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Python's dependency management is not ideal for installing old versions of libraries, because metadata in PyPI is static and upper version constraints are generally not a good idea for libraries. This means that installing old versions of napari for whatever reason (reproducing a paper or using a library that is no longer being updated) is very hard.
Since we started using version constraints/pinning for CI, from version 0.4.18 we have a record of all the library dependencies, both direct and indirect, that work for a specific napari release. (See this comment.) This is a great and unexpected* version of the pinning! (*at least by me 😅)
Additionally, I recently came across PyPI time machine, which lets you install packages with pip while pretending to live in the past.
It would be good to have a page, or a section in the installation guide, that points readers to these resources (including direct links to the constraints files).
Potentially, we should also generate equivalent conda environment definitions for each release.
The text was updated successfully, but these errors were encountered:
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Python's dependency management is not ideal for installing old versions of libraries, because metadata in PyPI is static and upper version constraints are generally not a good idea for libraries. This means that installing old versions of napari for whatever reason (reproducing a paper or using a library that is no longer being updated) is very hard.
Since we started using version constraints/pinning for CI, from version 0.4.18 we have a record of all the library dependencies, both direct and indirect, that work for a specific napari release. (See this comment.) This is a great and unexpected* version of the pinning! (*at least by me 😅)
Additionally, I recently came across PyPI time machine, which lets you install packages with pip while pretending to live in the past.
It would be good to have a page, or a section in the installation guide, that points readers to these resources (including direct links to the constraints files).
Potentially, we should also generate equivalent conda environment definitions for each release.
The text was updated successfully, but these errors were encountered: