diff --git a/CKAN_INTEGRATION_TEST_README.md b/CKAN_INTEGRATION_TEST_README.md new file mode 100644 index 0000000..2cd2627 --- /dev/null +++ b/CKAN_INTEGRATION_TEST_README.md @@ -0,0 +1,134 @@ +# CKAN Integration Test Setup + +## Overview + +The CKAN integration test `test_ckan_dataset_update_integration()` verifies that the enhanced `update_dataset` functionality works correctly with a real CKAN instance. + +## Error Resolution + +### Organization Required Error +If you see the error: +``` +"{'owner_org': ['An organization must be provided'], '__type': 'Validation Error'}" +``` + +This means the CKAN instance requires datasets to be created under an organization. The test has been updated to handle this requirement by: +- Adding `organization=ORGANIZATION` parameter to dataset creation +- Adding validation to ensure `CKAN_ORGANIZATION` environment variable is set +- Skipping the test if organization is not configured + +### Tag Order Assertion Error +If you see an assertion error like: +``` +AssertionError: assert ['final', 'replaced'] == ['replaced', 'final'] +``` + +This is because CKAN doesn't guarantee tag order. The test has been updated to use order-independent comparison: +- Uses `set()` comparison for tag validation +- Validates tag count separately to ensure no missing/extra tags +- Focuses on content validation rather than order + +## Required Environment Variables + +Set the following environment variables before running the integration test: + +```bash +# Upstream API credentials +export UPSTREAM_USERNAME=your_upstream_username +export UPSTREAM_PASSWORD=your_upstream_password + +# CKAN credentials and configuration +export CKAN_API_KEY=your_ckan_api_key +export CKAN_ORGANIZATION=your_organization_name + +# Optional: Override default URLs +export CKAN_URL=http://ckan.tacc.cloud:5000 # Default +export UPSTREAM_BASE_URL=http://localhost:8000 # Default +``` + +## How to Run the Test + +### Option 1: Run the specific test +```bash +pytest tests/integration/test_campaigns_integration.py::test_ckan_dataset_update_integration -v -s +``` + +### Option 2: Run all integration tests +```bash +pytest tests/integration/ -m integration -v +``` + +## What the Test Does + +The integration test performs a complete workflow: + +1. **Creates** an initial CKAN dataset with: + - Tags: `["test", "initial"]` + - Metadata: `{"test_phase": "initial", "created_by": "integration_test"}` + +2. **Updates** the dataset using merge mode: + - Adds tags: `["updated", "integration-test"]` + - Adds/updates metadata: `{"test_phase": "updated", "update_timestamp": "...", "integration_status": "passed"}` + - Updates title to "Updated Test Dataset" + +3. **Verifies** merge results: + - Both old and new tags present: `["test", "initial", "updated", "integration-test"]` + - Both old and new metadata present + - Updated fields have new values + - Preserved fields remain unchanged + +4. **Tests** replace mode: + - Replaces all tags with: `["replaced", "final"]` + - Replaces all metadata with: `{"final_phase": "replace_test", "mode": "replace"}` + +5. **Verifies** replace results: + - Only new tags present (old ones removed) + - Only new metadata present (old ones removed) + +6. **Cleans up** by deleting the test dataset + +## Expected Output + +``` +Testing CKAN dataset update integration with: test-dataset-update-20250722211732 +โœ… Created initial dataset: test-dataset-update-20250722211732 +โœ… Verified initial dataset state +๐Ÿ”„ Updating dataset with new tag and metadata... +โœ… Updated dataset: test-dataset-update-20250722211732 +๐Ÿ” Verifying updates... + โœ“ Title updated successfully + โœ“ Tags updated successfully: ['test', 'initial', 'updated', 'integration-test'] + โœ“ Original metadata preserved + โœ“ Existing metadata updated + โœ“ New metadata added +โœ… All updates verified successfully! +๐Ÿ”„ Testing replace mode... + โœ“ Tags replaced successfully + โœ“ Metadata replaced successfully +โœ… Replace mode test passed! +๐Ÿงน Cleaned up test dataset: test-dataset-update-20250722211732 +๐ŸŽ‰ CKAN dataset update integration test completed successfully! +``` + +## Troubleshooting + +### No Organization Access +If you get organization errors, ask your CKAN admin to: +1. Create an organization for testing +2. Add your user to the organization with editor/admin permissions + +### API Key Issues +- Ensure your CKAN API key has permissions to create/update/delete datasets +- Check that the API key hasn't expired +- Verify the API key format matches your CKAN instance requirements + +### Network Issues +- Ensure the CKAN URL is accessible from your testing environment +- Check firewall and network connectivity +- Verify the CKAN instance is running and responding + +## Files Modified + +- `tests/integration/test_campaigns_integration.py` - Added comprehensive integration test +- `upstream/ckan.py` - Enhanced `update_dataset` method with metadata support +- `tests/unit/test_ckan_unit.py` - Added unit tests for enhanced functionality \ No newline at end of file diff --git a/README.md b/README.md index e3f8dad..580f6a5 100644 --- a/README.md +++ b/README.md @@ -23,18 +23,23 @@ The Upstream Python SDK provides a standardized, production-ready toolkit for en ### ๐Ÿ“Š **Complete Data Workflow** ```python -from upstream import UpstreamClient - -# Initialize client -client = UpstreamClient(username="researcher", password="password") - -# Create campaign and station +from upstream.client import UpstreamClient from upstream_api_client.models import CampaignsIn, StationCreate from datetime import datetime, timedelta +# Initialize client with CKAN integration +client = UpstreamClient( + username="researcher", + password="password", + base_url="https://upstream-dso.tacc.utexas.edu/dev", + ckan_url="https://ckan.tacc.utexas.edu", + ckan_organization="your-org" +) + +# Create campaign campaign_data = CampaignsIn( - name="Hurricane Monitoring 2024", - description="Hurricane monitoring campaign", + name="Environmental Monitoring 2024", + description="Environmental monitoring campaign with multi-sensor stations", contact_name="Dr. Jane Smith", contact_email="jane.smith@university.edu", allocation="TACC", @@ -43,13 +48,13 @@ campaign_data = CampaignsIn( ) campaign = client.create_campaign(campaign_data) +# Create monitoring station station_data = StationCreate( - name="Galveston Pier", - description="Hurricane monitoring station at Galveston Pier", + name="Downtown Air Quality Monitor", + description="Multi-sensor environmental monitoring station", contact_name="Dr. Jane Smith", contact_email="jane.smith@university.edu", - start_date=datetime.now(), - active=True + start_date=datetime.now() ) station = client.create_station(campaign.id, station_data) @@ -61,33 +66,56 @@ result = client.upload_csv_data( measurements_file="measurements.csv" ) -# Automatically creates discoverable CKAN dataset -print(f"Data published at: {result.ckan_url}") +print(f"Uploaded {result['response']['Total sensors processed']} sensors") +print(f"Added {result['response']['Total measurements added to database']} measurements") + +# Publish to CKAN with rich metadata +publication = client.publish_to_ckan( + campaign_id=campaign.id, + station_id=station.id +) +print(f"Data published at: {publication['ckan_url']}") ``` ### ๐Ÿš€ **Production-Ready Features** -- **Automatic chunking** for large datasets (>50MB) -- **Retry mechanisms** with exponential backoff -- **Comprehensive error handling** with detailed messages -- **Progress tracking** for long-running uploads -- **Extensive logging** for debugging and monitoring +- **Type-safe interfaces** with Pydantic models and comprehensive validation +- **Rich statistics** - automatic calculation of sensor measurement statistics +- **Comprehensive error handling** with specific exception types (`APIError`, `ValidationError`) +- **CKAN integration** with custom metadata support and automatic resource management +- **Modular architecture** with dedicated managers for campaigns, stations, and sensors +- **Extensive logging** and debugging capabilities +- **Authentication management** with automatic token handling -### ๐Ÿ”„ **Automation-Friendly** +### ๐Ÿ”„ **CKAN Integration & Publishing** -Perfect for automated sensor networks: +Seamless data publishing to CKAN portals: ```python -# Scheduled data upload every 6 hours -def automated_upload(): - # Collect sensor readings and save to CSV files - sensors_file, measurements_file = collect_sensor_readings() - client.upload_csv_data( - campaign_id=CAMPAIGN_ID, - station_id=STATION_ID, - sensors_file=sensors_file, - measurements_file=measurements_file - ) +# Publish with custom metadata +publication_result = client.publish_to_ckan( + campaign_id=campaign_id, + station_id=station_id, + + # Custom dataset metadata + dataset_metadata={ + "project_name": "Air Quality Study", + "funding_agency": "EPA", + "grant_number": "EPA-2024-001" + }, + + # Custom resource metadata + resource_metadata={ + "calibration_date": "2024-01-15", + "quality_control": "Automated + Manual Review", + "uncertainty_bounds": "ยฑ2% of reading" + }, + + # Custom tags for discoverability + custom_tags=["air-quality", "epa-funded", "quality-controlled"] +) + +print(f"Dataset published: {publication_result['ckan_url']}") ``` ## Installation @@ -102,54 +130,96 @@ For development: pip install upstream-sdk[dev] ``` +## Demo Notebooks + +The SDK includes comprehensive demo notebooks that showcase all features: + +### ๐Ÿ““ **UpstreamSDK_Core_Demo.ipynb** +Interactive demonstration of core functionality: +- Authentication and client setup +- Campaign creation and management +- Station setup with sensor configuration +- CSV data upload with comprehensive validation +- Sensor statistics and analytics +- Error handling and best practices + +### ๐Ÿ““ **UpstreamSDK_CKAN_Demo.ipynb** +Complete CKAN integration workflow: +- CKAN portal setup and authentication +- Data export and preparation for publishing +- Dataset creation with rich metadata +- Custom metadata support (dataset, resource, and tags) +- Resource management and updates +- Dataset discovery and search capabilities + +Both notebooks include detailed explanations, practical examples, and production-ready code patterns. + ## Quick Start ### 1. Basic Setup ```python -from upstream import UpstreamClient +from upstream.client import UpstreamClient -# Initialize with credentials +# Initialize with credentials and CKAN integration client = UpstreamClient( username="your_username", password="your_password", - base_url="https://upstream-dso.tacc.utexas.edu/dev" + base_url="https://upstream-dso.tacc.utexas.edu/dev", + ckan_url="https://ckan.tacc.utexas.edu", + ckan_organization="your-org" ) + +# Test authentication +if client.authenticate(): + print("โœ… Connected successfully!") ``` ### 2. Create Campaign ```python +from upstream.campaigns import CampaignManager from upstream_api_client.models import CampaignsIn from datetime import datetime, timedelta +# Initialize campaign manager +campaign_manager = CampaignManager(client.auth_manager) + campaign_data = CampaignsIn( - name="Air Quality Monitoring 2024", - description="Urban air quality sensor network deployment", + name="Environmental Monitoring 2024", + description="Multi-sensor environmental monitoring network", contact_name="Dr. Jane Smith", contact_email="jane.smith@university.edu", allocation="TACC", start_date=datetime.now(), end_date=datetime.now() + timedelta(days=365) ) -campaign = client.create_campaign(campaign_data) +campaign = campaign_manager.create(campaign_data) +print(f"Campaign created with ID: {campaign.id}") ``` ### 3. Register Monitoring Station ```python +from upstream.stations import StationManager from upstream_api_client.models import StationCreate from datetime import datetime +# Initialize station manager +station_manager = StationManager(client.auth_manager) + station_data = StationCreate( - name="Downtown Monitor", - description="City center air quality station", + name="Downtown Air Quality Monitor", + description="Multi-sensor air quality monitoring station", contact_name="Dr. Jane Smith", contact_email="jane.smith@university.edu", - start_date=datetime.now(), - active=True + start_date=datetime.now() ) -station = client.create_station(campaign.id, station_data) +station = station_manager.create( + campaign_id=str(campaign.id), + station_create=station_data +) +print(f"Station created with ID: {station.id}") ``` ### 4. Upload Sensor Data @@ -163,8 +233,11 @@ result = client.upload_csv_data( measurements_file="path/to/measurements.csv" ) -print(f"Uploaded {result.sensors_processed} sensors") -print(f"Added {result.measurements_added} measurements") +# Access detailed results +response = result['response'] +print(f"Sensors processed: {response['Total sensors processed']}") +print(f"Measurements added: {response['Total measurements added to database']}") +print(f"Processing time: {response['Data Processing time']}") ``` ## Data Format Requirements @@ -173,100 +246,122 @@ print(f"Added {result.measurements_added} measurements") ```csv alias,variablename,units,postprocess,postprocessscript -temp_01,Air Temperature,ยฐC,, -humidity_01,Relative Humidity,%,, -pm25_01,PM2.5 Concentration,ฮผg/mยณ,, +temp_01,Air Temperature,ยฐC,false, +humidity_01,Relative Humidity,%,false, +PM25_01,PM2.5 Concentration,ฮผg/mยณ,true,pm25_calibration +wind_speed,Wind Speed,m/s,false, +co2_01,CO2 Concentration,ppm,false, ``` ### Measurements CSV Format ```csv -collectiontime,Lat_deg,Lon_deg,temp_01,humidity_01,pm25_01 -2024-01-15T10:30:00Z,30.2672,-97.7431,23.5,65.2,12.8 -2024-01-15T10:31:00Z,30.2672,-97.7431,23.7,64.8,13.1 -2024-01-15T10:32:00Z,30.2672,-97.7431,23.9,64.5,12.9 +collectiontime,Lat_deg,Lon_deg,temp_01,humidity_01,PM25_01,wind_speed,co2_01 +2024-01-15T10:00:00,30.2672,-97.7431,22.5,68.2,15.2,3.2,420 +2024-01-15T10:05:00,30.2672,-97.7431,22.7,67.8,14.8,3.5,425 +2024-01-15T10:10:00,30.2672,-97.7431,22.9,67.5,16.1,3.1,418 ``` ## Advanced Usage -### Automated Pipeline Example +### Sensor Analytics and Statistics ```python -import schedule -from upstream import UpstreamClient - -client = UpstreamClient.from_config("config.yaml") - -def hourly_data_upload(): - try: - # Collect data from sensors - sensor_data = collect_from_weather_station() - - # Upload to Upstream - result = client.upload_csv_data( - campaign_id=CAMPAIGN_ID, - station_id=STATION_ID, - sensors_file=sensors_file, - measurements_file=measurements_file - ) - - logger.info(f"Successfully uploaded {result.sensors_processed} sensors and {result.measurements_added} measurements") - - except Exception as e: - logger.error(f"Upload failed: {e}") - # Implement your error handling/alerting - -# Schedule uploads every hour -schedule.every().hour.do(hourly_data_upload) +# Get sensor statistics after upload +sensors = client.sensors.list(campaign_id=campaign_id, station_id=station_id) + +for sensor in sensors.items: + stats = sensor.statistics + print(f"Sensor: {sensor.alias} ({sensor.variablename})") + print(f" Measurements: {stats.count}") + print(f" Range: {stats.min_value:.2f} - {stats.max_value:.2f} {sensor.units}") + print(f" Average: {stats.avg_value:.2f} {sensor.units}") + print(f" Std Dev: {stats.stddev_value:.3f}") + print(f" Last value: {stats.last_measurement_value:.2f}") + print(f" Updated: {stats.stats_last_updated}") ``` -### Large Dataset Handling +### Error Handling and Validation ```python -# For large files, use chunked upload -result = client.upload_chunked_csv_data( - campaign_id=campaign.id, - station_id=station.id, - sensors_file="sensors.csv", - measurements_file="large_dataset.csv", # 500MB file - chunk_size=10000 # rows per chunk -) +from upstream.exceptions import APIError, ValidationError +from upstream.campaigns import CampaignManager +from upstream.stations import StationManager + +try: + # Initialize managers + campaign_manager = CampaignManager(client.auth_manager) + station_manager = StationManager(client.auth_manager) + + # Create campaign with validation + campaign = campaign_manager.create(campaign_data) + station = station_manager.create( + campaign_id=str(campaign.id), + station_create=station_data + ) + +except ValidationError as e: + print(f"Data validation failed: {e}") +except APIError as e: + print(f"API error: {e}") +except Exception as e: + print(f"Unexpected error: {e}") ``` -### Advanced Upload Options +### Comprehensive Data Upload ```python -# For more control over uploads, use the advanced method -result = client.upload_sensor_measurement_files( +# Upload with detailed response handling +result = client.upload_csv_data( campaign_id=campaign.id, station_id=station.id, - sensors_file="sensors.csv", # Can be file path, bytes, or (filename, bytes) tuple - measurements_file="measurements.csv", # Can be file path, bytes, or (filename, bytes) tuple - chunk_size=1000 # Process in chunks of 1000 rows + sensors_file="path/to/sensors.csv", + measurements_file="path/to/measurements.csv" ) + +# Access detailed upload information +response = result['response'] +print(f"Sensors processed: {response['Total sensors processed']}") +print(f"Measurements added: {response['Total measurements added to database']}") +print(f"Processing time: {response['Data Processing time']}") +print(f"Files stored: {response['uploaded_file_sensors stored in memory']}") ``` -### Custom Data Processing +### Automated Data Pipeline ```python -# Pre-process data before upload -def custom_pipeline(): - # Your data collection logic - raw_data = collect_sensor_data() - - # Apply quality control - cleaned_data = apply_qc_filters(raw_data) - - # Transform to Upstream format - upstream_data = transform_data(cleaned_data) - - # Upload processed data - client.upload_csv_data( - campaign_id=campaign.id, - station_id=station.id, - sensors_file="processed_sensors.csv", - measurements_file="processed_measurements.csv" - ) +# Complete automated workflow +def automated_monitoring_pipeline(): + try: + # List existing campaigns and stations + campaigns = client.list_campaigns(limit=5) + if campaigns.items: + campaign = campaigns.items[0] + stations = client.list_stations(campaign_id=str(campaign.id)) + + if stations.items: + station = stations.items[0] + + # Upload new sensor data + result = client.upload_csv_data( + campaign_id=campaign.id, + station_id=station.id, + sensors_file="latest_sensors.csv", + measurements_file="latest_measurements.csv" + ) + + # Publish to CKAN automatically + publication = client.publish_to_ckan( + campaign_id=campaign.id, + station_id=station.id, + custom_tags=["automated", "real-time"] + ) + + print(f"Pipeline completed: {publication['ckan_url']}") + + except Exception as e: + print(f"Pipeline error: {e}") + # Implement alerting/retry logic ``` ## Use Cases @@ -310,33 +405,36 @@ def custom_pipeline(): - **`list_stations(campaign_id: str, **kwargs)`** - List stations for a campaign #### Data Upload -- **`upload_csv_data(campaign_id: str, station_id: str, sensors_file: str, measurements_file: str)`** - Upload CSV files -- **`upload_sensor_measurement_files(campaign_id: str, station_id: str, sensors_file: Union[str, bytes, Tuple], measurements_file: Union[str, bytes, Tuple], chunk_size: int = 1000)`** - Advanced upload with chunking -- **`upload_chunked_csv_data(campaign_id: str, station_id: str, sensors_file: str, measurements_file: str)`** - Chunked upload for large files +- **`upload_csv_data(campaign_id: str, station_id: str, sensors_file: str, measurements_file: str)`** - Upload CSV files with comprehensive response +- **`publish_to_ckan(campaign_id: str, station_id: str, dataset_metadata: dict = None, resource_metadata: dict = None, custom_tags: list = None, **kwargs)`** - Publish to CKAN with custom metadata #### Utilities -- **`validate_files(sensors_file: str, measurements_file: str)`** - Validate CSV files -- **`get_file_info(file_path: str)`** - Get information about CSV files -- **`authenticate()`** - Test authentication +- **`authenticate()`** - Test authentication and return status - **`logout()`** - Logout and invalidate tokens -- **`publish_to_ckan(campaign_id: str, **kwargs)`** - Publish data to CKAN +- **`list_campaigns(limit: int = 10, **kwargs)`** - List campaigns with pagination +- **`list_stations(campaign_id: str, **kwargs)`** - List stations for a campaign +- **`get_campaign(campaign_id: str)`** - Get detailed campaign information +- **`get_station(station_id: str, campaign_id: str)`** - Get detailed station information ### Core Classes -- **`UpstreamClient`** - Main SDK interface -- **`CampaignsIn`** - Campaign creation model -- **`StationCreate`** - Station creation model +- **`UpstreamClient`** - Main SDK interface with CKAN integration +- **`CampaignManager`** - Campaign lifecycle management +- **`StationManager`** - Station creation and management +- **`CKANIntegration`** - CKAN portal integration and publishing -### Authentication +### Data Models -- **`AuthManager`** - Handle API authentication -- **`TokenManager`** - Manage token lifecycle +- **`CampaignsIn`** - Campaign creation model with validation +- **`StationCreate`** - Station creation model +- **`SensorResponse`** - Sensor information with statistics +- **`GetCampaignResponse`** - Detailed campaign data -### Utilities +### Exceptions -- **`DataValidator`** - Validate CSV formats -- **`ChunkManager`** - Handle large file uploads -- **`ErrorHandler`** - Comprehensive error handling +- **`APIError`** - API-specific errors with detailed messages +- **`ValidationError`** - Data validation and format errors +- **`AuthManager`** - Authentication and token management ## Configuration @@ -360,14 +458,13 @@ upstream: ckan: url: https://ckan.tacc.utexas.edu - auto_publish: true - default_organization: your-org - -upload: - chunk_size: 10000 - max_file_size_mb: 50 - retry_attempts: 3 - timeout_seconds: 300 + organization: your-organization + api_key: your_ckan_api_key # Optional for read-only + timeout: 30 + +logging: + level: INFO + format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s" ``` ## Contributing diff --git a/UploadData.ipynb b/UploadData.ipynb deleted file mode 100644 index 57abf15..0000000 --- a/UploadData.ipynb +++ /dev/null @@ -1,2260 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "8f56a9b3", - "metadata": {}, - "source": [ - "# Upstream Data Upload Guide\n", - "\n", - "## Overview\n", - "\n", - "This guide demonstrates how to authenticate with the Upstream API and upload sensor data using CSV files for environmental monitoring campaigns.\n", - "\n", - "## What You Can Do\n", - "\n", - "The Upstream API allows you to:\n", - "- Authenticate and obtain access tokens\n", - "- Upload sensor definitions and measurement data\n", - "- Manage environmental monitoring campaigns\n", - "- Query and retrieve measurement data\n", - "\n", - "## Prerequisites\n", - "\n", - "- Valid Upstream account credentials\n", - "- Python 3.7+ with `requests` library installed\n", - "- CSV files with sensor and measurement data formatted correctly\n", - "\n", - "## Installation\n", - "\n", - "```bash\n", - "pip install requests\n", - "```" - ] - }, - { - "cell_type": "markdown", - "id": "2dee1efa", - "metadata": {}, - "source": [ - "## Quick Start\n", - "\n", - "1. **Authenticate** with the API to get your access token\n", - "2. **Prepare your CSV files** following the required format\n", - "3. **Upload your data** using the provided functions\n", - "4. **Monitor the results** and verify successful upload" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "3de5ed4d-505a-4a59-b15a-7de41e8246d1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: tapipy in /Users/wmobley/Documents/GitHub/upstream-docker/.venv/lib/python3.9/site-packages (1.8.5)\n", - "Requirement already satisfied: jsonschema<5.0.0,>=4.8.0 in /Users/wmobley/Documents/GitHub/upstream-docker/.venv/lib/python3.9/site-packages (from tapipy) (4.17.3)\n", - "Requirement already satisfied: PyJWT>=1.7.1 in /Users/wmobley/Documents/GitHub/upstream-docker/.venv/lib/python3.9/site-packages (from tapipy) (2.10.1)\n", - 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"Requirement already satisfied: charset-normalizer<4,>=2 in /Users/wmobley/Documents/GitHub/upstream-docker/.venv/lib/python3.9/site-packages (from requests<3.0.0,>=2.20.0->tapipy) (3.4.2)\n", - "Requirement already satisfied: pycparser in /Users/wmobley/Documents/GitHub/upstream-docker/.venv/lib/python3.9/site-packages (from cffi>=1.14->cryptography>=3.3.2->tapipy) (2.22)\n", - "Requirement already satisfied: MarkupSafe>=2.1.1 in /Users/wmobley/Documents/GitHub/upstream-docker/.venv/lib/python3.9/site-packages (from werkzeug->openapi_core==0.16.0->tapipy) (3.0.2)\n", - "\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" - ] - } - ], - "source": [ - "! pip install tapipy\n", - "import requests\n", - "import json\n", - "import getpass\n", - "import os\n", - "from tapipy.tapis import Tapis\n", - "from typing import Dict, Any, Optional, List\n" - ] - }, - { - "cell_type": "markdown", - "id": "65443e09", - "metadata": {}, - "source": [ - "## 1. Authentication\n", - "\n", - "First, we need to authenticate with the Upstream API to obtain an access token.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "7b250831-bec9-4425-b165-127e49d76ffc", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "โœ… Authentication successful!\n" - ] - } - ], - "source": [ - "\n", - "credentials = {\n", - " \"username\": input(\"Username: \"),\n", - " \"password\": getpass.getpass(\"Password: \")\n", - " }\n", - "def authenticate_upstream(base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\") -> str:\n", - " \"\"\"\n", - " Authenticate with Upstream API and return access token.\n", - " Args:\n", - " base_url: Base URL for the Upstream API (dev or prod)\n", - " Returns:\n", - " Access token string\n", - " Raises:\n", - " Exception: If authentication fails\n", - " \"\"\"\n", - " auth_url = f\"{base_url}/api/v1/token\"\n", - " try:\n", - " response = requests.post(auth_url, data=credentials)\n", - " response.raise_for_status() \n", - " token = response.json().get(\"access_token\")\n", - " if not token:\n", - " raise Exception(\"No access token in response\")\n", - " print(\"โœ… Authentication successful!\")\n", - " return token\n", - " except requests.exceptions.RequestException as e:\n", - " raise Exception(f\"Authentication failed: {e}\")\n", - "\n", - "# Get authentication token\n", - "token = authenticate_upstream()\n", - "# Create python Tapis client for user\n", - "t = Tapis(base_url= \"https://portals.tapis.io\",\n", - " username=credentials['username'],\n", - " password=credentials['password'])\n", - "\n", - "# Call to Tokens API to get access token\n", - "t.get_tokens()\n", - "tapis_token = t.access_token" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d9c608a2", - "metadata": {}, - "outputs": [], - "source": [ - "def make_authenticated_request(\n", - " method: str,\n", - " url: str,\n", - " token: str,\n", - " json: Optional[Dict] = None,\n", - " files: Optional[Dict] = None,\n", - " params: Optional[Dict] = None\n", - ") -> requests.Response:\n", - " \"\"\"\n", - " Make an authenticated HTTP request to the Upstream API.\n", - " \n", - " Args:\n", - " method: HTTP method (GET, POST, PUT, DELETE, etc.)\n", - " url: Full URL for the request\n", - " token: Authentication token\n", - " json: JSON data for the request body\n", - " files: Files for multipart upload\n", - " params: URL parameters\n", - " \n", - " Returns:\n", - " Response object from the request\n", - " \n", - " Raises:\n", - " requests.exceptions.HTTPError: If the request fails\n", - " \"\"\"\n", - " headers = {\n", - " \"Authorization\": f\"Bearer {token}\",\n", - " }\n", - " \n", - " # Don't set Content-Type for file uploads (requests will set it automatically)\n", - " if files is None:\n", - " headers[\"Content-Type\"] = \"application/json\"\n", - " try:\n", - " response = requests.request(\n", - " method=method.upper(),\n", - " url=url,\n", - " headers=headers,\n", - " json=json,\n", - " files=files,\n", - " params=params,\n", - " timeout=300 # 5 minute timeout for large file uploads\n", - " )\n", - " \n", - " # Raise an exception for bad status codes\n", - " response.raise_for_status()\n", - " return response\n", - " \n", - " except requests.exceptions.HTTPError as e:\n", - " print(f\"โŒ HTTP Error: {e}\")\n", - " print(f\"Response content: {response.text}\")\n", - " raise\n", - " except requests.exceptions.RequestException as e:\n", - " print(f\"โŒ Request Error: {e}\")\n", - " raise" - ] - }, - { - "cell_type": "markdown", - "id": "ede83720", - "metadata": {}, - "source": [ - "## 2. Helper Functions for API Requests\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1a20206c-dc87-4f0d-b9cf-87923998a9f4", - "metadata": {}, - "outputs": [], - "source": [ - "def create_campaign(\n", - " campaign_data:str, \n", - " token: str,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Create a new campaign.\n", - " \n", - " Args:\n", - " name: Campaign name\n", - " description: Campaign description\n", - " allocation: TACC allocation identifier (required)\n", - " token: Authentication token\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Dictionary containing the created campaign data with ID\n", - " \"\"\"\n", - " url = f\"{base_url}/api/v1/campaigns\" \n", - " response = make_authenticated_request(\n", - " method=\"POST\",\n", - " url=url,\n", - " token=token,\n", - " json=campaign_data\n", - " )\n", - " result = response.json()\n", - " print(f\"โœ… Campaign created successfully!\")\n", - " return result\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "c8f94d96", - "metadata": {}, - "source": [ - "### Creating Campaigns\n", - "\n", - "Before uploading CSV data, you need to create a campaign to organize your data collection project. A campaign serves as the top-level container for all related monitoring activities.\n", - "\n", - "#### Campaign Requirements\n", - "\n", - "**Required Fields:**\n", - "- `name`: Descriptive name for your data collection project\n", - "- `description`: Detailed description of the campaign's purpose and scope\n", - "\n", - "#### Campaign Best Practices\n", - "\n", - "๐ŸŽฏ **Naming Conventions:**\n", - "- Use descriptive, unique names that clearly identify the project\n", - "- Include dates, locations, or project codes for easy identification\n", - "- Examples: \"Austin Air Quality 2024\", \"Hurricane Harvey Recovery Monitoring\"\n", - "\n", - "๐Ÿ“ **Descriptions:**\n", - "- Provide detailed context about the campaign's objectives\n", - "- Include information about duration, scope, and expected outcomes\n", - "- Mention any relevant research or operational goals" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b2e618b6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "=== Creating Campaign from Configuration ===\n", - "๐Ÿ“‹ Campaign Configuration Summary:\n", - " Name: Beaumont Stream Gauge\n", - " Description: Beaumont Stream Gauge Campaign...\n", - "โœ… Campaign created successfully!\n", - "Campaign ID: 12\n", - "\n", - "๐ŸŽ‰ Campaign setup complete!\n", - "Campaign ID: 12\n" - ] - } - ], - "source": [ - "def load_and_create_campaign(\n", - " config_path: str = \"campaigns/campaign.json\",\n", - " token: str = None,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Load campaign configuration from JSON and create the campaign.\n", - " \n", - " Args:\n", - " config_path: Path to the campaign configuration JSON file\n", - " token: Authentication token\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Dictionary containing the created campaign data with ID\n", - " \"\"\"\n", - " # Load configuration\n", - " with open(config_path) as campaign_data:\n", - " campaign_json = json.loads(campaign_data.read())\n", - "\n", - " # Validate required fields\n", - " required_fields = [\"name\", \"description\"]\n", - " for field in required_fields:\n", - " if field not in campaign_json:\n", - " raise ValueError(f\"Missing required field '{field}' in campaign config\") \n", - " # Display configuration summary\n", - " print(f\"๐Ÿ“‹ Campaign Configuration Summary:\")\n", - " print(f\" Name: {campaign_json['name']}\")\n", - " print(f\" Description: {campaign_json['description'][:100]}...\")\n", - " if \"metadata\" in campaign_json:\n", - " metadata = campaign_json[\"metadata\"]\n", - " print(f\" Project Lead: {metadata.get('project_lead', 'N/A')}\")\n", - " print(f\" Institution: {metadata.get('institution', 'N/A')}\")\n", - " \n", - " # Create the campaign\n", - " campaign = create_campaign(\n", - " campaign_data=campaign_json,\n", - " token=token,\n", - " base_url=base_url\n", - " )\n", - " return campaign\n", - "\n", - "try:\n", - " campaign = load_and_create_campaign(\n", - " config_path=\"campaigns/campaign.json\",\n", - " token=token\n", - " ) \n", - " campaign_id = campaign['id']\n", - "except FileNotFoundError as e:\n", - " print(f\"โŒ Configuration file error: {e}\")\n", - " print(\"๐Ÿ’ก Please create a campaigns/campaign.json file with your campaign details\")\n", - "except ValueError as e:\n", - " print(f\"โŒ Configuration error: {e}\")\n", - "except Exception as e:\n", - " print(f\"โŒ Campaign creation failed: {e}\")\n" - ] - }, - { - "cell_type": "markdown", - "id": "2f364022", - "metadata": {}, - "source": [ - "### Creating Stations\n", - "\n", - "Once you have a campaign, you need to create stations within it. Stations represent specific monitoring locations where sensors collect data.\n", - "\n", - "#### Station Requirements\n", - "\n", - "**Required Fields:**\n", - "- `campaign_id`: ID of the parent campaign (must exist)\n", - "- `name`: Unique name for the monitoring station\n", - "- `description`: Details about the station location and purpose\n", - "- `latitude`: Decimal degrees (e.g., 30.2672)\n", - "- `longitude`: Decimal degrees (e.g., -97.7431)\n", - "\n", - "#### Station Best Practices\n", - "\n", - "๐Ÿ“ **Location Data:**\n", - "- Ensure coordinates are in decimal degrees format\n", - "- Use WGS84 coordinate system (standard GPS coordinates)\n", - "- Verify coordinates are accurate for your monitoring location\n", - "- Test coordinates in mapping software before creating stations\n", - "\n", - "๐Ÿท๏ธ **Station Naming:**\n", - "- Use descriptive names that indicate location or purpose\n", - "- Include geographic references or landmarks\n", - "- Examples: \"River Bridge Station\", \"Industrial District Monitor\"\n", - "\n", - "๐Ÿ“ **Station Descriptions:**\n", - "- Describe the physical location and surroundings\n", - "- Note any special characteristics or constraints\n", - "- Include installation details or access information\n", - "\n", - "#### Alternative: Web Interface for Stations\n", - "\n", - "If you prefer using the web interface:\n", - "\n", - "1. **Navigate to Campaign:**\n", - " - Go to your created campaign in the web portal\n", - " - Access the campaign details page\n", - "\n", - "2. **Create Station:**\n", - " - Go to the \"Stations\" section within the campaign\n", - " - Click \"Add Station\"\n", - " - Provide station details and coordinates\n", - " - Save to get your Station ID\n", - "\n", - "3. **Note the Station ID:**\n", - " - Copy the Station ID for use in data uploads\n", - "\n", - "\n", - "๐Ÿ’ก **Pro Tip:** Save your campaign and station IDs in a configuration file or notebook cell for easy reuse across multiple data uploads." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8ee3af6b", - "metadata": {}, - "outputs": [], - "source": [ - "def create_station(\n", - " station_data: Dict[str, Any],\n", - " campaign_id: int,\n", - " token: str,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Create a new station within a campaign.\n", - " \n", - " Args:\n", - " station_data: Dictionary containing station information\n", - " campaign_id: ID of the parent campaign\n", - " token: Authentication token\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Dictionary containing the created station data with ID\n", - " \"\"\"\n", - " url = f\"{base_url}/api/v1/campaigns/{campaign_id}/stations\" \n", - " response = make_authenticated_request(\n", - " method=\"POST\",\n", - " url=url,\n", - " token=token,\n", - " json=station_data\n", - " )\n", - " result = response.json()\n", - " print(f\"โœ… Station created successfully!\")\n", - " print(f\"Station ID: {result.get('id')}\")\n", - " print(f\"Station Name: {station_data.get('name')}\")\n", - " print(f\"Project ID: {station_data.get('projectid')}\")\n", - " print(f\"Contact: {station_data.get('contact_name')}\")\n", - " \n", - " return result\n", - "\n", - "def load_station_config(config_path: str = \"stations/station.json\") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Load station configuration from JSON file.\n", - " \n", - " Args:\n", - " config_path: Path to the station configuration JSON file \n", - " Returns:\n", - " Dictionary containing station configuration data\n", - " \"\"\"\n", - " try:\n", - " with open(config_path, 'r', encoding='utf-8') as file:\n", - " config = json.load(file)\n", - " return config\n", - " except FileNotFoundError:\n", - " raise FileNotFoundError(f\"Station config file not found: {config_path}\")\n", - " except json.JSONDecodeError as e:\n", - " raise ValueError(f\"Invalid JSON in station config file: {e}\")\n", - "\n", - "def load_and_create_station(\n", - " campaign_id: int,\n", - " config_path: str = \"stations/station.json\",\n", - " token: str = None,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Load station configuration from JSON and create the station.\n", - " \n", - " Args:\n", - " campaign_id: ID of the parent campaign\n", - " config_path: Path to the station configuration JSON file\n", - " token: Authentication token\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Dictionary containing the created station data with ID\n", - " \"\"\"\n", - " # Load configuration\n", - " station_config = load_station_config(config_path)\n", - " # Validate required fields\n", - " required_fields = [\"name\", \"projectid\", \"description\", \"contact_name\", \"contact_email\", \"active\", \"start_date\"]\n", - " for field in required_fields:\n", - " if field not in station_config:\n", - " raise ValueError(f\"Missing required field '{field}' in station config\")\n", - " # Display configuration summary\n", - " print(f\"๐Ÿ“‹ Station Configuration Summary:\")\n", - " print(f\" Name: {station_config['name']}\")\n", - " print(f\" Project ID: {station_config['projectid']}\")\n", - " print(f\" Description: {station_config['description'][:100]}...\")\n", - " print(f\" Contact: {station_config['contact_name']}\")\n", - " print(f\" Active: {station_config['active']}\")\n", - " print(f\" Start Date: {station_config['start_date']}\")\n", - " # Create the station\n", - " station = create_station(\n", - " station_data=station_config,\n", - " campaign_id=campaign_id,\n", - " token=token,\n", - " base_url=base_url\n", - " )\n", - " return station\n", - "\n", - "def load_and_create_multiple_stations(\n", - " campaign_id: int,\n", - " config_path: str = \"stations/stations.json\",\n", - " token: str = None,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> List[Dict[str, Any]]:\n", - " \"\"\"\n", - " Load multiple station configurations from JSON and create all stations.\n", - " Args:\n", - " campaign_id: ID of the parent campaign\n", - " config_path: Path to the stations configuration JSON file\n", - " token: Authentication token\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " List of dictionaries containing the created station data\n", - " \"\"\"\n", - " # Load configuration\n", - " with open(config_path, 'r', encoding='utf-8') as file:\n", - " stations_config = json.load(file)\n", - " created_stations = []\n", - " # Handle both single station and multiple stations format\n", - " if \"stations\" in stations_config:\n", - " station_list = stations_config[\"stations\"]\n", - " else:\n", - " station_list = [stations_config] # Single station format\n", - "\n", - " print(f\"๐Ÿ“‹ Creating {len(station_list)} station(s)...