CONTRIBUTING.md

Contributing to Risk Analysis System

Thank you for considering contributing to the Risk Analysis Syatem! This document outlines the development and deployment process, including setup instructions, CI/CD configurations, and branching strategy.

Table of Contents

1. Getting Started
   • Prerequisites
   • Installation
   • Setting Up the Development Environment
2. Development Workflow
   • Branching Strategy
   • Code Style and Linting
   • Running Tests
3. CI/CD Pipeline
   • Continuous Integration
   • Continuous Deployment
4. Deployment Instructions
   • Heroku Deployment
   • AWS Elastic Beanstalk Deployment
5. Reporting Issues
6. Submitting Pull Requests

Getting Started

Prerequisites

Before you begin, ensure you have the following installed:

• Python 3.x: Required for running the application.
• pip: Python package manager.
• git: Version control system.
• Heroku CLI (if deploying to Heroku).
• AWS CLI (if deploying to AWS Elastic Beanstalk).

Installation

1. Clone the repository:

   git clone https://github.com/MALVMAS/RAS.git
   cd MALVMAS

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

Setting Up the Development Environment

1. Configure environment variables:

   Create a .env file in the root of your project and add the necessary environment variables:

   DEBUG=True
   SECRET_KEY=your-secret-key
   DATABASE_URL=your-database-url
   

2. Run the development server:

   python manage.py runserver

Development Workflow

Branching Strategy

We follow the GitFlow branching model:

• main: The main branch contains the production-ready code.
• develop: The development branch is where the latest development happens.
• feature/*: Feature branches are created from develop for new features.
• hotfix/*: Hotfix branches are created from main to address critical issues.

Code Style and Linting

We use autopep8 and pycodestyle to enforce code style:

• Run the linter:

  pycodestyle your_module/

• Auto-format code:

  autopep8 --in-place --aggressive --aggressive your_module/

Running Tests

We use pytest for testing:

• Run all tests:

  pytest

CI/CD Pipeline

Continuous Integration

We use GitHub Actions for continuous integration:

• The CI pipeline runs automatically on every push to the main and develop branches.
• It installs dependencies, runs tests, and checks code quality.

Example CI configuration (.github/workflows/ci.yml):

name: CI Pipeline

on:
  push:
    branches:
      - main
      - develop
  pull_request:
    branches:
      - main
      - develop

jobs:
  test:
    runs-on: ubuntu-latest

    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: '3.x'
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt

- name: Run tests
  run: pytest

Continuous Deployment

We use Heroku or AWS Elastic Beanstalk for automatic deployments:

The deployment pipeline triggers after a successful build on the main branch.

Heroku Deployment

Deployment to Heroku is configured in the CI pipeline:

deploy: runs-on: ubuntu-latest needs: test steps:

• uses: actions/checkout@v2
• name: Deploy to Heroku env: HEROKU_API_KEY: ${{ secrets.HEROKU_API_KEY }} run: | git remote add heroku https://git.heroku.com/.git git push heroku main

Deployment Instructions

Heroku Deployment

1. Install Heroku CLI: curl https://cli-assets.heroku.com/install.sh | sh
2. Login to Heroku: heroku login
3. Deploy manually (if needed): git push heroku main

AWS Elastic Beanstalk Deployment

1. Install AWS CLI: pip install awscli
2. Configure AWS CLI: aws configure
3. Deploy manually (if needed): eb deploy

Reporting Issues

If you encounter any issues or bugs, please open an issue in the GitHub repository. Provide as much detail as possible, including steps to reproduce the issue.

Submitting Pull Requests

1. Fork the repository.
2. Create a new branch: git checkout -b feature/your-feature-name.
3. Commit your changes: git commit -m 'Add some feature'.
4. Push to the branch: git push origin feature/your-feature-name.
5. Open a pull request in the GitHub repository.

Please ensure your pull request adheres to the following guidelines:

• Include tests that cover your changes.
• Follow the code style guidelines.
• Ensure that all tests pass before submitting.

Thank you for contributing to the Risk Analysis System Project!