Better use Poetry

When managing Python dependencies, two popular approaches are using requirements.txt files or managing dependencies with Poetry. Each method has its benefits and drawbacks, and the choice between them often depends on the specific needs of your project, your preferences, and the complexity of your dependency management requirements.

requirements.txt

A requirements.txt file is a simple, plain text file that lists the names of Python packages and their versions. You can generate or update this file manually, or by using pip commands such as pip freeze > requirements.txt to capture the current environment's packages.

Pros:

• Simplicity: It’s straightforward and easy to understand, making it accessible for beginners.
• Wide Adoption: It is widely used in the Python community, supported by default in many environments, CI/CD pipelines, and hosting platforms like Heroku.
• Direct Control: You have direct control over package versions, allowing for precise management of your environment.

Cons:

• Manual Management of Dependencies: It does not automatically handle dependency resolution or the updating of dependencies. You need to manage updates and compatible versions manually.
• Lack of Locking Mechanism: Without a lock file, reproducing an exact environment requires all dependencies to be strictly versioned, which can be cumbersome.

Poetry

Poetry is a more recent tool that aims to handle dependency management and packaging in a more holistic way. It uses the pyproject.toml file for configuration, which is part of a newer standard proposed in PEP 518.

Pros:

• Dependency Resolution: Poetry automatically resolves dependencies to ensure compatibility, making it easier to manage complex dependency trees.
• Reproducible Builds: The poetry.lock file ensures that builds are reproducible by locking the versions of both direct and transitive dependencies.
• Integrated Packaging and Publishing: Poetry includes tools for building, packaging, and publishing libraries to repositories like PyPI, streamlining the release process.
• Virtual Environment Management: Automatically creates and manages virtual environments, keeping project dependencies separate from the global Python environment.

Cons:

• Learning Curve: The additional features and the new pyproject.toml configuration file can introduce a learning curve for those accustomed to requirements.txt.
• Not Universally Supported: While growing in popularity, Poetry’s use is not as widespread as requirements.txt, and some CI/CD systems and deployment environments may require additional configuration steps to use Poetry.
• Overhead for Simple Projects: The additional functionality and automatic environment management can be overkill for very simple projects or scripts.

Summary

• Use requirements.txt for simplicity, for projects with a flat dependency structure, or when working in environments where Poetry's additional features are not needed.
• Consider Poetry for complex projects where automatic dependency resolution, reproducible builds, and integrated packaging and publishing capabilities can significantly streamline the development and deployment process.

Ultimately, the choice depends on your project’s specific needs, the complexity of its dependencies, and your workflow preferences.