYTER_PID=$! log_message "JupyterLab started with PID: $JUPYTER_PID" diff --git a/scripts/test_playwright_jupyter_parallel.sh b/scripts/test_playwright_jupyter_parallel.sh new file mode 100755 index 000000000..20b805667 --- /dev/null +++ b/scripts/test_playwright_jupyter_parallel.sh @@ -0,0 +1,438 @@ +#!/bin/bash +# Parallel Playwright tests against JupyterLab for Buckaroo widgets. +# Each parallel slot gets its own isolated JupyterLab server on a distinct port, +# eliminating ZMQ socket contention from concurrent kernel startups. +# +# Usage: +# bash scripts/test_playwright_jupyter_parallel.sh --venv-location=/path/to/venv +# bash scripts/test_playwright_jupyter_parallel.sh --use-local-venv +# PARALLEL=3 bash scripts/test_playwright_jupyter_parallel.sh # 3 isolated servers +# +# Ports used: BASE_PORT to BASE_PORT+PARALLEL-1 (default 8889..8889+N-1) +set -euo pipefail + +if [ -z "${ROOT_DIR:-}" ]; then + cd "$(dirname "$0")/.." + ROOT_DIR="$(pwd)" +fi +cd "$ROOT_DIR" + +# ── Argument parsing (same interface as before) ─────────────────────────────── + +USE_LOCAL_VENV=false +VENV_LOCATION="" +NOTEBOOK="" +PARALLEL=${PARALLEL:-9} +BASE_PORT=${BASE_PORT:-8889} +SERVERS_RUNNING=false + +while [[ $# -gt 0 ]]; do + case $1 in + --use-local-venv|--local-dev) USE_LOCAL_VENV=true; shift ;; + --venv-location=*) VENV_LOCATION="${1#*=}"; shift ;; + --venv-location) VENV_LOCATION="$2"; shift 2 ;; + --notebook=*) NOTEBOOK="${1#*=}"; shift ;; + --notebook) NOTEBOOK="$2"; shift 2 ;; + --parallel=*) PARALLEL="${1#*=}"; shift ;; + --parallel) PARALLEL="$2"; shift 2 ;; + --servers-running) SERVERS_RUNNING=true; shift ;; + *) shift ;; + esac +done + +# ── Notebooks ───────────────────────────────────────────────────────────────── + +NOTEBOOKS=( + "test_buckaroo_widget.ipynb" + "test_buckaroo_infinite_widget.ipynb" + "test_polars_widget.ipynb" + "test_polars_infinite_widget.ipynb" + "test_dfviewer.ipynb" + "test_dfviewer_infinite.ipynb" + "test_polars_dfviewer.ipynb" + "test_polars_dfviewer_infinite.ipynb" + "test_infinite_scroll_transcript.ipynb" +) + +if [ -n "$NOTEBOOK" ]; then + IFS=',' read -ra NOTEBOOKS <<< "$NOTEBOOK" +fi + +TOTAL=${#NOTEBOOKS[@]} + +# ── Logging ─────────────────────────────────────────────────────────────────── + +RED='\033[0;31m'; GREEN='\033[0;32m'; YELLOW='\033[1;33m'; BLUE='\033[0;34m'; NC='\033[0m' +log() { echo -e "${BLUE}[$(date +'%H:%M:%S')]${NC} $1"; } +ok() { echo -e "${GREEN}$1${NC}"; } +err() { echo -e "${RED}$1${NC}"; } + +# ── Venv setup ──────────────────────────────────────────────────────────────── + +if [ -n "$VENV_LOCATION" ]; then + VENV_DIR="$VENV_LOCATION" + [ -d "$VENV_DIR" ] || { err "Venv not found at $VENV_DIR"; exit 1; } + log "Using venv: $VENV_DIR" + source "$VENV_DIR/bin/activate" +elif [ "$USE_LOCAL_VENV" = true ]; then + VENV_DIR=".venv" + [ -d "$VENV_DIR" ] || { err "Local venv not found at $VENV_DIR"; exit 1; } + source "$VENV_DIR/bin/activate" +else + VENV_DIR="./test_venv" + log "Creating test venv..." + uv venv "$VENV_DIR" + source "$VENV_DIR/bin/activate" +fi + +# ── Dependency check ────────────────────────────────────────────────────────── + +if [ -z "$VENV_LOCATION" ] && [ "$USE_LOCAL_VENV" = false ]; then + python3 -c "import polars; import jupyterlab" 2>/dev/null || { + log "Installing Python deps..." + uv pip install pandas polars jupyterlab + } +fi + +if [ -n "$VENV_LOCATION" ] || [ "$USE_LOCAL_VENV" = true ]; then + python -c "import buckaroo" 2>/dev/null || { err "buckaroo not installed in venv"; exit 1; } +else + log "Running full build..." + bash scripts/full_build.sh + uv pip install --force-reinstall dist/*.whl +fi + +# websocket-client is needed for WebSocket-based kernel warmup +python -c "import websocket" 2>/dev/null || { + log "Installing websocket-client..." + uv pip install websocket-client +} + +python -c "import buckaroo; print(f'buckaroo {getattr(buckaroo, \"__version__\", \"?