Python dependency management is a dumpster fire
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Python dependency management can be complex and failure-prone. Reproducibility is crucial to ensure consistent behavior across different environments and stages, from development to deployment. This involves using version control and isolating environments, typically with virtual environments or dedicated tools. Tools like pip, Pipenv, Poetry, pyenv, UV, and Conda each provide different levels of functionality for managing dependencies and environments, each with their own advantages and drawbacks.
Table of contents
How a fire startsWhat are dependencies?Why should we "manage dependencies" and what does that even mean?What is the best way to manage dependencies?Why is managing dependencies in Python hard?Available tooling for PythonMeta-issue of most tools: self-versionsTooling beyond the Python ecosystemWhat should you use?Wrapping up and looking aheadSort: