There is an area of Python that many developers have problems with. This is an area that has seen many different solutions pop up over the years, with many different opinions, wars, and attempts to solve it. Many have complained about the packaging ecosystem and tools making their lives harder. Many beginners are confused about virtual environments. But does it have to be this way? Are the current solutions to packaging problems any good? And is the organization behind most of the packaging tools and standards part of the problem itself?

Join me on a journey through packaging in Python and elsewhere. We’ll start by describing the classic packaging stack (involving setuptools and friends), the scientific stack (with conda), and some of the modern/alternate tools, such as Pipenv, Poetry, Hatch, or PDM. We’ll also look at some examples of packaging and dependency-related workflows seen elsewhere (Node.js and .NET). We’ll also take a glimpse at a possible future (with a venv-less workflow with PDM), and see if the PyPA agrees with the vision and insights of eight thousand users.

Pipenv is a Python packaging tool that does one thing reasonably well — application dependency management. However, it is also plagued by issues, limitations and a break-neck development process. In the past, Pipenv’s promotional material was highly misleading as to its purpose and backers.

In this post, I will explore the problems with Pipenv. Was it really recommended by Python.org? Can everyone — or at least, the vast majority of people — benefit from it?

(This post has been updated in February 2020 and May 2020 to reflect the current state of Pipenv.)