---
module-name: "New Python Project"
version: "1.0.0"
description: "A project to explore and utilize Python for various applications."
related-modules:
  
technologies:
  
  - Flask
  
  - Django
  
  - Pandas
  
  - NumPy
  
conventions:
  
  - Use snake_case for variables
  
  - Follow PEP 8 style guide
  
architecture:
  style: "microservices"
  main-components:
    
    - API Gateway
    
    - User Service
    
    - Product Service
    
    - Database
    
    - Authentication Service
    
  data-flow: "User initiates a request through the API Gateway, which routes the request to the appropriate service (e.g., User Service for user data or Product Service for product information). Each service interacts with the database for data storage and retrieval. The Authentication Service handles user authentication and authorization, ensuring secure access to services."
development:
  setup-steps:
    
    - Install Python
    
    - Create a virtual environment
    
    - Run pip install -r requirements.txt
    
  build-command: "python setup.py build"
  test-command: "pytest"
business-requirements:
  key-features:
    
    - Project setup with virtual environment
    
    - Code organization for modularity
    
    - Integration with popular libraries and frameworks
    
    - Version control setup with Git
    
    - Documentation generation
    
  target-audience: "Developers and data scientists who want to leverage Python for their projects."
  success-metrics:
    
    - Number of projects created using the template
    
    - User satisfaction ratings
    
    - Growth in community contributions
    
    - Reduction in setup time for new projects
    
quality-assurance:
  testing-frameworks:
    
    - pytest
    
  coverage-threshold: "80%"
  performance-benchmarks:
    
    - Response time < 200ms
    
    - Throughput > 1000 requests/min
    
deployment:
  platform: "AWS"
  cicd-pipeline:
    
    - Code Commit
    
    - Build
    
    - Test
    
    - Deploy to Staging
    
    - Deploy to Production
    
  staging-environment: "https://staging.example.com"
  production-environment: "https://www.example.com"
---

# New Python Project

## Overview

A project to explore and utilize Python for various applications.

- **Version**: 1.0.0
- **Primary Language**: Python
- **Technologies Used**:
  
  - Flask
  
  - Django
  
  - Pandas
  
  - NumPy
  

## Architecture

- **Architecture Style**: microservices
- **Components**:
  
  - API Gateway
  
  - User Service
  
  - Product Service
  
  - Database
  
  - Authentication Service
  
- **Data Flow**:
  User initiates a request through the API Gateway, which routes the request to the appropriate service (e.g., User Service for user data or Product Service for product information). Each service interacts with the database for data storage and retrieval. The Authentication Service handles user authentication and authorization, ensuring secure access to services.


- **Diagrams**:
  
  - Type: UML
  - Description: Class diagram representing the main components and their relationships.
  
  - Type: Sequence Diagram
  - Description: Illustrating the interaction between the API Gateway and the various services.
  


## Development

- **Setup Steps**:
  
  - Install Python
  
  - Create a virtual environment
  
  - Run pip install -r requirements.txt
  
- **Build Command**: python setup.py build
- **Test Command**: pytest
- **Coding Conventions**:
  
  - Use snake_case for variables
  
  - Follow PEP 8 style guide
  
- **Directives**:
  
  - Document all functions and classes
  
  - Implement logging for error tracking
  

## Business Requirements

- **Key Features**:
  
  - Project setup with virtual environment
  
  - Code organization for modularity
  
  - Integration with popular libraries and frameworks
  
  - Version control setup with Git
  
  - Documentation generation
  
- **Target Audience**: Developers and data scientists who want to leverage Python for their projects.
- **Business Objectives**:
  
  - Facilitate rapid development of Python applications
  
  - Encourage best practices in coding and project management
  
  - Increase community engagement through open-source contributions
  
- **Success Metrics**:
  
  - Number of projects created using the template
  
  - User satisfaction ratings
  
  - Growth in community contributions
  
  - Reduction in setup time for new projects
  

## Quality Assurance

- **Testing Frameworks**:
  
  - pytest
  
- **Code Coverage Threshold**: 80%
- **Performance Benchmarks**:
  
  - Response time < 200ms
  
  - Throughput > 1000 requests/min
  
- **Quality Standards**:
  
  - ISO 25010
  
  - OWASP Top Ten
  

## Deployment

- **Deployment Platform**: AWS
- **CI/CD Pipeline**:
  
  - Code Commit
  
  - Build
  
  - Test
  
  - Deploy to Staging
  
  - Deploy to Production
  
- **Staging Environment**: https://staging.example.com
- **Production Environment**: https://www.example.com
- **Rollback Procedures**:
  
  - Monitor application for errors
  
  - If issues are detected, initiate rollback
  
  - Restore previous stable version from backup
  
  - Verify application functionality
  
  - Notify stakeholders of rollback completion
  