\")}')" + +# ── Playwright deps ─────────────────────────────────────────────────────────── + +cd packages/buckaroo-js-core +if [ "${SKIP_INSTALL:-0}" != "1" ]; then + pnpm install 2>/dev/null || npm install + pnpm exec playwright install chromium 2>/dev/null || true +fi + +# ── Multiple isolated JupyterLab servers (one per parallel slot) ────────────── + +JUPYTER_TOKEN="test-token-12345" +declare -a JUPYTER_PIDS=() + +cleanup() { + log "Cleaning up..." + # When --servers-running, caller manages server lifecycle + if [ "$SERVERS_RUNNING" = false ]; then + for pid in "${JUPYTER_PIDS[@]:-}"; do + [ -n "$pid" ] && kill "$pid" 2>/dev/null && wait "$pid" 2>/dev/null || true + done + fi + cd "$ROOT_DIR" + for nb in "${NOTEBOOKS[@]}"; do rm -f "$nb"; done + if [ -z "$VENV_LOCATION" ] && [ "$USE_LOCAL_VENV" = false ] && [ -d "$VENV_DIR" ]; then + rm -rf "$VENV_DIR" + fi +} +trap cleanup EXIT + +cd "$ROOT_DIR" + +export JUPYTER_TOKEN + +# ── Kernel warmup function (used for initial warmup and between-batch re-warmup) +# Creates a kernel, connects via WebSocket to trigger the "nudge" mechanism, +# waits for idle state, then deletes the warmup kernel. Without this, kernels +# can get stuck in "starting" state forever (REST API never transitions). +warmup_one_kernel() { + local port=$1 + python3 -c " +import json, sys, time, urllib.request, websocket + +port = $port +token = '$JUPYTER_TOKEN' +base = f'http://localhost:{port}' + +req = urllib.request.Request( + f'{base}/api/kernels?token={token}', + data=b'{}', + headers={'Content-Type': 'application/json'}, + method='POST', +) +resp = urllib.request.urlopen(req) +kid = json.loads(resp.read())['id'] +print(f' kernel {kid[:8]}... created on port {port}') + +ws_url = f'ws://localhost:{port}/api/kernels/{kid}/channels?token={token}' +ws = websocket.create_connection(ws_url, timeout=30) + +deadline = time.time() + 30 +state = 'unknown' +while time.time() < deadline: + ws.settimeout(max(1, deadline - time.time())) + try: + msg = json.loads(ws.recv()) + except (websocket.WebSocketTimeoutException, TimeoutError): + break + if msg.get('msg_type') == 'status': + state = msg.get('content', {}).get('execution_state', 'unknown') + if state == 'idle': + break + +ws.close() +print(f' kernel {kid[:8]}... on port {port} reached state: {state}') + +try: + req = urllib.request.Request( + f'{base}/api/kernels/{kid}?token={token}', method='DELETE') + urllib.request.urlopen(req) +except Exception: + pass + +sys.exit(0 if state == 'idle' else 1) +" 2>&1 +} +export -f warmup_one_kernel + +if [ "$SERVERS_RUNNING" = true ]; then + # Pre-warmed servers from job_jupyter_warmup — load PIDs for cleanup trap + if [[ -f /tmp/ci-jupyter-warmup-pids ]]; then + read -ra JUPYTER_PIDS < /tmp/ci-jupyter-warmup-pids + fi + log "Using pre-warmed servers (${#JUPYTER_PIDS[@]} PIDs loaded)" +else + # Kill stale processes on all ports we'll use + for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + lsof -ti:$port 2>/dev/null | while read -r pid; do + ps -p "$pid" -o comm= 2>/dev/null | grep -qE 'jupyter|python' && kill -9 "$pid" 2>/dev/null + done || true + done + + rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true + # Remove stale kernel connection files — accumulate across runs, delay startup + rm -f ~/.local/share/jupyter/runtime/kernel-*.json 2>/dev/null || true + rm -f ~/.local/share/jupyter/runtime/jpserver-*.json 2>/dev/null || true + rm -f ~/.local/share/jupyter/runtime/jpserver-*.html 2>/dev/null || true + + # ── Start JupyterLab servers (sequential — one at a time) ──────────────────── + # Starting one at a time prevents CPU competition during initialisation. + # We do NOT start warmup kernels here: the JupyterLab REST API keeps a kernel + # in "starting" state until a WebSocket client connects, so REST-only polling + # never reaches "idle" and the lingering kernel process interferes with + # batch-1 test kernels. Instead, we sleep once after all servers are HTTP-ready + # to let the kernel provisioners finish initialising. + + log "Starting $PARALLEL isolated JupyterLab servers (sequential — one at a time)..." + for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + jupyter lab --no-browser --port="$port" \ + --ServerApp.token="$JUPYTER_TOKEN" \ + --ServerApp.allow_origin='*' \ + --ServerApp.disable_check_xsrf=True \ + --allow-root \ + >/tmp/jupyter-port${port}-$$.log 2>&1 & + JUPYTER_PIDS[$slot]=$! + log " Waiting for JupyterLab on port $port (pid ${JUPYTER_PIDS[$slot]})..." + started=false + for i in $(seq 1 30); do + curl -sf "http://localhost:${port}/api?token=${JUPYTER_TOKEN}" >/dev/null 2>&1 && { started=true; break; } + sleep 1 + done + if [ "$started" = false ]; then + err "JupyterLab on port $port failed to start" + cat "/tmp/jupyter-port${port}-$$.log" || true + exit 1 + fi + ok " JupyterLab ready on port $port (slot $slot)" + done + + log "All $PARALLEL servers HTTP-ready — warming up kernels..." + # Pre-warm Python bytecaches so kernel imports don't compile .pyc concurrently. + python3 -c "import buckaroo; import pandas; import polars; print('Pre-warm done')" 2>&1 || \ + python3 -c "import buckaroo; import pandas; print('Pre-warm done (no polars)')" 2>&1 || true + + # Warm up each server via WebSocket nudge (uses warmup_one_kernel defined above). + + declare -a WARMUP_PIDS=() + for slot in $(seq 0 $((PARALLEL-1))); do + port=$((BASE_PORT + slot)) + log " Warming kernel on port $port (background)..." + warmup_one_kernel "$port" & + WARMUP_PIDS+=($!) + done + + warmup_ok=true + for pid in "${WARMUP_PIDS[@]}"; do + if ! wait "$pid"; then warmup_ok=false; fi + done + if [ "$warmup_ok" = true ]; then + ok " All $PARALLEL kernel warmups complete" + else + log " WARNING: some kernel warmups failed — continuing anyway" + fi + + # ── Copy and trust notebooks ────────────────────────────────────────────────── + + for nb in "${NOTEBOOKS[@]}"; do + cp "tests/integration_notebooks/$nb" "$nb" + done + for nb in "${NOTEBOOKS[@]}"; do + jupyter trust "$nb" 2>/dev/null || true + done + rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true +fi + +# ── Per-server kernel cleanup (between batches) ─────────────────────────────── + +shutdown_kernels_on_port() { + local port=$1 + local kernels + kernels=$(curl -s "http://localhost:$port/api/kernels?token=$JUPYTER_TOKEN" 2>/dev/null || echo "[]") + if [ "$kernels" != "[]" ] && [ -n "$kernels" ]; then + echo "$kernels" | grep -oE '[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}' | while read -r kid; do + curl -s -X DELETE "http://localhost:$port/api/kernels/$kid?token=$JUPYTER_TOKEN" >/dev/null 2>&1 || true + done || true + fi + local sessions + sessions=$(curl -s "http://localhost:$port/api/sessions?token=$JUPYTER_TOKEN" 2>/dev/null || echo "[]") + if [ "$sessions" != "[]" ] && [ -n "$sessions" ]; then + echo "$sessions" | grep -oE '[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}' | while read -r sid; do + curl -s -X DELETE "http://localhost:$port/api/sessions/$sid?token=$JUPYTER_TOKEN" >/dev/null 2>&1 || true + done || true + fi + rm -rf ~/.jupyter/lab/workspaces /repo/.jupyter/lab/workspaces 2>/dev/null || true + sleep 0.5 +} + +# ── Run one notebook (called in background, targets a specific server port) ─── + +run_one() { + local nb=$1 idx=$2 logfile=$3 port=$4 + local spec="pw-tests/integration.spec.ts" + local timeout=180000 + + if [[ "$nb" == "test_infinite_scroll_transcript.ipynb" ]]; then + spec="pw-tests/infinite-scroll-transcript.spec.ts" + fi + + cd "$ROOT_DIR/packages/buckaroo-js-core" + # Each parallel slot needs its own test-results dir to avoid ENOENT races + # when 9 Playwright processes try to mkdir .playwright-artifacts-0 simultaneously. + local results_dir="/tmp/pw-results-${nb%.ipynb}-$$" + TEST_NOTEBOOK="$nb" \ + JUPYTER_BASE_URL="http://localhost:$port" \ + JUPYTER_TOKEN="$JUPYTER_TOKEN" \ + PLAYWRIGHT_HTML_OUTPUT_DIR="/tmp/pw-html-jupyter-${nb%.ipynb}-$$" \ + npx playwright test "$spec" \ + --config playwright.config.integration.ts \ + --reporter=line \ + --timeout=$timeout \ + --retries=2 \ + --output="$results_dir" \ + >"$logfile" 2>&1 +} +export -f run_one +export ROOT_DIR JUPYTER_TOKEN + +# ── Batch execution ─────────────────────────────────────────────────────────── +# Each slot in a batch targets slot's dedicated JupyterLab server. +# No two notebooks ever share a server simultaneously. + +log "Running $TOTAL notebooks, $PARALLEL at a time ($PARALLEL isolated JupyterLab servers)" + +OVERALL=0 +PASSED=0 +FAILED_LIST=() +declare -A LOGFILES +QUEUE=("${NOTEBOOKS[@]}") +NEXT=0 +BATCH_NUM=0 + +TMPDIR=$(mktemp -d -t pw-jupyter-parallelXXXXXX) + +while [ $NEXT -lt $TOTAL ]; do + declare -A BATCH_PIDS=() + declare -A BATCH_PORTS=() + BATCH_COUNT=0 + BATCH_USED_PORTS=() + + while [ $BATCH_COUNT -lt "$PARALLEL" ] && [ $NEXT -lt $TOTAL ]; do + # Stagger Chromium launches — 1.5s fails on b2b runs; 2s is minimum reliable + [ $BATCH_COUNT -gt 0 ] && sleep 2 + local_nb="${QUEUE[$NEXT]}" + local_logfile="$TMPDIR/${local_nb%.ipynb}.log" + local_port=$((BASE_PORT + BATCH_COUNT)) + LOGFILES["$local_nb"]="$local_logfile" + run_one "$local_nb" "$NEXT" "$local_logfile" "$local_port" & + local_pid=$! + BATCH_PIDS[$local_pid]="$local_nb" + BATCH_PORTS[$local_pid]="$local_port" + BATCH_USED_PORTS+=("$local_port") + log "START [$((NEXT+1))/$TOTAL] $local_nb (port $local_port)" + ((NEXT++)) || true + ((BATCH_COUNT++)) || true + done + + for pid in "${!BATCH_PIDS[@]}"; do + set +e; wait "$pid"; rc=$?; set -e + nb="${BATCH_PIDS[$pid]}" + if [ $rc -eq 0 ]; then + ok " PASS $nb" + ((PASSED++)) || true + else + err " FAIL $nb (see ${LOGFILES[$nb]})" + FAILED_LIST+=("$nb") + OVERALL=1 + fi + done + + # Clean up each used server's kernel and re-warm before next batch. + # Without re-warmup, new kernels can get stuck in "starting" state — + # the REST API never transitions without a WebSocket nudge. + if [ $NEXT -lt $TOTAL ]; then + for p in "${BATCH_USED_PORTS[@]:-}"; do + shutdown_kernels_on_port "$p" + done + # Determine how many ports the next batch will use + remaining=$((TOTAL - NEXT)) + next_batch_size=$((remaining < PARALLEL ? remaining : PARALLEL)) + for slot in $(seq 0 $((next_batch_size - 1))); do + rwport=$((BASE_PORT + slot)) + # Verify server is responsive + curl -sf "http://localhost:${rwport}/api?token=${JUPYTER_TOKEN}" >/dev/null 2>&1 || { + log "WARNING: Server on port $rwport not responding after cleanup" + } + # Quick kernel warmup: create → WebSocket nudge → wait idle → delete + warmup_one_kernel "$rwport" >/dev/null 2>&1 || true + done + fi + ((BATCH_NUM++)) || true +done + +# ── Summary ─────────────────────────────────────────────────────────────────── + +log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" +if [ $OVERALL -eq 0 ]; then + ok "ALL $TOTAL JUPYTER TESTS PASSED (parallel=$PARALLEL)" +else + err "FAILED: ${#FAILED_LIST[@]}/$TOTAL notebooks" + for nb in "${FAILED_LIST[@]}"; do + err " - $nb" + tail -5 "${LOGFILES[$nb]}" 2>/dev/null | sed 's/^/ /' + done +fi +log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" + +if [ $OVERALL -ne 0 ]; then + for nb in "${FAILED_LIST[@]}"; do + log "=== Full log: $nb ===" + cat "${LOGFILES[$nb]}" 2>/dev/null || true + done +fi + +rm -rf "$TMPDIR" +exit $OVERALL diff --git a/scripts/test_playwright_marimo.sh b/scripts/test_playwright_marimo.sh index 1ad8ba619..76a4f5f44 100755 --- a/scripts/test_playwright_marimo.sh +++ b/scripts/test_playwright_marimo.sh @@ -43,27 +43,76 @@ success "marimo is available" cd packages/buckaroo-js-core -log_message "Installing npm dependencies..." -if command -v pnpm &> /dev/null; then - pnpm install +if [ "${SKIP_INSTALL:-0}" = "1" ]; then + log_message "SKIP_INSTALL=1 — skipping pnpm install + playwright install" else - npm install + log_message "Installing npm dependencies..." + if command -v pnpm &> /dev/null; then + pnpm install + else + npm install + fi + + log_message "Ensuring Playwright browsers are installed..." + if command -v pnpm &> /dev/null; then + pnpm exec playwright install chromium + else + npx playwright install chromium + fi + + success "Dependencies ready" fi -log_message "Ensuring Playwright browsers are installed..." -if command -v pnpm &> /dev/null; then - pnpm exec playwright install chromium -else - npx playwright install chromium +# ---------- 3. Warm up marimo server ------------------------------------------ +# Under CPU contention (CI with parallel jobs), marimo's first page load can +# take 30s+ to compile widgets. Start the server early, wait for it to serve +# a real page, then let Playwright reuse it. + +MARIMO_PORT=2718 +cd "$ROOT_DIR" + +log_message "Starting marimo server for warmup..." +uv run marimo run --headless --port $MARIMO_PORT --no-token \ + tests/notebooks/marimo_pw_test.py & +MARIMO_PID=$! + +# Wait for HTTP to respond +for i in $(seq 1 60); do + if curl -sf "http://localhost:$MARIMO_PORT" >/dev/null 2>&1; then + break + fi + sleep 1 +done + +if ! curl -sf "http://localhost:$MARIMO_PORT" >/dev/null 2>&1; then + error "marimo server failed to start within 60s" + kill $MARIMO_PID 2>/dev/null || true + exit 1 fi +success "marimo server is responding" + +# Warm up: fetch the page so marimo compiles widgets and caches them. +# Poll until the response contains JS (compiled widgets) instead of hard sleep. +log_message "Warming up marimo (fetching page to trigger widget compilation)..." +curl -sf "http://localhost:$MARIMO_PORT" >/dev/null 2>&1 +for _i in $(seq 1 20); do + body=$(curl -sf "http://localhost:$MARIMO_PORT" 2>/dev/null || echo "") + if echo "$body" | grep -q '/dev/null || true +wait $MARIMO_PID 2>/dev/null || true + exit $EXIT_CODE diff --git a/scripts/test_playwright_server.sh b/scripts/test_playwright_server.sh index 51a67ac1e..311323afd 100755 --- a/scripts/test_playwright_server.sh +++ b/scripts/test_playwright_server.sh @@ -62,27 +62,37 @@ export BUCKAROO_SERVER_PYTHON="$MCP_VENV/bin/python" cd packages/buckaroo-js-core -log_message "Installing npm dependencies..." -if command -v pnpm &> /dev/null; then - pnpm install +if [ "${SKIP_INSTALL:-0}" = "1" ]; then + log_message "SKIP_INSTALL=1 — skipping pnpm install + playwright install" else - npm install + log_message "Installing npm dependencies..." + if command -v pnpm &> /dev/null; then + pnpm install + else + npm install + fi + + log_message "Ensuring Playwright browsers are installed..." + if command -v pnpm &> /dev/null; then + pnpm exec playwright install chromium + else + npx playwright install chromium + fi + + success "Dependencies ready" fi -log_message "Ensuring Playwright browsers are installed..." -if command -v pnpm &> /dev/null; then - pnpm exec playwright install chromium -else - npx playwright install chromium -fi - -success "Dependencies ready" - # ---------- 4. Run the server playwright tests -------------------------------- log_message "Running Playwright tests against Buckaroo server..." -if pnpm test:server; then +# In CI, use list reporter for per-test timing in logs +PW_REPORTER_FLAG="" +if [ -n "${CI:-}" ] || [ -n "${PLAYWRIGHT_BROWSERS_PATH:-}" ]; then + PW_REPORTER_FLAG="--reporter=list" +fi + +if pnpm exec playwright test --config playwright.config.server.ts $PW_REPORTER_FLAG; then success "ALL SERVER PLAYWRIGHT TESTS PASSED!" EXIT_CODE=0 else diff --git a/scripts/test_playwright_storybook.sh b/scripts/test_playwright_storybook.sh index 796cbdeac..685f823a7 100755 --- a/scripts/test_playwright_storybook.sh +++ b/scripts/test_playwright_storybook.sh @@ -35,23 +35,27 @@ echo "🧪 Starting Storybook Playwright Tests" cd packages/buckaroo-js-core -# Install npm dependencies -log_message "Installing npm dependencies..." -if command -v pnpm &> /dev/null; then - pnpm install +if [ "${SKIP_INSTALL:-0}" = "1" ]; then + log_message "SKIP_INSTALL=1 — skipping pnpm install + playwright install" else - npm install -fi + # Install npm dependencies + log_message "Installing npm dependencies..." + if command -v pnpm &> /dev/null; then + pnpm install + else + npm install + fi -# Install Playwright browsers if needed -log_message "Ensuring Playwright browsers are installed..." -if command -v pnpm &> /dev/null; then - pnpm exec playwright install chromium -else - npx playwright install chromium -fi + # Install Playwright browsers if needed + log_message "Ensuring Playwright browsers are installed..." + if command -v pnpm &> /dev/null; then + pnpm exec playwright install chromium + else + npx playwright install chromium + fi -success "Dependencies ready" + success "Dependencies ready" +fi # Kill any existing storybook on port 6006 log_message "Cleaning up port 6006..." diff --git a/scripts/test_playwright_wasm_marimo.sh b/scripts/test_playwright_wasm_marimo.sh index 26abec445..52dc6de76 100644 --- a/scripts/test_playwright_wasm_marimo.sh +++ b/scripts/test_playwright_wasm_marimo.sh @@ -63,22 +63,26 @@ fi cd "$ROOT_DIR/packages/buckaroo-js-core" -log_message "Installing npm dependencies..." -if command -v pnpm &> /dev/null; then - pnpm install +if [ "${SKIP_INSTALL:-0}" = "1" ]; then + log_message "SKIP_INSTALL=1 — skipping