One of the development team’s biggest challenges is having a consistent and reproducible environment between team members. The bigger the team or more teams working on the same project codebase, the issue is amplified. Different languages try to manage dependencies using a specifically inbuilt language-specific package manager.
For example, Python is using by de-facto pip as a Python package installer that is using Python Package Index repository. All dependencies can be declared in the requirements.txt file and installed with pip install -r requirements.txt Pypi is limited in managing consistent Python packages and versioning. New Python package managers try to solve the limitation of the pip like Data Science oriented Anaconda or Poetry that bring multiple improvements over pip with dependency management and packaging. Poetry is arguably Python’s most advanced dependency management option today by using a configuration file in toml format and generating project scaffolding, locking dependency in the *.lock file.
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