Using pyenv to manage your Python interpreters

This entry is part 1 of 1 in the series Python version- and module management

When I started to learn Python a few years ago, I often wondered about what’s the “correct” or “best” way to prepare your system’s Python environment for the requirements your software project or some Python-based application you’d like to start using may have: Should I install modules using the package manager of my OS? Or by using Python tools for it like pip? What are “virtual environments” and how do I utilize these for my projects? What’s all this pyenv, pip, pipenv, easy_install, setuptools, anaconda, conda, miniconda …

In this article series, I’d like to introduce the most common tools and techniques on how to do this in the Python world.
At the end of the series, I will share some of my thoughts, doubts, and questions I had back then, tell about some experiences I gathered in the meantime and generally share the outcome of this journey and what my Python-Workflow looks like, nowadays.

Introduction to pyenv šŸ

This first article is about pyenv, a lightweight, yet powerful, Python version management tool that works in user – scope and does stay out of the way of systems global Python interpreters.

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