How do you manage dependencies in a Python project?

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Managing dependencies in a Python project is crucial for ensuring consistent behavior across development, testing, and production environments. Here’s how it’s typically done:

1. Virtual Environments: Tools like venv or virtualenv are used to create isolated environments. This keeps project-specific packages separate from the system-wide Python installation and avoids version conflicts between projects.

2. Requirements File: Dependencies are listed in a requirements.txt file using the pip freeze > requirements.txt command. This file can then be used to recreate the exact environment with pip install -r requirements.txt.

3. Dependency Management Tools:

   • Pip: The default package manager for Python, used to install packages from PyPI.

   • Pipenv: Combines pip and virtualenv, automatically creating a virtual environment and managing dependencies in Pipfile and Pipfile.lock.

   • Poetry: A modern dependency and packaging tool that manages dependencies in pyproject.toml. It simplifies publishing and ensures reproducible builds with a lock file.

4. Version Pinning: Always specifying package versions (e.g., requests==2.31.0) helps prevent unexpected updates that could break functionality.

5. Regular Updates and Security Checks: Using tools like pip-audit, safety, or built-in features of Poetry and GitHub Dependabot helps detect known vulnerabilities and outdated packages.

By following these practices, dependencies are managed reliably, ensuring consistent, secure, and reproducible project environments.

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