ExcelToJsonConverter

Converts CDISC Rules Engine Excel datasets to JSON for TEST command

Introduction

The ExcelToJsonConverter is a Python script designed to convert CDISC Rules Engine Excel datasets into JSON format. This tool is particularly useful for preparing datasets for the TEST command.

Usage

To use the ExcelToJsonConverter, you need to provide the paths to the directories containing the rule files and dataset files. The script will process these directories, find the corresponding Excel files, convert them to JSON, and save the JSON files in a specified folder.

Command-Line Arguments

• --rules: Path to the directory containing rule files.
• --datasets: Path to the directory containing dataset files.

Example

python XSLX-to-JSON.py --rules path/to/rules --datasets path/to/datasets

Directory Structure

The script expects the following directory structure for the rule and dataset folders:

Rules Directory

The rules directory should contain subfolders, each named after a specific rule ID. Each subfolder can contain multiple rule files.

rules_directory/
├── rule1/
│   ├── rule_file1.json
│   └── rule_file2.json
├── rule2/
│   ├── rule_file1.json
│   └── rule_file2.json
└── rule3/
    ├── rule_file1.json
    └── rule_file2.json

Datasets Directory

The datasets directory should contain subfolders, each named after a specific dataset. Each subfolder can contain multiple dataset files.

datasets_directory/
├── dataset1/
│   ├── dataset_file1.xlsx
│   └── dataset_file2.xlsx
├── dataset2/
│   ├── dataset_file1.xlsx
│   └── dataset_file2.xlsx
└── dataset3/
    ├── dataset_file1.xlsx
    └── dataset_file2.xlsx

Output

The converted JSON files will be saved in a folder named json_datasets, with subfolders named after the rule IDs.

json_datasets/
├── rule1/
│   └── converted_dataset.json
├── rule2/
│   └── converted_dataset.json
└── rule3/
    └── converted_dataset.json

Dependencies

1. pandas
2. argparse
3. json
4. shutil
5. os

You can install the required dependencies using pip: