[Python Package Dependency Management]¶
Context and Problem Statement¶
We as a team have been struggling with dependency management for a while now. Our current approach (‘manual’ requirements + pip constraints files) is cumbersome and error prone especially in case of dependency package version upgrades. Generally better tool support was seen as a solution to the issue.
The Process of upgrading a Python package dependency is an error prone, cumbersome and manual process
There were multiple occasions of failed dependency upgrades leading to failed CI builds and downstream incompatibilities
pip-tools was chosen after a discussion between @hackaugusto, @konradkonrad, @palango and
@ulope as it currently seems to be the least disruptive and most well-used tool available.
poetry might become the preferred solution but didn’t appear mature enough currently.
Pros and Cons of the Options¶
Currently the most mature tool.
Small scope, only manages dependencies
(Relatively) easy to understand operation model
Stable with a long history of being maintained
Better dependency solver than pip (which doesn’t have one)
No built-in support for dependencies between various requirement types (e.g. prod, dev). Requiring a custom wrapper tool.
CLI isn’t very intuitive
Looks to be a good candidate to switch to in the medium future.
Very polished cli
Handles the complete package life-cycle including optional venv management
Proper dependency solver
Still very new with some bugs and some usage types not supported (yet)
Very much a departure from the established ‘way of doing things’
Dependency resolution can currently be very slow
Similar in concept to poetry, yet seems to be not a stable tool to build upon.
Also a very new tools
Many reports of arbitrary breakage with minor upgrades
Dependency resolution appears not to be stable