Interface Diagram - Draw.io

This project provides tools to automatically generate end-to-end (E2E) interface diagrams based on JSON data. It fetches data, processes it, and creates a diagrammatic representation of interfaces using Draw.io.

Table of Contents

• Overview
• Features
• Requirements
• Setup
• Usage
• Directory Structure
• Testing
• Deployment
• Contributing
• License

Overview

This project aims to automate the generation of interface diagrams. It includes AWS Lambda functions that process JSON data, convert it to a diagram URL, and then optionally save the URL to an Excel file stored in an S3 bucket.

Features

• JSON Parsing: Converts JSON data into a structured Python object.
• Diagram Generation: Creates a Draw.io diagram URL based on the processed data.
• Excel File Management: Updates an Excel file with interface diagram URLs.
• AWS Lambda Support: Includes Lambda handlers for seamless integration with AWS.

Requirements

• Python 3.8
• AWS CLI (for deployment)
• openpyxl (for Excel operations)
• boto3 (for AWS S3 operations)

Setup

1. Clone the repository:

   git clone https://github.com/meirarc/InterfaceDiagram.git
   

2. Navigate to the project root:

   cd InterfaceDiagram
   

3. Install the required packages:

   pip install -r requirements.txt
   

Usage

To generate an interface diagram:

1. Place your JSON files in the 'in' folder of your S3 bucket.
2. Run the Lambda handler corresponding to your requirements.

Directory Structure

• src/main: Contains the main application code, including Lambda handlers and utilities for JSON parsing, encoding, and Excel file management.
• src/test: Contains test files and test data.
• scripts: Contains utility scripts, such as the one for generating the ZIP file for deployment.

Testing

1. To generate a test JSON object from a CSV, run:

   python .\scripts\generate_json_object.py

2. To run the unittest scripts:

   python -m unittest discover -s src/tests -p 'test_*.py’

3. To run the Pylint scripts

   python3 -m pylint .\src\main

Deployment

1. Modify the Git Hub action python_ci_cd.yml to automatically deploy the project on your AWS account using the cloud formation stack to provision the resources

2. Update the secrets AWS credentials on the Git Action configuration

Contributing

If you'd like to contribute, please fork the repository and use a feature branch. Pull requests are warmly welcome.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.