For those less familiar, I have also included a list of useful resources at the end of the article. The article assumes the reader is already familiar with the python packaging ecosystem, pipenv and conda. The article does not recommend one tool over another but should help the reader make a decision based on their needs. Package Availability Dependency resolution Python version Dependency Specification Disk Space Security Longevity Customisation Miscellaneous This article compares pipenv and conda as of Jan 2021 using the following set of criteria, some of which are more relevant to data scientists: Which could leave data scientists in a bit of a quandary.
For example Conda+Anaconda is recommended by which manages the ubiquitous scipy stack, whilst pipenv+PyPI is recommended by PyPA, the python packaging authority. Python has many tools available for distributing code to developers and does not adhere to “There should be one - and preferably only one - obvious way to do it”. A comparison of pipenv and conda as of Jan 2021 based on various “data science-ish” criteria Introduction
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