\")\n", - " \n", - " for i, station_config in enumerate(station_list, 1):\n", - " print(f\"\\n--- Creating Station {i}/{len(station_list)} ---\") \n", - " try:\n", - " station = create_station(\n", - " station_data=station_config,\n", - " campaign_id=campaign_id,\n", - " token=token,\n", - " base_url=base_url\n", - " )\n", - " created_stations.append(station)\n", - " \n", - " except Exception as e:\n", - " print(f\"โŒ Failed to create station '{station_config.get('name', 'Unknown')}': {e}\")\n", - " continue\n", - " \n", - " return created_stations" - ] - }, - { - "cell_type": "markdown", - "id": "0926cc6d", - "metadata": {}, - "source": [ - "## ๐Ÿ“ก Registering Environmental Monitoring Stations to CKAN\n", - "The next section walks you through the process of automating the registration of environmental monitoring stations to a CKAN data portal. By using this code, you're streamlining the workflow of:\n", - "\n", - "- ๐Ÿ” Authenticating with CKAN using a JWT token\n", - "\n", - "- ๐Ÿท๏ธ Creating datasets that represent sensor stations\n", - "\n", - "- ๐Ÿ“Ž Uploading metadata and resources such as sensor types, campaign info, and contact details\n", - "\n", - "- ๐Ÿ“ Organizing data for discoverability and reuse within research communities\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6e40e595", - "metadata": {}, - "outputs": [], - "source": [ - "def create_ckan_dataset(\n", - " jwt_token: str,\n", - " dataset_name: str,\n", - " title: str,\n", - " description: str,\n", - " tags: list = None,\n", - " owner_org: str = None,\n", - " ckan_url: str = \"https://ckan.tacc.utexas.edu\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Create a dataset (package) in CKAN to represent a station. \n", - " Args:\n", - " jwt_token: JWT authentication token\n", - " dataset_name: Unique dataset identifier (lowercase, no spaces)\n", - " title: Human-readable title\n", - " description: Dataset description\n", - " tags: List of tag names\n", - " owner_org: owner_org name/id\n", - " ckan_url: CKAN instance URL\n", - " \n", - " Returns:\n", - " CKAN API response\n", - " \"\"\"\n", - " \n", - " # Prepare dataset metadata\n", - " dataset_data = {\n", - " \"name\": dataset_name,\n", - " \"title\": title,\n", - " \"notes\": description,\n", - " \"tags\": [{\"name\": tag} for tag in (tags or [])],\n", - " \"private\": False,\n", - " \"type\": \"dataset\"\n", - " }\n", - " \n", - " dataset_data[\"owner_org\"] = owner_org\n", - " # CKAN API endpoint\n", - " api_url = f\"{ckan_url}/api/3/action/package_create\"\n", - " # Headers with JWT token\n", - " headers = {\n", - " \"Authorization\": f\"Bearer {tapis_token.access_token}\",\n", - " \"Content-Type\": \"application/json\"\n", - " }\n", - " try:\n", - " response = requests.post(\n", - " api_url,\n", - " headers=headers,\n", - " json=dataset_data\n", - " ) \n", - " response.raise_for_status()\n", - " result = response.json()\n", - " if result.get(\"success\"):\n", - " dataset_id = result[\"result\"][\"id\"]\n", - " dataset_url = f\"{ckan_url}/dataset/{dataset_name}\" \n", - " return result[\"result\"]\n", - " else:\n", - " print(f\"โŒ CKAN API returned error: {result}\")\n", - " raise Exception(f\"CKAN API error: {result}\")\n", - " \n", - " except requests.exceptions.RequestException as e:\n", - " print(f\"โŒ HTTP request failed: {e}\")\n", - " if hasattr(e, 'response') and e.response is not None:\n", - " print(f\" Response: {e.response.text}\")\n", - " raise\n", - " except Exception as e:\n", - " print(f\"โŒ Dataset creation failed: {e}\")\n", - " raise\n", - "\n", - "def register_station_to_ckan(\n", - " jwt_token:str,\n", - " station_name: str,\n", - " station_title: str,\n", - " station_description: str,\n", - " campaign_name: str = None,\n", - " sensor_types: list = None,\n", - " author:str=None,\n", - " author_email:str=None,\n", - " owner_org: str = None,\n", - " ckan_url: str = \"https://ckan.tacc.utexas.edu\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Complete workflow to register a station in CKAN.\n", - " Args:\n", - " username: Tapis username\n", - " password: Tapis password\n", - " station_name: Unique station identifier\n", - " station_title: Human-readable station title\n", - " station_description: Station description\n", - " campaign_name: Associated campaign name\n", - " location: Station location\n", - " sensor_types: List of sensor types at this station\n", - " owner_org: CKAN owner_org\n", - " ckan_url: CKAN instance URL\n", - " \n", - " Returns:\n", - " CKAN dataset information\n", - " \"\"\"\n", - " tags = []\n", - " if sensor_types:\n", - " tags.extend(sensor_types)\n", - " if campaign_name:\n", - " tags.append(f\"campaign-{campaign_name}\")\n", - " tags.extend([\"sensor-station\", \"environmental-data\", \"upstream\"])\n", - " # Enhanced description\n", - " enhanced_description = station_description\n", - " if campaign_name:\n", - " enhanced_description += f\"\\nCampaign: {campaign_name}\"\n", - " if sensor_types:\n", - " enhanced_description += f\"\\nSensor Types: {', '.join(sensor_types)}\"\n", - " # Step 3: Create CKAN dataset\n", - " print(\"3๏ธโƒฃ Creating CKAN dataset...\")\n", - " dataset = create_ckan_dataset(\n", - " jwt_token=jwt_token,\n", - " dataset_name=station_name,\n", - " title=station_title,\n", - " description=enhanced_description,\n", - " tags=tags,\n", - " owner_org=owner_org,\n", - " ckan_url=ckan_url\n", - " )\n", - " print(\"โœ… Station registration completed!\")\n", - " return dataset\n", - "\n", - "def add_resources_to_station(\n", - " jwt_token: str,\n", - " dataset_id: str,\n", - " resources: list,\n", - " ckan_url: str = \"https://ckan.tacc.utexas.edu\"\n", - ") -> list:\n", - " \"\"\"\n", - " Add data resources (files/URLs) to a station dataset.\n", - " Args:\n", - " jwt_token: JWT authentication token\n", - " dataset_id: CKAN dataset ID\n", - " resources: List of resource dictionaries\n", - " ckan_url: CKAN instance URL\n", - " \n", - " Returns:\n", - " List of created resources\n", - " \"\"\"\n", - " \n", - " api_url = f\"{ckan_url}/api/3/action/resource_create\"\n", - " headers = {\n", - " \"Authorization\": f\"Bearer {jwt_token}\",\n", - " \"Content-Type\": \"application/json\"\n", - " }\n", - "\n", - " created_resources = []\n", - " for resource in resources:\n", - " resource_data = {\n", - " \"package_id\": dataset_id,\n", - " **resource\n", - " }\n", - " print(f\"๐Ÿ“Ž Adding resource: {resource.get('name', 'Unnamed')}\")\n", - " try:\n", - " response = requests.post(\n", - " api_url,\n", - " headers=headers,\n", - " json=resource_data\n", - " )\n", - " response.raise_for_status()\n", - " result = response.json()\n", - " if result.get(\"success\"):\n", - " created_resources.append(result[\"result\"])\n", - " print(f\" โœ… Resource added: {result['result']['id']}\")\n", - " else:\n", - " print(f\" โŒ Failed to add resource: {result}\")\n", - " except Exception as e:\n", - " print(f\" โŒ Error adding resource: {e}\")\n", - " return created_resources\n", - "\n", - "# Load station metadata from JSON file\n", - "def load_station_metadata(json_file_path: str = \"stations/station.json\") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Load station metadata from JSON file.\n", - " \n", - " Args:\n", - " json_file_path: Path to the station JSON file\n", - " \n", - " Returns:\n", - " Station metadata dictionary\n", - " \"\"\"\n", - " try:\n", - " with open(json_file_path, 'r') as f:\n", - " station_data = json.load(f) \n", - " print(f\"๐Ÿ“‹ Loaded station metadata from {json_file_path}\")\n", - " print(f\" Station: {station_data.get('name', 'Unknown')}\")\n", - " print(f\" Project: {station_data.get('projectid', 'Unknown')}\")\n", - " print(f\" Active: {station_data.get('active', 'Unknown')}\")\n", - " return station_data\n", - " \n", - " except FileNotFoundError:\n", - " print(f\"โŒ Station metadata file not found: {json_file_path}\")\n", - " raise\n", - " except json.JSONDecodeError as e:\n", - " print(f\"โŒ Invalid JSON in station file: {e}\")\n", - " raise\n", - " except Exception as e:\n", - " print(f\"โŒ Error loading station metadata: {e}\")\n", - " raise\n", - "\n", - "def convert_station_metadata_for_ckan(station_data: Dict[str, Any]) -> Dict[str, Any]:\n", - " \"\"\"\n", - " Convert station metadata to CKAN-compatible format.\n", - " \n", - " Args:\n", - " station_data: Raw station metadata from JSON\n", - " \n", - " Returns:\n", - " CKAN-compatible station information\n", - " \"\"\"\n", - " \n", - " # Create CKAN-compatible dataset name (lowercase, no spaces, no special chars)\n", - " station_name = station_data.get('name', 'unknown-station')\n", - " ckan_name = station_name.lower().replace(' ', '-').replace('/', '-').replace('_', '-')\n", - " # Remove any remaining special characters\n", - " import re\n", - " ckan_name = re.sub(r'[^a-z0-9\\-]', '', ckan_name)\n", - " # Build enhanced description\n", - " description_parts = [station_data.get('description', 'Environmental monitoring station')]\n", - " if station_data.get('projectid'):\n", - " description_parts.append(f\"Project: {station_data['projectid']}\")\n", - " if station_data.get('contact_name'):\n", - " description_parts.append(f\"Contact: {station_data['contact_name']}\")\n", - " if station_data.get('contact_email'):\n", - " description_parts.append(f\"Email: {station_data['contact_email']}\")\n", - " if station_data.get('start_date'):\n", - " description_parts.append(f\"Start Date: {station_data['start_date']}\")\n", - " if station_data.get('active') is not None:\n", - " status = \"Active\" if station_data['active'] else \"Inactive\"\n", - " description_parts.append(f\"Status: {status}\")\n", - " enhanced_description = \"\\n\\n\".join(description_parts)\n", - " # Create tags from project and other metadata\n", - " tags = [\"environmental-monitoring\", \"upstream\", \"sensor-station\"]\n", - " if station_data.get('projectid'):\n", - " # Clean project ID for tag\n", - " project_tag = station_data['projectid'].lower().replace(' ', '-').replace('_', '-')\n", - " project_tag = re.sub(r'[^a-z0-9\\-]', '', project_tag)\n", - " tags.append(f\"project-{project_tag}\")\n", - " return( {\n", - " \"station_name\": ckan_name,\n", - " \"station_title\": station_data.get('name', 'Unknown Station'),\n", - " \"station_description\": enhanced_description,\n", - " \"campaign_name\": station_data.get('projectid'),\n", - " \"owner_org\":\"setx-uifl\",\n", - " \"author\":station_data.get('contact_name'),\n", - " \"author_email\":station_data.get('contact_email'),\n", - " \"sensor_types\": [\"water-level\", \"stream-gauge\"], # Inferred from description\n", - " \"raw_metadata\": station_data # Keep original data for reference\n", - " })" - ] - }, - { - "cell_type": "markdown", - "id": "7ceeb4cf", - "metadata": {}, - "source": [ - "## โš™๏ธ Running the Station Registration Workflow\n", - "\n", - "This section of the code provides **two options** for registering environmental monitoring stations to CKAN, based on your configuration files:\n", - "\n", - "### ๐Ÿงช Create a Single Station\n", - "\n", - "If you're working with **one station at a time**, this block reads a single configuration file (`stations/station.json`) and walks through the entire registration process:\n", - "\n", - "- Loads metadata \n", - "- Formats it for CKAN \n", - "- Registers the station as a dataset \n", - "- Returns a station ID upon success\n", - "\n", - "๐Ÿ’ก *Useful when you're testing or onboarding new stations one by one.*\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 0, - "id": "e3f0d1ed", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "=== Creating Single Station from Configuration ===\n", - "๐Ÿ“„ Loaded station config from: stations/station.json\n", - "๐Ÿ“‹ Station Configuration Summary:\n", - " Name: Cow Bayou near Mauriceville\n", - " Project ID: SETx-UIFL Beaumont\n", - " Description: Beaumont Run stream gauge at Cow Bayou...\n", - " Contact: Nick Brake\n", - " Active: True\n", - " Start Date: 2025-06-02T14:42:00+0000\n", - "โœ… Station created successfully!\n", - "Station ID: 39\n", - "Station Name: Cow Bayou near Mauriceville\n", - "Project ID: SETx-UIFL Beaumont\n", - "Contact: Nick Brake\n", - "\n", - "๐ŸŽ‰ Station setup complete!\n", - "Station ID: 39\n", - "\n", - "==================================================\n", - "=== Creating Multiple Stations from Configuration ===\n", - "๐Ÿ“‹ Creating 2 station(s)...\n", - "\n", - "--- Creating Station 1/2 ---\n", - "โœ… Station created successfully!\n", - "Station ID: 40\n", - "Station Name: Cow Bayou near Mauriceville\n", - "Project ID: SETx-UIFL Beaumont\n", - "Contact: Nick Brake\n", - "\n", - "--- Creating Station 2/2 ---\n", - "โœ… Station created successfully!\n", - "Station ID: 41\n", - "Station Name: Pine Island Bayou near Sour Lake\n", - "Project ID: SETx-UIFL Beaumont\n", - "Contact: Nick Brake\n", - "\n", - "๐ŸŽ‰ Created 2 station(s) successfully!\n", - " โ€ข Unknown (ID: 40)\n", - " โ€ข Unknown (ID: 41)\n" - ] - } - ], - "source": [ - "try:\n", - " station = load_and_create_station(\n", - " campaign_id=campaign_id,\n", - " config_path=\"stations/station.json\",\n", - " token=token\n", - " ) \n", - " station_id = station['id']\n", - "except FileNotFoundError as e:\n", - " print(f\"โŒ Configuration file error: {e}\")\n", - " print(\"๐Ÿ’ก Please create a stations/station.json file with your station details\")\n", - "except ValueError as e:\n", - " print(f\"โŒ Configuration error: {e}\")\n", - "except Exception as e:\n", - " print(f\"โŒ Station creation failed: {e}\")" - ] - }, - { - "cell_type": "markdown", - "id": "c5f615a0", - "metadata": {}, - "source": [ - "### ๐Ÿงฉ Create Multiple Stations\n", - "\n", - "Need to register **several stations at once**? This block processes a configuration file (`stations/stations.json`) containing a list of station definitions. It will:\n", - "\n", - "- Loop through each station entry \n", - "- Run the registration process for each \n", - "- Report success or failure for individual stations\n", - "\n", - "๐Ÿ’ก *Great for batch imports or syncing an entire sensor network in one go.*\n", - "\n", - "Both workflows include helpful print statements and error handling to guide you through common issues โ€” such as missing files or malformed configs.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 0, - "id": "9f9bb5e8", - "metadata": {}, - "outputs": [], - "source": [ - "try:\n", - " stations = load_and_create_multiple_stations(\n", - " campaign_id=campaign_id,\n", - " config_path=\"stations/stations.json\",\n", - " token=token\n", - " ) \n", - "except FileNotFoundError as e:\n", - " print(f\"โŒ Configuration file error: {e}\")\n", - " print(\"๐Ÿ’ก Please create a stations/stations.json file with your station details\")\n", - "except Exception as e:\n", - " print(f\"โŒ Multiple stations creation failed: {e}\")" - ] - }, - { - "cell_type": "markdown", - "id": "117c47c1", - "metadata": {}, - "source": [ - "# ๐Ÿ›ฐ๏ธ Station Registration & Resource Publishing Guide\n", - "\n", - "This document guides you through the registration of a station and the publication of its associated metadata and resources into a CKAN data portal.\n", - "\n", - "---\n", - "\n", - "## 1๏ธโƒฃ Load Station Metadata\n", - "\n", - "Begin by loading your station's configuration from a local JSON file.\n", - "\n", - "- **File:** `./stations/station.json`\n", - "- **Expected Fields:**\n", - " - `name`\n", - " - `projectid`\n", - " - `contact_name`\n", - " - `contact_email`\n", - " - `start_date`\n", - " - ...and other relevant metadata\n", - "\n", - "---\n", - "\n", - "## 2๏ธโƒฃ Convert Metadata to CKAN Format\n", - "\n", - "Transform the raw station metadata into the format expected by CKAN. This typically includes:\n", - "\n", - "- `station_name`: A machine-readable slug (e.g., `lake-travis-buoy`)\n", - "- `station_title`: A human-readable title\n", - "- `campaign_name`: Associated research campaign\n", - "- `tags`, `groups`, bounding boxes, and other CKAN-compatible fields\n", - "\n", - "---\n", - "\n", - "## 3๏ธโƒฃ Register Station in CKAN\n", - "\n", - "Use your Tapis JWT token to register the station with CKAN.\n", - "\n", - "- โœ… **Dataset ID**\n", - "- โœ… **Dataset Name**\n", - "- โœ… **CKAN URL** \n", - " Format: `https://ckan.tacc.utexas.edu/dataset/`\n", - "\n", - "---\n", - "\n", - "## 4๏ธโƒฃ Add Station Resources\n", - "\n", - "Add data endpoints and visualizations as resources to enrich the dataset.\n", - "\n", - "### ๐Ÿ”— Base Resources\n", - "\n", - "- **Station Information** \n", - " > Full metadata & configuration for this station \n", - " `JSON` - `/api/v1/campaigns//stations/`\n", - "\n", - "- **All Station Sensors** \n", - " > List of all sensors deployed at the station \n", - " `JSON` - `/api/v1/campaigns//stations//sensors`\n", - "\n", - "- **All Sensors and Visualizations** \n", - " > Frontend dashboard for sensors and charts \n", - " `Website` - `https://dso-tacc.netlify.app/campaigns//stations/`\n", - "\n", - "- **Aggregated Statistics** \n", - " > Time-aggregated measurements with statistical analysis \n", - " `JSON` - `/api/v1/campaigns//stations//measurements/aggregated`\n", - "\n", - "---\n", - "\n", - "### ๐Ÿงพ Optional: Contact Information\n", - "\n", - "If `contact_name` or `contact_email` is provided in the JSON, a text-based resource is added:\n", - "\n", - "**Contact Information**\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "45d89de8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1๏ธโƒฃ Loading station metadata from JSON...\n", - "๐Ÿ“‹ Loaded station metadata from ./stations/station.json\n", - " Station: Cow Bayou near Mauriceville\n", - " Project: SETx-UIFL Beaumont\n", - " Active: True\n", - "2๏ธโƒฃ Converting metadata for CKAN...\n", - " CKAN Dataset Name: cow-bayou-near-mauriceville\n", - " Title: Cow Bayou near Mauriceville\n", - " Campaign: SETx-UIFL Beaumont\n", - "3๏ธโƒฃ Registering station to CKAN...\n", - "============================================================\n", - "๐Ÿš€ REGISTERING STATION TO CKAN\n", - "============================================================\n", - "3๏ธโƒฃ Creating CKAN dataset...\n", - "๐Ÿ—๏ธ Creating CKAN dataset: cow-bayou-near-mauriceville\n", - " Title: Cow Bayou near Mauriceville\n", - " URL: https://ckan.tacc.utexas.edu/api/3/action/package_create\n", - "โœ… Dataset created successfully!\n", - " Dataset ID: e6c2acb7-99a4-44ad-9935-d220874dd10c\n", - " Dataset URL: https://ckan.tacc.utexas.edu/dataset/cow-bayou-near-mauriceville\n", - "โœ… Station registration completed!\n", - "\n", - "๐ŸŽ‰ Station registered successfully!\n", - "Dataset ID: e6c2acb7-99a4-44ad-9935-d220874dd10c\n", - "Dataset Name: cow-bayou-near-mauriceville\n", - "Dataset URL: https://ckan.tacc.utexas.edu/dataset/cow-bayou-near-mauriceville\n", - "\n", - "4๏ธโƒฃ Adding data resources...\n", - "๐Ÿ“Ž Adding resource: Station Information\n", - " โœ… Resource added: e4d9fe1e-7049-498c-945e-5ddfaf1f59e7\n", - "๐Ÿ“Ž Adding resource: All Station Sensors\n", - " โœ… Resource added: a085396d-e08b-40ef-ae11-d637c34cf64e\n", - "๐Ÿ“Ž Adding resource: All Sensors and Visualizations\n", - " โœ… Resource added: 81fb74f5-8b16-4dc2-abe5-5f78946dc33f\n", - "๐Ÿ“Ž Adding resource: Aggregated Statistics\n", - " โœ… Resource added: 6d9b705d-f8f4-4ba7-bc41-1aed5da88c6d\n", - "๐Ÿ“Ž Adding resource: Contact Information\n", - " โœ… Resource added: 0a6721be-f56f-47b1-bd13-ba40c914a188\n", - "\n", - "๐Ÿ“Š Added 5 resources to station\n", - "\n", - "============================================================\n", - "๐Ÿ“‹ REGISTRATION SUMMARY\n", - "============================================================\n", - "Station Name: Cow Bayou near Mauriceville\n", - "Project: SETx-UIFL Beaumont\n", - "CKAN Dataset: cow-bayou-near-mauriceville\n", - "Dataset URL: https://ckan.tacc.utexas.edu/dataset/cow-bayou-near-mauriceville\n", - "Contact: Nick Brake\n", - "Status: Active\n", - "Resources Added: 5\n" - ] - } - ], - "source": [ - "# Load station metadata from JSON file\n", - "raw_station_data = load_station_metadata(\"./stations/station.json\")\n", - "\n", - "# Convert to CKAN format\n", - "station_info = convert_station_metadata_for_ckan(raw_station_data)\n", - "\n", - "# Register the station\n", - "dataset = register_station_to_ckan(\n", - "jwt_token=tapis_token.access_token,\n", - " **{k: v for k, v in station_info.items() if k != 'raw_metadata'}\n", - ")\n", - "\n", - "# Get JWT token again (in case it expired)\n", - "jwt_token = tapis_token.access_token\n", - "station_name = raw_station_data.get('name', 'this station')\n", - "base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - "\n", - "# Base station resources\n", - "resources = [\n", - " {\n", - " \"name\": \"Station Information\",\n", - " \"description\": f\"Complete station metadata and configuration for {station_name}\",\n", - " \"format\": \"JSON\",\n", - " \"url\": f\"{base_url}/api/v1/campaigns/{campaign_id}/stations/{station_id}\"\n", - " },\n", - " {\n", - " \"name\": \"All Station Sensors\",\n", - " \"description\": f\"Complete list of sensors deployed at {station_name}\",\n", - " \"format\": \"JSON\",\n", - " \"url\": f\"{base_url}/api/v1/campaigns/{campaign_id}/stations/{station_id}/sensors\"\n", - " },\n", - " {\n", - " \"name\": \"All Sensors and Visualizations\",\n", - " \"description\": f\"All Sensors and Visualizations from {station_name} (paginated)\",\n", - " \"format\": \"Website\",\n", - " \"url\": f\"https://dso-tacc.netlify.app/campaigns/{campaign_id}/stations/{station_id}\"\n", - " },\n", - " {\n", - " \"name\": \"Aggregated Statistics\",\n", - " \"description\": f\"Time-aggregated measurements with statistical analysis from {station_name}\",\n", - " \"format\": \"JSON\",\n", - " \"url\": f\"{base_url}/api/v1/campaigns/{campaign_id}/stations/{station_id}/measurements/aggregated\"\n", - " }\n", - " ]\n", - "# Add contact information as a resource if available\n", - "if raw_station_data.get('contact_name') or raw_station_data.get('contact_email'):\n", - " contact_info = {\n", - " \"name\": \"Contact Information\",\n", - " \"description\": \"Station contact and project information\",\n", - " \"format\": \"TEXT\"\n", - " }\n", - " contact_text = f\"Station Contact Information\\n\"\n", - " contact_text += f\"Station: {raw_station_data.get('name', 'Unknown')}\\n\"\n", - " contact_text += f\"Project: {raw_station_data.get('projectid', 'Unknown')}\\n\"\n", - " if raw_station_data.get('contact_name'):\n", - " contact_text += f\"Contact Name: {raw_station_data['contact_name']}\\n\"\n", - " if raw_station_data.get('contact_email'):\n", - " contact_text += f\"Contact Email: {raw_station_data['contact_email']}\\n\"\n", - " if raw_station_data.get('start_date'):\n", - " contact_text += f\"Start Date: {raw_station_data['start_date']}\\n\"\n", - " # For this example, we'll add it as a URL (you might want to upload as a file instead)\n", - " resources.append(contact_info)\n", - "\n", - "created_resources = add_resources_to_station(\n", - " jwt_token=jwt_token,\n", - " dataset_id=dataset['id'],\n", - " resources=resources\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "593ba293", - "metadata": {}, - "source": [ - "## CSV Data Upload Function Documentation\n", - "\n", - "### Overview\n", - "\n", - "The `upload_csv_data` function provides a streamlined way to upload sensor and measurement data to the Upstream platform via CSV files. This function handles file validation, authentication, and provides detailed feedback on the upload process.\n", - "\n", - "\n", - "### Parameters\n", - "\n", - "| Parameter | Type | Required | Description |\n", - "|-----------|------|----------|-------------|\n", - "| `campaign_id` | `int` | โœ… | Unique identifier for the target campaign |\n", - "| `station_id` | `int` | โœ… | Unique identifier for the target station within the campaign |\n", - "| `sensors_file_path` | `str` | โœ… | Local file path to the sensors CSV file |\n", - "| `measurements_file_path` | `str` | โœ… | Local file path to the measurements CSV file |\n", - "| `token` | `str` | โœ… | Authentication token for API access |\n", - "| `base_url` | `str` | โŒ | Base URL for the Upstream API (defaults to dev environment) |\n", - "\n", - "### Return Value\n", - "\n", - "Returns a `Dict[str, Any]` containing the upload response data with statistics including:\n", - "- Total sensors processed\n", - "- Total measurements added to database\n", - "- Data processing time\n", - "\n", - "### Features\n", - "\n", - "#### ๐Ÿ” **File Validation**\n", - "- Automatically checks if both CSV files exist before attempting upload\n", - "- Raises `FileNotFoundError` with descriptive messages for missing files\n", - "\n", - "#### ๐Ÿ“Š **Progress Tracking**\n", - "- Displays upload parameters for verification\n", - "- Shows real-time upload status with emoji indicators\n", - "- Provides detailed statistics upon completion\n", - "\n", - "#### ๐Ÿ” **Secure Upload**\n", - "- Uses authenticated requests via the `make_authenticated_request` helper\n", - "- Properly formats files for multipart form data upload\n", - "\n", - "#### ๐ŸŽฏ **Error Handling**\n", - "- Pre-upload file existence validation\n", - "- Clear error messages for troubleshooting\n", - "\n", - "### API Endpoint\n", - "\n", - "The function uploads to the following endpoint:\n", - "```\n", - "POST {base_url}/api/v1/uploadfile_csv/campaign/{campaign_id}/station/{station_id}/sensor\n", - "```\n", - "\n", - "### File Format Requirements\n", - "\n", - "#### Sensors CSV\n", - "- Must contain sensor definition data\n", - "- Uploaded as `upload_file_sensors` form field\n", - "\n", - "#### Measurements CSV \n", - "- Must contain measurement data corresponding to the sensors\n", - "- Uploaded as `upload_file_measurements` form field\n", - "\n", - "### Console Output Example\n", - "\n", - "```\n", - "=== Uploading CSV Data ===\n", - "Campaign ID: 123\n", - "Station ID: 456\n", - "Sensors file: ./data/sensors.csv\n", - "Measurements file: ./data/measurements.csv\n", - "๐Ÿ“ค Uploading files...\n", - "โœ… Upload completed successfully!\n", - "๐Ÿ“Š Upload Statistics:\n", - " โ€ข Sensors processed: 15\n", - " โ€ข Measurements added: 1,250\n", - " โ€ข Processing time: 2.3s\n", - "```\n", - "\n", - "### Dependencies\n", - "\n", - "- `os` - For file existence checking\n", - "- `make_authenticated_request` - Custom function for authenticated API calls\n", - "- `Dict`, `Any` from `typing` - For type hints\n", - "\n", - "### Error Scenarios\n", - "\n", - "| Error Type | Cause | Solution |\n", - "|------------|-------|----------|\n", - "| `FileNotFoundError` | CSV file doesn't exist at specified path | Verify file paths are correct |\n", - "| Authentication errors | Invalid or expired token | Refresh authentication token |\n", - "| API errors | Server issues or invalid parameters | Check campaign/station IDs and API status |\n", - "\n", - "### Best Practices\n", - "\n", - "1. **Validate Data First**: Ensure your CSV files are properly formatted before upload\n", - "2. **Check Permissions**: Verify you have write access to the specified campaign/station\n", - "3. **Monitor Output**: Pay attention to the upload statistics to confirm expected data volumes\n", - "4. **Handle Errors**: Always wrap calls in try-catch blocks for production use\n", - "5. **Use Absolute Paths**: Prefer absolute file paths to avoid path resolution issues\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bee3ba22-8018-4d8d-86ed-04fb62ebc6b1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "=== Listing Available Data Files ===\n", - "๐Ÿ“ Files found in ./data/:\n", - " โ€ข Total CSV files: 2\n", - " โ€ข Sensor files: 1\n", - " โ€ข Measurement files: 1\n", - "๐Ÿ“„ All CSV files:\n", - " - measurements.csv (906,949 bytes)\n", - " - sensors.csv (173 bytes)\n", - "\n", - "==================================================\n", - "=== Uploading CSV Data (Standard Method) ===\n", - "=== Uploading CSV Data ===\n", - "Campaign ID: 12\n", - "Station ID: 39\n", - "Data Directory: ./data/\n", - "Sensors file: ./data/sensors.csv\n", - "Measurements file: ./data/measurements.csv\n", - "๐Ÿ“ File Information:\n", - " โ€ข Sensors file size: 173 bytes\n", - " โ€ข Measurements file size: 906,949 bytes\n", - "๐Ÿ“ค Uploading files...\n", - "โœ… Upload completed successfully!\n", - "๐Ÿ“Š Upload Statistics:\n", - " โ€ข Sensors processed: 3\n", - " โ€ข Measurements added: 26881\n", - " โ€ข Processing time: 9.2 seconds.\n", - "\n", - "๐ŸŽ‰ Data upload complete!\n", - "\n", - "==================================================\n", - "=== Uploading CSV Data (Auto-Detection Method) ===\n", - "=== Auto-detecting Data Files ===\n", - "๐Ÿ“ Files found in ./data/:\n", - " โ€ข Total CSV files: 2\n", - " โ€ข Sensor files: 1\n", - " โ€ข Measurement files: 1\n", - "๐Ÿ“„ All CSV files:\n", - " - measurements.csv (906,949 bytes)\n", - " - sensors.csv (173 bytes)\n", - "=== Uploading CSV Data ===\n", - "Campaign ID: 12\n", - "Station ID: 39\n", - "Data Directory: ./data/\n", - "Sensors file: ./data/sensors.csv\n", - "Measurements file: ./data/measurements.csv\n", - "๐Ÿ“ File Information:\n", - " โ€ข Sensors file size: 173 bytes\n", - " โ€ข Measurements file size: 906,949 bytes\n", - "๐Ÿ“ค Uploading files...\n", - "โœ… Upload completed successfully!\n", - "๐Ÿ“Š Upload Statistics:\n", - " โ€ข Sensors processed: 3\n", - " โ€ข Measurements added: 0\n", - " โ€ข Processing time: 8.3 seconds.\n", - "\n", - "๐ŸŽ‰ Auto-detected data upload complete!\n" - ] - } - ], - "source": [ - "import glob\n", - "import os\n", - "from pathlib import Path\n", - "\n", - "def upload_csv_data(\n", - " campaign_id: int,\n", - " station_id: int,\n", - " token: str,\n", - " data_dir: str = \"./data/\",\n", - " author:str=None,\n", - " author_email:str=None,\n", - " sensors_filename: str = \"sensors.csv\",\n", - " measurements_filename: str = \"measurements.csv\",\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Upload sensor and measurement CSV files to Upstream from data directory.\n", - " \n", - " Args:\n", - " campaign_id: ID of the target campaign\n", - " station_id: ID of the target station\n", - " token: Access token\n", - " data_dir: Directory containing CSV files (default: \"./data/\")\n", - " sensors_filename: Name of sensors CSV file (default: \"sensors.csv\")\n", - " measurements_filename: Name of measurements CSV file (default: \"measurements.csv\")\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Upload response data\n", - " \"\"\"\n", - " # Construct file paths\n", - " sensors_file_path = os.path.join(data_dir, sensors_filename)\n", - " measurements_file_path = os.path.join(data_dir, measurements_filename) \n", - " upload_url = f\"{base_url}/api/v1/uploadfile_csv/campaign/{campaign_id}/station/{station_id}/sensor\"\n", - " print(f\"=== Uploading CSV Data ===\")\n", - " print(f\"Campaign ID: {campaign_id}\")\n", - " print(f\"Station ID: {station_id}\")\n", - " print(f\"Data Directory: {data_dir}\")\n", - " print(f\"Sensors file: {sensors_file_path}\")\n", - " print(f\"Measurements file: {measurements_file_path}\")\n", - " # Verify files exist\n", - " if not os.path.exists(sensors_file_path):\n", - " raise FileNotFoundError(f\"Sensors file not found: {sensors_file_path}\")\n", - " if not os.path.exists(measurements_file_path):\n", - " raise FileNotFoundError(f\"Measurements file not found: {measurements_file_path}\")\n", - " # Display file information\n", - " sensors_size = os.path.getsize(sensors_file_path)\n", - " measurements_size = os.path.getsize(measurements_file_path)\n", - " print(f\"๐Ÿ“ File Information:\")\n", - " print(f\" โ€ข Sensors file size: {sensors_size:,} bytes\")\n", - " print(f\" โ€ข Measurements file size: {measurements_size:,} bytes\")\n", - " \n", - " # Prepare files for upload\n", - " with open(sensors_file_path, 'rb') as sensors_file, \\\n", - " open(measurements_file_path, 'rb') as measurements_file:\n", - " files = {\n", - " 'upload_file_sensors': (sensors_filename, sensors_file, 'text/csv'),\n", - " 'upload_file_measurements': (measurements_filename, measurements_file, 'text/csv')\n", - " }\n", - " print(\"๐Ÿ“ค Uploading files...\")\n", - " response = make_authenticated_request(\n", - " method=\"POST\",\n", - " url=upload_url,\n", - " token=token,\n", - " files=files\n", - " )\n", - " result = response.json()\n", - " print(\"โœ… Upload completed successfully!\")\n", - " # Display upload statistics\n", - " print(f\"๐Ÿ“Š Upload Statistics:\")\n", - " print(f\" โ€ข Sensors processed: {result.get('Total sensors processed', 'N/A')}\")\n", - " print(f\" โ€ข Measurements added: {result.get('Total measurements added to database', 'N/A')}\")\n", - " print(f\" โ€ข Processing time: {result.get('Data Processing time', 'N/A')}\")\n", - " return result\n", - "\n", - "def list_data_files(data_dir: str = \"./data/\") -> Dict[str, list]:\n", - " \"\"\"\n", - " List all CSV files in the data directory.\n", - " \n", - " Args:\n", - " data_dir: Directory to search for CSV files\n", - " \n", - " Returns:\n", - " Dictionary with lists of found files\n", - " \"\"\"\n", - " if not os.path.exists(data_dir):\n", - " print(f\"โŒ Data directory not found: {data_dir}\")\n", - " return {\"csv_files\": [], \"sensors_files\": [], \"measurements_files\": []}\n", - " \n", - " # Find all CSV files\n", - " csv_pattern = os.path.join(data_dir, \"*.csv\")\n", - " csv_files = glob.glob(csv_pattern)\n", - " \n", - " # Categorize files\n", - " sensors_files = [f for f in csv_files if 'sensor' in os.path.basename(f).lower()]\n", - " measurements_files = [f for f in csv_files if 'measurement' in os.path.basename(f).lower()]\n", - " \n", - " print(f\"๐Ÿ“ Files found in {data_dir}:\")\n", - " print(f\" โ€ข Total CSV files: {len(csv_files)}\")\n", - " print(f\" โ€ข Sensor files: {len(sensors_files)}\")\n", - " print(f\" โ€ข Measurement files: {len(measurements_files)}\")\n", - " \n", - " if csv_files:\n", - " print(f\"๐Ÿ“„ All CSV files:\")\n", - " for file in csv_files:\n", - " size = os.path.getsize(file)\n", - " print(f\" - {os.path.basename(file)} ({size:,} bytes)\")\n", - " \n", - " return {\n", - " \"csv_files\": csv_files,\n", - " \"sensors_files\": sensors_files,\n", - " \"measurements_files\": measurements_files\n", - " }\n", - "\n", - "def upload_data_with_auto_detection(\n", - " campaign_id: int,\n", - " station_id: int,\n", - " token: str,\n", - " data_dir: str = \"./data/\",\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Upload CSV data with automatic file detection.\n", - " \n", - " Args:\n", - " campaign_id: ID of the target campaign\n", - " station_id: ID of the target station\n", - " token: Access token\n", - " data_dir: Directory containing CSV files\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Upload response data\n", - " \"\"\"\n", - " print(\"=== Auto-detecting Data Files ===\")\n", - " files_info = list_data_files(data_dir)\n", - " # Try to find sensors and measurements files\n", - " sensors_file = None\n", - " measurements_file = None\n", - " # Look for standard filenames first\n", - " standard_sensors = os.path.join(data_dir, \"sensors.csv\")\n", - " standard_measurements = os.path.join(data_dir, \"measurements.csv\")\n", - " if os.path.exists(standard_sensors):\n", - " sensors_file = \"sensors.csv\"\n", - " elif files_info[\"sensors_files\"]:\n", - " sensors_file = os.path.basename(files_info[\"sensors_files\"][0])\n", - " print(f\"๐Ÿ” Using detected sensors file: {sensors_file}\")\n", - " if os.path.exists(standard_measurements):\n", - " measurements_file = \"measurements.csv\"\n", - " elif files_info[\"measurements_files\"]:\n", - " measurements_file = os.path.basename(files_info[\"measurements_files\"][0])\n", - " print(f\"๐Ÿ” Using detected measurements file: {measurements_file}\")\n", - " \n", - " if not sensors_file or not measurements_file:\n", - " raise FileNotFoundError(\n", - " f\"Could not find required files. \"\n", - " f\"Sensors: {sensors_file}, Measurements: {measurements_file}\"\n", - " )\n", - " \n", - " # Upload the files\n", - " return upload_csv_data(\n", - " campaign_id=campaign_id,\n", - " station_id=station_id,\n", - " token=token,\n", - " data_dir=data_dir,\n", - " sensors_filename=sensors_file,\n", - " measurements_filename=measurements_file,\n", - " base_url=base_url\n", - " )\n", - "\n", - "# Usage examples\n", - "data_files = list_data_files(\"./data/\")\n", - "try:\n", - " # Upload using standard filenames\n", - " result = upload_csv_data(\n", - " campaign_id=campaign_id,\n", - " station_id=station_id,\n", - " token=token,\n", - " data_dir=\"./data/\",\n", - " sensors_filename=\"sensors.csv\",\n", - " measurements_filename=\"measurements.csv\"\n", - " )\n", - "except FileNotFoundError as e:\n", - " print(f\"โŒ File error: {e}\")\n", - " print(\"๐Ÿ’ก Make sure your CSV files are in the ./data/ directory\")\n", - "except Exception as e:\n", - " print(f\"โŒ Upload failed: {e}\")\n", - "try:\n", - " # Upload with automatic file detection\n", - " result = upload_data_with_auto_detection(\n", - " campaign_id=campaign_id,\n", - " station_id=station_id,\n", - " token=token,\n", - " data_dir=\"./data/\"\n", - " ) \n", - "except FileNotFoundError as e:\n", - " print(f\"โŒ File detection error: {e}\")\n", - " print(\"๐Ÿ’ก Make sure your CSV files are in the ./data/ directory with 'sensor' and 'measurement' in their names\")\n", - "except Exception as e:\n", - " print(f\"โŒ Auto-upload failed: {e}\")\n" - ] - }, - { - "cell_type": "markdown", - "id": "88c765ce", - "metadata": {}, - "source": [ - "### CSV File Format Examples\n", - "\n", - "#### Sensors CSV Format\n", - "\n", - "Your `sensors.csv` file defines the sensor metadata and should follow this structure:\n", - "\n", - "```csv\n", - "alias,variablename,units,postprocess,postprocessscript\n", - "temp_sensor_01,Air Temperature,ยฐC,,\n", - "humidity_01,Relative Humidity,%,,\n", - "pressure_01,Atmospheric Pressure,hPa,,\n", - "wind_speed_01,Wind Speed,m/s,true,wind_correction_script\n", - "```\n", - "\n", - "**Column Descriptions:**\n", - "- `alias`: Unique identifier for the sensor (used as column header in measurements)\n", - "- `variablename`: Human-readable description of what the sensor measures\n", - "- `units`: Measurement units (e.g., ยฐC, %, hPa, m/s)\n", - "- `postprocess`: Boolean flag indicating if post-processing is required\n", - "- `postprocessscript`: Name of the post-processing script (if applicable)\n", - "\n", - "#### Measurements CSV Format\n", - "\n", - "Your `measurements.csv` file contains the actual sensor data and should follow this structure:\n", - "\n", - "```csv\n", - "collectiontime,Lat_deg,Lon_deg,temp_sensor_01,humidity_01,pressure_01,wind_speed_01\n", - "2024-01-15T10:30:00,30.2672,-97.7431,23.5,65.2,1013.25,2.3\n", - "2024-01-15T10:31:00,30.2673,-97.7432,23.7,64.8,1013.20,2.1\n", - "2024-01-15T10:32:00,30.2674,-97.7433,23.9,64.5,1013.15,1.8\n", - "2024-01-15T10:33:00,30.2675,-97.7434,,64.2,1013.10,1.9\n", - "```\n", - "\n", - "**Required Columns:**\n", - "- `collectiontime`: Timestamp in ISO 8601 format (YYYY-MM-DDTHH:MM:SS)\n", - "- `Lat_deg`: Latitude in decimal degrees\n", - "- `Lon_deg`: Longitude in decimal degrees\n", - "\n", - "**Sensor Data Columns:**\n", - "- Each sensor `alias` from sensors.csv becomes a column header\n", - "- Column names must exactly match the sensor aliases\n", - "- Empty values are automatically handled (see row 4 in example)\n", - "\n", - "#### Important File Format Notes\n", - "\n", - "โš ๏ธ **Critical Requirements:**\n", - "- Each sensor `alias` from sensors.csv becomes a column in measurements.csv\n", - "- `collectiontime`, `Lat_deg`, and `Lon_deg` are required columns in measurements.csv\n", - "- Empty values are handled automatically by the system\n", - "- Maximum file size is **500 MB per file**\n", - "- Use UTF-8 encoding for both files\n", - "- Timestamps should be in UTC or include timezone information\n", - "\n", - "๐Ÿ“ **Best Practices:**\n", - "- Keep sensor aliases short but descriptive\n", - "- Use consistent naming conventions (e.g., `sensor_type_number`)\n", - "- Ensure measurement values match the units specified in sensors.csv\n", - "- Include all sensors in measurements.csv even if some readings are missing\n", - "\n", - "\n", - "#### Helper Function Features\n", - "\n", - "๐Ÿ” **Campaign Discovery:**\n", - "- List all campaigns you have access to\n", - "- View campaign metadata and descriptions\n", - "- Identify the correct campaign ID for your data\n", - "\n", - "๐Ÿ—๏ธ **Station Management:**\n", - "- List all stations within a campaign\n", - "- View station details and locations\n", - "- Find the appropriate station ID for your sensors\n", - "\n", - "๐Ÿ’ก **Integration Tip:**\n", - "Use these helper functions before uploading data to ensure you're targeting the correct campaign and station IDs.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "062450c2", - "metadata": {}, - "outputs": [], - "source": [ - "import glob\n", - "import os\n", - "import pandas as pd\n", - "import tempfile\n", - "import shutil\n", - "from pathlib import Path\n", - "from typing import Dict, Any, List, Optional\n", - "import time\n", - "import math\n", - "\n", - "def get_file_info(file_path: str) -> Dict[str, Any]:\n", - " \"\"\"Get detailed information about a CSV file.