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Python

General Setup

Ensure Python is installed (preferably the latest stable version).

Set up a virtual environment for project isolation.

Use a version control system (e.g., Git) for source code management.

Project Structure

Organize project folders (e.g., src, tests, docs).

Include a README.md file with project description and setup instructions.

Create a requirements.txt file for dependencies.

Coding Standards

Follow PEP 8 style guidelines for Python code.

Use meaningful variable and function names.

Write modular and reusable code components.

Documentation

Include docstrings for all modules, classes, and functions.

Maintain an up-to-date CHANGELOG.md for version history.

Use tools like Sphinx for generating documentation from docstrings.

Testing

Write unit tests for all critical components.

Use a testing framework (e.g., pytest or unittest).

Ensure code coverage is above a predefined threshold (e.g., 80%).

Dependency Management

Regularly update dependencies and libraries.

Use a dependency checker (e.g., pip-audit) to identify vulnerabilities.

Document any special installation instructions for dependencies.

Continuous Integration/Continuous Deployment (CI/CD)

Set up a CI/CD pipeline to automate testing and deployment.

Use services like GitHub Actions, Travis CI, or Jenkins.

Ensure that the pipeline includes steps for linting, testing, and building.

Security Practices

Use environment variables for sensitive data (e.g., API keys).

Implement input validation and error handling.

Regularly review code for security vulnerabilities.

Performance Optimization

Profile code to identify bottlenecks (e.g., using cProfile).

Optimize algorithms and data structures where necessary.

Consider caching strategies for expensive computations.

Code Reviews

Implement a code review process to ensure quality and knowledge sharing.

Use pull requests for collaborative feedback.

Establish guidelines for constructive feedback.

Deployment

Prepare a deployment checklist (e.g., server configuration, environment setup).

Use containerization tools (e.g., Docker) for consistent environments.

Monitor application performance and logs post-deployment.

Maintenance

Schedule regular updates and maintenance for the codebase.

Encourage team members to document lessons learned and improvements.

Review and refactor code regularly to keep it clean and efficient.

This checklist can help ensure that Python projects in engineering organizations are well-structured, maintainable, and follow best practices.

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