Dear Python packagers, Am 16.01.21 um 21:43 schrieb Ben Greiner:
Am 26.12.20 um 16:01 schrieb Ben Greiner:
- If upstream does not support python 3.6 anymore (Numpy already deprecates to support it in new releases, according to NEP 29 [5]) you can use `%define skip_python36 1`. All depending packages need to do the same. Alternatively a branched package can provide an older version for this flavor, e.g. python-ipython715 has been created to provide the last version which support Python 3.6.
SciPy's recent update to 1.6.0 already dropped support for Python 3.6. Luckily for us, the update is stuck in Staging:I, and :N got merged before it. But in order to move on in the spirit of Tumbleweed, we need to `%define skip_python36 1` in python-scipy. As a consequence, all packages requiring python-scipy need to do the same.
This just happened: python-scipy 1.6.0 has been merged into openSUSE:Factory today. There is no longer a python36-scipy , and packages depending on SciPy, which are in Ring1, also already skip the build. Scikit-image and networkx are notable mentions. So do many packages in devel:languages:python:numeric. Due to the drop, the count of unresolvable packages in Factory rose from just below 100 to 184. Please check you python packages now and skip the python36 build if necessary. Please keep your singlespec definitions, so that a new python39 flavor in the (hopefully near) future can pick up, where we just left.
For an even larger set of packages, the same will be required for NumPy in the near future. NumPy 1.20 already has has an rc2 and will also drop Python 3.6 following its own NEP 29.
NumPy 1.20 is out and on it's way into Factory (https://build.opensuse.org/request/show/870996).
If your package's dependency on scipy is only optional and upstream still officially supports python 3.6, please consider providing the python36 flavor as long as upstream does it, and just remove the requirement for python <=3.6 while deselecting scipy specific tests. This way, you don't break the package in d:l:p:backports (if it is not already broken).
The same statement is valid for NumPy. Regards, Ben