[mattip]

While we are trying to minimize the disruptions, there is one thing project maintainers should do right now: pin the maximum NumPy to <2.0 in their ~`pyproject.toml`~ project dependencies. This will ensure they do not inadvertently upgrade before they are ready to do so. Once numpy2.0 is released, you can check that your code works with it, and then release the pin.

[appplication]

Definitely good advice on pinning the upper range for major versions. Pandas 2.0 inadvertently broke spark’s toPandas for (at the time) all existing spark versions, which some of our users lean on. Pandas response to this was apparently to upgrade spark to a version that was not yet released. We lost about half a day’s work from a small handful of devs trying to identify why some of our users were seeing sudden failures.