pnpm install + playwright install" else - npm install + log_message "Installing npm dependencies..." + if command -v pnpm &> /dev/null; then + pnpm install + else + npm install + fi + + log_message "Ensuring Playwright browsers are installed..." + if command -v pnpm &> /dev/null; then + pnpm exec playwright install chromium + else + npx playwright install chromium + fi + + success "Dependencies ready" fi -log_message "Ensuring Playwright browsers are installed..." -if command -v pnpm &> /dev/null; then - pnpm exec playwright install chromium -else - npx playwright install chromium -fi - -success "Dependencies ready" - # ---------- 4. Run the WASM marimo playwright tests -------------------------------- log_message "Running Playwright tests against WASM marimo notebook..." diff --git a/tests/integration_notebooks/test_infinite_scroll_transcript.ipynb b/tests/integration_notebooks/test_infinite_scroll_transcript.ipynb index fd8694132..c0ca8b1c3 100644 --- a/tests/integration_notebooks/test_infinite_scroll_transcript.ipynb +++ b/tests/integration_notebooks/test_infinite_scroll_transcript.ipynb @@ -1,40 +1,40 @@ { - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import buckaroo\n", - "import polars as pl\n", - "from buckaroo.polars_buckaroo import PolarsBuckarooInfiniteWidget\n", - "\n", - "# Create a large predictable DataFrame for testing infinite scroll\n", - "# Row i has: int_col = i + 10, str_col = f\"foo_{i + 10}\"\n", - "# 2000 rows ensures we need multiple data fetches to satisfy scroll requests\n", - "N_ROWS = 2000\n", - "df = pl.DataFrame({\n", - " 'row_num': list(range(N_ROWS)),\n", - " 'int_col': [i + 10 for i in range(N_ROWS)],\n", - " 'str_col': [f'foo_{i + 10}' for i in range(N_ROWS)]\n", - "})\n", - "print(f\"✅ Created DataFrame with shape: {df.shape}\")\n", - "print(f\" First row: row_num=0, int_col=10, str_col='foo_10'\")\n", - "print(f\" Last row: row_num={N_ROWS-1}, int_col={N_ROWS-1+10}, str_col='foo_{N_ROWS-1+10}'\")\n", - "\n", - "# Display the widget with transcript recording enabled\n", - "widget = PolarsBuckarooInfiniteWidget(df, record_transcript=True)\n", - "print(\"✅ PolarsBuckarooInfiniteWidget created successfully with transcript recording enabled\")\n", - "widget\n" - ] - } - ], - "metadata": { - "language_info": { - "name": "python" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import buckaroo\n", + "import polars as pl\n", + "from buckaroo.polars_buckaroo import PolarsBuckarooInfiniteWidget\n", + "\n", + "# Create a large predictable DataFrame for testing infinite scroll\n", + "# Row i has: int_col = i + 10, str_col = f\"foo_{i + 10}\"\n", + "# 500 rows ensures we need multiple data fetches to satisfy scroll requests\n", + "N_ROWS = 500\n", + "df = pl.DataFrame({\n", + " 'row_num': list(range(N_ROWS)),\n", + " 'int_col': [i + 10 for i in range(N_ROWS)],\n", + " 'str_col': [f'foo_{i + 10}' for i in range(N_ROWS)]\n", + "})\n", + "print(f\"\u2705 Created DataFrame with shape: {df.shape}\")\n", + "print(f\" First row: row_num=0, int_col=10, str_col='foo_10'\")\n", + "print(f\" Last row: row_num={N_ROWS-1}, int_col={N_ROWS-1+10}, str_col='foo_{N_ROWS-1+10}'\")\n", + "\n", + "# Display the widget with transcript recording enabled\n", + "widget = PolarsBuckarooInfiniteWidget(df, record_transcript=True)\n", + "print(\"\u2705 PolarsBuckarooInfiniteWidget created successfully with transcript recording enabled\")\n", + "widget\n" + ] + } + ], + 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