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Should you use upper bound version constraints?

Bound version constraints (upper caps) are starting to show up in the Python ecosystem. This is causing real world problems with libraries following this recommendation, and is likely to continue to get worse; this practice does not scale to large numbers of libraries or large numbers of users. In this discussion I would like to explain why always providing an upper limit causes far more harm than good even for true SemVer libraries, why libraries that pin upper limits require more frequent updates rather than less, and why it is not scalable. After reading this, hopefully you will always consider every cap you add, you will know the (few) places where pinning an upper limit is reasonable, and will possibly even avoid using libraries that pin upper limits needlessly until the author updates them to remove these pins. If this 10,000 word behemoth is a bit long for you, then skip around using the table of contents, or see the TL;DR section at the end, or read version numbers by Bernát Gábor, which is shorter but is a fantastic read with good examples and cute dog pictures. Or Hynek’s Semantic Versioning Will Not Save You Be sure to check at least the JavaScript project analysis before you leave! Also be warned, I pick on Poetry quite a bit. The rising popularity of Poetry is likely due to the simplicity of having one tool vs. many for packaging, but it happens to also have a special dependency solver, a new upper bound syntax, and a strong recommendation to always limit upper versions - in direct opposition to members of the Python core developer team and PyPA developers. Not all libraries with excessive version capping are Poetry projects (like TensorFlow), but many, many of them are. To be clear, Poetry doesn’t force version pinning on you, but it does push you really, really hard to always version cap, and it’s targeting new Python users that don’t know any better yet than to accept bad recommendations. And these affect the whole ecosystem, including users who do not use poetry, but want to depend on libraries that do! I do really like other aspects of Poetry, and would like to eventually help it build binary packages with Scikit-build (CMake) via a plugin, and I use it on some of my projects happily. If I don’t pick on Poetry enough for you, don’t worry, I have a follow-up post that picks on it in much more detail. Also, check out pdm, which gives many of the benefits of Poetry while following PEP standards.

While I’m not a huge fan of Google’s live-at-head philosophy (primarily because it has heavy requirements not applicable for most open-source projects), I appreciate and love catching a dependency incompatibility as soon as you possibly can; the smaller the change set, the easier it is to identify and fix the issue. This took hours of my time to roll back across half a dozen repos, it caused people trusting my style recommendations to also be affected, all for an untested version cap - Python 3.10 didn’t break the application at all. It also encourages hiding issues until they become harder to fix, it does not scale to larger systems, it limits your ability to access security and bugfix updates, and some tools (Poetry) force these bad decisions on your downstream users if you make them.

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