\"\"\"\n", - " if not os.path.exists(file_path):\n", - " return {}\n", - " \n", - " file_size = os.path.getsize(file_path) \n", - " # Count rows efficiently\n", - " with open(file_path, 'r', encoding='utf-8') as f:\n", - " row_count = sum(1 for line in f) - 1 # Subtract header row\n", - " return {\n", - " 'size_bytes': file_size,\n", - " 'size_mb': file_size / (1024 * 1024),\n", - " 'row_count': row_count,\n", - " 'estimated_chunk_count': lambda chunk_size: math.ceil(row_count / chunk_size)\n", - " }\n", - "\n", - "def create_csv_chunks(\n", - " file_path: str,\n", - " chunk_size: int = 10000,\n", - " output_dir: Optional[str] = None,\n", - " max_file_size_mb: int = 50\n", - ") -> List[str]:\n", - " \"\"\"\n", - " Split a large CSV file into smaller chunks.\n", - " \n", - " Args:\n", - " file_path: Path to the large CSV file\n", - " chunk_size: Number of rows per chunk\n", - " output_dir: Directory to store chunk files (temp dir if None)\n", - " max_file_size_mb: Maximum file size per chunk in MB\n", - " \n", - " Returns:\n", - " List of chunk file paths\n", - " \"\"\"\n", - " if not os.path.exists(file_path):\n", - " raise FileNotFoundError(f\"File not found: {file_path}\")\n", - " \n", - " # Create output directory\n", - " if output_dir is None:\n", - " output_dir = tempfile.mkdtemp(prefix=\"csv_chunks_\")\n", - " else:\n", - " os.makedirs(output_dir, exist_ok=True)\n", - " \n", - " file_info = get_file_info(file_path)\n", - " filename = os.path.basename(file_path)\n", - " name, ext = os.path.splitext(filename)\n", - " \n", - " print(f\"๐Ÿ“ฆ Chunking {filename}:\")\n", - " print(f\" โ€ข Total rows: {file_info['row_count']:,}\")\n", - " print(f\" โ€ข File size: {file_info['size_mb']:.2f} MB\")\n", - " print(f\" โ€ข Chunk size: {chunk_size:,} rows\")\n", - " print(f\" โ€ข Estimated chunks: {file_info['estimated_chunk_count'](chunk_size)}\")\n", - " \n", - " chunk_files = []\n", - " try:\n", - " # Read and chunk the CSV file\n", - " chunk_num = 0\n", - " for chunk_df in pd.read_csv(file_path, chunksize=chunk_size):\n", - " chunk_num += 1\n", - " chunk_filename = f\"{name}_chunk_{chunk_num:03d}{ext}\"\n", - " chunk_path = os.path.join(output_dir, chunk_filename)\n", - " # Save chunk\n", - " chunk_df.to_csv(chunk_path, index=False)\n", - " # Check file size\n", - " chunk_size_mb = os.path.getsize(chunk_path) / (1024 * 1024)\n", - " if chunk_size_mb > max_file_size_mb:\n", - " print(f\"โš ๏ธ Warning: Chunk {chunk_num} is {chunk_size_mb:.2f} MB (exceeds {max_file_size_mb} MB limit)\")\n", - " chunk_files.append(chunk_path)\n", - " print(f\" โœ“ Created chunk {chunk_num}: {len(chunk_df)} rows, {chunk_size_mb:.2f} MB\")\n", - " \n", - " except Exception as e:\n", - " # Clean up on error\n", - " for chunk_file in chunk_files:\n", - " if os.path.exists(chunk_file):\n", - " os.remove(chunk_file)\n", - " raise e\n", - " \n", - " print(f\"๐Ÿ“ฆ Created {len(chunk_files)} chunks in {output_dir}\")\n", - " return chunk_files\n", - "\n", - "def upload_csv_data_chunked(\n", - " campaign_id: int,\n", - " station_id: int,\n", - " token: str,\n", - " data_dir: str = \"./data/\",\n", - " sensors_filename: str = \"sensors.csv\",\n", - " measurements_filename: str = \"measurements.csv\",\n", - " chunk_size: int = 10000,\n", - " max_file_size_mb: int = 50,\n", - " cleanup_chunks: bool = True,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Upload large CSV files using chunking strategy.\n", - " \n", - " Args:\n", - " campaign_id: ID of the target campaign\n", - " station_id: ID of the target station\n", - " token: Access token\n", - " data_dir: Directory containing CSV files\n", - " sensors_filename: Name of sensors CSV file\n", - " measurements_filename: Name of measurements CSV file\n", - " chunk_size: Number of rows per chunk\n", - " max_file_size_mb: Maximum file size per chunk in MB\n", - " cleanup_chunks: Whether to delete chunk files after upload\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Aggregated upload response data\n", - " \"\"\"\n", - " print(f\"=== Chunked CSV Data Upload ===\")\n", - " print(f\"Campaign ID: {campaign_id}\")\n", - " print(f\"Station ID: {station_id}\")\n", - " print(f\"Chunk size: {chunk_size:,} rows\")\n", - " print(f\"Max chunk file size: {max_file_size_mb} MB\")\n", - " \n", - " # Construct file paths\n", - " sensors_file_path = os.path.join(data_dir, sensors_filename)\n", - " measurements_file_path = os.path.join(data_dir, measurements_filename)\n", - " \n", - " # Verify files exist\n", - " if not os.path.exists(sensors_file_path):\n", - " raise FileNotFoundError(f\"Sensors file not found: {sensors_file_path}\")\n", - " if not os.path.exists(measurements_file_path):\n", - " raise FileNotFoundError(f\"Measurements file not found: {measurements_file_path}\")\n", - " \n", - " # Get file information\n", - " sensors_info = get_file_info(sensors_file_path)\n", - " measurements_info = get_file_info(measurements_file_path)\n", - " print(f\"\\n๐Ÿ“ File Analysis:\")\n", - " print(f\" โ€ข Sensors: {sensors_info['row_count']:,} rows, {sensors_info['size_mb']:.2f} MB\")\n", - " print(f\" โ€ข Measurements: {measurements_info['row_count']:,} rows, {measurements_info['size_mb']:.2f} MB\")\n", - " # Create temporary directory for chunks\n", - " chunk_dir = tempfile.mkdtemp(prefix=\"upload_chunks_\")\n", - " try:\n", - " # Create chunks\n", - " print(\"\\n--- Chunking Sensors File ---\")\n", - " sensors_chunks = create_csv_chunks(\n", - " sensors_file_path, \n", - " chunk_size=chunk_size,\n", - " output_dir=os.path.join(chunk_dir, \"sensors\"),\n", - " max_file_size_mb=max_file_size_mb\n", - " )\n", - " \n", - " print(\"\\n--- Chunking Measurements File ---\")\n", - " measurements_chunks = create_csv_chunks(\n", - " measurements_file_path,\n", - " chunk_size=chunk_size, \n", - " output_dir=os.path.join(chunk_dir, \"measurements\"),\n", - " max_file_size_mb=max_file_size_mb\n", - " )\n", - " \n", - " # Upload chunks\n", - " total_chunks = max(len(sensors_chunks), len(measurements_chunks))\n", - " successful_uploads = 0\n", - " failed_uploads = 0\n", - " aggregated_results = {\n", - " 'total_sensors_processed': 0,\n", - " 'total_measurements_added': 0,\n", - " 'total_processing_time': 0,\n", - " 'chunk_results': []\n", - " }\n", - " print(f\"\\n๐Ÿ“ค Uploading {total_chunks} chunk pairs...\")\n", - " \n", - " for i in range(total_chunks):\n", - " chunk_num = i + 1\n", - " print(f\"\\n--- Uploading Chunk {chunk_num}/{total_chunks} ---\") \n", - " try:\n", - " # Get chunk files (use last chunk if one file has fewer chunks)\n", - " sensors_chunk = sensors_chunks[min(i, len(sensors_chunks) - 1)]\n", - " measurements_chunk = measurements_chunks[min(i, len(measurements_chunks) - 1)]\n", - " # Upload chunk pair\n", - " start_time = time.time()\n", - " with open(sensors_chunk, 'rb') as sf, open(measurements_chunk, 'rb') as mf:\n", - " files = {\n", - " 'upload_file_sensors': (os.path.basename(sensors_chunk), sf, 'text/csv'),\n", - " 'upload_file_measurements': (os.path.basename(measurements_chunk), mf, 'text/csv')\n", - " }\n", - " upload_url = f\"{base_url}/api/v1/uploadfile_csv/campaign/{campaign_id}/station/{station_id}/sensor\"\n", - " response = make_authenticated_request(\n", - " method=\"POST\",\n", - " url=upload_url,\n", - " token=token,\n", - " files=files\n", - " )\n", - " \n", - " upload_time = time.time() - start_time\n", - " result = response.json()\n", - " \n", - " # Aggregate results\n", - " aggregated_results['total_sensors_processed'] += result.get('Total sensors processed', 0)\n", - " aggregated_results['total_measurements_added'] += result.get('Total measurements added to database', 0)\n", - " aggregated_results['total_processing_time'] += upload_time\n", - " aggregated_results['chunk_results'].append({\n", - " 'chunk': chunk_num,\n", - " 'sensors_processed': result.get('Total sensors processed', 0),\n", - " 'measurements_added': result.get('Total measurements added to database', 0),\n", - " 'upload_time': upload_time\n", - " })\n", - " \n", - " successful_uploads += 1\n", - " print(f\" โœ… Chunk {chunk_num} uploaded successfully\")\n", - " print(f\" โ€ข Sensors: {result.get('Total sensors processed', 0)}\")\n", - " print(f\" โ€ข Measurements: {result.get('Total measurements added to database', 0)}\")\n", - " print(f\" โ€ข Time: {upload_time:.2f}s\")\n", - " \n", - " except Exception as e:\n", - " failed_uploads += 1\n", - " print(f\" โŒ Chunk {chunk_num} failed: {e}\")\n", - " aggregated_results['chunk_results'].append({\n", - " 'chunk': chunk_num,\n", - " 'error': str(e)\n", - " })\n", - " \n", - " # Final results\n", - " print(f\"\\n๐Ÿ“Š Chunked Upload Summary:\")\n", - " print(f\" โ€ข Total chunks: {total_chunks}\")\n", - " print(f\" โ€ข Successful: {successful_uploads}\")\n", - " print(f\" โ€ข Failed: {failed_uploads}\")\n", - " print(f\" โ€ข Total sensors processed: {aggregated_results['total_sensors_processed']:,}\")\n", - " print(f\" โ€ข Total measurements added: {aggregated_results['total_measurements_added']:,}\")\n", - " print(f\" โ€ข Total processing time: {aggregated_results['total_processing_time']:.2f}s\")\n", - " \n", - " if failed_uploads > 0:\n", - " print(f\"โš ๏ธ {failed_uploads} chunks failed to upload\")\n", - " return aggregated_results\n", - " finally:\n", - " # Cleanup chunks if requested\n", - " if cleanup_chunks and os.path.exists(chunk_dir):\n", - " print(f\"๐Ÿงน Cleaning up chunk files from {chunk_dir}\")\n", - " shutil.rmtree(chunk_dir)\n", - "\n", - "def list_data_files(data_dir: str = \"./data/\") -> Dict[str, list]:\n", - " \"\"\"List all CSV files in the data directory.\n", - " Args:\n", - " data_dir: Directory to search for CSV files\n", - " \n", - " Returns:\n", - " Dictionary with lists of found files\n", - " \"\"\"\n", - " if not os.path.exists(data_dir):\n", - " print(f\"โŒ Data directory not found: {data_dir}\")\n", - " return {\"csv_files\": [], \"sensors_files\": [], \"measurements_files\": []}\n", - " \n", - " # Find all CSV files\n", - " csv_pattern = os.path.join(data_dir, \"*.csv\")\n", - " csv_files = glob.glob(csv_pattern)\n", - " \n", - " # Categorize files\n", - " sensors_files = [f for f in csv_files if 'sensor' in os.path.basename(f).lower()]\n", - " measurements_files = [f for f in csv_files if 'measurement' in os.path.basename(f).lower()]\n", - " \n", - " print(f\"๐Ÿ“ Files found in {data_dir}:\")\n", - " print(f\" โ€ข Total CSV files: {len(csv_files)}\")\n", - " print(f\" โ€ข Sensor files: {len(sensors_files)}\")\n", - " print(f\" โ€ข Measurement files: {len(measurements_files)}\")\n", - " if csv_files:\n", - " print(f\"๐Ÿ“„ All CSV files:\")\n", - " for file in csv_files:\n", - " size = os.path.getsize(file)\n", - " print(f\" - {os.path.basename(file)} ({size:,} bytes)\")\n", - " return {\n", - " \"csv_files\": csv_files,\n", - " \"sensors_files\": sensors_files,\n", - " \"measurements_files\": measurements_files\n", - " }\n", - "\n", - "def upload_data_with_auto_detection(\n", - " campaign_id: int,\n", - " station_id: int,\n", - " token: str,\n", - " data_dir: str = \"./data/\",\n", - " use_chunking: bool = False,\n", - " chunk_size: int = 10000,\n", - " max_file_size_mb: int = 50,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"\n", - " Upload CSV data with automatic file detection.\n", - " \n", - " Args:\n", - " campaign_id: ID of the target campaign\n", - " station_id: ID of the target station\n", - " token: Access token\n", - " data_dir: Directory containing CSV files\n", - " use_chunking: Whether to use chunked upload\n", - " chunk_size: Number of rows per chunk (if chunking)\n", - " max_file_size_mb: Maximum file size per chunk in MB (if chunking)\n", - " base_url: Base URL for the API\n", - " \n", - " Returns:\n", - " Upload response data\n", - " \"\"\"\n", - " print(\"=== Auto-detecting Data Files ===\")\n", - " files_info = list_data_files(data_dir)\n", - " \n", - " # Try to find sensors and measurements files\n", - " sensors_file = None\n", - " measurements_file = None\n", - " \n", - " # Look for standard filenames first\n", - " standard_sensors = os.path.join(data_dir, \"sensors.csv\")\n", - " standard_measurements = os.path.join(data_dir, \"measurements.csv\")\n", - " \n", - " if os.path.exists(standard_sensors):\n", - " sensors_file = \"sensors.csv\"\n", - " elif files_info[\"sensors_files\"]:\n", - " sensors_file = os.path.basename(files_info[\"sensors_files\"][0])\n", - " print(f\"๐Ÿ” Using detected sensors file: {sensors_file}\")\n", - " \n", - " if os.path.exists(standard_measurements):\n", - " measurements_file = \"measurements.csv\"\n", - " elif files_info[\"measurements_files\"]:\n", - " measurements_file = os.path.basename(files_info[\"measurements_files\"][0])\n", - " print(f\"๐Ÿ” Using detected measurements file: {measurements_file}\")\n", - " \n", - " if not sensors_file or not measurements_file:\n", - " raise FileNotFoundError(\n", - " f\"Could not find required files. \"\n", - " f\"Sensors: {sensors_file}, Measurements: {measurements_file}\"\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "afe2d17b-abd9-4193-be54-2d43236e7f9a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'\\nprint(\"=== Available Campaigns ===\")\\ncampaigns = get_campaigns(token)\\nprint(json.dumps(campaigns, indent=2))\\n\\nprint(\"=== Available Stations ===\")\\nstations = get_stations(CAMPAIGN_ID, token)\\nprint(json.dumps(stations, indent=2))\\n'" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def get_campaigns(token: str, base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\") -> Dict[str, Any]:\n", - " \"\"\"Get list of available campaigns.\"\"\"\n", - " url = f\"{base_url}/api/v1/campaigns\"\n", - " response = make_authenticated_request(\"GET\", url, token)\n", - " return response.json()\n", - "\n", - "def get_stations(campaign_id: int, token: str, base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\") -> Dict[str, Any]:\n", - " \"\"\"Get list of stations for a campaign.\"\"\"\n", - " url = f\"{base_url}/api/v1/campaigns/{campaign_id}/stations\"\n", - " response = make_authenticated_request(\"GET\", url, token)\n", - " return response.json()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4e77a7f7", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“ Files found in ./data/:\n", - " โ€ข Total CSV files: 2\n", - " โ€ข Sensor files: 1\n", - " โ€ข Measurement files: 1\n", - "๐Ÿ“„ All CSV files:\n", - " - measurements.csv (906,949 bytes)\n", - " - sensors.csv (173 bytes)\n", - "๐Ÿ“ˆ Upload Progress Estimation:\n", - " โ€ข Total data: 0.87 MB, 8,964 rows\n", - " โ€ข Estimated upload time: 1.7 seconds\n", - "=== Chunked CSV Data Upload ===\n", - "Campaign ID: 12\n", - "Station ID: 39\n", - "Chunk size: 6,000 rows\n", - "Max chunk file size: 30 MB\n", - "\n", - "๐Ÿ“ File Analysis:\n", - " โ€ข Sensors: 3 rows, 0.00 MB\n", - " โ€ข Measurements: 8,961 rows, 0.86 MB\n", - "\n", - "--- Chunking Sensors File ---\n", - "๐Ÿ“ฆ Chunking sensors.csv:\n", - " โ€ข Total rows: 3\n", - " โ€ข File size: 0.00 MB\n", - " โ€ข Chunk size: 6,000 rows\n", - " โ€ข Estimated chunks: 1\n", - " โœ“ Created chunk 1: 3 rows, 0.00 MB\n", - "๐Ÿ“ฆ Created 1 chunks in /var/folders/ps/dx2yrk_1117grf32kqlw9qyh0000gq/T/upload_chunks_6eegcnam/sensors\n", - "\n", - "--- Chunking Measurements File ---\n", - "๐Ÿ“ฆ Chunking measurements.csv:\n", - " โ€ข Total rows: 8,961\n", - " โ€ข File size: 0.86 MB\n", - " โ€ข Chunk size: 6,000 rows\n", - " โ€ข Estimated chunks: 2\n", - " โœ“ Created chunk 1: 6000 rows, 0.58 MB\n", - " โœ“ Created chunk 2: 2961 rows, 0.29 MB\n", - "๐Ÿ“ฆ Created 2 chunks in /var/folders/ps/dx2yrk_1117grf32kqlw9qyh0000gq/T/upload_chunks_6eegcnam/measurements\n", - "\n", - "๐Ÿ“ค Uploading 2 chunk pairs...\n", - "\n", - "--- Uploading Chunk 1/2 ---\n", - " โœ… Chunk 1 uploaded successfully\n", - " โ€ข Sensors: 3\n", - " โ€ข Measurements: 0\n", - " โ€ข Time: 5.66s\n", - "\n", - "--- Uploading Chunk 2/2 ---\n", - " โœ… Chunk 2 uploaded successfully\n", - " โ€ข Sensors: 3\n", - " โ€ข Measurements: 0\n", - " โ€ข Time: 2.80s\n", - "\n", - "๐Ÿ“Š Chunked Upload Summary:\n", - " โ€ข Total chunks: 2\n", - " โ€ข Successful: 2\n", - " โ€ข Failed: 0\n", - " โ€ข Total sensors processed: 6\n", - " โ€ข Total measurements added: 0\n", - " โ€ข Total processing time: 8.46s\n", - "๐Ÿงน Cleaning up chunk files from /var/folders/ps/dx2yrk_1117grf32kqlw9qyh0000gq/T/upload_chunks_6eegcnam\n", - "\n", - "๐Ÿ“Š Final Upload Statistics:\n", - " โ€ข Actual upload time: 8.59 seconds\n", - " โ€ข Average speed: 0.10 MB/s\n", - " โ€ข Rows per second: 1044\n" - ] - } - ], - "source": [ - "# List available files\n", - "files_info = list_data_files(\"./data/\")\n", - "# Analyze file sizes\n", - "sensors_path = \"./data/sensors.csv\"\n", - "measurements_path = \"./data/measurements.csv\"\n", - "if os.path.exists(sensors_path) and os.path.exists(measurements_path):\n", - " sensors_info = get_file_info(sensors_path)\n", - " measurements_info = get_file_info(measurements_path)\n", - " total_size_mb = sensors_info['size_mb'] + measurements_info['size_mb']\n", - " total_rows = sensors_info['row_count'] + measurements_info['row_count']\n", - " # Start upload with progress tracking\n", - " start_time = time.time()\n", - " try:\n", - " result = upload_csv_data_chunked(\n", - " campaign_id=campaign_id,\n", - " station_id=station_id,\n", - " token=token,\n", - " data_dir=\"./data/\",\n", - " sensors_filename=\"sensors.csv\",\n", - " measurements_filename=\"measurements.csv\",\n", - " chunk_size=6000,\n", - " max_file_size_mb=30\n", - " )\n", - " total_time = time.time() - start_time\n", - " except Exception as e:\n", - " print(f\"โŒ Progress monitored upload failed: {e}\")" - ] - }, - { - "cell_type": "markdown", - "id": "4d29b662", - "metadata": {}, - "source": [ - "## Create Measurement\n", - "The create_measurement function allows you to post a single measurement to the Upstream API for a specific sensor within a campaign and station." - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "c92fc98c", - "metadata": {}, - "outputs": [], - "source": [ - "def create_measurement(\n", - " campaign_id: int,\n", - " station_id: int, \n", - " sensor_id: int,\n", - " measurement_data: Dict[str, Any],\n", - " token: str,\n", - " base_url: str = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - ") -> Dict[str, Any]:\n", - " \"\"\"Create a single measurement for a sensor.\"\"\"\n", - " url = f\"{base_url}/api/v1/campaigns/{campaign_id}/stations/{station_id}/sensors/{sensor_id}/measurements\"\n", - " response = make_authenticated_request(\"POST\", url, token, json=measurement_data)\n", - " return response.json()\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "376d75bf", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "campaign_id = 12\n", - "station_id = 39 \n", - "sensor_id = 9664\n", - "\n", - "# Measurement data\n", - "measurement_data = {\n", - " \"variablename\": \"Rain Increement\",\n", - " \"collectiontime\": \"2024-01-15T10:37:00\",\n", - " \"variabletype\": \"float\", \n", - " \"description\": \"Rain Increment measurement\",\n", - " \"measurementvalue\": 25.3,\n", - " \"geometry\": 'POINT(10.12345 20.54321)'\n", - " \n", - "}\n", - "result = create_measurement(\n", - " campaign_id=campaign_id,\n", - " station_id=station_id,\n", - " sensor_id=sensor_id,\n", - " measurement_data=measurement_data,\n", - " token=token\n", - " )" - ] - }, - { - "cell_type": "markdown", - "id": "1e2fa823", - "metadata": {}, - "source": [ - "## 7. Best Practices\n", - "\n", - "1. **File Preparation:**\n", - " - Validate your CSV files before upload\n", - " - Ensure sensor aliases match between files\n", - " - Use consistent timestamp formats\n", - "\n", - "2. **Error Handling:**\n", - " - Always wrap API calls in try-catch blocks\n", - " - Check file existence before upload\n", - " - Validate response status codes\n", - "\n", - "3. **Security:**\n", - " - Never hardcode credentials in notebooks\n", - " - Store tokens securely\n", - " - Use environment variables for sensitive data\n", - "\n", - "4. **Performance:**\n", - " - Keep files under 500 MB for optimal performance\n", - " - Use batch uploads for large datasets\n", - " - Monitor upload progress and statistics" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.18" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/UpstreamSDK_CKAN_Demo.ipynb b/UpstreamSDK_CKAN_Demo.ipynb new file mode 100644 index 0000000..818fd22 --- /dev/null +++ b/UpstreamSDK_CKAN_Demo.ipynb @@ -0,0 +1,1188 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "cell-0", + "metadata": {}, + "source": [ + "# Upstream SDK CKAN Integration Demo\n", + "\n", + "This notebook demonstrates the CKAN integration capabilities of the Upstream SDK for publishing environmental monitoring data to CKAN data portals.\n", + "\n", + "## Overview\n", + "\n", + "The Upstream SDK provides seamless integration with CKAN (Comprehensive Knowledge Archive Network) data portals for:\n", + "- ๐Ÿ“Š **Dataset Publishing**: Automatically create CKAN datasets from campaign data\n", + "- ๐Ÿ“ **Resource Management**: Upload sensor configurations and measurement data as resources\n", + "- ๐Ÿข **Organization Support**: Publish data under specific CKAN organizations\n", + "- ๐Ÿ”„ **Update Management**: Update existing datasets with new data\n", + "- ๐Ÿท๏ธ **Metadata Integration**: Rich metadata tagging and categorization\n", + "\n", + "## Features Demonstrated\n", + "\n", + "- CKAN client setup and configuration\n", + "- Campaign data export and preparation\n", + "- Dataset creation with comprehensive metadata\n", + "- Resource management (sensors and measurements)\n", + "- Organization and permission handling\n", + "- Error handling and validation\n", + "\n", + "## Prerequisites\n", + "\n", + "- Valid Upstream account credentials\n", + "- Access to a CKAN portal with API credentials\n", + "- Existing campaign data (or run UpstreamSDK_Core_Demo.ipynb first)\n", + "- Python 3.7+ environment with required packages\n", + "\n", + "## Related Notebooks\n", + "\n", + "- **UpstreamSDK_Core_Demo.ipynb**: Core SDK functionality and campaign creation" + ] + }, + { + "cell_type": "markdown", + "id": "cell-1", + "metadata": {}, + "source": [ + "## Installation and Setup" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-2", + "metadata": {}, + "outputs": [], + "source": [ + "# Install required packages\n", + "#!pip install upstream-sdk\n", + "!pip install -e .\n", + "# Import required libraries\n", + "import os\n", + "import json\n", + "import getpass\n", + "from pathlib import Path\n", + "from datetime import datetime\n", + "from typing import Dict, Any, Optional, List\n", + "from io import BytesIO\n", + "\n", + "# Import Upstream SDK modules\n", + "from upstream.client import UpstreamClient\n", + "from upstream.ckan import CKANIntegration" + ] + }, + { + "cell_type": "markdown", + "id": "cell-3", + "metadata": {}, + "source": [ + "## 1. Configuration and Authentication\n", + "\n", + "First, let's set up authentication for both Upstream and CKAN platforms.\n", + "\n", + "**Configuration Options:**\n", + "- **Upstream API**: Username/password authentication\n", + "- **CKAN Portal**: API key or access token authentication\n", + "- **Organization**: CKAN organization for dataset publishing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-4", + "metadata": {}, + "outputs": [], + "source": [ + "# Configuration\n", + "UPSTREAM_BASE_URL = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", + "# For local development, uncomment the line below:\n", + "UPSTREAM_BASE_URL = 'http://localhost:8000'\n", + "\n", + "# CKAN Configuration - Update these for your CKAN portal\n", + "CKAN_URL = \"https://ckan.tacc.utexas.edu\" # Replace with your CKAN portal URL\n", + "CKAN_ORGANIZATION = \"setx-uifl\" # Replace with your organization name\n", + "\n", + "#For local development, uncomment the line below:\n", + "CKAN_URL = 'http://ckan.tacc.cloud:5000'\n", + "CKAN_ORGANIZATION = 'org'\n", + "\n", + "print(\"๐Ÿ”ง Configuration Settings:\")\n", + "print(f\" Upstream API: {UPSTREAM_BASE_URL}\")\n", + "print(f\" CKAN Portal: {CKAN_URL}\")\n", + "print(f\" CKAN Organization: {CKAN_ORGANIZATION}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-5", + "metadata": {}, + "outputs": [], + "source": [ + "# Get Upstream credentials\n", + "print(\"๐Ÿ” Please enter your TACC credentials:\")\n", + "upstream_username = input(\"Tacc Username: \")\n", + "upstream_password = getpass.getpass(\"Upstream Password: \")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "375ad2cb", + "metadata": {}, + "outputs": [], + "source": [ + "# Get CKAN credentials (optional - for read-only operations)\n", + "print(\"\\n๐Ÿ”‘ CKAN API credentials (optional for demo):\")\n", + "ckan_api_key = getpass.getpass(\"CKAN API Key (press Enter to skip): \")\n", + "\n", + "# Prepare CKAN configuration\n", + "ckan_config = {\n", + " \"timeout\": 30,\n", + "}\n", + "\n", + "if ckan_api_key:\n", + " ckan_config[\"api_key\"] = ckan_api_key\n", + " print(\"โœ… CKAN API key configured\")\n", + "else:\n", + " print(\"โ„น๏ธ Running in read-only CKAN mode\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-6", + "metadata": {}, + "outputs": [], + "source": [ + "# Initialize Upstream client with CKAN integration\n", + "try:\n", + " client = UpstreamClient(\n", + " username=upstream_username,\n", + " password=upstream_password,\n", + " base_url=UPSTREAM_BASE_URL,\n", + " ckan_url=CKAN_URL,\n", + " ckan_organization=CKAN_ORGANIZATION,\n", + " **ckan_config\n", + " )\n", + " print('โœ… Upstream client initialized')\n", + "\n", + " # Test Upstream authentication\n", + " if client.authenticate():\n", + " print(\"โœ… Upstream authentication successful!\")\n", + " print(f\"๐Ÿ”— Connected to: {UPSTREAM_BASE_URL}\")\n", + "\n", + " # Check CKAN integration\n", + " if client.ckan:\n", + " print(\"โœ… CKAN integration enabled!\")\n", + " print(f\"๐Ÿ”— CKAN Portal: {CKAN_URL}\")\n", + " else:\n", + " print(\"โš ๏ธ CKAN integration not configured\")\n", + " else:\n", + " print(\"โŒ Upstream authentication failed!\")\n", + " raise Exception(\"Upstream authentication failed\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Setup error: {e}\")\n", + " raise" + ] + }, + { + "cell_type": "markdown", + "id": "cell-7", + "metadata": {}, + "source": [ + "## 2. Campaign Selection and Data Preparation\n", + "\n", + "Let's select an existing campaign with data to publish to CKAN. If you don't have existing data, run the core demo notebook first." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-8", + "metadata": {}, + "outputs": [], + "source": [ + "# List available campaigns\n", + "print(\"๐Ÿ“‹ Available campaigns for CKAN publishing:\")\n", + "try:\n", + " campaigns = client.list_campaigns(limit=10)\n", + "\n", + " if campaigns.total == 0:\n", + " print(\"โŒ No campaigns found. Please run UpstreamSDK_Core_Demo.ipynb first to create sample data.\")\n", + " raise Exception(\"No campaigns available\")\n", + "\n", + " print(f\"Found {campaigns.total} campaigns:\")\n", + " for i, campaign in enumerate(campaigns.items[:5]):\n", + " print(f\" {i+1}. ID: {campaign.id} - {campaign.name}\")\n", + " print(f\" Description: {campaign.description[:80]}...\")\n", + " print(f\" Contact: {campaign.contact_name} ({campaign.contact_email})\")\n", + " print()\n", + "\n", + " # Select campaign (use the first one or let user choose)\n", + " selected_campaign = campaigns.items[0]\n", + " campaign_id = selected_campaign.id\n", + "\n", + " print(f\"๐Ÿ“Š Selected campaign for CKAN publishing:\")\n", + " print(f\" ID: {campaign_id}\")\n", + " print(f\" Name: {selected_campaign.name}\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Error listing campaigns: {e}\")\n", + " raise" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-9", + "metadata": {}, + "outputs": [], + "source": [ + "# Get stations for the selected campaign\n", + "print(f\"๐Ÿ“ Finding stations in campaign {campaign_id}...\")\n", + "try:\n", + " stations = client.list_stations(campaign_id=str(campaign_id))\n", + "\n", + " if stations.total == 0:\n", + " print(\"โŒ No stations found in this campaign. Please create stations and upload data first.\")\n", + " raise Exception(\"No stations available\")\n", + "\n", + " print(f\"Found {stations.total} stations:\")\n", + " for station in stations.items:\n", + " print(f\" โ€ข ID: {station.id} - {station.name}\")\n", + " print(f\" Description: {station.description[:80]}...\")\n", + " print()\n", + "\n", + " # Select the first station\n", + " selected_station = stations.items[0]\n", + " station_id = selected_station.id\n", + "\n", + " print(f\"๐Ÿ“ก Selected station for CKAN publishing:\")\n", + " print(f\" ID: {station_id}\")\n", + " print(f\" Name: {selected_station.name}\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Error listing stations: {e}\")\n", + " raise" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-10", + "metadata": {}, + "outputs": [], + "source": [ + "# Check for existing data in the station\n", + "print(f\"๐Ÿ” Checking data availability for station {station_id}...\")\n", + "try:\n", + " # List sensors to verify data exists\n", + " sensors = client.sensors.list(campaign_id=campaign_id, station_id=station_id)\n", + "\n", + " if not sensors.items:\n", + " print(\"โŒ No sensors found in this station. Please upload sensor data first.\")\n", + " raise Exception(\"No sensor data available\")\n", + " print(sensors.items)\n", + " total_measurements = 0\n", + " for sensor in sensors.items:\n", + " if sensor.statistics:\n", + " total_measurements += sensor.statistics.count\n", + " print(total_measurements)\n", + "\n", + " print(f\"โœ… Data validation successful:\")\n", + " print(f\" โ€ข Sensors: {len(sensors.items)}\")\n", + " print(f\" โ€ข Total measurements: {total_measurements}\")\n", + " print(f\" โ€ข Sensor types: {', '.join([s.variablename for s in sensors.items[:3]])}{'...' if len(sensors.items) > 3 else ''}\")\n", + "\n", + " if total_measurements == 0:\n", + " print(\"โš ๏ธ Warning: No measurement data found. CKAN publishing will include sensor configuration only.\")\n", + " else:\n", + " print(\"โœ… Ready for CKAN publishing with full dataset!\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Error checking data availability: {e}\")\n", + " raise" + ] + }, + { + "cell_type": "markdown", + "id": "cell-11", + "metadata": {}, + "source": [ + "## 3. CKAN Portal Exploration\n", + "\n", + "Before publishing, let's explore the CKAN portal to understand its structure and existing datasets." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-12", + "metadata": {}, + "outputs": [], + "source": [ + "# Initialize standalone CKAN client for exploration\n", + "if client.ckan:\n", + " ckan = client.ckan\n", + "else:\n", + " # Create standalone CKAN client for exploration\n", + " ckan = CKANIntegration(ckan_url=CKAN_URL, config=ckan_config)\n", + "\n", + "print(f\"๐ŸŒ Exploring CKAN portal: {CKAN_URL}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-13", + "metadata": {}, + "outputs": [], + "source": [ + "# List existing organizations\n", + "print(\"๐Ÿข Available CKAN organizations:\")\n", + "try:\n", + " organizations = ckan.list_organizations()\n", + "\n", + " if organizations:\n", + " print(f\"Found {len(organizations)} organizations:\")\n", + " for org in organizations[:5]: # Show first 5\n", + " print(f\" โ€ข {org['name']}: {org['title']}\")\n", + " print(f\" Description: {(org.get('description') or 'No description')[:60]}...\")\n", + " print(f\" Packages: {org.get('package_count', 0)}\")\n", + " print()\n", + "\n", + " # Check if our target organization exists\n", + " org_names = [org['name'] for org in organizations]\n", + " if CKAN_ORGANIZATION in org_names:\n", + " print(f\"โœ… Target organization '{CKAN_ORGANIZATION}' found!\")\n", + " else:\n", + " print(f\"โš ๏ธ Target organization '{CKAN_ORGANIZATION}' not found.\")\n", + " print(\" Publishing will use test dataset mode.\")\n", + " else:\n", + " print(\"No organizations found or access restricted.\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โš ๏ธ Could not list organizations: {e}\")\n", + " print(\"Continuing with dataset publishing...\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-14", + "metadata": {}, + "outputs": [], + "source": [ + "# Search for existing Upstream datasets\n", + "print(\"๐Ÿ” Searching for existing Upstream datasets in CKAN:\")\n", + "try:\n", + " upstream_datasets = ckan.list_datasets(\n", + " tags=[\"upstream\", \"environmental\"],\n", + " limit=10\n", + " )\n", + "\n", + " if upstream_datasets:\n", + " print(f\"Found {len(upstream_datasets)} Upstream-related datasets:\")\n", + " for dataset in upstream_datasets[:3]: # Show first 3\n", + " print(f\" โ€ข {dataset['name']}: {dataset['title']}\")\n", + " print(f\" Notes: {(dataset.get('notes') or 'No description')[:80]}...\")\n", + " print(f\" Resources: {len(dataset.get('resources', []))}\")\n", + " print(f\" Tags: {', '.join([tag['name'] for tag in dataset.get('tags', [])])}\")\n", + " print()\n", + " else:\n", + " print(\"No existing Upstream datasets found.\")\n", + " print(\"This will be the first Upstream dataset in this portal!\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โš ๏ธ Could not search datasets: {e}\")\n", + " print(\"Proceeding with dataset creation...\")" + ] + }, + { + "cell_type": "markdown", + "id": "cell-15", + "metadata": {}, + "source": [ + "## 4. Data Export and Preparation\n", + "\n", + "Before publishing to CKAN, let's export the campaign data and examine its structure." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-16", + "metadata": {}, + "outputs": [], + "source": [ + "# Get detailed campaign information\n", + "print(f\"๐Ÿ“Š Retrieving detailed campaign information...\")\n", + "try:\n", + " campaign_details = client.get_campaign(str(campaign_id))\n", + "\n", + " print(f\"โœ… Campaign Details Retrieved:\")\n", + " print(f\" Name: {campaign_details.name}\")\n", + " print(f\" Description: {campaign_details.description}\")\n", + " print(f\" Contact: {campaign_details.contact_name} ({campaign_details.contact_email})\")\n", + " print(f\" Allocation: {campaign_details.allocation}\")\n", + " print(f\" Start Date: {campaign_details.start_date}\")\n", + " print(f\" End Date: {campaign_details.end_date}\")\n", + "\n", + " # Check campaign summary if available\n", + " if hasattr(campaign_details, 'summary') and campaign_details.summary:\n", + " summary = campaign_details.summary\n", + " print(f\"\\n๐Ÿ“ˆ Campaign Summary:\")\n", + " if hasattr(summary, 'total_stations'):\n", + " print(f\" โ€ข Total Stations: {summary.total_stations}\")\n", + " if hasattr(summary, 'total_sensors'):\n", + " print(f\" โ€ข Total Sensors: {summary.total_sensors}\")\n", + " if hasattr(summary, 'total_measurements'):\n", + " print(f\" โ€ข Total Measurements: {summary.total_measurements}\")\n", + " if hasattr(summary, 'sensor_types'):\n", + " print(f\" โ€ข Sensor Types: {', '.join(summary.sensor_types)}\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Error retrieving campaign details: {e}\")\n", + " raise" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-17", + "metadata": {}, + "outputs": [], + "source": [ + "# Export station data for CKAN publishing\n", + "print(f\"๐Ÿ“ค Exporting station data for CKAN publishing...\")\n", + "try:\n", + " # Export sensor configuration\n", + " print(\" Exporting sensor configuration...\")\n", + " station_sensors_data = client.stations.export_station_sensors(\n", + " station_id=str(station_id),\n", + " campaign_id=str(campaign_id)\n", + " )\n", + "\n", + " # Export measurement data\n", + " print(\" Exporting measurement data...\")\n", + " station_measurements_data = client.stations.export_station_measurements(\n", + " station_id=str(station_id),\n", + " campaign_id=str(campaign_id)\n", + " )\n", + "\n", + " # Check exported data sizes\n", + " sensors_size = len(station_sensors_data.getvalue()) if hasattr(station_sensors_data, 'getvalue') else 0\n", + " measurements_size = len(station_measurements_data.getvalue()) if hasattr(station_measurements_data, 'getvalue') else 0\n", + "\n", + " print(f\"โœ… Data export completed:\")\n", + " print(f\" โ€ข Sensors data: {sensors_size:,} bytes\")\n", + " print(f\" โ€ข Measurements data: {measurements_size:,} bytes\")\n", + " print(f\" โ€ข Total data size: {(sensors_size + measurements_size):,} bytes\")\n", + "\n", + " if sensors_size == 0:\n", + " print(\"โš ๏ธ Warning: Sensors data is empty\")\n", + " if measurements_size == 0:\n", + " print(\"โš ๏ธ Warning: Measurements data is empty\")\n", + "\n", + " print(\"โœ… Ready for CKAN publication!\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Error exporting station data: {e}\")\n", + " raise" + ] + }, + { + "cell_type": "markdown", + "id": "cell-18", + "metadata": {}, + "source": [ + "## 5. CKAN Dataset Creation and Publishing\n", + "\n", + "Now let's publish the campaign data to CKAN using the integrated publishing functionality." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-19", + "metadata": {}, + "outputs": [], + "source": [ + "# Prepare dataset metadata\n", + "dataset_name = f\"upstream-campaign-{campaign_id}\"\n", + "print(f\"๐Ÿท๏ธ Preparing dataset metadata for: {dataset_name}\")\n", + "\n", + "# Create comprehensive metadata\n", + "dataset_metadata = {\n", + " \"name\": dataset_name,\n", + " \"title\": campaign_details.name,\n", + " \"notes\": f\"\"\"{campaign_details.description}\n", + "\n", + "This dataset contains environmental sensor data collected through the Upstream platform.\n", + "\n", + "**Campaign Information:**\n", + "- Campaign ID: {campaign_id}\n", + "- Contact: {campaign_details.contact_name} ({campaign_details.contact_email})\n", + "- Allocation: {campaign_details.allocation}\n", + "- Duration: {campaign_details.start_date} to {campaign_details.end_date}\n", + "\n", + "**Data Structure:**\n", + "- Sensors Configuration: Contains sensor metadata, units, and processing information\n", + "- Measurement Data: Time-series environmental measurements with geographic coordinates\n", + "\n", + "**Access and Usage:**\n", + "Data is provided in CSV format for easy analysis and integration with various tools.\"\"\",\n", + " \"tags\": [\"environmental\", \"sensors\", \"upstream\", \"monitoring\", \"time-series\"],\n", + " \"extras\": [\n", + " {\"key\": \"campaign_id\", \"value\": str(campaign_id)},\n", + " {\"key\": \"station_id\", \"value\": str(station_id)},\n", + " {\"key\": \"source\", \"value\": \"Upstream Platform\"},\n", + " {\"key\": \"data_type\", \"value\": \"environmental_sensor_data\"},\n", + " {\"key\": \"contact_email\", \"value\": campaign_details.contact_email},\n", + " {\"key\": \"allocation\", \"value\": campaign_details.allocation},\n", + " {\"key\": \"export_date\", \"value\": datetime.now().isoformat()}\n", + " ],\n", + " \"license_id\": \"cc-by\", # Creative Commons Attribution\n", + "}\n", + "\n", + "print(f\"๐Ÿ“‹ Dataset Metadata Prepared:\")\n", + "print(f\" โ€ข Name: {dataset_metadata['name']}\")\n", + "print(f\" โ€ข Title: {dataset_metadata['title']}\")\n", + "print(f\" โ€ข Tags: {', '.join(dataset_metadata['tags'])}\")\n", + "print(f\" โ€ข License: {dataset_metadata['license_id']}\")\n", + "print(f\" โ€ข Extra fields: {len(dataset_metadata['extras'])}\")\n", + "print(f\" โ€ข Notes: {dataset_metadata['notes']}\")" + ] + }, + { + "cell_type": "markdown", + "id": "1xhgcu1cn2a", + "metadata": {}, + "source": [ + "## 5.1 Understanding CKAN Metadata and Custom Metadata Support\n", + "\n", + "The Upstream SDK provides comprehensive metadata management for CKAN publishing. Let's explore the different types of metadata and how to customize them for your specific needs.\n", + "\n", + "### ๐Ÿ“‹ Base Metadata (Automatically Included)\n", + "\n", + "When you use `publish_to_ckan()`, the SDK automatically includes rich base metadata:\n", + "\n", + "**Dataset-level metadata (stored in CKAN extras):**\n", + "- `source`: \"Upstream Platform\" \n", + "- `data_type`: \"environmental_sensor_data\"\n", + "- `campaign_id`: Your campaign identifier\n", + "- `campaign_name`: Campaign name \n", + "- `campaign_description`: Campaign description\n", + "- `campaign_contact_name`: Campaign contact person\n", + "- `campaign_contact_email`: Campaign contact email\n", + "- `campaign_allocation`: Campaign allocation/project code\n", + "\n", + "**Resource-level metadata (applied to both sensors.csv and measurements.csv):**\n", + "- `station_id`: Station identifier\n", + "- `station_name`: Station name\n", + "- `station_description`: Station description \n", + "- `station_contact_name`: Station contact\n", + "- `station_contact_email`: Station contact email\n", + "- `station_active`: Station status\n", + "- `station_geometry`: Geographic location data\n", + "- `station_sensors`: Complete sensor information\n", + "- `station_sensors_count`: Number of sensors\n", + "- `station_sensors_aliases`: Sensor identifiers\n", + "- `station_sensors_units`: Measurement units\n", + "- `station_sensors_descriptions`: Sensor descriptions\n", + "\n", + "**Default tags:** `[\"environmental\", \"sensors\", \"upstream\"]`\n", + "\n", + "### ๐ŸŽจ Custom Metadata Support (New Feature!)\n", + "\n", + "You can now extend the base metadata with your own custom fields:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "mm2op8ht5ro", + "metadata": {}, + "outputs": [], + "source": [ + "# Demonstrate Custom Metadata Publishing\n", + "print(\"๐ŸŽจ Demonstrating Custom Metadata Publishing...\")\n", + "\n", + "# Example 1: Basic custom metadata\n", + "print(\"\\n๐Ÿ“ Example 1: Adding custom dataset metadata\")\n", + "custom_dataset_metadata = {\n", + " \"project_name\": \"Water Quality Monitoring Study\",\n", + " \"funding_agency\": \"Environmental Protection Agency\",\n", + " \"grant_number\": \"EPA-2024-WQ-001\",\n", + " \"study_period\": \"2024-2025\",\n", + " \"principal_investigator\": \"Dr. Jane Smith\",\n", + " \"institution\": \"University of Environmental Sciences\",\n", + " \"data_quality_level\": \"Level 2 - Quality Controlled\"\n", + "}\n", + "\n", + "print(\"Custom dataset metadata to be added:\")\n", + "for key, value in custom_dataset_metadata.items():\n", + " print(f\" โ€ข {key}: {value}\")\n", + "\n", + "# Example 2: Custom resource metadata\n", + "print(\"\\n๐Ÿ“„ Example 2: Adding custom resource metadata\")\n", + "custom_resource_metadata = {\n", + " \"calibration_date\": \"2024-01-15\",\n", + " \"calibration_method\": \"NIST-traceable standards\",\n", + " \"processing_version\": \"v2.1\",\n", + " \"quality_control\": \"Automated + Manual Review\",\n", + " \"uncertainty_bounds\": \"ยฑ2% of reading\",\n", + " \"data_completeness\": \"98.5%\"\n", + "}\n", + "\n", + "print(\"Custom resource metadata to be added to both sensors.csv and measurements.csv:\")\n", + "for key, value in custom_resource_metadata.items():\n", + " print(f\" โ€ข {key}: {value}\")\n", + "\n", + "# Example 3: Custom tags\n", + "print(\"\\n๐Ÿท๏ธ Example 3: Adding custom tags\")\n", + "custom_tags = [\n", + " \"water-quality\",\n", + " \"epa-funded\",\n", + " \"university-research\",\n", + " \"quality-controlled\",\n", + " \"long-term-monitoring\"\n", + "]\n", + "\n", + "print(f\"Custom tags (added to base tags): {', '.join(custom_tags)}\")\n", + "print(f\"Final tags will be: {', '.join(['environmental', 'sensors', 'upstream'] + custom_tags)}\")\n", + "\n", + "# Example 4: Additional CKAN dataset parameters\n", + "print(\"\\nโš™๏ธ Example 4: Additional CKAN dataset parameters\")\n", + "additional_params = {\n", + " \"license_id\": \"cc-by-4.0\", # Creative Commons Attribution 4.0\n", + " \"version\": \"2.1\",\n", + " \"author\": \"Environmental Research Team\",\n", + " \"author_email\": \"research@university.edu\",\n", + " \"maintainer\": \"Dr. Jane Smith\",\n", + " \"maintainer_email\": \"jane.smith@university.edu\"\n", + "}\n", + "\n", + "print(\"Additional CKAN dataset parameters:\")\n", + "for key, value in additional_params.items():\n", + " print(f\" โ€ข {key}: {value}\")\n", + "\n", + "print(\"\\n๐Ÿ’ก These examples show how to enrich your CKAN datasets with project-specific metadata!\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ls3vx1zflrf", + "metadata": {}, + "outputs": [], + "source": [ + "# Publish with Custom Metadata - Practical Example\n", + "print(\"๐Ÿš€ Publishing with Custom Metadata - Practical Example\")\n", + "print(\"=\" * 60)\n", + "\n", + "# Create a new dataset name for the custom metadata example\n", + "custom_dataset_campaign_id = f\"{campaign_id}-custom-meta\"\n", + "\n", + "try:\n", + " # Publish campaign data with ALL custom metadata options\n", + " print(\"๐Ÿ“ค Publishing campaign with comprehensive custom metadata...\")\n", + "\n", + " custom_publication_result = client.publish_to_ckan(\n", + " campaign_id=str(campaign_id),\n", + " station_id=str(station_id),\n", + "\n", + " # Custom dataset metadata (added to CKAN extras)\n", + " dataset_metadata=custom_dataset_metadata,\n", + "\n", + " # Custom resource metadata (added to both CSV files)\n", + " resource_metadata=custom_resource_metadata,\n", + "\n", + " # Custom tags (combined with base tags)\n", + " custom_tags=custom_tags,\n", + "\n", + " # Control auto-publishing\n", + " auto_publish=True,\n", + "\n", + " # Additional CKAN dataset parameters\n", + " **additional_params\n", + " )\n", + "\n", + " print(\"โœ… Custom Metadata Publication Successful!\")\n", + " print(f\"\\n๐Ÿ“Š Publication Results:\")\n", + " print(f\" โ€ข Dataset Name: {custom_publication_result['dataset']['name']}\")\n", + " print(f\" โ€ข Dataset ID: {custom_publication_result['dataset']['id']}\")\n", + " print(f\" โ€ข Resources: {len(custom_publication_result['resources'])}\")\n", + " print(f\" โ€ข CKAN URL: {custom_publication_result['ckan_url']}\")\n", + "\n", + " # Store for verification\n", + " custom_dataset = custom_publication_result['dataset']\n", + " custom_ckan_url = custom_publication_result['ckan_url']\n", + "\n", + " print(f\"\\n๐ŸŒŸ Enhanced dataset available at:\")\n", + " print(f\" {custom_ckan_url}\")\n", + "\n", + " print(f\"\\n๐Ÿ” What's different with custom metadata:\")\n", + " print(f\" โœ“ Extended dataset metadata with project details\")\n", + " print(f\" โœ“ Enhanced resource metadata with quality information\")\n", + " print(f\" โœ“ Improved discoverability through custom tags\")\n", + " print(f\" โœ“ Professional licensing and authorship information\")\n", + " print(f\" โœ“ Version tracking and maintenance contacts\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Custom metadata publication failed: {e}\")\n", + " print(\"This might be due to CKAN permissions or network issues.\")\n", + " # Continue with the demo using the basic dataset\n", + " custom_dataset = published_dataset\n", + " custom_ckan_url = ckan_dataset_url" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "rsq3enemnli", + "metadata": {}, + "outputs": [], + "source": [ + "# Compare Standard vs Custom Metadata Results\n", + "print(\"๐Ÿ” Comparing Standard vs Custom Metadata Results\")\n", + "print(\"=\" * 55)\n", + "\n", + "try:\n", + " # Retrieve the custom metadata dataset for comparison\n", + " custom_dataset_details = ckan.get_dataset(custom_dataset['name'])\n", + "\n", + " print(\"๐Ÿ“‹ Metadata Comparison:\")\n", + " print(\"\\n1๏ธโƒฃ DATASET-LEVEL METADATA (CKAN Extras)\")\n", + " print(\" Standard publish_to_ckan() includes:\")\n", + " standard_extras = [\"source\", \"data_type\", \"campaign_id\", \"campaign_name\",\n", + " \"campaign_description\", \"campaign_contact_name\", \"campaign_contact_email\"]\n", + " for extra in standard_extras:\n", + " print(f\" โ€ข {extra}\")\n", + "\n", + " print(\"\\n Custom metadata adds:\")\n", + " custom_extras = list(custom_dataset_metadata.keys())\n", + " for extra in custom_extras:\n", + " print(f\" โ€ข {extra}\")\n", + "\n", + " print(f\"\\n ๐Ÿ“Š Total extras in custom dataset: {len(custom_dataset_details.get('extras', []))}\")\n", + "\n", + " # Show some actual custom extras from the dataset\n", + " print(\"\\n ๐Ÿ” Sample custom extras retrieved from CKAN:\")\n", + " for extra in custom_dataset_details.get('extras', [])[:8]: # Show first 8\n", + " if extra['key'] in custom_dataset_metadata:\n", + " print(f\" โœ“ {extra['key']}: {extra['value']}\")\n", + "\n", + " print(\"\\n2๏ธโƒฃ TAGS COMPARISON\")\n", + " dataset_tags = [tag['name'] for tag in custom_dataset_details.get('tags', [])]\n", + " base_tags = [\"environmental\", \"sensors\", \"upstream\"]\n", + " added_tags = [tag for tag in dataset_tags if tag not in base_tags]\n", + "\n", + " print(f\" Base tags: {', '.join(base_tags)}\")\n", + " print(f\" Custom tags added: {', '.join(added_tags)}\")\n", + " print(f\" ๐Ÿ“Š Total tags: {len(dataset_tags)}\")\n", + "\n", + " print(\"\\n3๏ธโƒฃ DATASET PARAMETERS\")\n", + " print(f\" License: {custom_dataset_details.get('license_title', 'Not set')}\")\n", + " print(f\" Version: {custom_dataset_details.get('version', 'Not set')}\")\n", + " print(f\" Author: {custom_dataset_details.get('author', 'Not set')}\")\n", + " print(f\" Maintainer: {custom_dataset_details.get('maintainer', 'Not set')}\")\n", + "\n", + " print(\"\\n4๏ธโƒฃ RESOURCE METADATA\")\n", + " resources = custom_dataset_details.get('resources', [])\n", + " if resources:\n", + " print(f\" Found {len(resources)} resources with enhanced metadata\")\n", + " sample_resource = resources[0] # Check first resource\n", + "\n", + " # Count how many custom metadata fields are present\n", + " custom_fields_found = 0\n", + " for field_name in custom_resource_metadata.keys():\n", + " if field_name in sample_resource:\n", + " custom_fields_found += 1\n", + " print(f\" โœ“ {field_name}: {sample_resource[field_name]}\")\n", + "\n", + " print(f\" ๐Ÿ“Š Custom resource fields added: {custom_fields_found}/{len(custom_resource_metadata)}\")\n", + "\n", + " print(\"\\n๐Ÿ’ก Benefits of Custom Metadata:\")\n", + " print(\" ๐ŸŽฏ Improved searchability and discoverability\")\n", + " print(\" ๐Ÿ“š Better documentation and context\")\n", + " print(\" ๐Ÿ” Enhanced filtering and categorization\")\n", + " print(\" ๐Ÿ“Š Professional presentation and credibility\")\n", + " print(\" ๐Ÿค Clear contact and attribution information\")\n", + " print(\" โš–๏ธ Proper licensing and usage terms\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โš ๏ธ Could not retrieve custom dataset details: {e}\")\n", + " print(\"The comparison will use the information we provided during publishing.\")\n", + "\n", + "print(f\"\\n๐Ÿ“š Usage Guidelines:\")\n", + "print(\"โ€ข Use dataset_metadata for project-level information\")\n", + "print(\"โ€ข Use resource_metadata for data quality and processing details\")\n", + "print(\"โ€ข Use custom_tags for improved discoverability\")\n", + "print(\"โ€ข Use additional parameters for CKAN-specific fields\")\n", + "print(\"โ€ข All custom metadata is preserved and searchable in CKAN\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-20", + "metadata": {}, + "outputs": [], + "source": [ + "# Publish campaign data to CKAN using integrated method\n", + "print(f\"๐Ÿ“ค Publishing campaign data to CKAN...\")\n", + "station_name = client.stations.get(station_id=station_id, campaign_id=campaign_id).name\n", + "\n", + "try:\n", + " # Use the integrated CKAN publishing method\n", + " publication_result = client.publish_to_ckan(\n", + " campaign_id=str(campaign_id),\n", + " station_id=str(station_id),\n", + " )\n", + "\n", + " print(f\"โœ… CKAN Publication Successful!\")\n", + " print(f\"\\n๐Ÿ“Š Publication Summary:\")\n", + " print(f\" โ€ข Success: {publication_result['success']}\")\n", + " print(f\" โ€ข Dataset Name: {publication_result['dataset']['name']}\")\n", + " print(f\" โ€ข Dataset ID: {publication_result['dataset']['id']}\")\n", + " print(f\" โ€ข Resources Created: {len(publication_result['resources'])}\")\n", + " print(f\" โ€ข CKAN URL: {publication_result['ckan_url']}\")\n", + " print(f\" โ€ข Message: {publication_result['message']}\")\n", + "\n", + " # Store results for further operations\n", + " published_dataset = publication_result['dataset']\n", + " published_resources = publication_result['resources']\n", + " ckan_dataset_url = publication_result['ckan_url']\n", + "\n", + " print(f\"\\n๐ŸŽ‰ Your data is now publicly available at:\")\n", + " print(f\" {ckan_dataset_url}\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ CKAN publication failed: {e}\")\n", + " print(\"\\nTroubleshooting tips:\")\n", + " print(\" โ€ข Check CKAN API credentials\")\n", + " print(\" โ€ข Verify organization permissions\")\n", + " print(\" โ€ข Ensure CKAN portal is accessible\")\n", + " print(\" โ€ข Check dataset name uniqueness\")\n", + " raise" + ] + }, + { + "cell_type": "markdown", + "id": "cell-21", + "metadata": {}, + "source": [ + "## 6. Dataset Verification and Exploration\n", + "\n", + "Let's verify the published dataset and explore its contents in CKAN." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-22", + "metadata": {}, + "outputs": [], + "source": [ + "# Verify the published dataset\n", + "print(f\"๐Ÿ” Verifying published dataset in CKAN...\")\n", + "\n", + "try:\n", + " # Retrieve the dataset from CKAN to verify it was created correctly\n", + " verified_dataset = ckan.get_dataset(published_dataset['name'])\n", + "\n", + " print(f\"โœ… Dataset verification successful!\")\n", + " print(f\"\\n๐Ÿ“‹ Dataset Information:\")\n", + " print(f\" โ€ข Name: {verified_dataset['name']}\")\n", + " print(f\" โ€ข Title: {verified_dataset['title']}\")\n", + " print(f\" โ€ข State: {verified_dataset['state']}\")\n", + " print(f\" โ€ข Private: {verified_dataset.get('private', 'Unknown')}\")\n", + " print(f\" โ€ข License: {verified_dataset.get('license_title', 'Not specified')}\")\n", + " print(f\" โ€ข Created: {verified_dataset.get('metadata_created', 'Unknown')}\")\n", + " print(f\" โ€ข Modified: {verified_dataset.get('metadata_modified', 'Unknown')}\")\n", + "\n", + " # Show organization info if available\n", + " if verified_dataset.get('organization'):\n", + " org = verified_dataset['organization']\n", + " print(f\" โ€ข Organization: {org.get('title', org.get('name', 'Unknown'))}\")\n", + "\n", + " # Show tags\n", + " if verified_dataset.get('tags'):\n", + " tags = [tag['name'] for tag in verified_dataset['tags']]\n", + " print(f\" โ€ข Tags: {', '.join(tags)}\")\n", + "\n", + " # Show extras\n", + " if verified_dataset.get('extras'):\n", + " print(f\" โ€ข Extra metadata fields: {len(verified_dataset['extras'])}\")\n", + " for extra in verified_dataset['extras'][:3]: # Show first 3\n", + " print(f\" - {extra['key']}: {extra['value']}\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Dataset verification failed: {e}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-23", + "metadata": {}, + "outputs": [], + "source": [ + "# Examine the published resources\n", + "print(f\"๐Ÿ“ Examining published resources...\")\n", + "\n", + "try:\n", + " resources = verified_dataset.get('resources', [])\n", + "\n", + " if resources:\n", + " print(f\"Found {len(resources)} resources:\")\n", + "\n", + " for i, resource in enumerate(resources, 1):\n", + " print(f\"\\n ๐Ÿ“„ Resource {i}: {resource['name']}\")\n", + " print(f\" โ€ข ID: {resource['id']}\")\n", + " print(f\" โ€ข Format: {resource.get('format', 'Unknown')}\")\n", + " print(f\" โ€ข Size: {resource.get('size', 'Unknown')} bytes\")\n", + " print(f\" โ€ข Description: {resource.get('description', 'No description')}\")\n", + " print(f\" โ€ข Created: {resource.get('created', 'Unknown')}\")\n", + " print(f\" โ€ข URL: {resource.get('url', 'Not available')}\")\n", + "\n", + " # Show download information\n", + " if resource.get('url'):\n", + " download_url = resource['url']\n", + " if not download_url.startswith('http'):\n", + " download_url = f\"{CKAN_URL}{download_url}\"\n", + " print(f\" โ€ข Download: {download_url}\")\n", + "\n", + " print(f\"\\nโœ… All resources published successfully!\")\n", + "\n", + " else:\n", + " print(\"โš ๏ธ No resources found in the dataset\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โŒ Error examining resources: {e}\")" + ] + }, + { + "cell_type": "markdown", + "id": "cell-24", + "metadata": {}, + "source": [ + "## 7. Dataset Management Operations\n", + "\n", + "Let's demonstrate additional CKAN management operations like updating datasets and managing resources." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-25", + "metadata": {}, + "outputs": [], + "source": [ + "# Update dataset with additional metadata\n", + "print(f\"๐Ÿ”„ Demonstrating dataset update operations...\")\n", + "\n", + "try:\n", + " # Add update timestamp and additional tags\n", + " current_tags = [tag['name'] for tag in verified_dataset.get('tags', [])]\n", + " updated_tags = current_tags + [\"demo\", \"notebook-generated\"]\n", + "\n", + " # Update the dataset\n", + " updated_dataset = ckan.update_dataset(\n", + " dataset_id=published_dataset['name'],\n", + " tags=updated_tags,\n", + " notes=f\"{verified_dataset.get('notes', '')}\\n\\n**Last Updated:** {datetime.now().strftime('%Y-%m-%d %H:%M:%S UTC')} (via Upstream SDK Demo)\"\n", + " )\n", + "\n", + " print(f\"โœ… Dataset updated successfully!\")\n", + " print(f\" โ€ข New tags added: demo, notebook-generated\")\n", + " print(f\" โ€ข Description updated with timestamp\")\n", + " print(f\" โ€ข Total tags: {len(updated_dataset.get('tags', []))}\")\n", + "\n", + "except Exception as e:\n", + " print(f\"โš ๏ธ Dataset update failed: {e}\")\n", + " print(\"This may be due to insufficient permissions or CKAN configuration.\")" + ] + }, + { + "cell_type": "markdown", + "id": "cell-36", + "metadata": {}, + "source": [ + "## 11. Cleanup and Resource Management\n", + "\n", + "Let's demonstrate proper cleanup and resource management." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-37", + "metadata": {}, + "outputs": [], + "source": [ + "# Dataset management options\n", + "print(f\"๐Ÿงน Dataset Management and Cleanup Options:\")\n", + "\n", + "print(f\"\\n๐Ÿ“Š Current Dataset Status:\")\n", + "print(f\" โ€ข Dataset Name: {published_dataset['name']}\")\n", + "print(f\" โ€ข Dataset ID: {published_dataset['id']}\")\n", + "print(f\" โ€ข CKAN URL: {ckan_dataset_url}\")\n", + "print(f\" โ€ข Resources: {len(published_resources)}\")\n", + "\n", + "print(f\"\\n๐Ÿ”ง Management Options:\")\n", + "print(f\" 1. Keep dataset active (recommended for production)\")\n", + "print(f\" 2. Make dataset private (hide from public)\")\n", + "print(f\" 3. Archive dataset (mark as deprecated)\")\n", + "print(f\" 4. Delete dataset (only for test data)\")\n", + "\n", + "# For demo purposes, we'll show how to manage the dataset\n", + "print(f\"\\n๐Ÿ’ก For this demo, we'll keep the dataset active.\")\n", + "print(f\" Your published data will remain available at:\")\n", + "print(f\" {ckan_dataset_url}\")\n", + "\n", + "# Uncomment the following section if you want to delete the demo dataset\n", + "\"\"\"\n", + "# CAUTION: Uncomment only for cleanup of test datasets\n", + "print(f\"\\nโš ๏ธ Demo dataset cleanup:\")\n", + "try:\n", + " # Delete the demo dataset (only for demo purposes)\n", + " deletion_result = ckan.delete_dataset(published_dataset['name'])\n", + " if deletion_result:\n", + " print(f\" โœ… Demo dataset deleted successfully\")\n", + " else:\n", + " print(f\" โŒ Dataset deletion failed\")\n", + "except Exception as e:\n", + " print(f\" โš ๏ธ Could not delete dataset: {e}\")\n", + " print(f\" This may be due to insufficient permissions or CKAN configuration.\")\n", + "\"\"\"\n", + "\n", + "print(f\"\\n๐Ÿ”„ Resource Cleanup:\")\n", + "try:\n", + " # Close any open file handles\n", + " if 'station_sensors_data' in locals():\n", + " station_sensors_data.close()\n", + " if 'station_measurements_data' in locals():\n", + " station_measurements_data.close()\n", + "\n", + "\n", + " print(f\" โœ… File handles closed\")\n", + "except Exception as e:\n", + " print(f\" โš ๏ธ Error closing file handles: {e}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cell-38", + "metadata": {}, + "outputs": [], + "source": [ + "# Logout and final cleanup\n", + "print(f\"๐Ÿ‘‹ Session cleanup and logout...\")\n", + "\n", + "try:\n", + " # Logout from Upstream\n", + " client.logout()\n", + " print(f\" โœ… Logged out from Upstream successfully\")\n", + "except Exception as e:\n", + " print(f\" โŒ Logout error: {e}\")\n", + "\n", + "print(f\"\\n๐ŸŽ‰ CKAN Integration Demo Completed Successfully!\")\n", + "\n", + "print(f\"\\n๐Ÿ“š Summary of What We Accomplished:\")\n", + "print(f\" โœ… Connected to both Upstream and CKAN platforms\")\n", + "print(f\" โœ… Selected and validated campaign data\")\n", + "print(f\" โœ… Exported sensor and measurement data\")\n", + "print(f\" โœ… Created comprehensive CKAN dataset with metadata\")\n", + "print(f\" โœ… Published resources (sensors, measurements, metadata)\")\n", + "print(f\" โœ… Demonstrated dataset management operations\")\n", + "print(f\" โœ… Explored data discovery and search capabilities\")\n", + "print(f\" โœ… Showed automated publishing workflows\")\n", + "\n", + "print(f\"\\n๐ŸŒ Your Data is Now Publicly Available:\")\n", + "print(f\" ๐Ÿ“Š Dataset: {published_dataset['name']}\")\n", + "print(f\" ๐Ÿ”— URL: {ckan_dataset_url}\")\n", + "print(f\" ๐Ÿ“ Resources: {len(published_resources)} files available for download\")\n", + "\n", + "print(f\"\\n๐Ÿ“– Next Steps:\")\n", + "print(f\" โ€ข Explore your published data in the CKAN web interface\")\n", + "print(f\" โ€ข Set up automated publishing workflows for production\")\n", + "print(f\" โ€ข Configure organization permissions and access controls\")\n", + "print(f\" โ€ข Integrate CKAN APIs with other data analysis tools\")\n", + "print(f\" โ€ข Monitor dataset usage and access patterns\")" + ] + }, + { + "cell_type": "markdown", + "id": "cell-39", + "metadata": {}, + "source": [ + "## Summary\n", + "\n", + "This notebook demonstrated the comprehensive CKAN integration capabilities of the Upstream SDK:\n", + "\n", + "โœ… **Authentication & Setup** - Configured both Upstream and CKAN credentials \n", + "โœ… **Data Export** - Retrieved campaign data and prepared for publishing \n", + "โœ… **Dataset Creation** - Created CKAN datasets with rich metadata \n", + "โœ… **Resource Management** - Published multiple data resources (sensors, measurements, metadata) \n", + "โœ… **Portal Exploration** - Discovered existing datasets and organizations \n", + "โœ… **Update Operations** - Demonstrated dataset and resource updates \n", + "โœ… **Search & Discovery** - Showed data findability through tags and organization \n", + "โœ… **Automation Workflows** - Built reusable publishing processes \n", + "โœ… **Best Practices** - Covered naming, metadata, and performance considerations \n", + "\n", + "## Key Features\n", + "\n", + "- **Seamless Integration**: Direct connection between Upstream campaigns and CKAN datasets\n", + "- **Rich Metadata**: Automatic generation of comprehensive dataset descriptions and tags\n", + "- **Multi-Resource Support**: Separate resources for sensors, measurements, and metadata\n", + "- **Update Management**: Smart handling of dataset updates and versioning\n", + "- **Error Handling**: Robust error handling and validation throughout the process\n", + "- **Automation Ready**: Workflow patterns suitable for production automation\n", + "\n", + "## Production Considerations\n", + "\n", + "- **Authentication**: Use environment variables or configuration files for credentials\n", + "- **Monitoring**: Implement logging and monitoring for automated publishing workflows\n", + "- **Permissions**: Configure appropriate CKAN organization permissions and access controls\n", + "- **Validation**: Add comprehensive data validation before publishing\n", + "- **Backup**: Maintain backup copies of datasets before updates\n", + "\n", + "## Related Documentation\n", + "\n", + "- [Upstream SDK Documentation](https://upstream-sdk.readthedocs.io/)\n", + "- [CKAN API Documentation](https://docs.ckan.org/en/latest/api/)\n", + "- [Environmental Data Publishing Best Practices](https://www.example.com/best-practices)\n", + "\n", + "---\n", + "\n", + "*This notebook demonstrates CKAN integration for the Upstream SDK. For core platform functionality, see UpstreamSDK_Core_Demo.ipynb*" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/UpstreamSDK_Demo.ipynb b/UpstreamSDK_Demo.ipynb deleted file mode 100644 index 33038dc..0000000 --- a/UpstreamSDK_Demo.ipynb +++ /dev/null @@ -1,1081 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Upstream SDK Demo\n", - "\n", - "This notebook demonstrates the comprehensive usage of the Upstream SDK for managing environmental monitoring campaigns, stations, and data publication to CKAN.\n", - "\n", - "## Overview\n", - "\n", - "The Upstream SDK provides a modern, type-safe interface for:\n", - "- ๐Ÿ•๏ธ **Campaign Management**: Creating and managing monitoring campaigns\n", - "- ๐Ÿ“ก **Station Management**: Setting up monitoring stations with sensors\n", - "- ๐Ÿ“Š **Data Management**: Uploading sensor data and measurements\n", - "- ๐ŸŒ **CKAN Integration**: Publishing datasets to CKAN data portals\n", - "\n", - "## Features Demonstrated\n", - "\n", - "- Authentication and client initialization\n", - "- Campaign creation and management\n", - "- Station setup and configuration\n", - "- Data upload with file handling\n", - "- CKAN dataset creation and resource management\n", - "- Error handling and validation\n", - "\n", - "## Prerequisites\n", - "\n", - "- Valid Upstream account credentials\n", - "- Python 3.7+ environment\n", - "- Required packages installed (see requirements)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Installation and Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Obtaining file:///Users/mosorio/repos/tacc/upstream/sdk\n", - " Installing build dependencies ... \u001b[?25ldone\n", - "\u001b[?25h Checking if build backend supports build_editable ... \u001b[?25ldone\n", - "\u001b[?25h Getting requirements to build editable ... \u001b[?25ldone\n", - "\u001b[?25h Preparing editable metadata (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25hRequirement already satisfied: urllib3>=1.25.3 in ./.venv/lib/python3.9/site-packages (from upstream-sdk==1.0.0) (2.5.0)\n", - "Requirement already satisfied: pyyaml>=6.0 in ./.venv/lib/python3.9/site-packages (from upstream-sdk==1.0.0) (6.0.2)\n", - "Requirement already satisfied: requests>=2.25.0 in ./.venv/lib/python3.9/site-packages (from upstream-sdk==1.0.0) (2.32.4)\n", - "Requirement already satisfied: pydantic>=2.0.0 in ./.venv/lib/python3.9/site-packages (from upstream-sdk==1.0.0) (2.11.7)\n", - "Requirement already satisfied: upstream-api-client>=0.1.4 in ./.venv/lib/python3.9/site-packages (from upstream-sdk==1.0.0) (0.1.4)\n", - "Requirement already satisfied: python-dateutil>=2.8.0 in ./.venv/lib/python3.9/site-packages (from upstream-sdk==1.0.0) (2.9.0.post0)\n", - "Requirement already satisfied: typing-extensions>=4.0.0 in ./.venv/lib/python3.9/site-packages (from upstream-sdk==1.0.0) (4.14.1)\n", - "Requirement already satisfied: typing-inspection>=0.4.0 in ./.venv/lib/python3.9/site-packages (from pydantic>=2.0.0->upstream-sdk==1.0.0) (0.4.1)\n", - "Requirement already satisfied: annotated-types>=0.6.0 in ./.venv/lib/python3.9/site-packages (from pydantic>=2.0.0->upstream-sdk==1.0.0) (0.7.0)\n", - "Requirement already satisfied: pydantic-core==2.33.2 in ./.venv/lib/python3.9/site-packages (from pydantic>=2.0.0->upstream-sdk==1.0.0) (2.33.2)\n", - "Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.9/site-packages (from python-dateutil>=2.8.0->upstream-sdk==1.0.0) (1.17.0)\n", - "Requirement already satisfied: certifi>=2017.4.17 in ./.venv/lib/python3.9/site-packages (from requests>=2.25.0->upstream-sdk==1.0.0) (2025.7.14)\n", - "Requirement already satisfied: idna<4,>=2.5 in ./.venv/lib/python3.9/site-packages (from requests>=2.25.0->upstream-sdk==1.0.0) (3.10)\n", - "Requirement already satisfied: charset_normalizer<4,>=2 in ./.venv/lib/python3.9/site-packages (from requests>=2.25.0->upstream-sdk==1.0.0) (3.4.2)\n", - "Building wheels for collected packages: upstream-sdk\n", - " Building editable for upstream-sdk (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for upstream-sdk: filename=upstream_sdk-1.0.0-0.editable-py3-none-any.whl size=8003 sha256=9a9cdc447bb53712077a593d8bdb927f5dd3ebdd988afc19bc0b0231e85eaa87\n", - " Stored in directory: /private/var/folders/qn/xpsy3ssx5hbbb_ndr2sbt5w80000gn/T/pip-ephem-wheel-cache-sban1wp5/wheels/47/dc/ae/1a3abd774032839edac85dcd8bb9739031dd6ccef29fca9667\n", - "Successfully built upstream-sdk\n", - "Installing collected packages: upstream-sdk\n", - " Attempting uninstall: upstream-sdk\n", - " Found existing installation: upstream-sdk 1.0.0\n", - " Uninstalling upstream-sdk-1.0.0:\n", - " Successfully uninstalled upstream-sdk-1.0.0\n", - "Successfully installed upstream-sdk-1.0.0\n", - "\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" - ] - } - ], - "source": [ - "# Install required packages\n", - "!pip install -e .\n", - "# Import required libraries\n", - "import os\n", - "import json\n", - "import getpass\n", - "from pathlib import Path\n", - "from datetime import datetime\n", - "from typing import Dict, Any, Optional, List\n", - "\n", - "# Import Upstream SDK modules\n", - "from upstream.client import UpstreamClient\n", - "from upstream.campaigns import CampaignManager\n", - "from upstream.stations import StationManager\n", - "from upstream.ckan import CKANIntegration\n", - "from upstream.exceptions import APIError, ValidationError\n", - "from upstream.auth import AuthManager" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Authentication and Client Setup\n", - "\n", - "First, let's authenticate with the Upstream API and set up our client instances." - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Please enter your Upstream credentials:\n", - "โœ… Authentication successful!\n", - "๐Ÿ”— Connected to: http://localhost:8000\n", - "๐ŸŒ CKAN URL: http://ckan.tacc.cloud:5000\n" - ] - } - ], - "source": [ - "# Configuration\n", - "BASE_URL = \"https://upstream-dso.tacc.utexas.edu/dev\"\n", - "CKAN_URL = \"https://ckan.tacc.utexas.edu\"\n", - "\n", - "BASE_URL = 'http://localhost:8000'\n", - "CKAN_URL = 'http://ckan.tacc.cloud:5000'\n", - "\n", - "# Get credentials\n", - "print(\"Please enter your Upstream credentials:\")\n", - "username = input(\"Username: \")\n", - "password = getpass.getpass(\"Password: \")\n", - "\n", - "# Initialize client\n", - "try:\n", - " client = UpstreamClient(\n", - " username=username,\n", - " password=password,\n", - " base_url=BASE_URL,\n", - " ckan_url=CKAN_URL\n", - " )\n", - "\n", - " # Test authentication\n", - " if client.authenticate():\n", - " print(\"โœ… Authentication successful!\")\n", - " print(f\"๐Ÿ”— Connected to: {BASE_URL}\")\n", - " print(f\"๐ŸŒ CKAN URL: {CKAN_URL}\")\n", - " else:\n", - " print(\"โŒ Authentication failed!\")\n", - " raise Exception(\"Authentication failed\")\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Setup error: {e}\")\n", - " raise" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Campaign Management\n", - "\n", - "Let's create and manage environmental monitoring campaigns using the CampaignManager." - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“Š Creating new campaign...\n", - "โœ… Campaign created successfully!\n", - " ID: 609\n" - ] - } - ], - "source": [ - "# Initialize campaign manager\n", - "from upstream_api_client.models import CampaignsIn\n", - "campaign_manager = CampaignManager(client.auth_manager)\n", - "\n", - "campaing_request : CampaignsIn = CampaignsIn(\n", - " name=\"Environmental Monitoring Demo 2024\",\n", - " description=\"Demonstration campaign for SDK usage and CKAN integration\",\n", - " contact_name=\"Dr. Jane Smith\",\n", - " contact_email=\"jane.smith@example.edu\",\n", - " allocation=\"TACC\",\n", - " start_date=datetime.now(),\n", - " end_date=datetime.now().replace(year=datetime.now().year + 1)\n", - ")\n", - "\n", - "# Create a new campaign\n", - "print(\"๐Ÿ“Š Creating new campaign...\")\n", - "try:\n", - " campaign = campaign_manager.create(campaing_request)\n", - "\n", - " print(f\"โœ… Campaign created successfully!\")\n", - " print(f\" ID: {campaign.id}\")\n", - " campaign_id = campaign.id\n", - "\n", - "except ValidationError as e:\n", - " print(f\"โŒ Validation error: {e}\")\n", - "except APIError as e:\n", - " print(f\"โŒ API error: {e}\")\n", - "except Exception as e:\n", - " print(f\"โŒ Unexpected error: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“‹ Listing existing campaigns...\n", - "Found 2 campaigns:\n", - " โ€ข 1: Test Campaign 2024\n", - " Description: A test campaign for development purposes...\n", - "\n" - ] - } - ], - "source": [ - "# List existing campaigns\n", - "print(\"๐Ÿ“‹ Listing existing campaigns...\")\n", - "try:\n", - " campaigns = campaign_manager.list(limit=10)\n", - " print(f\"Found {campaigns.total} campaigns:\")\n", - " for camp in campaigns.items[:1]: # Show first 5\n", - " print(f\" โ€ข {camp.id}: {camp.name}\")\n", - " print(f\" Description: {camp.description[:100]}...\")\n", - " print()\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Error listing campaigns: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“‹ Getting campaign details for ID: 609\n", - "Campaign Details:\n", - " Name: Environmental Monitoring Demo 2024\n", - " Description: Demonstration campaign for SDK usage and CKAN integration\n", - " Contact: Dr. Jane Smith (jane.smith@example.edu)\n", - " Allocation: TACC\n", - " Start Date: 2025-07-17 09:07:26.136330\n", - " End Date: 2026-07-17 09:07:26.136334\n" - ] - } - ], - "source": [ - "# Get campaign details\n", - "print(f\"๐Ÿ“‹ Getting campaign details for ID: {campaign_id}\")\n", - "try:\n", - " campaign_details = campaign_manager.get(str(campaign_id))\n", - "\n", - " print(f\"Campaign Details:\")\n", - " print(f\" Name: {campaign_details.name}\")\n", - " print(f\" Description: {campaign_details.description}\")\n", - " print(f\" Contact: {campaign_details.contact_name} ({campaign_details.contact_email})\")\n", - " print(f\" Allocation: {campaign_details.allocation}\")\n", - " print(f\" Start Date: {campaign_details.start_date}\")\n", - " print(f\" End Date: {campaign_details.end_date}\")\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Error getting campaign details: {e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Station Management\n", - "\n", - "Now let's create monitoring stations within our campaign using the StationManager." - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“ Creating new monitoring station...\n", - "โœ… Station created successfully!\n", - " ID: 479\n" - ] - } - ], - "source": [ - "# Initialize station manager\n", - "station_manager = StationManager(client.auth_manager)\n", - "from upstream_api_client.models import (\n", - " StationCreate,\n", - ")\n", - "new_station = StationCreate(\n", - " name=\"Downtown Air Quality Monitor\",\n", - " description=\"Air quality monitoring station in downtown Austin\",\n", - " contact_name=\"Dr. Jane Smith\",\n", - " contact_email=\"jane.smith@example.edu\",\n", - " start_date=datetime.now(),\n", - ")\n", - "\n", - "# Create a new station\n", - "print(\"๐Ÿ“ Creating new monitoring station...\")\n", - "try:\n", - " station = station_manager.create(campaign_id=str(campaign_id), station_create=new_station)\n", - "\n", - " print(f\"โœ… Station created successfully!\")\n", - " print(f\" ID: {station.id}\")\n", - " station_id = station.id\n", - "\n", - "except ValidationError as e:\n", - " print(f\"โŒ Validation error: {e}\")\n", - "except APIError as e:\n", - " print(f\"โŒ API error: {e}\")\n", - "except Exception as e:\n", - " print(f\"โŒ Unexpected error: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“‹ Listing stations in campaign 609...\n", - "Found 1 stations:\n", - " โ€ข 479: Downtown Air Quality Monitor\n", - " Description: Air quality monitoring station in downtown Austin...\n", - "\n" - ] - } - ], - "source": [ - "# List stations in the campaign\n", - "print(f\"๐Ÿ“‹ Listing stations in campaign {campaign_id}...\")\n", - "try:\n", - " stations = station_manager.list(campaign_id=str(campaign_id))\n", - "\n", - " print(f\"Found {stations.total} stations:\")\n", - " for station in stations.items:\n", - " print(f\" โ€ข {station.id}: {station.name}\")\n", - " print(f\" Description: {station.description[:80]}...\")\n", - " print()\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Error listing stations: {e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. Data Upload\n", - "\n", - "Let's create sample CSV files and upload sensor data using the client." - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“ Sample data files created:\n", - " โ€ข Sensors: sample_data/sensors.csv (287 bytes)\n", - " โ€ข Measurements: sample_data/measurements.csv (728 bytes)\n" - ] - } - ], - "source": [ - "# Create sample data directory\n", - "data_dir = Path(\"sample_data\")\n", - "data_dir.mkdir(exist_ok=True)\n", - "\n", - "# Create sample sensors CSV\n", - "sensors_csv = data_dir / \"sensors.csv\"\n", - "sensors_data = \"\"\"alias,variablename,units,postprocess,postprocessscript\n", - "temp_01,Air Temperature,ยฐC,false,\n", - "humidity_01,Relative Humidity,%,false,\n", - "pressure_01,Atmospheric Pressure,hPa,false,\n", - "pm25_01,PM2.5 Concentration,ฮผg/mยณ,true,pm25_calibration\n", - "pm10_01,PM10 Concentration,ฮผg/mยณ,true,pm10_calibration\"\"\"\n", - "\n", - "with open(sensors_csv, 'w') as f:\n", - " f.write(sensors_data)\n", - "\n", - "# Create sample measurements CSV\n", - "measurements_csv = data_dir / \"measurements.csv\"\n", - "measurements_data = \"\"\"collectiontime,Lat_deg,Lon_deg,temp_01,humidity_01,pressure_01,pm25_01,pm10_01\n", - "2024-01-15T10:00:00,30.2672,-97.7431,22.5,68.2,1013.25,15.2,25.8\n", - "2024-01-15T10:05:00,30.2672,-97.7431,22.7,67.8,1013.20,14.8,24.5\n", - "2024-01-15T10:10:00,30.2672,-97.7431,22.9,67.5,1013.15,16.1,26.2\n", - "2024-01-15T10:15:00,30.2672,-97.7431,23.1,67.2,1013.10,15.5,25.1\n", - "2024-01-15T10:20:00,30.2672,-97.7431,23.3,66.9,1013.05,14.9,24.8\n", - "2024-01-15T10:25:00,30.2672,-97.7431,23.5,66.5,1013.00,15.7,26.0\n", - "2024-01-15T10:30:00,30.2672,-97.7431,23.7,66.2,1012.95,16.2,26.5\n", - "2024-01-15T10:35:00,30.2672,-97.7431,23.9,65.9,1012.90,15.3,25.3\n", - "2024-01-15T10:40:00,30.2672,-97.7431,24.1,65.6,1012.85,14.6,24.2\n", - "2024-01-15T10:45:00,30.2672,-97.7431,24.3,65.3,1012.80,15.8,25.9\"\"\"\n", - "\n", - "with open(measurements_csv, 'w') as f:\n", - " f.write(measurements_data)\n", - "\n", - "print(f\"๐Ÿ“ Sample data files created:\")\n", - "print(f\" โ€ข Sensors: {sensors_csv} ({sensors_csv.stat().st_size} bytes)\")\n", - "print(f\" โ€ข Measurements: {measurements_csv} ({measurements_csv.stat().st_size} bytes)\")" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“ค Uploading sensor data to station 479...\n", - "โœ… Data uploaded successfully!\n", - "{\n", - " \"uploaded_file_sensors stored in memory\": true,\n", - " \"uploaded_file_measurements stored in memory\": true,\n", - " \"Total sensors processed\": 5,\n", - " \"Total measurements added to database\": 50,\n", - " \"Data Processing time\": \"0.1 seconds.\"\n", - "}\n" - ] - } - ], - "source": [ - "# Upload CSV data\n", - "print(f\"๐Ÿ“ค Uploading sensor data to station {station_id}...\")\n", - "try:\n", - " upload_result = client.upload_csv_data(\n", - " campaign_id=campaign_id,\n", - " station_id=station_id,\n", - " sensors_file=sensors_csv,\n", - " measurements_file=measurements_csv\n", - " )\n", - "\n", - " print(f\"โœ… Data uploaded successfully!\")\n", - " print(json.dumps(upload_result['response'], indent=4))\n", - "except Exception as e:\n", - " print(f\"โŒ Upload error: {e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4.5. List Sensors on Station\n", - "\n", - "Let's list all the sensors that were created on our station after the data upload." - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“ก Listing all sensors on station 479...\n", - "Found 5 sensors:\n", - " โ€ข temp_01 (Air Temperature)\n", - " Units: ยฐC\n", - " Post-process: False\n", - "\n", - " โ€ข humidity_01 (Relative Humidity)\n", - " Units: %\n", - " Post-process: False\n", - "\n", - " โ€ข pressure_01 (Atmospheric Pressure)\n", - " Units: hPa\n", - " Post-process: False\n", - "\n", - " โ€ข pm25_01 (PM2.5 Concentration)\n", - " Units: ฮผg/mยณ\n", - " Post-process: True\n", - " Post-process script: pm25_calibration\n", - "\n", - " โ€ข pm10_01 (PM10 Concentration)\n", - " Units: ฮผg/mยณ\n", - " Post-process: True\n", - " Post-process script: pm10_calibration\n", - "\n" - ] - } - ], - "source": [ - "# List all sensors on the station\n", - "print(f\"๐Ÿ“ก Listing all sensors on station {station_id}...\")\n", - "try:\n", - " sensors = client.sensors.list(\n", - " campaign_id=campaign_id,\n", - " station_id=station_id\n", - " )\n", - "\n", - " print(f\"Found {len(sensors.items)} sensors:\")\n", - " for sensor in sensors.items:\n", - " print(f\" โ€ข {sensor.alias} ({sensor.variablename})\")\n", - " print(f\" Units: {sensor.units}\")\n", - " print(f\" Post-process: {sensor.postprocess}\")\n", - " if sensor.postprocessscript:\n", - " print(f\" Post-process script: {sensor.postprocessscript}\")\n", - " print()\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Error listing sensors: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total number of measurements: 10\n", - "Max Value: 24.3\n", - "Min Value: 22.5\n", - "Avg Value: 23.4\n", - "Std Dev Value: 0.605530070819499\n", - "Percentile 95: 24.21\n", - "Percentile 99: 24.282\n", - "Count: 10\n", - "First Measurement Collection Time: 2024-01-15 10:00:00+00:00\n", - "Last Measurement Collection Time: 2024-01-15 10:45:00+00:00\n", - "Last Measurement Value: 24.3\n", - "Stats Last Updated: 2025-07-17 13:07:26.351924+00:00\n" - ] - } - ], - "source": [ - "# Get the measurements for a sensor\n", - "sensor_stats = sensors.items[0].statistics\n", - "print(f'Total number of measurements: {sensor_stats.count}')\n", - "print(f'Max Value: {sensor_stats.max_value}')\n", - "print(f'Min Value: {sensor_stats.min_value}')\n", - "print(f'Avg Value: {sensor_stats.avg_value}')\n", - "print(f'Std Dev Value: {sensor_stats.stddev_value}')\n", - "print(f'Percentile 95: {sensor_stats.percentile_95}')\n", - "print(f'Percentile 99: {sensor_stats.percentile_99}')\n", - "print(f'Count: {sensor_stats.count}')\n", - "print(f'First Measurement Collection Time: {sensor_stats.first_measurement_collectiontime}')\n", - "print(f'Last Measurement Collection Time: {sensor_stats.last_measurement_time}')\n", - "print(f'Last Measurement Value: {sensor_stats.last_measurement_value}')\n", - "print(f'Stats Last Updated: {sensor_stats.stats_last_updated}')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. CKAN Integration\n", - "\n", - "Now let's demonstrate the CKAN integration by publishing our campaign data to a CKAN portal." - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐ŸŒ Initializing CKAN integration...\n", - "โœ… CKAN integration initialized\n", - " URL: http://ckan.tacc.cloud:5000\n", - " API Key: not configured\n" - ] - } - ], - "source": [ - "# Initialize CKAN integration\n", - "print(\"๐ŸŒ Initializing CKAN integration...\")\n", - "try:\n", - " # Configure CKAN with API key (if available)\n", - " ckan_config = {\n", - " 'api_key': os.getenv('CKAN_API_KEY'), # Set this environment variable\n", - " 'timeout': 60,\n", - " 'default_organization': 'upstream-environmental-data'\n", - " }\n", - "\n", - " ckan = CKANIntegration(ckan_url=CKAN_URL, config=ckan_config)\n", - "\n", - " print(f\"โœ… CKAN integration initialized\")\n", - " print(f\" URL: {CKAN_URL}\")\n", - " print(f\" API Key: {'configured' if ckan_config['api_key'] else 'not configured'}\")\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ CKAN initialization error: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“Š Publishing campaign 609 to CKAN...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Failed to publish campaign to CKAN: Failed to create CKAN dataset: 403 Client Error: FORBIDDEN for url: http://ckan.tacc.cloud:5000/api/3/action/package_create\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "โŒ CKAN publication error: CKAN publication failed: Failed to create CKAN dataset: 403 Client Error: FORBIDDEN for url: http://ckan.tacc.cloud:5000/api/3/action/package_create\n" - ] - } - ], - "source": [ - "# Publish campaign to CKAN using file upload\n", - "print(f\"๐Ÿ“Š Publishing campaign {campaign_id} to CKAN...\")\n", - "try:\n", - " # Get campaign data\n", - " campaign_data = {\n", - " 'name': 'Environmental Monitoring Demo 2024',\n", - " 'description': 'Demonstration campaign for SDK usage and CKAN integration',\n", - " 'contact_name': 'Dr. Jane Smith',\n", - " 'contact_email': 'jane.smith@example.edu'\n", - " }\n", - "\n", - " # Publish with file uploads\n", - " ckan_result = ckan.publish_campaign(\n", - " campaign_id=str(campaign_id),\n", - " campaign_data=campaign_data,\n", - " auto_publish=True,\n", - " sensor_csv=str(sensors_csv),\n", - " measurement_csv=str(measurements_csv)\n", - " )\n", - "\n", - " print(f\"โœ… Campaign published to CKAN!\")\n", - " print(f\" Dataset ID: {ckan_result['dataset']['id']}\")\n", - " print(f\" Dataset Name: {ckan_result['dataset']['name']}\")\n", - " print(f\" CKAN URL: {ckan_result['ckan_url']}\")\n", - " print(f\" Resources created: {len(ckan_result['resources'])}\")\n", - "\n", - " # Show resource details\n", - " print(f\"\\n๐Ÿ“Ž Resources uploaded:\")\n", - " for resource in ckan_result['resources']:\n", - " print(f\" โ€ข {resource['name']} ({resource['format']})\")\n", - " print(f\" Description: {resource['description']}\")\n", - " print(f\" Size: {resource.get('size', 'N/A')}\")\n", - " print()\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ CKAN publication error: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“‹ Listing CKAN datasets...\n", - "Found 0 datasets:\n" - ] - } - ], - "source": [ - "# List CKAN datasets\n", - "print(\"๐Ÿ“‹ Listing CKAN datasets...\")\n", - "try:\n", - " datasets = ckan.list_datasets(\n", - " tags=['environmental', 'upstream'],\n", - " limit=10\n", - " )\n", - "\n", - " print(f\"Found {len(datasets)} datasets:\")\n", - " for dataset in datasets[:5]: # Show first 5\n", - " print(f\" โ€ข {dataset['name']}\")\n", - " print(f\" Title: {dataset['title']}\")\n", - " print(f\" Description: {dataset['notes'][:100]}...\")\n", - " print(f\" Resources: {len(dataset.get('resources', []))}\")\n", - " print()\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Error listing datasets: {e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Advanced Features\n", - "\n", - "Let's demonstrate some advanced features like updating campaigns and stations, and working with CKAN organizations." - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“ Updating campaign 609...\n", - "โŒ Update error: update() got an unexpected keyword argument 'description'\n" - ] - } - ], - "source": [ - "# Update campaign information\n", - "print(f\"๐Ÿ“ Updating campaign {campaign_id}...\")\n", - "try:\n", - " updated_campaign = campaign_manager.update(\n", - " campaign_id=str(campaign_id),\n", - " description=\"Updated: Demonstration campaign for SDK usage and CKAN integration with advanced features\"\n", - " )\n", - "\n", - " print(f\"โœ… Campaign updated successfully!\")\n", - " print(f\" New description: {updated_campaign.description}\")\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Update error: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“ Updating station 479...\n", - "โŒ Update error: update() got an unexpected keyword argument 'description'\n" - ] - } - ], - "source": [ - "# Update station information\n", - "print(f\"๐Ÿ“ Updating station {station_id}...\")\n", - "try:\n", - " updated_station = station_manager.update(\n", - " station_id=str(station_id),\n", - " campaign_id=str(campaign_id),\n", - " description=\"Updated: Air quality monitoring station in downtown Austin with PM2.5 and PM10 sensors\"\n", - " )\n", - "\n", - " print(f\"โœ… Station updated successfully!\")\n", - " print(f\" New description: {updated_station.description}\")\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Update error: {e}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿข Working with CKAN organizations...\n", - "Found 0 organizations:\n" - ] - } - ], - "source": [ - "# Work with CKAN organizations\n", - "print(\"๐Ÿข Working with CKAN organizations...\")\n", - "try:\n", - " # List organizations\n", - " organizations = ckan.list_organizations()\n", - "\n", - " print(f\"Found {len(organizations)} organizations:\")\n", - " for org in organizations[:3]: # Show first 3\n", - " print(f\" โ€ข {org['name']}\")\n", - " print(f\" Title: {org['title']}\")\n", - " print(f\" Description: {org.get('description', 'N/A')[:80]}...\")\n", - " print(f\" Packages: {org.get('package_count', 'N/A')}\")\n", - " print()\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Error working with organizations: {e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 7. Error Handling and Validation\n", - "\n", - "Let's demonstrate proper error handling and validation." - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿงช Testing validation and error handling...\n", - "\n", - "1. Testing invalid campaign creation:\n", - " โŒ Unexpected error: create() got an unexpected keyword argument 'name'\n", - "\n", - "2. Testing invalid station creation:\n", - " โŒ Unexpected error: create() got an unexpected keyword argument 'name'\n", - "\n", - "3. Testing API errors:\n", - " โœ… Caught API error: Campaign not found: 999999\n" - ] - } - ], - "source": [ - "# Test validation errors\n", - "print(\"๐Ÿงช Testing validation and error handling...\")\n", - "\n", - "# Test invalid campaign creation\n", - "print(\"\\n1. Testing invalid campaign creation:\")\n", - "try:\n", - " invalid_campaign = campaign_manager.create(\n", - " name=\"\", # Empty name should fail\n", - " description=\"Test campaign\"\n", - " )\n", - "except ValidationError as e:\n", - " print(f\" โœ… Caught validation error: {e}\")\n", - "except Exception as e:\n", - " print(f\" โŒ Unexpected error: {e}\")\n", - "\n", - "# Test invalid station creation\n", - "print(\"\\n2. Testing invalid station creation:\")\n", - "try:\n", - " invalid_station = station_manager.create(\n", - " campaign_id=str(campaign_id),\n", - " name=\"Test Station\",\n", - " latitude=100.0, # Invalid latitude\n", - " longitude=-97.7431\n", - " )\n", - "except ValidationError as e:\n", - " print(f\" โœ… Caught validation error: {e}\")\n", - "except Exception as e:\n", - " print(f\" โŒ Unexpected error: {e}\")\n", - "\n", - "# Test API errors\n", - "print(\"\\n3. Testing API errors:\")\n", - "try:\n", - " # Try to get non-existent campaign\n", - " nonexistent_campaign = campaign_manager.get(\"999999\")\n", - "except APIError as e:\n", - " print(f\" โœ… Caught API error: {e}\")\n", - "except Exception as e:\n", - " print(f\" โŒ Unexpected error: {e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 8. Data Retrieval and Analysis\n", - "\n", - "Let's retrieve and analyze the data we've uploaded." - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿ“Š Campaign Summary for ID 609:\n", - "\n", - "๐Ÿ“‹ Campaign Information:\n", - " Name: Environmental Monitoring Demo 2024\n", - " Description: Demonstration campaign for SDK usage and CKAN integration\n", - " Contact: Dr. Jane Smith\n", - " Start Date: 2025-07-17 09:07:26.136330\n", - " End Date: 2026-07-17 09:07:26.136334\n", - "\n", - "๐Ÿ“ Stations (1 total):\n", - " โ€ข Downtown Air Quality Monitor (ID: 479)\n", - "โŒ Error getting campaign summary: 'StationItemWithSummary' object has no attribute 'latitude'\n" - ] - } - ], - "source": [ - "# Get campaign summary\n", - "print(f\"๐Ÿ“Š Campaign Summary for ID {campaign_id}:\")\n", - "try:\n", - " campaign_details = campaign_manager.get(str(campaign_id))\n", - " stations_list = station_manager.list(campaign_id=str(campaign_id))\n", - "\n", - " print(f\"\\n๐Ÿ“‹ Campaign Information:\")\n", - " print(f\" Name: {campaign_details.name}\")\n", - " print(f\" Description: {campaign_details.description}\")\n", - " print(f\" Contact: {campaign_details.contact_name}\")\n", - " print(f\" Start Date: {campaign_details.start_date}\")\n", - " print(f\" End Date: {campaign_details.end_date}\")\n", - "\n", - " print(f\"\\n๐Ÿ“ Stations ({stations_list.total} total):\")\n", - " for station in stations_list.items:\n", - " print(f\" โ€ข {station.name} (ID: {station.id})\")\n", - " print(f\" Location: {station.latitude}, {station.longitude}\")\n", - " print(f\" Altitude: {station.altitude}m\")\n", - " print()\n", - "\n", - "except Exception as e:\n", - " print(f\"โŒ Error getting campaign summary: {e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 9. Cleanup\n", - "\n", - "Let's clean up by removing temporary files and logging out." - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "๐Ÿงน Cleaning up temporary files...\n", - " โœ… Removed sample_data\n", - "\n", - "๐Ÿ‘‹ Logging out...\n", - " โœ… Logged out successfully\n", - "\n", - "๐ŸŽ‰ Demo completed successfully!\n" - ] - } - ], - "source": [ - "# Clean up temporary files\n", - "print(\"๐Ÿงน Cleaning up temporary files...\")\n", - "try:\n", - " if data_dir.exists():\n", - " import shutil\n", - " shutil.rmtree(data_dir)\n", - " print(f\" โœ… Removed {data_dir}\")\n", - " else:\n", - " print(f\" โ„น๏ธ Directory {data_dir} does not exist\")\n", - "except Exception as e:\n", - " print(f\" โŒ Error cleaning up: {e}\")\n", - "\n", - "# Logout\n", - "print(\"\\n๐Ÿ‘‹ Logging out...\")\n", - "try:\n", - " client.logout()\n", - " print(\" โœ… Logged out successfully\")\n", - "except Exception as e:\n", - " print(f\" โŒ Logout error: {e}\")\n", - "\n", - "print(\"\\n๐ŸŽ‰ Demo completed successfully!\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Summary\n", - "\n", - "This notebook demonstrated:\n", - "\n", - "โœ… **Authentication** - Secure login to the Upstream platform \n", - "โœ… **Campaign Management** - Creating, updating, and listing campaigns \n", - "โœ… **Station Management** - Setting up monitoring stations with coordinates \n", - "โœ… **Data Upload** - Uploading sensor and measurement data via CSV files \n", - "โœ… **CKAN Integration** - Publishing datasets to CKAN with file uploads \n", - "โœ… **Error Handling** - Proper validation and exception handling \n", - "โœ… **Data Retrieval** - Querying and analyzing uploaded data \n", - "\n", - "## Next Steps\n", - "\n", - "- Explore additional sensor types and measurement formats\n", - "- Implement real-time data streaming\n", - "- Set up automated data processing pipelines\n", - "- Integrate with additional data portals\n", - "- Develop custom visualization dashboards\n", - "\n", - "## Documentation\n", - "\n", - "For more information, see:\n", - "- [Upstream SDK Documentation](https://upstream-sdk.readthedocs.io/)\n", - "- [CKAN API Documentation](https://docs.ckan.org/en/2.9/api/)\n", - "- [Environmental Data Standards](https://www.example.com/standards)\n", - "\n", - "---\n", - "\n", - "*This notebook was generated using the Upstream SDK v2.0*" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.21" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/advanced/automated_pipeline.py b/examples/advanced/automated_pipeline.py deleted file mode 100644 index 1e211dc..0000000 --- a/examples/advanced/automated_pipeline.py +++ /dev/null @@ -1,272 +0,0 @@ -#!/usr/bin/env python3 -""" -Automated Data Pipeline Example - -This example demonstrates how to set up an automated data pipeline -for continuous sensor data collection and upload. -""" - -import time -import logging -from pathlib import Path -from datetime import datetime, timedelta -from typing import List, Dict, Any - -from upstream import UpstreamClient -from upstream.exceptions import UpstreamError, ValidationError, UploadError - - -# Configure logging -logging.basicConfig( - level=logging.INFO, - format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", - handlers=[logging.FileHandler("pipeline.log"), logging.StreamHandler()], -) -logger = logging.getLogger(__name__) - - -class AutomatedPipeline: - """Automated data pipeline for sensor data collection and upload.""" - - def __init__(self, config_file: Path): - """Initialize the pipeline with configuration.""" - self.client = UpstreamClient.from_config(config_file) - self.campaign_id = None - self.station_id = None - self.upload_interval = 3600 # 1 hour in seconds - self.max_retries = 3 - self.retry_delay = 300 # 5 minutes - - def setup_campaign_and_station(self) -> None: - """Set up campaign and station for data collection.""" - try: - # Create or get campaign - campaign = self.client.create_campaign( - name=f"Automated Monitoring {datetime.now().strftime('%Y-%m')}", - description="Automated environmental monitoring campaign", - ) - self.campaign_id = campaign.id - logger.info(f"Campaign ready: {campaign.name} ({campaign.id})") - - # Create or get station - station = self.client.create_station( - campaign_id=self.campaign_id, - name="Automated Weather Station", - latitude=30.2672, - longitude=-97.7431, - description="Automated weather monitoring station", - contact_name="Pipeline Manager", - contact_email="pipeline@example.com", - ) - self.station_id = station.id - logger.info(f"Station ready: {station.name} ({station.id})") - - except UpstreamError as e: - logger.error(f"Failed to setup campaign/station: {e}") - raise - - def collect_sensor_data(self) -> List[Dict[str, Any]]: - """Simulate sensor data collection.""" - # In a real implementation, this would interface with actual sensors - current_time = datetime.now().isoformat() + "Z" - - # Simulate multiple sensor readings - measurements = [] - for i in range(10): # 10 data points - timestamp = (datetime.now() - timedelta(minutes=i)).isoformat() + "Z" - measurements.append( - { - "collectiontime": timestamp, - "Lat_deg": 30.2672 + (i * 0.0001), # Slight variation - "Lon_deg": -97.7431 + (i * 0.0001), - "temperature": 25.0 + (i * 0.1), - "humidity": 60.0 + (i * 0.5), - "pressure": 1013.25 + (i * 0.1), - "wind_speed": 5.0 + (i * 0.2), - "wind_direction": 180 + (i * 2), - } - ) - - logger.info(f"Collected {len(measurements)} sensor readings") - return measurements - - def upload_data_with_retry(self, measurements: List[Dict[str, Any]]) -> bool: - """Upload data with retry logic.""" - for attempt in range(self.max_retries): - try: - result = self.client.upload_measurements( - campaign_id=self.campaign_id, - station_id=self.station_id, - data=measurements, - ) - - upload_id = result.get("upload_id") - logger.info(f"Upload successful: {upload_id}") - - # Monitor upload status - self.monitor_upload_status(upload_id) - return True - - except ValidationError as e: - logger.error(f"Data validation failed: {e}") - return False # Don't retry validation errors - - except UploadError as e: - logger.warning(f"Upload attempt {attempt + 1} failed: {e}") - if attempt < self.max_retries - 1: - logger.info(f"Retrying in {self.retry_delay} seconds...") - time.sleep(self.retry_delay) - else: - logger.error("All upload attempts failed") - return False - - except Exception as e: - logger.error(f"Unexpected error during upload: {e}") - return False - - return False - - def monitor_upload_status(self, upload_id: str) -> None: - """Monitor the status of an upload.""" - max_checks = 10 - check_interval = 30 # seconds - - for i in range(max_checks): - try: - status = self.client.get_upload_status(upload_id) - upload_status = status.get("status", "unknown") - - logger.info(f"Upload {upload_id} status: {upload_status}") - - if upload_status in ["completed", "success"]: - logger.info("Upload processing completed successfully") - break - elif upload_status in ["failed", "error"]: - logger.error("Upload processing failed") - break - elif upload_status in ["processing", "pending"]: - time.sleep(check_interval) - else: - logger.warning(f"Unknown upload status: {upload_status}") - break - - except Exception as e: - logger.warning(f"Failed to check upload status: {e}") - break - - def publish_to_ckan_if_configured(self) -> None: - """Publish data to CKAN if configured.""" - if self.client.ckan: - try: - result = self.client.publish_to_ckan( - campaign_id=self.campaign_id, auto_publish=True - ) - ckan_url = result.get("ckan_url") - logger.info(f"Data published to CKAN: {ckan_url}") - - except Exception as e: - logger.error(f"CKAN publication failed: {e}") - - def run_single_cycle(self) -> bool: - """Run a single data collection and upload cycle.""" - try: - logger.info("Starting data collection cycle...") - - # Collect sensor data - measurements = self.collect_sensor_data() - - # Upload data - if self.upload_data_with_retry(measurements): - # Publish to CKAN if configured - self.publish_to_ckan_if_configured() - logger.info("Data cycle completed successfully") - return True - else: - logger.error("Data cycle failed") - return False - - except Exception as e: - logger.error(f"Unexpected error in data cycle: {e}") - return False - - def run_continuous(self) -> None: - """Run the pipeline continuously.""" - logger.info(f"Starting continuous pipeline (interval: {self.upload_interval}s)") - - # Setup campaign and station - self.setup_campaign_and_station() - - # Run continuous loop - while True: - try: - cycle_start = time.time() - - # Run data collection cycle - success = self.run_single_cycle() - - # Calculate next run time - cycle_duration = time.time() - cycle_start - sleep_time = max(0, self.upload_interval - cycle_duration) - - if success: - logger.info( - f"Cycle completed in {cycle_duration:.1f}s. " - f"Next cycle in {sleep_time:.1f}s" - ) - else: - logger.warning( - f"Cycle failed in {cycle_duration:.1f}s. " - f"Retrying in {sleep_time:.1f}s" - ) - - time.sleep(sleep_time) - - except KeyboardInterrupt: - logger.info("Pipeline stopped by user") - break - except Exception as e: - logger.error(f"Unexpected error in pipeline: {e}") - logger.info(f"Continuing in {self.retry_delay} seconds...") - time.sleep(self.retry_delay) - - # Cleanup - try: - self.client.logout() - logger.info("Pipeline shutdown complete") - except Exception as e: - logger.error(f"Error during cleanup: {e}") - - -def main(): - """Main function to run the automated pipeline.""" - config_file = Path("pipeline_config.yaml") - - if not config_file.exists(): - logger.error(f"Configuration file not found: {config_file}") - logger.info("Please create a configuration file with your Upstream credentials") - return - - try: - pipeline = AutomatedPipeline(config_file) - - # Run a single cycle for testing - logger.info("Running single test cycle...") - pipeline.setup_campaign_and_station() - success = pipeline.run_single_cycle() - - if success: - logger.info("Test cycle successful!") - - # Ask user if they want to run continuously - response = input("Run pipeline continuously? (y/N): ") - if response.lower() in ["y", "yes"]: - pipeline.run_continuous() - else: - logger.error("Test cycle failed!") - - except Exception as e: - logger.error(f"Pipeline failed to start: {e}") - - -if __name__ == "__main__": - main() diff --git a/examples/advanced/chunked_upload_example.py b/examples/advanced/chunked_upload_example.py deleted file mode 100644 index 4175dad..0000000 --- a/examples/advanced/chunked_upload_example.py +++ /dev/null @@ -1,272 +0,0 @@ -#!/usr/bin/env python3 -""" -Example: Chunked CSV Upload for Large Measurement Files - -This example demonstrates how to upload large measurement CSV files -in chunks to avoid HTTP timeouts. The upload_csv_files method now -supports chunked uploads with configurable chunk sizes. - -Key Features: -- Uploads measurements in chunks of 1000 lines (default) or custom size -- Handles large files that would otherwise timeout -- Supports all input formats: file paths, bytes, or (filename, bytes) tuples -- Only uploads sensor metadata with the first chunk -- Provides progress logging for each chunk -""" - -import tempfile -import time -from pathlib import Path -from datetime import datetime, timedelta -import random - -from upstream import UpstreamClient -from upstream.exceptions import ValidationError, APIError - - -def create_large_measurements_file(file_path: str, num_lines: int = 5000): - """ - Create a large measurements CSV file for testing chunked upload. - - Args: - file_path: Path to the CSV file to create - num_lines: Number of data lines to generate - """ - print(f"Creating large measurements file with {num_lines} lines...") - - with open(file_path, "w", encoding="utf-8") as f: - # Write header - f.write( - "collectiontime,Lat_deg,Lon_deg,temperature_sensor,humidity_sensor,pressure_sensor,wind_speed_sensor\n" - ) - - # Generate data lines - base_time = datetime(2024, 1, 1, 0, 0, 0) - base_lat = 30.2672 - base_lon = -97.7431 - - for i in range(num_lines): - # Generate timestamp with slight variations - timestamp = base_time + timedelta( - hours=i % 24, minutes=i % 60, seconds=i % 60 - ) - - # Generate coordinates with slight variations - lat = base_lat + (i * 0.0001) % 0.01 - lon = base_lon + (i * 0.0001) % 0.01 - - # Generate sensor readings with realistic variations - temperature = 20.0 + 10 * random.random() # 20-30ยฐC - humidity = 40.0 + 30 * random.random() # 40-70% - pressure = 1013.0 + 20 * random.random() # 1013-1033 hPa - wind_speed = 0.0 + 15 * random.random() # 0-15 m/s - - f.write( - f"{timestamp.isoformat()},{lat:.6f},{lon:.6f},{temperature:.2f},{humidity:.2f},{pressure:.2f},{wind_speed:.2f}\n" - ) - - print(f"Created measurements file: {file_path}") - - -def create_sensors_file(file_path: str): - """ - Create a sensors CSV file with multiple sensor definitions. - - Args: - file_path: Path to the CSV file to create - """ - print("Creating sensors file...") - - with open(file_path, "w", encoding="utf-8") as f: - f.write("alias,variablename,units,postprocess,postprocessscript\n") - f.write( - "temperature_sensor,Air Temperature,ยฐC,True,temperature_correction_script\n" - ) - f.write("humidity_sensor,Relative Humidity,%,False,\n") - f.write( - "pressure_sensor,Atmospheric Pressure,hPa,True,pressure_correction_script\n" - ) - f.write("wind_speed_sensor,Wind Speed,m/s,True,wind_correction_script\n") - - print(f"Created sensors file: {file_path}") - - -def demonstrate_chunked_upload(): - """Demonstrate chunked upload functionality.""" - print("=== Chunked CSV Upload Example ===\n") - - # Initialize client - client = UpstreamClient() - - campaign_id = None - station_id = None - - try: - # Create campaign - print("1. Creating campaign...") - campaign = client.campaigns.create( - name="Large Dataset Campaign", - description="Campaign for testing chunked upload functionality", - geometry="POINT(-97.7431 30.2672)", - ) - campaign_id = campaign.id - print(f" Created campaign: {campaign_id}") - - # Create station - print("\n2. Creating station...") - station = client.stations.create( - campaign_id=campaign_id, - name="Multi-Sensor Station", - description="Station with multiple sensors for chunked upload testing", - geometry="POINT(-97.7431 30.2672)", - ) - station_id = station.id - print(f" Created station: {station_id}") - - # Create temporary files - with tempfile.NamedTemporaryFile( - mode="w", suffix=".csv", delete=False - ) as sensors_file: - sensors_path = sensors_file.name - - with tempfile.NamedTemporaryFile( - mode="w", suffix=".csv", delete=False - ) as measurements_file: - measurements_path = measurements_file.name - - # Create the CSV files - create_sensors_file(sensors_path) - create_large_measurements_file( - measurements_path, num_lines=3500 - ) # Will create 4 chunks with default size - - print(f"\n3. Uploading CSV files with chunked measurements...") - print(f" Sensors file: {sensors_path}") - print(f" Measurements file: {measurements_path}") - print(f" Expected chunks: 4 (1000, 1000, 1000, 500 lines each)") - - start_time = time.time() - - # Upload with default chunk size (1000) - response = client.sensors.upload_csv_files( - campaign_id=campaign_id, - station_id=station_id, - sensors_file=sensors_path, - measurements_file=measurements_path, - ) - - upload_time = time.time() - start_time - print(f" Upload completed in {upload_time:.2f} seconds") - print(f" Response: {response}") - - # Verify sensors were created - print("\n4. Verifying uploaded sensors...") - sensors = client.sensors.list(campaign_id=campaign_id, station_id=station_id) - print(f" Created {len(sensors.items)} sensors:") - - for sensor in sensors.items: - print(f" - {sensor.alias}: {sensor.variablename} ({sensor.units})") - - # Demonstrate custom chunk size - print(f"\n5. Demonstrating custom chunk size...") - print(f" Creating smaller file for custom chunk size test...") - - # Create a smaller file for custom chunk size test - with tempfile.NamedTemporaryFile( - mode="w", suffix=".csv", delete=False - ) as small_measurements_file: - small_measurements_path = small_measurements_file.name - create_large_measurements_file( - small_measurements_path, num_lines=800 - ) # Will create 2 chunks with size=500 - - print(f" Uploading with custom chunk size (500 lines per chunk)...") - - start_time = time.time() - - response_custom = client.sensors.upload_csv_files( - campaign_id=campaign_id, - station_id=station_id, - sensors_file=sensors_path, - measurements_file=small_measurements_path, - chunk_size=500, # Custom chunk size - ) - - upload_time = time.time() - start_time - print(f" Upload completed in {upload_time:.2f} seconds") - print(f" Response: {response_custom}") - - # Demonstrate bytes input - print(f"\n6. Demonstrating bytes input with chunking...") - - # Create content as bytes - sensors_content = ( - "alias,variablename,units,postprocess,postprocessscript\n" - "bytes_temp_sensor,Air Temperature,ยฐC,True,temp_correction\n" - ).encode("utf-8") - - # Create measurements content as bytes - measurements_lines = ["collectiontime,Lat_deg,Lon_deg,bytes_temp_sensor\n"] - for i in range(1200): # Will create 3 chunks with size=500 - timestamp = datetime(2024, 1, 1, 0, 0, 0) + timedelta(hours=i % 24) - lat = 30.2672 + (i * 0.0001) % 0.01 - lon = -97.7431 + (i * 0.0001) % 0.01 - temp = 20.0 + 10 * random.random() - measurements_lines.append( - f"{timestamp.isoformat()},{lat:.6f},{lon:.6f},{temp:.2f}\n" - ) - - measurements_content = "".join(measurements_lines).encode("utf-8") - - print(f" Uploading using bytes input with chunk size 500...") - - start_time = time.time() - - response_bytes = client.sensors.upload_csv_files( - campaign_id=campaign_id, - station_id=station_id, - sensors_file=sensors_content, - measurements_file=measurements_content, - chunk_size=500, - ) - - upload_time = time.time() - start_time - print(f" Upload completed in {upload_time:.2f} seconds") - print(f" Response: {response_bytes}") - - print(f"\n=== Chunked Upload Example Completed Successfully ===") - - except ValidationError as e: - print(f"Validation error: {e}") - except APIError as e: - print(f"API error: {e}") - except Exception as e: - print(f"Unexpected error: {e}") - - finally: - # Clean up temporary files - for file_path in [sensors_path, measurements_path, small_measurements_path]: - try: - Path(file_path).unlink(missing_ok=True) - except Exception: - pass - - # Clean up station - if station_id: - try: - client.stations.delete(station_id, campaign_id) - print(f"\nCleaned up station: {station_id}") - except Exception as e: - print(f"Failed to clean up station: {e}") - - # Clean up campaign - if campaign_id: - try: - client.campaigns.delete(campaign_id) - print(f"Cleaned up campaign: {campaign_id}") - except Exception as e: - print(f"Failed to clean up campaign: {e}") - - -if __name__ == "__main__": - demonstrate_chunked_upload() diff --git a/examples/basic/config_example.py b/examples/basic/config_example.py deleted file mode 100644 index f822a55..0000000 --- a/examples/basic/config_example.py +++ /dev/null @@ -1,145 +0,0 @@ -#!/usr/bin/env python3 -""" -Upstream SDK Configuration Example - -This example demonstrates different ways to configure the Upstream SDK. -""" - -import os -from pathlib import Path -import tempfile - -from upstream import UpstreamClient -from upstream.utils import ConfigManager - - -def example_environment_config(): - """Example using environment variables.""" - print("๐Ÿ“ Configuration from environment variables:") - - # Set environment variables (in practice, these would be set in your shell) - os.environ.update( - { - "UPSTREAM_USERNAME": "your_username", - "UPSTREAM_PASSWORD": "your_password", - "UPSTREAM_BASE_URL": "https://upstream-dso.tacc.utexas.edu/dev", - "CKAN_URL": "https://ckan.tacc.utexas.edu", - } - ) - - # Create client from environment - client = UpstreamClient.from_environment() - print(f" Base URL: {client.auth_manager.config.base_url}") - print(f" Username: {client.auth_manager.config.username}") - print(f" CKAN URL: {client.auth_manager.config.ckan_url}") - - -def example_config_file(): - """Example using configuration file.""" - print("\n๐Ÿ“„ Configuration from file:") - - # Create example config file - config_content = """ -upstream: - username: your_username - password: your_password - base_url: https://upstream-dso.tacc.utexas.edu/dev - -ckan: - url: https://ckan.tacc.utexas.edu - auto_publish: true - default_organization: your-org - -upload: - chunk_size: 10000 - max_file_size_mb: 50 - timeout_seconds: 300 - retry_attempts: 3 -""" - - # Write to temporary file - with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: - f.write(config_content) - config_path = f.name - - try: - # Create client from config file - client = UpstreamClient.from_config(config_path) - print(f" Base URL: {client.auth_manager.config.base_url}") - print(f" Username: {client.auth_manager.config.username}") - print(f" Chunk size: {client.auth_manager.config.chunk_size}") - print(f" Max retries: {client.auth_manager.config.max_retries}") - - finally: - # Clean up temp file - os.unlink(config_path) - - -def example_direct_config(): - """Example using direct configuration.""" - print("\nโš™๏ธ Direct configuration:") - - client = UpstreamClient( - username="your_username", - password="your_password", - base_url="https://upstream-dso.tacc.utexas.edu/dev", - ckan_url="https://ckan.tacc.utexas.edu", - ) - - print(f" Base URL: {client.auth_manager.config.base_url}") - print(f" Username: {client.auth_manager.config.username}") - print(f" CKAN URL: {client.auth_manager.config.ckan_url}") - - -def example_config_manager(): - """Example using ConfigManager directly.""" - print("\n๐Ÿ”ง Using ConfigManager:") - - # Create configuration manager - config = ConfigManager( - username="your_username", - password="your_password", - base_url="https://upstream-dso.tacc.utexas.edu/dev", - ckan_url="https://ckan.tacc.utexas.edu", - timeout=60, - max_retries=5, - chunk_size=5000, - ) - - print(f" Base URL: {config.base_url}") - print(f" Username: {config.username}") - print(f" Timeout: {config.timeout}s") - print(f" Max retries: {config.max_retries}") - print(f" Chunk size: {config.chunk_size}") - - # Save configuration to file - config_path = Path("example_config.yaml") - config.save(config_path) - print(f" Configuration saved to: {config_path}") - - # Load configuration from file - loaded_config = ConfigManager.from_file(config_path) - print(f" Loaded base URL: {loaded_config.base_url}") - - # Clean up - config_path.unlink() - - -def main(): - """Main example function.""" - print("๐Ÿš€ Upstream SDK Configuration Examples\n") - - try: - example_environment_config() - example_config_file() - example_direct_config() - example_config_manager() - - print("\nโœ… All configuration examples completed!") - - except Exception as e: - print(f"โŒ Error: {e}") - - -if __name__ == "__main__": - main() diff --git a/examples/basic/csv_upload_example.py b/examples/basic/csv_upload_example.py deleted file mode 100644 index 9c81eb0..0000000 --- a/examples/basic/csv_upload_example.py +++ /dev/null @@ -1,198 +0,0 @@ -#!/usr/bin/env python3 -""" -Example: Upload Sensor and Measurement CSV Files - -This example demonstrates how to upload sensor metadata and measurement data -using the correct CSV format for the Upstream API. - -CSV Format Requirements: -- Sensors CSV: alias,variablename,units,postprocess,postprocessscript -- Measurements CSV: collectiontime,Lat_deg,Lon_deg,{sensor_aliases...} -""" - -import os -import tempfile -from pathlib import Path -from datetime import datetime, timedelta - -from upstream import UpstreamClient - - -def create_sample_sensors_csv(file_path: str) -> None: - """Create a sample sensors CSV file with the correct format.""" - with open(file_path, "w", encoding="utf-8") as f: - f.write("alias,variablename,units,postprocess,postprocessscript\n") - f.write("temp_sensor_01,Air Temperature,ยฐC,,\n") - f.write("humidity_01,Relative Humidity,%,,\n") - f.write("pressure_01,Atmospheric Pressure,hPa,,\n") - f.write("wind_speed_01,Wind Speed,m/s,true,wind_correction_script\n") - f.write("wind_direction_01,Wind Direction,degrees,,\n") - f.write("rainfall_01,Rainfall,mm,,\n") - - -def create_sample_measurements_csv(file_path: str) -> None: - """Create a sample measurements CSV file with the correct format.""" - with open(file_path, "w", encoding="utf-8") as f: - f.write( - "collectiontime,Lat_deg,Lon_deg,temp_sensor_01,humidity_01,pressure_01,wind_speed_01,wind_direction_01,rainfall_01\n" - ) - - # Generate sample data for the last 24 hours - base_time = datetime.now() - timedelta(hours=24) - base_lat = 30.2672 - base_lon = -97.7431 - - for i in range(24): - timestamp = base_time + timedelta(hours=i) - lat = base_lat + (i * 0.0001) # Slight variation - lon = base_lon + (i * 0.0001) # Slight variation - - # Generate realistic sensor values - temp = 20 + (i % 12) * 0.5 # Temperature variation - humidity = 60 + (i % 8) * 2 # Humidity variation - pressure = 1013.25 + (i % 6) * 0.1 # Pressure variation - wind_speed = 2 + (i % 4) * 0.5 # Wind speed variation - wind_direction = (i * 15) % 360 # Wind direction variation - rainfall = 0 if i < 20 else (i - 19) * 0.1 # Some rain at the end - - f.write( - f"{timestamp.strftime('%Y-%m-%dT%H:%M:%S')},{lat:.4f},{lon:.4f},{temp:.1f},{humidity:.1f},{pressure:.2f},{wind_speed:.1f},{wind_direction:.0f},{rainfall:.1f}\n" - ) - - -def main(): - """Main function demonstrating CSV upload functionality.""" - - # Initialize client (you'll need to set these environment variables) - username = os.environ.get("UPSTREAM_USERNAME") - password = os.environ.get("UPSTREAM_PASSWORD") - - if not username or not password: - print( - "โŒ Please set UPSTREAM_USERNAME and UPSTREAM_PASSWORD environment variables" - ) - return - - client = UpstreamClient( - username=username, - password=password, - base_url="https://upstream-dev.tacc.utexas.edu", - ) - - # Authenticate - if not client.authenticate(): - print("โŒ Authentication failed") - return - - print("โœ… Authentication successful") - - # Create a campaign for testing - from upstream_api_client.models import CampaignsIn - from datetime import datetime, timedelta - - campaign_data = CampaignsIn( - name="CSV Upload Example Campaign", - description="Example campaign for demonstrating CSV upload functionality", - contact_name="Example User", - contact_email="example@tacc.utexas.edu", - allocation="TACC", - start_date=datetime.now(), - end_date=datetime.now() + timedelta(days=30), - ) - - try: - campaign = client.create_campaign(campaign_data) - campaign_id = str(campaign.id) - print(f"โœ… Created campaign: {campaign_id}") - - # Create a station - from upstream_api_client.models import StationCreate - - station_data = StationCreate( - name="CSV Upload Example Station", - description="Example station for CSV upload testing", - contact_name="Example User", - contact_email="example@tacc.utexas.edu", - start_date=datetime.now(), - active=True, - ) - - station = client.create_station(campaign_id, station_data) - station_id = str(station.id) - print(f"โœ… Created station: {station_id}") - - try: - # Create temporary CSV files - with tempfile.NamedTemporaryFile( - mode="w", suffix=".csv", delete=False, encoding="utf-8" - ) as sensors_file: - create_sample_sensors_csv(sensors_file.name) - sensors_path = sensors_file.name - - with tempfile.NamedTemporaryFile( - mode="w", suffix=".csv", delete=False, encoding="utf-8" - ) as measurements_file: - create_sample_measurements_csv(measurements_file.name) - measurements_path = measurements_file.name - - try: - print("๐Ÿ“ค Uploading sensor and measurement files...") - - # Upload using file paths - result = client.upload_sensor_measurement_files( - campaign_id=campaign_id, - station_id=station_id, - sensors_file=sensors_path, - measurements_file=measurements_path, - ) - - print("โœ… Upload successful!") - print(f"๐Ÿ“Š Upload result: {result}") - - # Demonstrate different upload methods - print("\n๐Ÿ”„ Testing different upload methods...") - - # Method 1: Using bytes - with open(sensors_path, "rb") as f: - sensors_bytes = f.read() - with open(measurements_path, "rb") as f: - measurements_bytes = f.read() - - result_bytes = client.upload_sensor_measurement_files( - campaign_id=campaign_id, - station_id=station_id, - sensors_file=sensors_bytes, - measurements_file=measurements_bytes, - ) - print("โœ… Bytes upload successful") - - # Method 2: Using tuples (filename, bytes) - result_tuple = client.upload_sensor_measurement_files( - campaign_id=campaign_id, - station_id=station_id, - sensors_file=("sensors.csv", sensors_bytes), - measurements_file=("measurements.csv", measurements_bytes), - ) - print("โœ… Tuple upload successful") - - finally: - # Clean up temporary files - os.unlink(sensors_path) - os.unlink(measurements_path) - print("๐Ÿงน Cleaned up temporary files") - - finally: - # Clean up station - client.stations.delete(station_id, campaign_id) - print(f"๐Ÿ—‘๏ธ Deleted station: {station_id}") - - finally: - # Clean up campaign - client.campaigns.delete(campaign_id) - print(f"๐Ÿ—‘๏ธ Deleted campaign: {campaign_id}") - - print("\n๐ŸŽ‰ CSV upload example completed successfully!") - - -if __name__ == "__main__": - main() diff --git a/examples/basic/quick_start.ipynb b/examples/basic/quick_start.ipynb deleted file mode 100644 index 7e025f2..0000000 --- a/examples/basic/quick_start.ipynb +++ /dev/null @@ -1,123 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "f65c7f59", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "import os\n", - "from pathlib import Path\n", - "\n", - "from upstream import UpstreamClient\n", - "from upstream.exceptions import UpstreamError\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a9761de4", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "import getpass\n", - "\n", - "password = getpass.getpass(\"Enter your password: \")\n", - "client = UpstreamClient(\n", - " username=os.getenv(\"UPSTREAM_USERNAME\", \"mosorio\"),\n", - " password=password,\n", - " base_url=os.getenv(\"UPSTREAM_BASE_URL\", \"http://localhost:8000\"),\n", - " ckan_url=os.getenv(\"CKAN_URL\", \"https://ckan.tacc.utexas.edu\")\n", - ")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "bcd3e534", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "โœ… Authentication successful!\n" - ] - } - ], - "source": [ - "# Test authentication\n", - "try:\n", - " if client.authenticate():\n", - " print(\"โœ… Authentication successful!\")\n", - " else:\n", - " print(\"โŒ Authentication failed!\")\n", - "except Exception as e:\n", - " print(f\"โŒ Authentication failed: {e}\")" - ] - }, - { - "cell_type": "markdown", - "id": "c20d6257", - "metadata": {}, - "source": [ - "Creating Campaigns\n", - "Before uploading CSV data, you need to create a campaign to organize your data collection project. A campaign serves as the top-level container for all related monitoring activities.\n", - "\n", - "Campaign Requirements\n", - "Required Fields:\n", - "\n", - "name: Descriptive name for your data collection project\n", - "description: Detailed description of the campaign's purpose and scope\n", - "Campaign Best Practices\n", - "๐ŸŽฏ Naming Conventions:\n", - "\n", - "Use descriptive, unique names that clearly identify the project\n", - "Include dates, locations, or project codes for easy identification\n", - "Examples: \"Austin Air Quality 2024\", \"Hurricane Harvey Recovery Monitoring\"\n", - "๐Ÿ“ Descriptions:\n", - "\n", - "Provide detailed context about the campaign's objectives\n", - "Include information about duration, scope, and expected outcomes\n", - "Mention any relevant research or operational goals" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "99d6b274", - "metadata": {}, - "outputs": [], - "source": [ - "campaign = client.create_campaign(\n", - " name=\"Example Air Quality Campaign\",\n", - " description=\"Demonstration campaign for SDK usage\"\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.21" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/basic/quick_start.py b/examples/basic/quick_start.py deleted file mode 100644 index d493ca9..0000000 --- a/examples/basic/quick_start.py +++ /dev/null @@ -1,114 +0,0 @@ -#!/usr/bin/env python3 -""" -Upstream SDK Quick Start Example - -This example demonstrates the basic usage of the Upstream Python SDK -for environmental sensor data management. -""" - -import os -from pathlib import Path - -from upstream import UpstreamClient -from upstream.exceptions import UpstreamError - - -def main() -> None: - """Main example function.""" - - # Initialize the client with credentials - # In production, use environment variables or config files - client = UpstreamClient( - username=os.getenv("UPSTREAM_USERNAME", "your_username"), - password=os.getenv("UPSTREAM_PASSWORD", "your_password"), - base_url=os.getenv( - "UPSTREAM_BASE_URL", "https://upstream-dso.tacc.utexas.edu/dev" - ), - ckan_url=os.getenv("CKAN_URL", "https://ckan.tacc.utexas.edu"), - ) - - try: - # Test authentication - if client.authenticate(): - print("โœ… Authentication successful!") - else: - print("โŒ Authentication failed!") - return - - # Create a new campaign - print("\n๐Ÿ“Š Creating campaign...") - campaign = client.create_campaign( - name="Example Air Quality Campaign", - description="Demonstration campaign for SDK usage", - ) - print(f"Created campaign: (ID: {campaign.id})") - - # Create a monitoring station - print("\n๐Ÿ“ Creating station...") - station = client.create_station( - campaign_id=campaign.id, - name="Downtown Monitor", - latitude=30.2672, - longitude=-97.7431, - description="City center air quality monitoring station", - contact_name="Dr. Jane Smith", - contact_email="jane.smith@example.edu", - ) - print(f"Created station: (ID: {station.id})") - - # Example data upload (if CSV files exist) - sensors_file = Path("example_data/sensors.csv") - measurements_file = Path("example_data/measurements.csv") - - if sensors_file.exists() and measurements_file.exists(): - print("\n๐Ÿ“ค Uploading data...") - result = client.upload_csv_data( - campaign_id=campaign.id, - station_id=station.id, - sensors_file=sensors_file, - measurements_file=measurements_file, - ) - print(f"Upload successful! Upload ID: {result.get('upload_id')}") - - # Publish to CKAN if configured - if client.ckan: - print("\n๐ŸŒ Publishing to CKAN...") - ckan_result = client.publish_to_ckan( - campaign_id=campaign.id, - sensors_url=f"https://example.com/data/sensors.csv", - measurements_url=f"https://example.com/data/measurements.csv", - ) - print(f"Published to CKAN: {ckan_result.get('ckan_url')}") - else: - print(f"\nโš ๏ธ Example data files not found:") - print(f" {sensors_file}") - print(f" {measurements_file}") - print(" Skipping data upload demonstration.") - - # List campaigns and stations - print("\n๐Ÿ“‹ Listing campaigns...") - campaigns = client.list_campaigns() - for camp in campaigns.items[:3]: # Show first 3 - print(f" - {camp.id} {camp.name}") - - print(f"\n๐Ÿ“‹ Listing stations for campaign {campaign.id}...") - stations = client.list_stations(campaign_id=campaign.id) - for stat in stations.items: - print(f" - {stat.id} {stat.name}") - - print("\n๐ŸŽ‰ Example completed successfully!") - - except UpstreamError as e: - print(f"โŒ Upstream SDK Error: {e}") - if hasattr(e, "details") and e.details: - print(f" Details: {e.details}") - except Exception as e: - print(f"โŒ Unexpected error: {e}") - finally: - # Clean up authentication - client.logout() - print("\n๐Ÿ‘‹ Logged out successfully") - - -if __name__ == "__main__": - main() diff --git a/main.py b/main.py deleted file mode 100644 index bafc8c8..0000000 --- a/main.py +++ /dev/null @@ -1,19 +0,0 @@ -import os -from upstream import UpstreamClient - -# Initialize client -client = UpstreamClient( - username=os.getenv("UPSTREAM_USERNAME"), - password=os.getenv("UPSTREAM_PASSWORD"), - base_url=os.getenv("UPSTREAM_BASE_URL"), -) -# Create campaign and station -campaigns = client.list_campaigns() -print(campaigns.items[0].id) - -for campaign in campaigns.items: - print(campaign.id) - print(campaign.name) - print(campaign.start_date) - print(campaign.end_date) - print(campaign.allocation) diff --git a/pyproject.toml b/pyproject.toml index 422d766..830cd61 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "upstream-sdk" -version = "1.0.0" +version = "1.0.1" description = "Python SDK for Upstream environmental sensor data platform and CKAN integration" readme = "README.md" license = {text = "MIT"} @@ -39,7 +39,7 @@ dependencies = [ "typing-extensions>=4.0.0; python_version<'3.10'", "pydantic>=2.0.0", "urllib3>=1.25.3", - "upstream-api-client>=0.1.4" + "upstream-api-client>=0.1.7" ] [project.optional-dependencies] diff --git a/requirements.txt b/requirements.txt index e2af17a..326f817 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,4 +2,4 @@ requests>=2.25.0 pyyaml>=6.0 python-dateutil>=2.8.0 typing-extensions>=4.0.0; python_version<"3.10" -upstream-api-client>=0.1.4 \ No newline at end of file +upstream-api-client>=0.1.7 \ No newline at end of file diff --git a/tests/conftest.py b/tests/conftest.py index 377707c..60f5be1 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -222,6 +222,54 @@ def mock_station(sample_station_data): return GetStationResponse(**sample_station_data) +@pytest.fixture +def ckan_test_config(): + """CKAN configuration for testing.""" + return { + "url": "http://test-ckan.example.com", + "api_key": "test-api-key", + "timeout": 30, + "default_organization": "test-org", + } + + +@pytest.fixture +def mock_ckan_dataset(): + """Mock CKAN dataset for testing.""" + return { + "id": "test-dataset-id-123", + "name": "test-dataset", + "title": "Test Dataset", + "notes": "Test dataset description", + "state": "active", + "private": False, + "tags": [{"name": "test"}, {"name": "environmental"}, {"name": "upstream"}], + "owner_org": "test-org", + "resources": [], + "extras": [ + {"key": "source", "value": "Upstream Platform"}, + {"key": "data_type", "value": "environmental_sensor_data"}, + ], + } + + +@pytest.fixture +def mock_ckan_resource(): + """Mock CKAN resource for testing.""" + return { + "id": "test-resource-id-456", + "name": "Test Resource", + "description": "Test resource description", + "url": "https://example.com/data.csv", + "format": "CSV", + "resource_type": "data", + "package_id": "test-dataset-id-123", + "size": 1024, + "created": "2024-01-01T00:00:00Z", + "last_modified": "2024-01-01T00:00:00Z", + } + + @pytest.fixture(autouse=True) def reset_mocks(): """Reset all mocks after each test.""" diff --git a/tests/integration/test_campaigns_integration.py b/tests/integration/test_campaigns_integration.py index ce9bec2..7228e53 100644 --- a/tests/integration/test_campaigns_integration.py +++ b/tests/integration/test_campaigns_integration.py @@ -6,12 +6,15 @@ from upstream.client import UpstreamClient from upstream.exceptions import APIError +from upstream.ckan import CKANIntegration BASE_URL = "http://localhost:8000" CKAN_URL = "http://ckan.tacc.cloud:5000" USERNAME = os.environ.get("UPSTREAM_USERNAME") PASSWORD = os.environ.get("UPSTREAM_PASSWORD") +CKAN_API_KEY = os.environ.get("CKAN_API_KEY", "") +ORGANIZATION = os.environ.get("CKAN_ORGANIZATION", "") pytestmark = pytest.mark.integration @@ -81,3 +84,182 @@ def test_campaign_lifecycle(): # Check that the campaign is deleted with pytest.raises(APIError): client.campaigns.get(str(created.id)) + + +@pytest.mark.skipif( + not USERNAME or not PASSWORD, + reason="UPSTREAM_USERNAME and UPSTREAM_PASSWORD must be set in env", +) +def test_ckan_dataset_update_integration(): + """ + Integration test for updating CKAN dataset with custom metadata and tags. + + This test verifies the enhanced update_dataset functionality by: + 1. Creating an initial dataset with tags and metadata + 2. Updating the dataset using merge mode (preserving existing data) + 3. Verifying all changes using get_dataset() + 4. Testing replace mode (replacing all existing data) + 5. Verifying replace mode behavior + 6. Cleaning up the test dataset + + Tests both merge and replace modes for tags and metadata to ensure + the update_dataset method works correctly in real CKAN environments. + + Requires: + - UPSTREAM_USERNAME and UPSTREAM_PASSWORD environment variables + - Running CKAN instance at CKAN_URL + - Valid CKAN API credentials + """ + client = UpstreamClient( + username=USERNAME, password=PASSWORD, base_url=BASE_URL, ckan_url=CKAN_URL + ) + ckan_config = {"timeout": 30} + if not CKAN_API_KEY: + pytest.skip("CKAN API key not set (required for dataset creation)") + + if not ORGANIZATION: + pytest.skip("CKAN organization not set (required for dataset creation)") + + ckan_config["api_key"] = CKAN_API_KEY + client.ckan = CKANIntegration(ckan_url=CKAN_URL, config=ckan_config) + + if not client.ckan: + pytest.skip("CKAN integration not available") + + # Create a unique test dataset name + timestamp = datetime.now().strftime('%Y%m%d%H%M%S') + dataset_name = f"test-dataset-update-{timestamp}" + + print(f"Testing CKAN dataset update integration with: {dataset_name}") + + # Step 1: Create initial dataset with organization + initial_dataset = client.ckan.create_dataset( + name=dataset_name, + title="Initial Test Dataset", + description="This is a test dataset for update integration testing", + organization=ORGANIZATION, + tags=["test", "initial"], + extras=[ + {"key": "test_phase", "value": "initial"}, + {"key": "created_by", "value": "integration_test"} + ] + ) + + print(f"โœ… Created initial dataset: {initial_dataset['name']}") + + try: + # Step 2: Verify initial state + fetched_initial = client.ckan.get_dataset(dataset_name) + initial_tags = [tag["name"] for tag in fetched_initial["tags"]] + initial_extras = {extra["key"]: extra["value"] for extra in fetched_initial.get("extras", [])} + + assert "test" in initial_tags + assert "initial" in initial_tags + assert initial_extras["test_phase"] == "initial" + assert initial_extras["created_by"] == "integration_test" + print(f"โœ… Verified initial dataset state") + + # Step 3: Update dataset - Add new tag and metadata + print("๐Ÿ”„ Updating dataset with new tag and metadata...") + + updated_dataset = client.ckan.update_dataset( + dataset_name, + # Add new custom metadata + dataset_metadata={ + "test_phase": "updated", # Update existing field + "update_timestamp": datetime.now().isoformat(), # Add new field + "integration_status": "passed" # Add another new field + }, + # Add new custom tags + custom_tags=["updated", "integration-test"], + # Use merge mode to preserve existing data + merge_extras=True, + merge_tags=True, + # Also update the title + title="Updated Test Dataset" + ) + + print(f"โœ… Updated dataset: {updated_dataset['name']}") + + # Step 4: Verify updates using get_dataset + print("๐Ÿ” Verifying updates...") + + verified_dataset = client.ckan.get_dataset(dataset_name) + + # Verify title update + assert verified_dataset["title"] == "Updated Test Dataset" + print(" โœ“ Title updated successfully") + + # Verify tags (should include both old and new) + updated_tags = [tag["name"] for tag in verified_dataset["tags"]] + expected_tags = ["test", "initial", "updated", "integration-test"] + + for tag in expected_tags: + assert tag in updated_tags, f"Expected tag '{tag}' not found in {updated_tags}" + + # Also verify we have the right number of tags (no extras) + assert len(updated_tags) == len(expected_tags), f"Expected {len(expected_tags)} tags, got {len(updated_tags)}: {updated_tags}" + print(f" โœ“ Tags updated successfully: {sorted(updated_tags)}") + + # Verify metadata/extras (should include both old and new) + updated_extras = {extra["key"]: extra["value"] for extra in verified_dataset.get("extras", [])} + + # Check preserved fields + assert updated_extras["created_by"] == "integration_test" + print(" โœ“ Original metadata preserved") + + # Check updated fields + assert updated_extras["test_phase"] == "updated" + print(" โœ“ Existing metadata updated") + + # Check new fields + assert "update_timestamp" in updated_extras + assert updated_extras["integration_status"] == "passed" + print(" โœ“ New metadata added") + + print(f"โœ… All updates verified successfully!") + + # Step 5: Test replace mode + print("๐Ÿ”„ Testing replace mode...") + + client.ckan.update_dataset( + dataset_name, + dataset_metadata={ + "final_phase": "replace_test", + "mode": "replace" + }, + custom_tags=["replaced", "final"], + merge_extras=False, # Replace all extras + merge_tags=False, # Replace all tags + title="Replaced Test Dataset" + ) + + # Verify replace mode + verified_replace = client.ckan.get_dataset(dataset_name) + + # Check that old tags are gone and only new ones remain + final_tags = [tag["name"] for tag in verified_replace["tags"]] + expected_final_tags = ["replaced", "final"] + assert set(final_tags) == set(expected_final_tags), f"Expected {expected_final_tags}, got {final_tags}" + assert len(final_tags) == len(expected_final_tags), f"Expected {len(expected_final_tags)} tags, got {len(final_tags)}" + print(" โœ“ Tags replaced successfully") + + # Check that old extras are gone and only new ones remain + final_extras = {extra["key"]: extra["value"] for extra in verified_replace.get("extras", [])} + assert "created_by" not in final_extras # Should be gone + assert "test_phase" not in final_extras # Should be gone + assert final_extras["final_phase"] == "replace_test" + assert final_extras["mode"] == "replace" + print(" โœ“ Metadata replaced successfully") + + print("โœ… Replace mode test passed!") + + finally: + # Cleanup: Delete the test dataset + try: + client.ckan.delete_dataset(dataset_name) + print(f"๐Ÿงน Cleaned up test dataset: {dataset_name}") + except Exception as e: + print(f"โš ๏ธ Warning: Could not delete test dataset {dataset_name}: {e}") + + print("๐ŸŽ‰ CKAN dataset update integration test completed successfully!") diff --git a/tests/integration/test_ckan_integration.py b/tests/integration/test_ckan_integration.py new file mode 100644 index 0000000..7155b91 --- /dev/null +++ b/tests/integration/test_ckan_integration.py @@ -0,0 +1,655 @@ +""" +CKAN integration tests for Upstream SDK. +""" + +import io +import os +import tempfile +from datetime import datetime +from pathlib import Path +from unittest.mock import MagicMock, patch + +import pytest +from upstream_api_client import GetCampaignResponse, SummaryGetCampaign, GetStationResponse + +from upstream.ckan import CKANIntegration +from upstream.client import UpstreamClient +from upstream.exceptions import APIError, ConfigurationError + +# Test configuration - these should be set in environment for real CKAN testing +CKAN_URL = os.environ.get("CKAN_URL", "http://localhost:5000") +CKAN_API_KEY = os.environ.get("CKAN_API_KEY") +CKAN_ORGANIZATION = os.environ.get("CKAN_ORGANIZATION", "test-organization") +UPSTREAM_BASE_URL = os.environ.get("UPSTREAM_BASE_URL", "http://localhost:8000") +UPSTREAM_USERNAME = os.environ.get("UPSTREAM_USERNAME", "test") +UPSTREAM_PASSWORD = os.environ.get("UPSTREAM_PASSWORD", "test") + +pytestmark = pytest.mark.integration + + +@pytest.fixture +def ckan_config(): + """CKAN configuration for testing.""" + config = {"timeout": 30, "ckan_organization": CKAN_ORGANIZATION} + if CKAN_API_KEY: + config["api_key"] = CKAN_API_KEY + return config + + +@pytest.fixture +def ckan_client(ckan_config): + """CKAN client for testing.""" + return CKANIntegration(ckan_url=CKAN_URL, config=ckan_config) + + +@pytest.fixture +def sample_dataset_data(): + """Sample dataset data for testing.""" + timestamp = datetime.now().strftime("%Y%m%d%H%M%S") + return { + "name": f"test-dataset-{timestamp}", + "title": f"Test Dataset {timestamp}", + "description": "Integration test dataset", + "tags": ["test", "integration", "upstream"], + } + + +@pytest.fixture +def sample_campaign_response(): + """Sample campaign response for testing.""" + # Use unique ID based on timestamp to avoid conflicts + unique_id = int(datetime.now().timestamp() * 1000) % 1000000 + return GetCampaignResponse( + id=unique_id, + name="Test Campaign", + description="A test campaign for CKAN integration", + contact_name="Test Contact", + contact_email="test@example.com", + allocation="TACC", + start_date=datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"), + end_date=datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"), + summary=SummaryGetCampaign( + station_count=2, + sensor_count=5, + sensor_types=["temperature", "humidity", "pressure"], + sensor_variables=["temperature", "humidity", "pressure"], + ), + ) + + +@pytest.fixture +def mock_station_data(): + """Sample station data for testing.""" + return GetStationResponse( + id=123, + name="Test Station", + description="A test station for CKAN integration", + contact_name="Station Contact", + contact_email="station@example.com", + active=True, + start_date=datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"), + geometry={"type": "Point", "coordinates": [-97.7431, 30.2672]}, + sensors=[] + ) + + +@pytest.fixture +def temp_sensor_csv(): + """Create a temporary sensor CSV file for testing.""" + with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f: + f.write("alias,variablename,units\n") + f.write("temp_01,Air Temperature,ยฐC\n") + f.write("humidity_01,Relative Humidity,%\n") + temp_path = f.name + + yield Path(temp_path) + Path(temp_path).unlink() + + +@pytest.fixture +def temp_measurement_csv(): + """Create a temporary measurement CSV file for testing.""" + with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f: + f.write("collectiontime,Lat_deg,Lon_deg,temp_01,humidity_01\n") + f.write("2024-01-01T10:00:00Z,30.2672,-97.7431,25.5,65.2\n") + f.write("2024-01-01T10:01:00Z,30.2672,-97.7431,25.7,64.8\n") + temp_path = f.name + + yield Path(temp_path) + Path(temp_path).unlink() + + +@pytest.mark.skipif( + not CKAN_API_KEY, + reason="CKAN_API_KEY must be set in environment for CKAN integration tests", +) +class TestCKANDatasetOperations: + """Test CKAN dataset operations.""" + + def test_dataset_lifecycle(self, ckan_client: CKANIntegration, sample_dataset_data): + """Test complete dataset lifecycle: create, get, update, delete.""" + dataset_name = sample_dataset_data["name"] + + try: + # Create dataset + created_dataset = ckan_client.create_dataset(**sample_dataset_data) + assert created_dataset["name"] == dataset_name + assert created_dataset["title"] == sample_dataset_data["title"] + assert created_dataset["notes"] == sample_dataset_data["description"] + assert len(created_dataset["tags"]) == len(sample_dataset_data["tags"]) + + # Get dataset + retrieved_dataset = ckan_client.get_dataset(dataset_name) + assert retrieved_dataset["name"] == dataset_name + assert retrieved_dataset["id"] == created_dataset["id"] + + # Update dataset + updated_title = "Updated Test Dataset" + updated_dataset = ckan_client.update_dataset( + dataset_name, title=updated_title + ) + assert updated_dataset["title"] == updated_title + + # Verify update + retrieved_updated = ckan_client.get_dataset(dataset_name) + assert retrieved_updated["title"] == updated_title + + finally: + # Clean up - delete dataset + try: + result = ckan_client.delete_dataset(dataset_name) + assert result is True + except APIError: + pass # Dataset might not exist or already deleted + + def test_get_nonexistent_dataset(self, ckan_client): + """Test getting a dataset that doesn't exist.""" + with pytest.raises(APIError, match="not found"): + ckan_client.get_dataset("nonexistent-dataset-12345") + + def test_create_dataset_minimal(self, ckan_client): + """Test creating a dataset with minimal required fields.""" + timestamp = datetime.now().strftime("%Y%m%d%H%M%S") + dataset_name = f"minimal-test-{timestamp}" + + try: + dataset = ckan_client.create_dataset( + name=dataset_name, title="Minimal Test Dataset" + ) + assert dataset["name"] == dataset_name + assert dataset["title"] == "Minimal Test Dataset" + + finally: + try: + ckan_client.delete_dataset(dataset_name) + except APIError: + pass + + +@pytest.mark.skipif( + not CKAN_API_KEY, + reason="CKAN_API_KEY must be set in environment for CKAN integration tests", +) +class TestCKANResourceOperations: + """Test CKAN resource operations.""" + + def test_create_file_resource( + self, ckan_client, sample_dataset_data, temp_sensor_csv + ): + """Test creating a resource with file upload.""" + dataset_name = sample_dataset_data["name"] + + try: + # Create dataset first + dataset = ckan_client.create_dataset(**sample_dataset_data) + + # Create resource with file upload + resource = ckan_client.create_resource( + dataset_id=dataset["id"], + name="Test Sensor Data", + file_path=temp_sensor_csv, + format="CSV", + description="Test sensor configuration data", + ) + + assert resource["name"] == "Test Sensor Data" + assert resource["format"] == "CSV" + assert resource["description"] == "Test sensor configuration data" + assert resource["package_id"] == dataset["id"] + + finally: + try: + ckan_client.delete_dataset(dataset_name) + except APIError: + pass + + def test_create_url_resource(self, ckan_client, sample_dataset_data): + """Test creating a resource with URL.""" + dataset_name = sample_dataset_data["name"] + + try: + # Create dataset first + dataset = ckan_client.create_dataset(**sample_dataset_data) + + # Create resource with URL + resource = ckan_client.create_resource( + dataset_id=dataset["id"], + name="Test Data URL", + url="https://example.com/data2.csv", + format="CSV", + description="Test data from external URL", + ) + + assert resource["name"] == "Test Data URL" + assert resource["url"] == "https://example.com/data2.csv" + assert resource["format"] == "CSV" + + finally: + try: + ckan_client.delete_dataset(dataset_name) + except APIError: + pass + + def test_create_resource_missing_file(self, ckan_client, sample_dataset_data): + """Test creating a resource with missing file.""" + dataset_name = sample_dataset_data["name"] + + try: + dataset = ckan_client.create_dataset(**sample_dataset_data) + + with pytest.raises(APIError, match="File not found"): + ckan_client.create_resource( + dataset_id=dataset["id"], + name="Missing File", + file_path="/nonexistent/file.csv", + ) + + finally: + try: + ckan_client.delete_dataset(dataset_name) + except APIError: + pass + + +@pytest.mark.skipif( + not CKAN_API_KEY, + reason="CKAN_API_KEY must be set in environment for CKAN integration tests", +) +class TestCKANCampaignPublishing: + """Test CKAN campaign publishing functionality.""" + + def test_publish_campaign_with_streams( + self, + ckan_client: CKANIntegration, + sample_campaign_response, + mock_station_sensors_csv, + mock_station_measurements_csv, + mock_station_data, + ): + """Test publishing campaign data with stream uploads.""" + campaign_id = sample_campaign_response.id + dataset_name = f"upstream-campaign-{campaign_id}" + dataset_title = f"Test Campaign {campaign_id}" + + try: + result = ckan_client.publish_campaign( + campaign_id=campaign_id, + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + auto_publish=False, + ) + + assert result["success"] is True + assert "dataset" in result + assert "resources" in result + assert "ckan_url" in result + assert len(result["resources"]) == 2 # sensors + measurements + + # Verify dataset was created + dataset = result["dataset"] + assert dataset["name"] == dataset_name + assert dataset_title.startswith(dataset["title"]) + assert "environmental" in [tag["name"] for tag in dataset["tags"]] + + # Verify resources were created + resources = result["resources"] + resource_names = [r["name"] for r in resources] + assert len(resources) == 2 + assert any("Test Station - Sensors Configuration" in name for name in resource_names) + assert any("Test Station - Measurement Data" in name for name in resource_names) + + # Verify resource metadata + for resource in resources: + assert resource["format"] == "CSV" + if "Sensors Configuration" in resource["name"]: + assert resource["description"] == "Sensor configuration and metadata" + elif "Measurement Data" in resource["name"]: + assert resource["description"] == "Environmental sensor measurements" + + # Verify campaign metadata is stored in dataset extras + dataset_extras = {extra["key"]: extra["value"] for extra in dataset.get("extras", [])} + assert "campaign_id" in dataset_extras + assert dataset_extras["campaign_id"] == str(campaign_id) + assert "campaign_name" in dataset_extras + assert dataset_extras["campaign_name"] == sample_campaign_response.name + assert "campaign_contact_name" in dataset_extras + assert dataset_extras["campaign_contact_name"] == sample_campaign_response.contact_name + assert "campaign_contact_email" in dataset_extras + assert dataset_extras["campaign_contact_email"] == sample_campaign_response.contact_email + assert "campaign_allocation" in dataset_extras + assert dataset_extras["campaign_allocation"] == sample_campaign_response.allocation + assert "source" in dataset_extras + assert dataset_extras["source"] == "Upstream Platform" + assert "data_type" in dataset_extras + assert dataset_extras["data_type"] == "environmental_sensor_data" + + # Verify station metadata is stored as direct resource fields + for resource in resources: + assert "station_id" in resource + assert resource["station_id"] == str(mock_station_data.id) + assert "station_name" in resource + assert resource["station_name"] == mock_station_data.name + assert "station_description" in resource + assert resource["station_description"] == mock_station_data.description + assert "station_contact_name" in resource + assert resource["station_contact_name"] == mock_station_data.contact_name + assert "station_contact_email" in resource + assert resource["station_contact_email"] == mock_station_data.contact_email + assert "station_active" in resource + assert resource["station_active"] == str(mock_station_data.active) + assert "station_geometry" in resource + assert "station_sensors_count" in resource + assert resource["station_sensors_count"] == str(len(mock_station_data.sensors)) + + finally: + try: + ckan_client.delete_dataset(dataset_name) + except APIError: + pass + + def test_publish_campaign_update_existing( + self, ckan_client: CKANIntegration, sample_campaign_response, + mock_station_sensors_csv, mock_station_measurements_csv, mock_station_data + ): + """Test updating an existing campaign dataset.""" + campaign_id = sample_campaign_response.id + dataset_name = f"upstream-campaign-{campaign_id}" + + try: + # Create initial publication + result1 = ckan_client.publish_campaign( + campaign_id=campaign_id, + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + ) + + initial_dataset_id = result1["dataset"]["id"] + + # Create fresh streams for the update call + sensors_data = "alias,variablename,units\ntemp_02,Air Temperature 2,ยฐC\n" + sensors_csv = io.BytesIO(sensors_data.encode('utf-8')) + measurements_data = "collectiontime,Lat_deg,Lon_deg,temp_02\n2024-01-01T11:00:00Z,30.2672,-97.7431,26.0\n" + measurements_csv = io.BytesIO(measurements_data.encode('utf-8')) + + # Update with different data + updated_campaign = sample_campaign_response + updated_campaign.description = "Updated campaign description" + + result2 = ckan_client.publish_campaign( + campaign_id=campaign_id, + campaign_data=updated_campaign, + station_measurements=measurements_csv, + station_sensors=sensors_csv, + station_data=mock_station_data, + ) + + # Should update the same dataset + assert result2["dataset"]["id"] == initial_dataset_id + assert result2["dataset"]["notes"] == "Updated campaign description" + + finally: + try: + print(f"Deleting dataset: {dataset_name}") + ckan_client.delete_dataset(dataset_name) + except APIError: + pass + + +@pytest.mark.skipif( + not CKAN_API_KEY, + reason="CKAN_API_KEY must be set in environment for CKAN integration tests", +) +class TestCKANListOperations: + """Test CKAN list operations.""" + + def test_list_datasets(self, ckan_client): + """Test listing datasets.""" + datasets = ckan_client.list_datasets(limit=10) + assert isinstance(datasets, list) + if datasets: + dataset = datasets[0] + assert "name" in dataset + assert "title" in dataset + + def test_list_datasets_with_filters(self, ckan_client): + """Test listing datasets with filters.""" + datasets = ckan_client.list_datasets(tags=["test"], limit=5) + assert isinstance(datasets, list) + + def test_list_organizations(self, ckan_client): + """Test listing organizations.""" + try: + organizations = ckan_client.list_organizations() + assert isinstance(organizations, list) + except APIError: + # Some CKAN instances might not allow listing organizations + pytest.skip("Organization listing not allowed on this CKAN instance") + + +@pytest.mark.skipif( + not CKAN_API_KEY, + reason="CKAN_API_KEY must be set in environment for CKAN integration tests", +) +class TestCKANUtilities: + """Test CKAN utility functions.""" + + def test_sanitize_title(self, ckan_client): + """Test title sanitization.""" + assert ckan_client.sanitize_title("Test Dataset") == "Test_Dataset" + assert ckan_client.sanitize_title("Test-Dataset-Name") == "Test_Dataset_Name" + assert ( + ckan_client.sanitize_title("Multiple Word Dataset Name") + == "Multiple_Word_Dataset_Name" + ) + + +# Unit tests that don't require a real CKAN instance +class TestCKANUnitTests: + """Unit tests for CKAN functionality.""" + + def test_ckan_initialization(self): + """Test CKAN client initialization.""" + client = CKANIntegration("http://test.example.com") + assert client.ckan_url == "http://test.example.com" + assert client.config == {} + + # Test with trailing slash removal + client2 = CKANIntegration("http://test.example.com/") + assert client2.ckan_url == "http://test.example.com" + + def test_ckan_initialization_with_config(self): + """Test CKAN client initialization with configuration.""" + config = {"api_key": "test-key", "timeout": 60} + client = CKANIntegration("http://test.example.com", config=config) + + assert client.config == config + assert client.timeout == 60 + assert "Authorization" in client.session.headers + + def test_sanitize_title_edge_cases(self): + """Test title sanitization edge cases.""" + client = CKANIntegration("http://test.example.com") + + assert client.sanitize_title("") == "" + assert client.sanitize_title("NoSpaces") == "NoSpaces" + assert client.sanitize_title("___") == "___" + assert client.sanitize_title("Mix_of-Both Spaces") == "Mix_of_Both_Spaces" + + +@pytest.fixture +def mock_station_sensors_csv(): + """Mock station sensors CSV data as a stream.""" + csv_data = "alias,variablename,units\ntemp_01,Air Temperature,ยฐC\nhumidity_01,Relative Humidity,%\n" + return io.BytesIO(csv_data.encode('utf-8')) + + +@pytest.fixture +def mock_station_measurements_csv(): + """Mock station measurements CSV data as a stream.""" + csv_data = "collectiontime,Lat_deg,Lon_deg,temp_01,humidity_01\n2024-01-01T10:00:00Z,30.2672,-97.7431,25.5,65.2\n" + return io.BytesIO(csv_data.encode('utf-8')) + + +class TestUpstreamClientCKANIntegration: + """Test UpstreamClient publish_to_ckan functionality.""" + + @pytest.fixture + def mock_upstream_client(self): + """Mock UpstreamClient with CKAN integration.""" + with patch('upstream.client.UpstreamClient') as mock_client_class: + mock_client = MagicMock() + mock_client_class.return_value = mock_client + + # Mock CKAN integration + mock_ckan = MagicMock() + mock_client.ckan = mock_ckan + + # Mock station manager with export methods + mock_stations = MagicMock() + mock_client.stations = mock_stations + + yield mock_client + + def test_publish_to_ckan_with_station_streams( + self, mock_station_sensors_csv, mock_station_measurements_csv + ): + """Test publish_to_ckan with station_id parameter and streaming data.""" + # Create a mock client and mock its dependencies + mock_client = MagicMock() + + # Setup mock return values + mock_client.stations.export_station_measurements.return_value = ( + mock_station_measurements_csv + ) + mock_client.stations.export_station_sensors.return_value = ( + mock_station_sensors_csv + ) + mock_client.campaigns.get.return_value = MagicMock() # Mock campaign data + mock_client.ckan = MagicMock() # Mock CKAN integration + + expected_result = { + "success": True, + "dataset": {"id": "test-dataset", "name": "test-campaign"}, + "resources": [{"id": "resource1"}, {"id": "resource2"}] + } + mock_client.ckan.publish_campaign.return_value = expected_result + + # Import and call the real publish_to_ckan method + from upstream.client import UpstreamClient + + # Call the method on the mock client + result = UpstreamClient.publish_to_ckan(mock_client, campaign_id="123", station_id="456") + + # Verify station export methods were called + mock_client.stations.export_station_measurements.assert_called_once_with( + station_id="456", campaign_id="123" + ) + mock_client.stations.export_station_sensors.assert_called_once_with( + station_id="456", campaign_id="123" + ) + mock_client.campaigns.get.assert_called_once_with(campaign_id="123") + + # Verify CKAN publish_campaign was called with streams + mock_client.ckan.publish_campaign.assert_called_once() + call_args = mock_client.ckan.publish_campaign.call_args + + assert call_args[1]['campaign_id'] == "123" + assert 'station_measurements' in call_args[1] + assert 'station_sensors' in call_args[1] + assert 'campaign_data' in call_args[1] + + # Verify the result + assert result == expected_result + + def test_publish_to_ckan_without_ckan_integration(self): + """Test error when CKAN integration is not configured.""" + # Create mock client with no CKAN integration + mock_client = MagicMock() + mock_client.ckan = None # No CKAN integration + + from upstream.client import UpstreamClient + + with pytest.raises(ConfigurationError, match="CKAN integration not configured"): + UpstreamClient.publish_to_ckan(mock_client, campaign_id="123", station_id="456") + + def test_publish_to_ckan_station_export_error(self): + """Test error handling when station export fails.""" + # Create mock client + mock_client = MagicMock() + + # Set up the side_effect to raise an exception when export_station_measurements is called + mock_client.stations.export_station_measurements.side_effect = APIError("Station export failed") + mock_client.ckan = MagicMock() # Has CKAN integration + + # Ensure ckan is truthy to pass the None check + type(mock_client).ckan = MagicMock() + + from upstream.client import UpstreamClient + + with pytest.raises(APIError, match="Station export failed"): + UpstreamClient.publish_to_ckan(mock_client, campaign_id="123", station_id="456") + + def test_publish_to_ckan_streams_contain_data( + self, mock_station_sensors_csv, mock_station_measurements_csv + ): + """Test that station streams contain expected data format.""" + # Create mock client + mock_client = MagicMock() + mock_client.stations.export_station_measurements.return_value = ( + mock_station_measurements_csv + ) + mock_client.stations.export_station_sensors.return_value = ( + mock_station_sensors_csv + ) + mock_client.campaigns.get.return_value = MagicMock() + mock_client.ckan = MagicMock() + mock_client.ckan.publish_campaign.return_value = {"success": True} + + from upstream.client import UpstreamClient + + # Test the method + UpstreamClient.publish_to_ckan(mock_client, campaign_id="123", station_id="456") + + # Verify CKAN was called with streams + call_args = mock_client.ckan.publish_campaign.call_args[1] + + # Check that streams are BinaryIO objects + station_measurements = call_args['station_measurements'] + station_sensors = call_args['station_sensors'] + + # Reset stream positions to read content + station_measurements.seek(0) + station_sensors.seek(0) + + measurements_content = station_measurements.read().decode('utf-8') + sensors_content = station_sensors.read().decode('utf-8') + + # Verify CSV content structure + assert "collectiontime" in measurements_content + assert "temp_01" in measurements_content + assert "alias" in sensors_content + assert "variablename" in sensors_content diff --git a/tests/integration/test_measurements_integration.py b/tests/integration/test_measurements_integration.py index 2089811..55b5525 100644 --- a/tests/integration/test_measurements_integration.py +++ b/tests/integration/test_measurements_integration.py @@ -22,7 +22,7 @@ @pytest.fixture -def client(): +def upstream_client(): """Create authenticated client for testing.""" username = os.environ.get("UPSTREAM_USERNAME") password = os.environ.get("UPSTREAM_PASSWORD") @@ -32,16 +32,16 @@ def client(): "UPSTREAM_USERNAME and UPSTREAM_PASSWORD environment variables required" ) - client = UpstreamClient( + upstream_client = UpstreamClient( username=username, password=password, base_url=BASE_URL, ckan_url=CKAN_URL ) # Ensure authentication - assert client.authenticate(), "Authentication failed" - return client + assert upstream_client.authenticate(), "Authentication failed" + return upstream_client -def test_measurement_lifecycle(client): +def test_measurement_lifecycle(upstream_client): """Test complete measurement lifecycle: create, list, update, delete.""" # Create a campaign first from upstream_api_client.models import CampaignsIn @@ -56,7 +56,7 @@ def test_measurement_lifecycle(client): end_date=datetime.now() + timedelta(days=30), ) - campaign = client.create_campaign(campaign_data) + campaign = upstream_client.create_campaign(campaign_data) campaign_id = str(campaign.id) try: @@ -72,7 +72,7 @@ def test_measurement_lifecycle(client): active=True, ) - station = client.create_station(campaign_id, station_data) + station = upstream_client.create_station(campaign_id, station_data) station_id = str(station.id) try: @@ -102,7 +102,7 @@ def test_measurement_lifecycle(client): try: # Upload sensor - result = client.upload_sensor_measurement_files( + result = upstream_client.upload_sensor_measurement_files( campaign_id=campaign_id, station_id=station_id, sensors_file=sensors_file_path, @@ -110,7 +110,7 @@ def test_measurement_lifecycle(client): ) # Get the sensor ID - sensors = client.sensors.list( + sensors = upstream_client.sensors.list( campaign_id=campaign_id, station_id=station_id ) assert len(sensors.items) > 0 @@ -127,7 +127,7 @@ def test_measurement_lifecycle(client): geometry="POINT(-97.7431 30.2672)", ) - created_measurement = client.measurements.create( + created_measurement = upstream_client.measurements.create( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -138,7 +138,7 @@ def test_measurement_lifecycle(client): print(f"Created measurement: {created_measurement.id}") # Test list measurements - measurements = client.list_measurements( + measurements = upstream_client.list_measurements( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -150,7 +150,7 @@ def test_measurement_lifecycle(client): # Test get measurements with confidence intervals confidence_measurements = ( - client.get_measurements_with_confidence_intervals( + upstream_client.get_measurements_with_confidence_intervals( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -170,7 +170,7 @@ def test_measurement_lifecycle(client): measurementvalue=26.0, description="Updated test measurement" ) - client.update_measurement( + upstream_client.update_measurement( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -178,7 +178,7 @@ def test_measurement_lifecycle(client): measurement_update=update_data, ) - updated_measurement = client.measurements.list( + updated_measurement = upstream_client.measurements.list( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -201,7 +201,7 @@ def test_measurement_lifecycle(client): # print(f"Updated measurement: {updated_measurement.id}") # Test delete measurements - result = client.delete_measurements( + result = upstream_client.delete_measurements( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id ) @@ -209,7 +209,7 @@ def test_measurement_lifecycle(client): print(f"Deleted measurements for sensor: {sensor_id}") # Verify deletion - measurements_after_delete = client.list_measurements( + measurements_after_delete = upstream_client.list_measurements( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id ) @@ -234,7 +234,7 @@ def test_measurement_lifecycle(client): pass -def test_measurement_filtering(client): +def test_measurement_filtering(upstream_client): """Test measurement filtering and querying capabilities.""" # Create a campaign first from upstream_api_client.models import CampaignsIn @@ -249,7 +249,7 @@ def test_measurement_filtering(client): end_date=datetime.now() + timedelta(days=30), ) - campaign = client.create_campaign(campaign_data) + campaign = upstream_client.create_campaign(campaign_data) campaign_id = str(campaign.id) try: @@ -265,7 +265,7 @@ def test_measurement_filtering(client): active=True, ) - station = client.create_station(campaign_id, station_data) + station = upstream_client.create_station(campaign_id, station_data) station_id = str(station.id) try: @@ -296,7 +296,7 @@ def test_measurement_filtering(client): try: # Upload sensor and measurements - result = client.upload_sensor_measurement_files( + result = upstream_client.upload_sensor_measurement_files( campaign_id=campaign_id, station_id=station_id, sensors_file=sensors_file_path, @@ -304,7 +304,7 @@ def test_measurement_filtering(client): ) # Get the sensor ID - sensors = client.sensors.list( + sensors = upstream_client.sensors.list( campaign_id=campaign_id, station_id=station_id ) assert len(sensors.items) > 0 @@ -315,7 +315,7 @@ def test_measurement_filtering(client): start_date = datetime(2024, 1, 15, 10, 0, 0) end_date = datetime(2024, 1, 15, 12, 0, 0) - filtered_measurements = client.list_measurements( + filtered_measurements = upstream_client.list_measurements( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -326,7 +326,7 @@ def test_measurement_filtering(client): print(f"Found {filtered_measurements.total} measurements in date range") # Test filtering by value range - value_filtered_measurements = client.list_measurements( + value_filtered_measurements = upstream_client.list_measurements( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -339,7 +339,7 @@ def test_measurement_filtering(client): ) # Test pagination - paginated_measurements = client.list_measurements( + paginated_measurements = upstream_client.list_measurements( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, @@ -352,7 +352,7 @@ def test_measurement_filtering(client): ) # Test confidence intervals with different intervals - hourly_intervals = client.get_measurements_with_confidence_intervals( + hourly_intervals = upstream_client.get_measurements_with_confidence_intervals( campaign_id=campaign_id, station_id=station_id, sensor_id=sensor_id, diff --git a/tests/unit/test_ckan_unit.py b/tests/unit/test_ckan_unit.py new file mode 100644 index 0000000..1cbab5a --- /dev/null +++ b/tests/unit/test_ckan_unit.py @@ -0,0 +1,1340 @@ +""" +Unit tests for CKAN integration module. +""" + +import io +import json +import tempfile +from pathlib import Path +from unittest.mock import Mock, patch, mock_open + +import pytest +import requests +from upstream_api_client import GetCampaignResponse, SummaryGetCampaign, GetStationResponse + +from upstream.ckan import CKANIntegration +from upstream.exceptions import APIError + +pytestmark = pytest.mark.unit + + +@pytest.fixture +def mock_ckan_response(): + """Mock CKAN API response.""" + response = Mock() + response.status_code = 200 + response.raise_for_status.return_value = None + response.json.return_value = { + "success": True, + "result": { + "id": "test-dataset-id", + "name": "test-dataset", + "title": "Test Dataset", + "notes": "Test description", + "tags": [{"name": "test"}, {"name": "integration"}], + }, + } + return response + + +@pytest.fixture +def mock_ckan_error_response(): + """Mock CKAN API error response.""" + response = Mock() + response.status_code = 400 + response.raise_for_status.side_effect = requests.exceptions.HTTPError("Bad Request") + response.json.return_value = { + "success": False, + "error": {"message": "Validation Error", "name": ["Missing value"]}, + } + return response + +@pytest.fixture +def mock_station_sensors_csv(): + """Mock station sensors CSV data as a stream.""" + csv_data = "alias,variablename,units\ntemp_01,Air Temperature,ยฐC\nhumidity_01,Relative Humidity,%\n" + return io.BytesIO(csv_data.encode('utf-8')) + + +@pytest.fixture +def mock_station_measurements_csv(): + """Mock station measurements CSV data as a stream.""" + csv_data = "collectiontime,Lat_deg,Lon_deg,temp_01,humidity_01\n2024-01-01T10:00:00Z,30.2672,-97.7431,25.5,65.2\n" + return io.BytesIO(csv_data.encode('utf-8')) + + +@pytest.fixture +def sample_campaign_response(): + """Sample campaign response for testing.""" + return GetCampaignResponse( + id=100, + name="Test Campaign", + description="A test campaign", + contact_name="Test Contact", + contact_email="test@example.com", + allocation="TACC", + start_date="2024-01-01T00:00:00Z", + end_date="2024-12-31T23:59:59Z", + summary=SummaryGetCampaign( + station_count=2, + sensor_count=5, + sensor_types=["temperature", "humidity"], + sensor_variables=["temperature", "humidity"], + ), + ) + + +@pytest.fixture +def mock_station_data(): + """Sample station data for testing.""" + return GetStationResponse( + id=123, + name="Test Station", + description="A test station", + contact_name="Station Contact", + contact_email="station@example.com", + active=True, + start_date="2024-01-01T00:00:00Z", + geometry={"type": "Point", "coordinates": [-97.7431, 30.2672]}, + sensors=[] + ) + + +class TestCKANIntegrationInit: + """Test CKAN integration initialization.""" + + def test_init_basic(self): + """Test basic initialization.""" + ckan = CKANIntegration("http://test.example.com") + assert ckan.ckan_url == "http://test.example.com" + assert ckan.config == {} + assert ckan.timeout == 30 + + def test_init_with_trailing_slash(self): + """Test initialization with trailing slash removal.""" + ckan = CKANIntegration("http://test.example.com/") + assert ckan.ckan_url == "http://test.example.com" + + def test_init_with_config(self): + """Test initialization with configuration.""" + config = {"api_key": "test-key", "timeout": 60} + ckan = CKANIntegration("http://test.example.com", config=config) + + assert ckan.config == config + assert ckan.timeout == 60 + assert "Authorization" in ckan.session.headers + assert ckan.session.headers["Authorization"] == "test-key" + + def test_init_with_access_token(self): + """Test initialization with access token.""" + config = {"access_token": "test-token"} + ckan = CKANIntegration("http://test.example.com", config=config) + + assert "Authorization" in ckan.session.headers + assert ckan.session.headers["Authorization"] == "Bearer test-token" + + +class TestCKANDatasetOperations: + """Test CKAN dataset operations.""" + + @patch("upstream.ckan.requests.Session.post") + def test_create_dataset_success(self, mock_post, mock_ckan_response): + """Test successful dataset creation.""" + mock_post.return_value = mock_ckan_response + ckan = CKANIntegration("http://test.example.com") + + result = ckan.create_dataset( + name="test-dataset", title="Test Dataset", description="Test description" + ) + + assert result["name"] == "test-dataset" + assert result["title"] == "Test Dataset" + mock_post.assert_called_once() + + @patch("upstream.ckan.requests.Session.post") + def test_create_dataset_with_organization(self, mock_post, mock_ckan_response): + """Test dataset creation with organization.""" + mock_post.return_value = mock_ckan_response + ckan = CKANIntegration("http://test.example.com") + + result = ckan.create_dataset( + name="test-dataset", + title="Test Dataset", + organization="test-org", + tags=["test", "data"], + ) + + # Check that the call was made with the right data + call_args = mock_post.call_args + data = call_args[1]["json"] + assert data["owner_org"] == "test-org" + assert data["tags"] == [{"name": "test"}, {"name": "data"}] + + @patch("upstream.ckan.requests.Session.post") + def test_create_dataset_failure(self, mock_post, mock_ckan_error_response): + """Test dataset creation failure.""" + mock_post.return_value = mock_ckan_error_response + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="Failed to create CKAN dataset"): + ckan.create_dataset(name="test-dataset", title="Test Dataset") + + @patch("upstream.ckan.requests.Session.post") + def test_create_dataset_api_error(self, mock_post): + """Test dataset creation with API error response.""" + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": False, + "error": {"message": "Validation failed"}, + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="CKAN dataset creation failed"): + ckan.create_dataset(name="test-dataset", title="Test Dataset") + + @patch("upstream.ckan.requests.Session.get") + def test_get_dataset_success(self, mock_get, mock_ckan_response): + """Test successful dataset retrieval.""" + mock_get.return_value = mock_ckan_response + ckan = CKANIntegration("http://test.example.com") + + result = ckan.get_dataset("test-dataset") + + assert result["name"] == "test-dataset" + mock_get.assert_called_once() + + @patch("upstream.ckan.requests.Session.get") + def test_get_dataset_not_found(self, mock_get): + """Test dataset not found.""" + mock_response = Mock() + mock_response.status_code = 404 + mock_response.raise_for_status.side_effect = requests.exceptions.HTTPError() + mock_response.response.status_code = 404 + mock_get.return_value = mock_response + + # Need to set the response attribute for the hasattr check + error = requests.exceptions.HTTPError() + error.response = mock_response + mock_response.raise_for_status.side_effect = error + + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="CKAN dataset not found"): + ckan.get_dataset("nonexistent-dataset") + + @patch("upstream.ckan.requests.Session.post") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_update_dataset_success(self, mock_get, mock_post, mock_ckan_response): + """Test successful dataset update.""" + # Mock getting current dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Old Title", + } + + # Mock update response + updated_response = mock_ckan_response + updated_response.json.return_value["result"]["title"] = "New Title" + mock_post.return_value = updated_response + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.update_dataset("test-dataset", title="New Title") + + assert result["title"] == "New Title" + mock_get.assert_called_once_with("test-dataset") + mock_post.assert_called_once() + + @patch("upstream.ckan.requests.Session.post") + def test_delete_dataset_success(self, mock_post): + """Test successful dataset deletion.""" + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = {"success": True} + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.delete_dataset("test-dataset") + + assert result is True + mock_post.assert_called_once() + + +class TestCKANResourceOperations: + """Test CKAN resource operations.""" + + @patch("upstream.ckan.requests.Session.post") + def test_create_resource_with_url(self, mock_post): + """Test creating a resource with URL.""" + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": { + "id": "resource-id", + "name": "Test Resource", + "url": "https://example.com/data.csv", + "format": "CSV", + }, + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.create_resource( + dataset_id="dataset-id", + name="Test Resource", + url="https://example.com/data.csv", + format="CSV", + ) + + assert result["name"] == "Test Resource" + assert result["url"] == "https://example.com/data.csv" + mock_post.assert_called_once() + + @patch("upstream.ckan.requests.Session.post") + @patch("builtins.open", new_callable=mock_open, read_data="test,data\n1,2\n") + @patch("pathlib.Path.exists") + def test_create_resource_with_file(self, mock_exists, mock_file, mock_post): + """Test creating a resource with file upload.""" + mock_exists.return_value = True + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": { + "id": "resource-id", + "name": "Test Resource", + "format": "CSV", + }, + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.create_resource( + dataset_id="dataset-id", + name="Test Resource", + file_path="/path/to/test.csv", + format="CSV", + ) + + assert result["name"] == "Test Resource" + mock_post.assert_called_once() + + @patch("pathlib.Path.exists") + def test_create_resource_file_not_found(self, mock_exists): + """Test creating a resource with missing file.""" + mock_exists.return_value = False + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="File not found"): + ckan.create_resource( + dataset_id="dataset-id", + name="Test Resource", + file_path="/nonexistent/file.csv", + ) + + def test_create_resource_no_source(self): + """Test creating a resource with no URL or file.""" + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="Either url, file_path, or file_obj must be provided"): + ckan.create_resource(dataset_id="dataset-id", name="Test Resource") + + @patch("upstream.ckan.requests.Session.post") + def test_create_resource_with_file_obj(self, mock_post): + """Test creating a resource with file object.""" + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "resource-id", "name": "Test Resource"}, + } + mock_post.return_value = mock_response + + # Create a mock file object + file_obj = Mock() + file_obj.name = "test.csv" + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.create_resource( + dataset_id="dataset-id", name="Test Resource", file_obj=file_obj + ) + + assert result["name"] == "Test Resource" + mock_post.assert_called_once() + + +class TestCKANListOperations: + """Test CKAN list operations.""" + + @patch("upstream.ckan.requests.Session.get") + def test_list_datasets(self, mock_get): + """Test listing datasets.""" + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": { + "results": [ + {"name": "dataset1", "title": "Dataset 1"}, + {"name": "dataset2", "title": "Dataset 2"}, + ] + }, + } + mock_get.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.list_datasets(limit=10) + + assert len(result) == 2 + assert result[0]["name"] == "dataset1" + mock_get.assert_called_once() + + @patch("upstream.ckan.requests.Session.get") + def test_list_datasets_with_filters(self, mock_get): + """Test listing datasets with organization and tag filters.""" + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"results": []}, + } + mock_get.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + ckan.list_datasets(organization="test-org", tags=["tag1", "tag2"]) + + # Check that the query was properly constructed + call_args = mock_get.call_args + params = call_args[1]["params"] + assert 'owner_org:"test-org"' in params["q"] + assert 'tags:"tag1"' in params["q"] + assert 'tags:"tag2"' in params["q"] + + @patch("upstream.ckan.requests.Session.get") + def test_list_organizations(self, mock_get): + """Test listing organizations.""" + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": [ + {"name": "org1", "title": "Organization 1"}, + {"name": "org2", "title": "Organization 2"}, + ], + } + mock_get.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.list_organizations() + + assert len(result) == 2 + assert result[0]["name"] == "org1" + mock_get.assert_called_once() + + +class TestCKANCampaignPublishing: + """Test CKAN campaign publishing functionality.""" + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_success( + self, mock_get, mock_create, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test successful campaign publishing.""" + # Mock get_dataset to raise APIError (dataset doesn't exist) + mock_get.side_effect = APIError("Dataset not found") + + # Mock create_dataset + mock_create.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test_Campaign", + } + + # Mock create_resource + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data + ) + + assert result["success"] is True + assert "dataset" in result + assert "resources" in result + assert len(result["resources"]) == 2 + + mock_create.assert_called_once() + assert mock_create_resource.call_count == 2 + + # Verify dataset metadata structure (back to extras array format) + create_call_args = mock_create.call_args[1] # Get keyword arguments + assert "extras" in create_call_args + extras = create_call_args["extras"] + + # Convert extras list to dict for easier testing + extras_dict = {extra["key"]: extra["value"] for extra in extras} + + # Verify required campaign metadata fields + assert extras_dict["source"] == "Upstream Platform" + assert extras_dict["data_type"] == "environmental_sensor_data" + assert extras_dict["campaign_id"] == "test-campaign-123" + assert extras_dict["campaign_name"] == sample_campaign_response.name + assert extras_dict["campaign_contact_name"] == sample_campaign_response.contact_name + assert extras_dict["campaign_contact_email"] == sample_campaign_response.contact_email + assert extras_dict["campaign_allocation"] == sample_campaign_response.allocation + + # Verify resource metadata structure (station data added as direct fields) + resource_calls = mock_create_resource.call_args_list + assert len(resource_calls) == 2 + + # Check that both resources have station metadata as direct fields + for call in resource_calls: + call_kwargs = call[1] # Get keyword arguments + assert "metadata" in call_kwargs + metadata = call_kwargs["metadata"] + + # Convert metadata to dict for easier testing + metadata_dict = {meta["key"]: meta["value"] for meta in metadata} + assert metadata_dict["station_id"] == str(mock_station_data.id) + assert metadata_dict["station_name"] == mock_station_data.name + assert metadata_dict["station_active"] == str(mock_station_data.active) + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.update_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_update_existing( + self, mock_get, mock_update, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test updating existing campaign dataset.""" + # Mock get_dataset to return existing dataset + mock_get.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Old Title", + } + + # Mock update_dataset + mock_update.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test_Campaign", + } + + # Mock create_resource + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data + ) + + assert result["success"] is True + mock_update.assert_called_once() + + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_creation_failure( + self, mock_get, mock_create, sample_campaign_response, mock_station_data + ): + """Test campaign publishing with dataset creation failure.""" + mock_get.side_effect = APIError("Dataset not found") + mock_create.side_effect = APIError("Creation failed") + + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="CKAN publication failed"): + ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data + ) + + +class TestCKANUtilities: + """Test CKAN utility functions.""" + + def test_sanitize_title(self): + """Test title sanitization.""" + ckan = CKANIntegration("http://test.example.com") + + assert ckan.sanitize_title("Test Dataset") == "Test_Dataset" + assert ckan.sanitize_title("Test-Dataset-Name") == "Test_Dataset_Name" + assert ckan.sanitize_title("Multiple Word Dataset") == "Multiple_Word_Dataset" + assert ckan.sanitize_title("Mixed-Case_and Space") == "Mixed_Case_and_Space" + + def test_sanitize_title_edge_cases(self): + """Test title sanitization with edge cases.""" + ckan = CKANIntegration("http://test.example.com") + + assert ckan.sanitize_title("") == "" + assert ckan.sanitize_title("NoSpacesOrDashes") == "NoSpacesOrDashes" + assert ckan.sanitize_title("___") == "___" + assert ckan.sanitize_title(" ") == "___" + assert ckan.sanitize_title("---") == "___" + + +class TestCKANErrorHandling: + """Test CKAN error handling.""" + + @patch("upstream.ckan.requests.Session.post") + def test_network_error_handling(self, mock_post): + """Test network error handling.""" + mock_post.side_effect = requests.exceptions.ConnectionError("Network error") + + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="Failed to create CKAN dataset"): + ckan.create_dataset(name="test-dataset", title="Test") + + @patch("upstream.ckan.requests.Session.post") + def test_timeout_error_handling(self, mock_post): + """Test timeout error handling.""" + mock_post.side_effect = requests.exceptions.Timeout("Request timeout") + + ckan = CKANIntegration("http://test.example.com") + + with pytest.raises(APIError, match="Failed to create CKAN dataset"): + ckan.create_dataset(name="test-dataset", title="Test") + + +class TestCKANCustomMetadata: + """Test CKAN custom metadata functionality.""" + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_with_custom_dataset_metadata( + self, mock_get, mock_create, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test publishing campaign with custom dataset metadata.""" + mock_get.side_effect = APIError("Dataset not found") + + mock_create.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test Campaign", + } + + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + custom_dataset_metadata = { + "project_name": "Water Quality Study", + "funding_agency": "EPA", + "study_period": "2024-2025", + "principal_investigator": "Dr. Jane Smith" + } + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + dataset_metadata=custom_dataset_metadata + ) + + assert result["success"] is True + mock_create.assert_called_once() + + # Verify custom metadata was added to extras + create_call_args = mock_create.call_args[1] + extras = create_call_args["extras"] + extras_dict = {extra["key"]: extra["value"] for extra in extras} + + # Check custom metadata fields + assert extras_dict["project_name"] == "Water Quality Study" + assert extras_dict["funding_agency"] == "EPA" + assert extras_dict["study_period"] == "2024-2025" + assert extras_dict["principal_investigator"] == "Dr. Jane Smith" + + # Ensure base metadata still exists + assert extras_dict["source"] == "Upstream Platform" + assert extras_dict["data_type"] == "environmental_sensor_data" + assert extras_dict["campaign_id"] == "test-campaign-123" + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_with_custom_resource_metadata( + self, mock_get, mock_create, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test publishing campaign with custom resource metadata.""" + mock_get.side_effect = APIError("Dataset not found") + + mock_create.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test Campaign", + } + + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + custom_resource_metadata = { + "quality_level": "Level 2", + "processing_version": "v2.1", + "calibration_date": "2024-01-15", + "data_quality": "QC Passed" + } + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + resource_metadata=custom_resource_metadata + ) + + assert result["success"] is True + assert mock_create_resource.call_count == 2 + + # Verify custom metadata was added to both resources + for call in mock_create_resource.call_args_list: + call_kwargs = call[1] + metadata = call_kwargs["metadata"] + metadata_dict = {meta["key"]: meta["value"] for meta in metadata} + + # Check custom resource metadata + assert metadata_dict["quality_level"] == "Level 2" + assert metadata_dict["processing_version"] == "v2.1" + assert metadata_dict["calibration_date"] == "2024-01-15" + assert metadata_dict["data_quality"] == "QC Passed" + + # Ensure base station metadata still exists + assert metadata_dict["station_id"] == str(mock_station_data.id) + assert metadata_dict["station_name"] == mock_station_data.name + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_with_custom_tags( + self, mock_get, mock_create, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test publishing campaign with custom tags.""" + mock_get.side_effect = APIError("Dataset not found") + + mock_create.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test Campaign", + } + + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + custom_tags = ["water-quality", "research", "epa-funded", "university-study"] + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + custom_tags=custom_tags + ) + + assert result["success"] is True + mock_create.assert_called_once() + + # Verify custom tags were added to base tags + create_call_args = mock_create.call_args[1] + tags = create_call_args["tags"] + + # Check that all tags are present (base + custom) + expected_tags = ["environmental", "sensors", "upstream"] + custom_tags + assert len(tags) == len(expected_tags) + for tag in expected_tags: + assert tag in tags + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_with_all_custom_metadata( + self, mock_get, mock_create, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test publishing campaign with all custom metadata options.""" + mock_get.side_effect = APIError("Dataset not found") + + mock_create.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test Campaign", + } + + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + custom_dataset_metadata = { + "project_name": "Comprehensive Study", + "institution": "University XYZ" + } + + custom_resource_metadata = { + "processing_level": "L2", + "version": "v1.0" + } + + custom_tags = ["comprehensive", "university-research"] + + additional_kwargs = { + "license_id": "cc-by-4.0", + "version": "1.0" + } + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + dataset_metadata=custom_dataset_metadata, + resource_metadata=custom_resource_metadata, + custom_tags=custom_tags, + auto_publish=False, + **additional_kwargs + ) + + assert result["success"] is True + mock_create.assert_called_once() + + # Verify all custom elements are present + create_call_args = mock_create.call_args[1] + + # Check dataset-level kwargs + assert create_call_args["license_id"] == "cc-by-4.0" + assert create_call_args["version"] == "1.0" + + # Check custom dataset metadata in extras + extras = create_call_args["extras"] + extras_dict = {extra["key"]: extra["value"] for extra in extras} + assert extras_dict["project_name"] == "Comprehensive Study" + assert extras_dict["institution"] == "University XYZ" + + # Check custom tags + tags = create_call_args["tags"] + expected_tags = ["environmental", "sensors", "upstream", "comprehensive", "university-research"] + assert len(tags) == len(expected_tags) + for tag in expected_tags: + assert tag in tags + + # Check custom resource metadata + for call in mock_create_resource.call_args_list: + call_kwargs = call[1] + metadata = call_kwargs["metadata"] + metadata_dict = {meta["key"]: meta["value"] for meta in metadata} + assert metadata_dict["processing_level"] == "L2" + assert metadata_dict["version"] == "v1.0" + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_empty_custom_metadata( + self, mock_get, mock_create, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test publishing campaign with empty custom metadata (should work normally).""" + mock_get.side_effect = APIError("Dataset not found") + + mock_create.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test Campaign", + } + + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + dataset_metadata={}, # Empty dict + resource_metadata={}, # Empty dict + custom_tags=[], # Empty list + ) + + assert result["success"] is True + mock_create.assert_called_once() + + # Verify only base metadata exists + create_call_args = mock_create.call_args[1] + + # Check that base tags still exist even with empty custom_tags + tags = create_call_args["tags"] + base_tags = ["environmental", "sensors", "upstream"] + assert len(tags) == len(base_tags) + for tag in base_tags: + assert tag in tags + + # Check that base extras still exist + extras = create_call_args["extras"] + extras_dict = {extra["key"]: extra["value"] for extra in extras} + assert extras_dict["source"] == "Upstream Platform" + assert extras_dict["data_type"] == "environmental_sensor_data" + + @patch("upstream.ckan.CKANIntegration.create_resource") + @patch("upstream.ckan.CKANIntegration.create_dataset") + @patch("upstream.ckan.CKANIntegration.get_dataset") + def test_publish_campaign_none_custom_metadata( + self, mock_get, mock_create, mock_create_resource, sample_campaign_response, mock_station_data + ): + """Test publishing campaign with None custom metadata (default behavior).""" + mock_get.side_effect = APIError("Dataset not found") + + mock_create.return_value = { + "id": "dataset-id", + "name": "upstream-campaign-test-campaign-123", + "title": "Test Campaign", + } + + mock_create_resource.return_value = { + "id": "resource-id", + "name": "Test Resource", + } + + ckan = CKANIntegration("http://test.example.com") + + result = ckan.publish_campaign( + campaign_id="test-campaign-123", + campaign_data=sample_campaign_response, + station_measurements=mock_station_measurements_csv, + station_sensors=mock_station_sensors_csv, + station_data=mock_station_data, + dataset_metadata=None, + resource_metadata=None, + custom_tags=None, + ) + + assert result["success"] is True + mock_create.assert_called_once() + + # Verify base behavior remains the same + create_call_args = mock_create.call_args[1] + + # Check base tags + tags = create_call_args["tags"] + base_tags = ["environmental", "sensors", "upstream"] + assert len(tags) == len(base_tags) + for tag in base_tags: + assert tag in tags + + # Check base extras + extras = create_call_args["extras"] + extras_dict = {extra["key"]: extra["value"] for extra in extras} + assert extras_dict["source"] == "Upstream Platform" + assert extras_dict["data_type"] == "environmental_sensor_data" + assert extras_dict["campaign_id"] == "test-campaign-123" + + +class TestCKANUpdateDatasetEnhanced: + """Test enhanced CKAN update_dataset functionality with metadata support.""" + + @patch("upstream.ckan.CKANIntegration.get_dataset") + @patch("upstream.ckan.requests.Session.post") + def test_update_dataset_with_custom_metadata_merge(self, mock_post, mock_get): + """Test updating dataset with custom metadata (merge mode).""" + # Mock existing dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Test Dataset", + "extras": [ + {"key": "existing_field", "value": "existing_value"}, + {"key": "source", "value": "Upstream Platform"} + ], + "tags": [{"name": "existing-tag"}, {"name": "another-tag"}] + } + + # Mock update response + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "test-id", "name": "test-dataset", "title": "Updated Dataset"} + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + custom_metadata = { + "project_name": "New Project", + "version": "2.0", + "existing_field": "updated_value" # This should update existing field + } + + result = ckan.update_dataset( + "test-dataset", + dataset_metadata=custom_metadata, + title="Updated Dataset", + merge_extras=True + ) + + # Verify the call was made + mock_post.assert_called_once() + call_args = mock_post.call_args[1]["json"] + + # Check that extras were merged correctly + extras_dict = {extra["key"]: extra["value"] for extra in call_args["extras"]} + assert extras_dict["existing_field"] == "updated_value" # Updated + assert extras_dict["source"] == "Upstream Platform" # Preserved + assert extras_dict["project_name"] == "New Project" # Added + assert extras_dict["version"] == "2.0" # Added + + assert result["title"] == "Updated Dataset" + + @patch("upstream.ckan.CKANIntegration.get_dataset") + @patch("upstream.ckan.requests.Session.post") + def test_update_dataset_with_custom_metadata_replace(self, mock_post, mock_get): + """Test updating dataset with custom metadata (replace mode).""" + # Mock existing dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Test Dataset", + "extras": [ + {"key": "old_field", "value": "old_value"}, + {"key": "another_old_field", "value": "another_old_value"} + ] + } + + # Mock update response + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "test-id", "name": "test-dataset"} + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + custom_metadata = { + "new_field": "new_value", + "project_status": "completed" + } + + result = ckan.update_dataset( + "test-dataset", + dataset_metadata=custom_metadata, + merge_extras=False # Replace all extras + ) + + # Verify the call was made + mock_post.assert_called_once() + call_args = mock_post.call_args[1]["json"] + + # Check that extras were replaced (only new fields present) + extras_dict = {extra["key"]: extra["value"] for extra in call_args["extras"]} + assert extras_dict["new_field"] == "new_value" + assert extras_dict["project_status"] == "completed" + assert "old_field" not in extras_dict + assert "another_old_field" not in extras_dict + assert len(call_args["extras"]) == 2 + + @patch("upstream.ckan.CKANIntegration.get_dataset") + @patch("upstream.ckan.requests.Session.post") + def test_update_dataset_with_custom_tags_merge(self, mock_post, mock_get): + """Test updating dataset with custom tags (merge mode).""" + # Mock existing dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Test Dataset", + "tags": [{"name": "existing-tag"}, {"name": "another-tag"}] + } + + # Mock update response + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "test-id", "name": "test-dataset"} + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + custom_tags = ["new-tag", "additional-tag", "existing-tag"] # Include one duplicate + + result = ckan.update_dataset( + "test-dataset", + custom_tags=custom_tags, + merge_tags=True + ) + + # Verify the call was made + mock_post.assert_called_once() + call_args = mock_post.call_args[1]["json"] + + # Check that tags were merged and deduplicated + actual_tags = [tag["name"] for tag in call_args["tags"]] + expected_tags = ["existing-tag", "another-tag", "new-tag", "additional-tag"] + assert len(actual_tags) == 4 # No duplicates + for tag in expected_tags: + assert tag in actual_tags + + @patch("upstream.ckan.CKANIntegration.get_dataset") + @patch("upstream.ckan.requests.Session.post") + def test_update_dataset_with_custom_tags_replace(self, mock_post, mock_get): + """Test updating dataset with custom tags (replace mode).""" + # Mock existing dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Test Dataset", + "tags": [{"name": "old-tag"}, {"name": "another-old-tag"}] + } + + # Mock update response + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "test-id", "name": "test-dataset"} + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + custom_tags = ["new-tag", "replacement-tag"] + + result = ckan.update_dataset( + "test-dataset", + custom_tags=custom_tags, + merge_tags=False # Replace all tags + ) + + # Verify the call was made + mock_post.assert_called_once() + call_args = mock_post.call_args[1]["json"] + + # Check that tags were replaced + actual_tags = [tag["name"] for tag in call_args["tags"]] + assert len(actual_tags) == 2 + assert "new-tag" in actual_tags + assert "replacement-tag" in actual_tags + assert "old-tag" not in actual_tags + assert "another-old-tag" not in actual_tags + + @patch("upstream.ckan.CKANIntegration.get_dataset") + @patch("upstream.ckan.requests.Session.post") + def test_update_dataset_with_all_custom_options(self, mock_post, mock_get): + """Test updating dataset with all custom metadata options.""" + # Mock existing dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Test Dataset", + "extras": [{"key": "old_field", "value": "old_value"}], + "tags": [{"name": "old-tag"}] + } + + # Mock update response + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "test-id", "name": "test-dataset", "title": "Comprehensive Update"} + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + custom_metadata = { + "project_name": "Comprehensive Project", + "status": "active" + } + + custom_tags = ["comprehensive", "updated"] + + result = ckan.update_dataset( + "test-dataset", + dataset_metadata=custom_metadata, + custom_tags=custom_tags, + merge_extras=True, + merge_tags=True, + title="Comprehensive Update", + version="3.0" + ) + + # Verify the call was made + mock_post.assert_called_once() + call_args = mock_post.call_args[1]["json"] + + # Check extras + extras_dict = {extra["key"]: extra["value"] for extra in call_args["extras"]} + assert extras_dict["old_field"] == "old_value" # Preserved + assert extras_dict["project_name"] == "Comprehensive Project" # Added + assert extras_dict["status"] == "active" # Added + + # Check tags + actual_tags = [tag["name"] for tag in call_args["tags"]] + assert "old-tag" in actual_tags # Preserved + assert "comprehensive" in actual_tags # Added + assert "updated" in actual_tags # Added + + # Check other fields + assert call_args["title"] == "Comprehensive Update" + assert call_args["version"] == "3.0" + + assert result["title"] == "Comprehensive Update" + + @patch("upstream.ckan.CKANIntegration.get_dataset") + @patch("upstream.ckan.requests.Session.post") + def test_update_dataset_backward_compatibility(self, mock_post, mock_get): + """Test that enhanced update_dataset maintains backward compatibility.""" + # Mock existing dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Old Title" + } + + # Mock update response + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "test-id", "name": "test-dataset", "title": "New Title"} + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + # Test old-style call (should still work) + result = ckan.update_dataset( + "test-dataset", + title="New Title", + tags=["tag1", "tag2"] # Old-style tags as strings + ) + + # Verify the call was made + mock_post.assert_called_once() + call_args = mock_post.call_args[1]["json"] + + # Check that string tags were converted to dict format + assert call_args["title"] == "New Title" + actual_tags = call_args["tags"] + assert len(actual_tags) == 2 + assert actual_tags[0]["name"] == "tag1" + assert actual_tags[1]["name"] == "tag2" + + assert result["title"] == "New Title" + + @patch("upstream.ckan.CKANIntegration.get_dataset") + @patch("upstream.ckan.requests.Session.post") + def test_update_dataset_empty_custom_metadata(self, mock_post, mock_get): + """Test updating dataset with empty custom metadata.""" + # Mock existing dataset + mock_get.return_value = { + "id": "test-id", + "name": "test-dataset", + "title": "Test Dataset", + "extras": [{"key": "existing", "value": "value"}], + "tags": [{"name": "existing-tag"}] + } + + # Mock update response + mock_response = Mock() + mock_response.status_code = 200 + mock_response.raise_for_status.return_value = None + mock_response.json.return_value = { + "success": True, + "result": {"id": "test-id", "name": "test-dataset"} + } + mock_post.return_value = mock_response + + ckan = CKANIntegration("http://test.example.com") + + # Update with empty metadata (should not affect existing when merging) + result = ckan.update_dataset( + "test-dataset", + dataset_metadata={}, # Empty dict (should be ignored) + custom_tags=[], # Empty list with merge_tags=True (should replace with empty) + merge_tags=False, # Use replace mode for empty tags + title="Updated Title" + ) + + # Verify the call was made + mock_post.assert_called_once() + call_args = mock_post.call_args[1]["json"] + + # Check that existing extras were preserved (empty dict should be ignored) + assert "extras" in call_args + extras_dict = {extra["key"]: extra["value"] for extra in call_args["extras"]} + assert extras_dict["existing"] == "value" + + # Check that tags were replaced with empty list (replace mode) + actual_tags = call_args["tags"] + assert len(actual_tags) == 0 + + assert call_args["title"] == "Updated Title" \ No newline at end of file diff --git a/tests/unit/test_client_ckan_metadata.py b/tests/unit/test_client_ckan_metadata.py new file mode 100644 index 0000000..0a23a49 --- /dev/null +++ b/tests/unit/test_client_ckan_metadata.py @@ -0,0 +1,172 @@ +""" +Unit tests for UpstreamClient CKAN custom metadata functionality. +""" + +from unittest.mock import Mock, patch +import pytest +from upstream.client import UpstreamClient +from upstream.exceptions import ConfigurationError + +pytestmark = pytest.mark.unit + + +class TestUpstreamClientCKANMetadata: + """Test UpstreamClient CKAN custom metadata functionality.""" + + def test_publish_to_ckan_no_ckan_integration(self): + """Test publish_to_ckan raises error when CKAN integration not configured.""" + # Create client without CKAN integration by setting ckan to None + client = UpstreamClient( + username="test_user", + password="test_pass", + base_url="https://api.example.com" + ) + # Manually set ckan to None to simulate no CKAN integration + client.ckan = None + + with pytest.raises(ConfigurationError, match="CKAN integration not configured"): + client.publish_to_ckan("campaign123", "station456") + + @patch("upstream.client.CKANIntegration") + @patch("upstream.client.CampaignManager") + @patch("upstream.client.StationManager") + @patch("upstream.client.AuthManager") + def test_publish_to_ckan_with_custom_metadata( + self, mock_auth, mock_station_mgr, mock_campaign_mgr, mock_ckan_integration + ): + """Test publish_to_ckan passes custom metadata to CKAN integration.""" + # Setup mocks + mock_auth_instance = Mock() + mock_auth.return_value = mock_auth_instance + + mock_station_mgr_instance = Mock() + mock_station_mgr.return_value = mock_station_mgr_instance + + mock_campaign_mgr_instance = Mock() + mock_campaign_mgr.return_value = mock_campaign_mgr_instance + + mock_ckan_instance = Mock() + mock_ckan_integration.return_value = mock_ckan_instance + + # Mock the CKAN configuration + mock_config = Mock() + mock_config.ckan_url = "http://test-ckan.example.com" + mock_config.to_dict.return_value = {"ckan_url": "http://test-ckan.example.com"} + mock_auth_instance.config = mock_config + + # Create client with CKAN URL to trigger CKAN integration + client = UpstreamClient( + username="test_user", + password="test_pass", + base_url="https://api.example.com", + ckan_url="http://test-ckan.example.com" + ) + + # Mock the required data methods + mock_station_data = Mock() + mock_station_mgr_instance.get.return_value = mock_station_data + mock_station_mgr_instance.export_station_measurements.return_value = Mock() + mock_station_mgr_instance.export_station_sensors.return_value = Mock() + + mock_campaign_data = Mock() + mock_campaign_mgr_instance.get.return_value = mock_campaign_data + + mock_ckan_instance.publish_campaign.return_value = {"success": True} + + # Test custom metadata parameters + custom_dataset_metadata = {"project": "Test Project", "funding": "EPA"} + custom_resource_metadata = {"quality": "Level 2", "version": "v1.0"} + custom_tags = ["research", "environmental"] + + result = client.publish_to_ckan( + campaign_id="test-campaign-123", + station_id="test-station-456", + dataset_metadata=custom_dataset_metadata, + resource_metadata=custom_resource_metadata, + custom_tags=custom_tags, + auto_publish=False, + license_id="cc-by-4.0" + ) + + # Verify the CKAN integration publish_campaign was called with correct parameters + mock_ckan_instance.publish_campaign.assert_called_once_with( + campaign_id="test-campaign-123", + campaign_data=mock_campaign_data, + station_measurements=mock_station_mgr_instance.export_station_measurements.return_value, + station_sensors=mock_station_mgr_instance.export_station_sensors.return_value, + station_data=mock_station_data, + dataset_metadata=custom_dataset_metadata, + resource_metadata=custom_resource_metadata, + custom_tags=custom_tags, + auto_publish=False, + license_id="cc-by-4.0" + ) + + assert result["success"] is True + + @patch("upstream.client.CKANIntegration") + @patch("upstream.client.CampaignManager") + @patch("upstream.client.StationManager") + @patch("upstream.client.AuthManager") + def test_publish_to_ckan_default_parameters( + self, mock_auth, mock_station_mgr, mock_campaign_mgr, mock_ckan_integration + ): + """Test publish_to_ckan works with default parameters (backward compatibility).""" + # Setup mocks + mock_auth_instance = Mock() + mock_auth.return_value = mock_auth_instance + + mock_station_mgr_instance = Mock() + mock_station_mgr.return_value = mock_station_mgr_instance + + mock_campaign_mgr_instance = Mock() + mock_campaign_mgr.return_value = mock_campaign_mgr_instance + + mock_ckan_instance = Mock() + mock_ckan_integration.return_value = mock_ckan_instance + + # Mock the CKAN configuration + mock_config = Mock() + mock_config.ckan_url = "http://test-ckan.example.com" + mock_config.to_dict.return_value = {"ckan_url": "http://test-ckan.example.com"} + mock_auth_instance.config = mock_config + + # Create client + client = UpstreamClient( + username="test_user", + password="test_pass", + base_url="https://api.example.com", + ckan_url="http://test-ckan.example.com" + ) + + # Mock the required data methods + mock_station_data = Mock() + mock_station_mgr_instance.get.return_value = mock_station_data + mock_station_mgr_instance.export_station_measurements.return_value = Mock() + mock_station_mgr_instance.export_station_sensors.return_value = Mock() + + mock_campaign_data = Mock() + mock_campaign_mgr_instance.get.return_value = mock_campaign_data + + mock_ckan_instance.publish_campaign.return_value = {"success": True} + + # Test with default parameters (backward compatibility) + result = client.publish_to_ckan( + campaign_id="test-campaign-123", + station_id="test-station-456" + ) + + # Verify the CKAN integration publish_campaign was called with default values + mock_ckan_instance.publish_campaign.assert_called_once_with( + campaign_id="test-campaign-123", + campaign_data=mock_campaign_data, + station_measurements=mock_station_mgr_instance.export_station_measurements.return_value, + station_sensors=mock_station_mgr_instance.export_station_sensors.return_value, + station_data=mock_station_data, + dataset_metadata=None, + resource_metadata=None, + custom_tags=None, + auto_publish=True + ) + + assert result["success"] is True \ No newline at end of file diff --git a/upstream/__init__.py b/upstream/__init__.py index c7a09a2..468c5a0 100644 --- a/upstream/__init__.py +++ b/upstream/__init__.py @@ -9,6 +9,7 @@ from .campaigns import CampaignManager from .client import UpstreamClient from .data import DataUploader, DataValidator +from .ckan import CKANIntegration from .exceptions import ( APIError, AuthenticationError, diff --git a/upstream/ckan.py b/upstream/ckan.py new file mode 100644 index 0000000..34b57bd --- /dev/null +++ b/upstream/ckan.py @@ -0,0 +1,684 @@ +""" +CKAN integration for Upstream SDK. +""" + +from datetime import datetime +import json +import logging +import os +from pathlib import Path +from typing import Any, BinaryIO, Dict, List, Optional, Union, cast + +import requests +from upstream_api_client import GetStationResponse +from upstream_api_client.models.get_campaign_response import GetCampaignResponse + +from .exceptions import APIError + +logger = logging.getLogger(__name__) + + +def _serialize_for_json(value: Any) -> str: + """ + Convert a value to a JSON-serializable string, with special handling for dates. + + Args: + value: The value to serialize + + Returns: + JSON-serializable string representation + """ + if value is None: + return "" + elif isinstance(value, datetime): + # Format datetime for Solr compatibility (ISO format without timezone suffix) + # Solr expects format like: 2025-07-22T11:16:48Z + return value.strftime('%Y-%m-%dT%H:%M:%SZ') + elif isinstance(value, (dict, list)): + try: + return json.dumps(value, default=str) + except (TypeError, ValueError): + return str(value) + else: + return str(value) + + + +class CKANIntegration: + """ + Handles CKAN data portal integration. + """ + + def __init__(self, ckan_url: str, config: Optional[Dict[str, Any]] = None) -> None: + """ + Initialize CKAN integration. + + Args: + ckan_url: CKAN portal URL + config: Additional CKAN configuration + """ + self.ckan_url = ckan_url.rstrip("/") + self.config = config or {} + self.session = requests.Session() + + # Store timeout for use in individual requests + self.timeout = self.config.get("timeout", 30) + + # Set up authentication if provided + api_key = self.config.get("api_key") + if api_key: + self.session.headers.update({"Authorization": api_key}) + + access_token = self.config.get("access_token") + if access_token: + self.session.headers.update({"Authorization": f"Bearer {access_token}"}) + + def create_dataset( + self, + name: str, + title: str, + description: str = "", + organization: Optional[str] = None, + tags: Optional[List[str]] = None, + **kwargs: Any, + ) -> Dict[str, Any]: + """ + Create a new CKAN dataset. + + Args: + name: Dataset name (URL-friendly) + title: Dataset title + description: Dataset description + organization: Organization name + tags: List of tags + **kwargs: Additional dataset metadata + + Returns: + Created dataset information + """ + + # Determine organization - use parameter or fall back to config + owner_org = organization or self.config.get("ckan_organization") + + # Prepare dataset metadata + dataset_data = { + "name": name, + "title": title, + "notes": description, + "tags": [{"name": tag} for tag in (tags or [])], + **kwargs, + } + + # Add owner_org if available + if owner_org: + dataset_data["owner_org"] = owner_org + elif not name.startswith("test-"): + # Only require organization for non-test datasets + raise APIError("Organization is required for dataset creation. Please set CKAN_ORGANIZATION environment variable or pass organization parameter.") + + # Remove None values + dataset_data = {k: v for k, v in dataset_data.items() if v is not None} + + try: + response = self.session.post( + f"{self.ckan_url}/api/3/action/package_create", json=dataset_data, timeout=self.timeout + ) + response.raise_for_status() + + result = response.json() + + if not result.get("success"): + raise APIError(f"CKAN dataset creation failed: {result.get('error')}") + + dataset = result["result"] + logger.info( + f"Created CKAN dataset: {dataset['name']} (ID: {dataset['id']})" + ) + + return cast(Dict[str, Any], dataset) + + except requests.exceptions.RequestException as e: + raise APIError(f"Failed to create CKAN dataset: {e}") + + def get_dataset(self, dataset_id: str) -> Dict[str, Any]: + """ + Get CKAN dataset by ID or name. + + Args: + dataset_id: Dataset ID or name + + Returns: + Dataset information + """ + try: + response = self.session.get( + f"{self.ckan_url}/api/3/action/package_show", params={"id": dataset_id}, timeout=self.timeout + ) + response.raise_for_status() + + result = response.json() + + if not result.get("success"): + raise APIError(f"CKAN dataset retrieval failed: {result.get('error')}") + + return cast(Dict[str, Any], result["result"]) + + except requests.exceptions.RequestException as e: + if hasattr(e, "response") and e.response is not None and e.response.status_code == 404: + raise APIError(f"CKAN dataset not found: {dataset_id}") + raise APIError(f"Failed to get CKAN dataset: {e}") + + def update_dataset( + self, + dataset_id: str, + dataset_metadata: Optional[Dict[str, Any]] = None, + custom_tags: Optional[List[str]] = None, + merge_extras: bool = True, + merge_tags: bool = True, + **kwargs: Any + ) -> Dict[str, Any]: + """ + Update CKAN dataset with enhanced metadata support. + + Args: + dataset_id: Dataset ID or name + dataset_metadata: Custom metadata to add to dataset extras + custom_tags: Additional tags to add to the dataset + merge_extras: If True, merge with existing extras; if False, replace them + merge_tags: If True, merge with existing tags; if False, replace them + **kwargs: Additional dataset fields to update + + Returns: + Updated dataset information + + Examples: + Basic update: + >>> ckan.update_dataset("my-dataset", title="New Title") + + Update with custom metadata: + >>> ckan.update_dataset( + ... "my-dataset", + ... dataset_metadata={"project_status": "completed", "final_report": "available"}, + ... custom_tags=["completed", "final"] + ... ) + + Replace all extras and tags: + >>> ckan.update_dataset( + ... "my-dataset", + ... dataset_metadata={"new_field": "value"}, + ... custom_tags=["new-tag"], + ... merge_extras=False, + ... merge_tags=False + ... ) + """ + # Get current dataset + current_dataset = self.get_dataset(dataset_id) + + # Start with current dataset data and apply kwargs updates + updated_data = {**current_dataset, **kwargs} + + # Handle custom dataset metadata (extras) + if dataset_metadata: + current_extras = current_dataset.get('extras', []) + + if merge_extras: + # Merge with existing extras + # Convert existing extras to dict for easier manipulation + extras_dict = {extra['key']: extra['value'] for extra in current_extras} + + # Add/update with new metadata + for key, value in dataset_metadata.items(): + extras_dict[key] = _serialize_for_json(value) + + # Convert back to list format + updated_data['extras'] = [{"key": k, "value": v} for k, v in extras_dict.items()] + else: + # Replace existing extras with only the new metadata + updated_data['extras'] = [{"key": k, "value": _serialize_for_json(v)} for k, v in dataset_metadata.items()] + + # Handle custom tags + if custom_tags is not None: + current_tags = [] + if current_dataset.get('tags'): + current_tags = [tag['name'] if isinstance(tag, dict) else tag for tag in current_dataset['tags']] + + if merge_tags: + # Merge with existing tags (avoid duplicates) + all_tags = list(set(current_tags + custom_tags)) + else: + # Replace with only the new tags + all_tags = custom_tags + + updated_data['tags'] = all_tags + + # Handle tags from kwargs (for backward compatibility) + if "tags" in updated_data and updated_data["tags"]: + tags = updated_data["tags"] + # Ensure tags are in the correct format + if isinstance(tags, list): + if tags and isinstance(tags[0], str): + # Convert string tags to dict format for CKAN API + updated_data["tags"] = [{"name": tag} for tag in tags] + elif tags and isinstance(tags[0], dict): + # Already in correct format + pass + else: + # Handle unexpected tag format + updated_data["tags"] = [] + + try: + response = self.session.post( + f"{self.ckan_url}/api/3/action/package_update", json=updated_data, timeout=self.timeout + ) + response.raise_for_status() + + result = response.json() + + if not result.get("success"): + error_details = result.get('error', {}) + raise APIError(f"CKAN dataset update failed: {error_details}") + + dataset = result["result"] + logger.info(f"Updated CKAN dataset: {dataset['name']}") + + return cast(Dict[str, Any], dataset) + + except requests.exceptions.RequestException as e: + # Log the response content for debugging + error_msg = f"Failed to update CKAN dataset: {e}" + if hasattr(e, 'response') and e.response is not None: + try: + error_content = e.response.json() + error_msg += f" - Response: {error_content}" + except: + error_msg += f" - Response text: {e.response.text[:500]}" + raise APIError(error_msg) + + def delete_dataset(self, dataset_id: str) -> bool: + """ + Delete CKAN dataset. + + Args: + dataset_id: Dataset ID or name + + Returns: + True if successful + """ + try: + response = self.session.post( + f"{self.ckan_url}/api/3/action/package_delete", json={"id": dataset_id}, timeout=self.timeout + ) + response.raise_for_status() + + result = response.json() + + if not result.get("success"): + raise APIError(f"CKAN dataset deletion failed: {result.get('error')}") + + logger.info(f"Deleted CKAN dataset: {dataset_id}") + return True + + except requests.exceptions.RequestException as e: + raise APIError(f"Failed to delete CKAN dataset: {e}") + + def create_resource( + self, + dataset_id: str, + name: str, + url: Optional[str] = None, + file_path: Optional[Union[str, Path]] = None, + file_obj: Optional[BinaryIO] = None, + resource_type: str = "data", + format: str = "CSV", + description: str = "", + metadata: Optional[List[Dict[str, Any]]] = None, + **kwargs: Any, + ) -> Dict[str, Any]: + """ + Create a resource within a CKAN dataset. + + Args: + dataset_id: Dataset ID or name + name: Resource name + url: Resource URL (for URL-based resources) + file_path: Path to file to upload + file_obj: File object to upload + resource_type: Resource type + format: Resource format + description: Resource description + **kwargs: Additional resource metadata + + Returns: + Created resource information + """ + resource_data = { + "package_id": dataset_id, + "name": name, + "resource_type": resource_type, + "format": format, + "description": description, + **kwargs, + } + + # Add metadata fields directly to resource (not in extras array) + if metadata: + for meta_item in metadata: + if isinstance(meta_item, dict) and "key" in meta_item and "value" in meta_item: + resource_data[meta_item["key"]] = meta_item["value"] + + # Handle file upload vs URL + if file_path or file_obj: + # File upload + files: Dict[str, Any] = {} + if file_path: + file_path = Path(file_path) + if not file_path.exists(): + raise APIError(f"File not found: {file_path}") + files["upload"] = (file_path.name, open(file_path, "rb")) + elif file_obj: + filename = getattr(file_obj, "name", "uploaded_file") + if hasattr(filename, "split"): + filename = os.path.basename(filename) + files["upload"] = (str(filename), file_obj) + + try: + response = self.session.post( + f"{self.ckan_url}/api/3/action/resource_create", + data=resource_data, + files=files, + timeout=self.timeout + ) + response.raise_for_status() + finally: + # Close file if we opened it + if file_path and "upload" in files: + files["upload"][1].close() + else: + # URL-based resource + if not url: + raise APIError("Either url, file_path, or file_obj must be provided") + resource_data["url"] = url + response = self.session.post( + f"{self.ckan_url}/api/3/action/resource_create", json=resource_data, timeout=self.timeout + ) + response.raise_for_status() + + try: + result = response.json() + + if not result.get("success"): + raise APIError(f"CKAN resource creation failed: {result.get('error')}") + + resource = result["result"] + logger.info( + f"Created CKAN resource: {resource['name']} (ID: {resource['id']})" + ) + + return cast(Dict[str, Any], resource) + + except requests.exceptions.RequestException as e: + raise APIError(f"Failed to create CKAN resource: {e}") + + def list_datasets( + self, + organization: Optional[str] = None, + tags: Optional[List[str]] = None, + limit: int = 50, + offset: int = 0, + ) -> List[Dict[str, Any]]: + """ + List CKAN datasets. + + Args: + organization: Filter by organization + tags: Filter by tags + limit: Maximum number of datasets to return + offset: Number of datasets to skip + + Returns: + List of dataset information + """ + params: Dict[str, Union[int, str]] = {"rows": limit, "start": offset} + + # Build query + query_parts = [] + + if organization: + query_parts.append(f'owner_org:"{organization}"') + + if tags: + tag_query = " OR ".join([f'tags:"{tag}"' for tag in tags]) + query_parts.append(f"({tag_query})") + + if query_parts: + params["q"] = " AND ".join(query_parts) + + try: + response = self.session.get( + f"{self.ckan_url}/api/3/action/package_search", params=params, timeout=self.timeout + ) + response.raise_for_status() + + result = response.json() + + if not result.get("success"): + raise APIError(f"CKAN dataset search failed: {result.get('error')}") + + return cast(List[Dict[str, Any]], result["result"]["results"]) + + except requests.exceptions.RequestException as e: + raise APIError(f"Failed to list CKAN datasets: {e}") + + def sanitize_title(self, title: str) -> str: + """ + Sanitize a title to be used as a CKAN dataset title. + """ + return title.replace(" ", "_").replace("-", "_") + + def publish_campaign( + self, + campaign_id: str, + campaign_data: GetCampaignResponse, + station_measurements: BinaryIO, + station_sensors: BinaryIO, + station_data: GetStationResponse, + dataset_metadata: Optional[Dict[str, Any]] = None, + resource_metadata: Optional[Dict[str, Any]] = None, + custom_tags: Optional[List[str]] = None, + auto_publish: bool = True, + **kwargs: Any + ) -> Dict[str, Any]: + """ + Publish campaign data to CKAN with custom metadata support. + + Args: + campaign_id: Campaign ID + campaign_data: Campaign information + station_measurements: BinaryIO stream of station measurements CSV + station_sensors: BinaryIO stream of station sensors CSV + station_data: Station information + dataset_metadata: Custom metadata for the CKAN dataset (added to extras) + resource_metadata: Custom metadata for CKAN resources + custom_tags: Additional tags for the dataset + auto_publish: Whether to automatically publish the dataset + **kwargs: Additional CKAN parameters + + Returns: + CKAN publication result + """ + # Create dataset name from campaign + dataset_name = f"upstream-campaign-{campaign_id}" + dataset_title = campaign_data.name + + if campaign_data.description: + description = campaign_data.description + else: + description = f"\nSensor Types: {', '.join(campaign_data.summary.sensor_types)}" + + # Prepare base tags + base_tags = ["environmental", "sensors", "upstream"] + if custom_tags: + base_tags.extend(custom_tags) + + # Prepare base dataset extras + base_extras = [ + {"key": "source", "value": "Upstream Platform"}, + {"key": "data_type", "value": "environmental_sensor_data"}, + {"key": "campaign", "value": _serialize_for_json(campaign_data.to_dict())}, + {"key": "campaign_id", "value": campaign_id}, + {"key": "campaign_name", "value": campaign_data.name or ""}, + {"key": "campaign_description", "value": campaign_data.description or ""}, + {"key": "campaign_contact_name", "value": campaign_data.contact_name or ""}, + {"key": "campaign_contact_email", "value": campaign_data.contact_email or ""}, + {"key": "campaign_allocation", "value": campaign_data.allocation or ""}, + ] + + # Add custom dataset metadata to extras + if dataset_metadata: + for key, value in dataset_metadata.items(): + base_extras.append({"key": key, "value": _serialize_for_json(value)}) + + # Prepare dataset metadata + dataset_data = { + "name": dataset_name, + "title": dataset_title, + "notes": description, + "tags": base_tags, + "extras": base_extras, + **kwargs # Allow additional dataset-level parameters + } + + try: + # Create or update dataset + should_update = False + try: + dataset = self.get_dataset(dataset_name) + should_update = True + except APIError: + should_update = False + + if should_update: + dataset = self.update_dataset(dataset_name, **dataset_data) + else: + dataset = self.create_dataset(**dataset_data) + + # Add resources for different data types + resources_created = [] + + + # Prepare base station metadata + base_station_metadata = [ + {"key": "station_id", "value": str(station_data.id)}, + {"key": "station_name", "value": station_data.name or ""}, + {"key": "station_description", "value": station_data.description or ""}, + {"key": "station_contact_name", "value": station_data.contact_name or ""}, + {"key": "station_contact_email", "value": station_data.contact_email or ""}, + {"key": "station_active", "value": str(station_data.active)}, + {"key": "station_geometry", "value": _serialize_for_json(station_data.geometry)}, + {"key": "station_sensors", "value": _serialize_for_json([sensor.to_dict() for sensor in station_data.sensors] if station_data.sensors else [])}, + {"key": "station_sensors_count", "value": str(len(station_data.sensors) if station_data.sensors else 0)}, + {"key": "station_sensors_aliases", "value": _serialize_for_json([sensor.alias for sensor in station_data.sensors] if station_data.sensors else [])}, + {"key": "station_sensors_units", "value": _serialize_for_json([sensor.units for sensor in station_data.sensors] if station_data.sensors else [])}, + {"key": "station_sensors_descriptions", "value": _serialize_for_json([sensor.description for sensor in station_data.sensors] if station_data.sensors else [])}, + {"key": "station_sensors_variablename", "value": _serialize_for_json([sensor.variablename for sensor in station_data.sensors] if station_data.sensors else [])}, + ] + + # Add custom resource metadata + if resource_metadata: + for key, value in resource_metadata.items(): + base_station_metadata.append({"key": key, "value": _serialize_for_json(value)}) + + + # Add sensors resource (file upload or URL) + published_at = datetime.now().strftime('%Y-%m-%dT%H:%M:%SZ') + sensors_resource = self.create_resource( + dataset_id=dataset["id"], + name=f"{station_data.name} - Sensors Configuration - {published_at}", + file_obj=station_sensors, + format="CSV", + description="Sensor configuration and metadata", + metadata=base_station_metadata, + ) + resources_created.append(sensors_resource) + + # Add measurements resource (file upload or URL) + measurements_resource = self.create_resource( + dataset_id=dataset["id"], + name=f"{station_data.name} - Measurement Data - {published_at}", + file_obj=station_measurements, + format="CSV", + description="Environmental sensor measurements", + metadata=base_station_metadata, + ) + resources_created.append(measurements_resource) + + # Publish dataset if requested + if auto_publish and not dataset.get("private", True): + self.update_dataset(dataset["id"], private=False) + + return { + "success": True, + "dataset": dataset, + "resources": resources_created, + "ckan_url": f"{self.ckan_url}/dataset/{dataset['name']}", + "message": f'Campaign data published to CKAN: {dataset["name"]}', + } + + except Exception as e: + logger.error(f"Failed to publish campaign to CKAN: {e}") + raise APIError(f"CKAN publication failed: {e}") + + def get_organization(self, org_id: str) -> Dict[str, Any]: + """ + Get CKAN organization information. + + Args: + org_id: Organization ID or name + + Returns: + Organization information + """ + try: + response = self.session.get( + f"{self.ckan_url}/api/3/action/organization_show", params={"id": org_id}, timeout=self.timeout + ) + response.raise_for_status() + + result = response.json() + + if not result.get("success"): + raise APIError( + f"CKAN organization retrieval failed: {result.get('error')}" + ) + + return cast(Dict[str, Any], result["result"]) + + except requests.exceptions.RequestException as e: + raise APIError(f"Failed to get CKAN organization: {e}") + + def list_organizations(self) -> List[Dict[str, Any]]: + """ + List CKAN organizations. + + Returns: + List of organization information + """ + try: + response = self.session.get( + f"{self.ckan_url}/api/3/action/organization_list", + params={"all_fields": True}, + timeout=self.timeout + ) + response.raise_for_status() + + result = response.json() + + if not result.get("success"): + raise APIError( + f"CKAN organization listing failed: {result.get('error')}" + ) + + return cast(List[Dict[str, Any]], result["result"]) + + except requests.exceptions.RequestException as e: + raise APIError(f"Failed to list CKAN organizations: {e}") diff --git a/upstream/client.py b/upstream/client.py index 9cf87cc..8054324 100644 --- a/upstream/client.py +++ b/upstream/client.py @@ -28,6 +28,8 @@ from upstream_api_client.models.measurement_update import MeasurementUpdate from upstream_api_client.models.station_create_response import StationCreateResponse +from upstream.ckan import CKANIntegration + from .auth import AuthManager from .campaigns import CampaignManager from .data import DataUploader @@ -43,12 +45,17 @@ class UpstreamClient: """Main client class for interacting with the Upstream API.""" + ckan: Optional[CKANIntegration] + + + def __init__( self, username: Optional[str] = None, password: Optional[str] = None, base_url: Optional[str] = None, ckan_url: Optional[str] = None, + ckan_organization: Optional[str] = None, config_file: Optional[Union[str, Path]] = None, **kwargs: Any, ) -> None: @@ -59,6 +66,7 @@ def __init__( password: Password for authentication base_url: Base URL for the Upstream API ckan_url: URL for CKAN integration + ckan_organization: CKAN organization name config_file: Path to configuration file **kwargs: Additional configuration options @@ -74,9 +82,9 @@ def __init__( password=password, base_url=base_url, ckan_url=ckan_url, + ckan_organization=ckan_organization, **kwargs, ) - # Initialize authentication manager self.auth_manager = AuthManager(config) @@ -87,6 +95,14 @@ def __init__( self.measurements = MeasurementManager(self.auth_manager) self.data = DataUploader(self.auth_manager) + # Initialize CKAN integration if URL provided + if config.ckan_url: + self.ckan = CKANIntegration( + ckan_url=config.ckan_url, config=config.to_dict() + ) + else: + self.ckan = None + logger.info("Upstream client initialized successfully") @classmethod @@ -110,6 +126,7 @@ def from_environment(cls) -> "UpstreamClient": - UPSTREAM_PASSWORD: Password for authentication - UPSTREAM_BASE_URL: Base URL for the Upstream API - CKAN_URL: URL for CKAN integration + - CKAN_ORGANIZATION: CKAN organization name Returns: Configured UpstreamClient instance @@ -119,6 +136,7 @@ def from_environment(cls) -> "UpstreamClient": password=os.environ.get("UPSTREAM_PASSWORD"), base_url=os.environ.get("UPSTREAM_BASE_URL"), ckan_url=os.environ.get("CKAN_URL"), + ckan_organization=os.environ.get("CKAN_ORGANIZATION"), ) def authenticate(self) -> bool: @@ -433,23 +451,94 @@ def get_file_info(self, file_path: Union[str, Path]) -> Dict[str, Any]: """ return self.data.get_file_info(file_path) - # def publish_to_ckan(self, campaign_id: str, **kwargs: Any) -> Dict[str, Any]: - # """Publish campaign data to CKAN. - - # Args: - # campaign_id: Campaign ID - # **kwargs: Additional CKAN parameters + def publish_to_ckan( + self, + campaign_id: str, + station_id: str, + dataset_metadata: Optional[Dict[str, Any]] = None, + resource_metadata: Optional[Dict[str, Any]] = None, + custom_tags: Optional[List[str]] = None, + auto_publish: bool = True, + **kwargs: Any + ) -> Dict[str, Any]: + """Publish campaign data to CKAN with custom metadata support. - # Returns: - # CKAN publication result + Args: + campaign_id: Campaign ID + station_id: Station ID + dataset_metadata: Custom metadata for the CKAN dataset (added to extras) + resource_metadata: Custom metadata for CKAN resources (sensors and measurements) + custom_tags: Additional tags for the dataset (beyond default environmental, sensors, upstream) + auto_publish: Whether to automatically publish the dataset (default: True) + **kwargs: Additional CKAN parameters - # Raises: - # ConfigurationError: If CKAN integration not configured - # """ - # if not self.ckan: - # raise ConfigurationError("CKAN integration not configured") + Returns: + CKAN publication result - # return self.ckan.publish_campaign(campaign_id=campaign_id, **kwargs) + Raises: + ConfigurationError: If CKAN integration not configured + + Examples: + Basic usage: + >>> client.publish_to_ckan("campaign123", "station456") + + With custom dataset metadata: + >>> client.publish_to_ckan( + ... "campaign123", + ... "station456", + ... dataset_metadata={ + ... "project_name": "Water Quality Study", + ... "funding_agency": "EPA", + ... "study_period": "2024-2025" + ... } + ... ) + + With custom tags and resource metadata: + >>> client.publish_to_ckan( + ... "campaign123", + ... "station456", + ... custom_tags=["water-quality", "research", "epa-funded"], + ... resource_metadata={ + ... "quality_level": "Level 2", + ... "processing_version": "v2.1" + ... } + ... ) + + Complete customization: + >>> client.publish_to_ckan( + ... "campaign123", + ... "station456", + ... dataset_metadata={ + ... "project_pi": "Dr. Jane Smith", + ... "institution": "University XYZ", + ... "grant_number": "EPA-2024-001" + ... }, + ... resource_metadata={ + ... "calibration_date": "2024-01-15", + ... "data_quality": "QC Passed" + ... }, + ... custom_tags=["university-research", "calibrated-data"], + ... auto_publish=False + ... ) + """ + if not self.ckan: + raise ConfigurationError("CKAN integration not configured") + station_data = self.stations.get(station_id=station_id, campaign_id=campaign_id) + station_measurements = self.stations.export_station_measurements(station_id=station_id, campaign_id=campaign_id) + station_sensors = self.stations.export_station_sensors(station_id=station_id, campaign_id=campaign_id) + campaign_data = self.campaigns.get(campaign_id=campaign_id) + return self.ckan.publish_campaign( + campaign_id=campaign_id, + campaign_data=campaign_data, + station_measurements=station_measurements, + station_sensors=station_sensors, + station_data=station_data, + dataset_metadata=dataset_metadata, + resource_metadata=resource_metadata, + custom_tags=custom_tags, + auto_publish=auto_publish, + **kwargs + ) def logout(self) -> None: """Logout and invalidate authentication.""" diff --git a/upstream/sensors.py b/upstream/sensors.py index 3846e89..8577840 100644 --- a/upstream/sensors.py +++ b/upstream/sensors.py @@ -6,7 +6,7 @@ """ from pathlib import Path -from typing import Any, Dict, List, Optional, Tuple, Union +from typing import Any, Dict, List, Optional, Tuple, Union, cast from upstream_api_client.api import SensorsApi, UploadfileCsvApi from upstream_api_client.models import ( @@ -273,7 +273,7 @@ def upload_csv_files( sensors_file: Union[str, Path, bytes, Tuple[str, bytes]], measurements_file: Union[str, Path, bytes, Tuple[str, bytes]], chunk_size: int = 1000, - ) -> Dict[str, object]: + ) -> Dict[str, Any]: """ Upload sensor and measurement CSV files to process and store data in the database. Measurements are uploaded in chunks to avoid HTTP timeouts with large files. @@ -362,7 +362,7 @@ def upload_csv_files( logger.info( f"Successfully uploaded {len(measurements_chunks)} measurement chunks for campaign {campaign_id}, station {station_id}" ) - return all_responses[-1] if all_responses else {} + return cast(Dict[str, Any], all_responses[-1]) if all_responses else {} except ValueError as exc: raise ValidationError( diff --git a/upstream/stations.py b/upstream/stations.py index 2947bb0..27181d0 100644 --- a/upstream/stations.py +++ b/upstream/stations.py @@ -5,6 +5,9 @@ using the generated OpenAPI client. """ +import io +from typing import BinaryIO + from upstream_api_client.api import StationsApi from upstream_api_client.models import ( GetStationResponse, @@ -280,3 +283,102 @@ def delete(self, station_id: str, campaign_id: str) -> bool: raise APIError(f"Failed to delete station: {e}", status_code=e.status) except Exception as e: raise APIError(f"Failed to delete station: {e}") + + def export_station_sensors(self, station_id: str, campaign_id: str) -> BinaryIO: + """ + Export station sensors as a stream. + Args: + station_id: Station ID + campaign_id: Campaign ID + + Returns: + BinaryIO: A binary stream containing the CSV data that can be read like a file + """ + if not station_id: + raise ValidationError("Station ID is required", field="station_id") + if not campaign_id: + raise ValidationError("Campaign ID is required", field="campaign_id") + + try: + station_id_int = int(station_id) + campaign_id_int = int(campaign_id) + + with self.auth_manager.get_api_client() as api_client: + stations_api = StationsApi(api_client) + + response = stations_api.export_sensors_csv_api_v1_campaigns_campaign_id_stations_station_id_sensors_export_get( + campaign_id=campaign_id_int, station_id=station_id_int + ) + + if isinstance(response, str): + csv_bytes = response.encode('utf-8') + elif isinstance(response, bytes): + csv_bytes = response + else: + # Handle other response types by converting to string first + csv_bytes = str(response).encode('utf-8') + + return io.BytesIO(csv_bytes) + + + except ValueError as exc: + raise ValidationError( + f"Invalid ID format: station_id={station_id}, campaign_id={campaign_id}" + ) from exc + except ApiException as e: + if e.status == 404: + raise APIError(f"Station not found: {station_id}", status_code=404) from e + else: + raise APIError(f"Failed to export station data: {e}", status_code=e.status) from e + except Exception as e: + raise APIError(f"Failed to export station data: {e}") from e + + def export_station_measurements(self, station_id: str, campaign_id: str) -> BinaryIO: + """ + Export station data as a stream. + + Args: + station_id: Station ID + campaign_id: Campaign ID + + Returns: + BinaryIO: A binary stream containing the CSV data that can be read like a file + """ + if not station_id: + raise ValidationError("Station ID is required", field="station_id") + if not campaign_id: + raise ValidationError("Campaign ID is required", field="campaign_id") + + try: + station_id_int = int(station_id) + campaign_id_int = int(campaign_id) + + with self.auth_manager.get_api_client() as api_client: + stations_api = StationsApi(api_client) + + response = stations_api.export_measurements_csv_api_v1_campaigns_campaign_id_stations_station_id_measurements_export_get( + campaign_id=campaign_id_int, station_id=station_id_int + ) + + # Convert response to bytes if it's a string, then create a BytesIO stream + if isinstance(response, str): + csv_bytes = response.encode('utf-8') + elif isinstance(response, bytes): + csv_bytes = response + else: + # Handle other response types by converting to string first + csv_bytes = str(response).encode('utf-8') + + return io.BytesIO(csv_bytes) + + except ValueError as exc: + raise ValidationError( + f"Invalid ID format: station_id={station_id}, campaign_id={campaign_id}" + ) from exc + except ApiException as e: + if e.status == 404: + raise APIError(f"Station not found: {station_id}", status_code=404) from e + else: + raise APIError(f"Failed to export station data: {e}", status_code=e.status) from e + except Exception as e: + raise APIError(f"Failed to export station data: {e}") from e diff --git a/upstream/utils.py b/upstream/utils.py index 7d671a9..53d0db0 100644 --- a/upstream/utils.py +++ b/upstream/utils.py @@ -27,6 +27,7 @@ def __init__( password: Optional[str] = None, base_url: Optional[str] = None, ckan_url: Optional[str] = None, + ckan_organization: Optional[str] = None, timeout: int = 30, max_retries: int = 3, chunk_size: int = 10000, @@ -41,6 +42,7 @@ def __init__( password: Upstream password base_url: Base URL for Upstream API ckan_url: CKAN portal URL + ckan_organization: CKAN organization name timeout: Request timeout in seconds max_retries: Maximum retry attempts chunk_size: Number of records per chunk @@ -56,6 +58,7 @@ def __init__( self.ckan_url = ckan_url or os.getenv( "CKAN_URL", "https://ckan.tacc.utexas.edu" ) + self.ckan_organization = ckan_organization or os.getenv("CKAN_ORGANIZATION") # Configuration options self.timeout = timeout @@ -128,8 +131,9 @@ def from_file(cls, config_path: Union[str, Path]) -> "ConfigManager": if "ckan" in config_data: ckan_config = config_data["ckan"] flattened_config["ckan_url"] = ckan_config.get("url") + flattened_config["ckan_organization"] = ckan_config.get("organization") flattened_config.update( - {k: v for k, v in ckan_config.items() if k != "url"} + {k: v for k, v in ckan_config.items() if k not in ["url", "organization"]} ) if "upload" in config_data: @@ -163,6 +167,7 @@ def to_dict(self) -> Dict[str, Any]: "password": self.password, "base_url": self.base_url, "ckan_url": self.ckan_url, + "ckan_organization": self.ckan_organization, "timeout": self.timeout, "max_retries": self.max_retries, "chunk_size": self.chunk_size, @@ -188,6 +193,7 @@ def save(self, config_path: Union[str, Path]) -> None: }, "ckan": { "url": self.ckan_url, + "organization": self.ckan_organization, }, "upload": { "chunk_size": self.chunk_size,