Closed sfinkens closed 10 months ago
Merging #81 (1c8cc0f) into main (1ed7063) will not change coverage. The diff coverage is
n/a
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## main #81 +/- ##
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Coverage 77.61% 77.61%
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Files 21 21
Lines 1452 1452
Branches 107 120 +13
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Hits 1127 1127
Misses 301 301
Partials 24 24
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unittests | 77.61% <ø> (ø) |
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level1c4pps/calibration_coefs.py | 100.00% <ø> (ø) |
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level1c4pps/tests/test_seviri2pps.py | 96.76% <ø> (ø) |
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Can we just remove support for python 3.8? Or do you still need to run level1c4pps for python-3.8?
Can we just remove support for python 3.8? Or do you still need to run level1c4pps for python-3.8?
Forwarding this to @yeigenbrodt :slightly_smiling_face:
Can we just remove support for python 3.8? Or do you still need to run level1c4pps for python-3.8?
I see no reason to support 3.8.
I simplified the satpy version requirement a little (> 0.41), which speeds up the build a bit:
OS | Python | Build time old [min] | Build time new [min] |
---|---|---|---|
ubuntu | 3.9 | inf | 22 |
ubuntu | 3.10 | 116 | 11 |
ubuntu | 3.11 | 13 | 3 |
macos | 3.9 | inf | 46 |
macos | 3.10 | 37 | 22 |
macos | 3.11 | 14 | 8 |
So at least from the Python-3.11 jobs you get a quick feedback. But 46 minutes for Python-3.9 is way too long... Any idea how to speed this up?
I see this is already using mamba, which I was going to suggest. I'm very surprised it takes such a long time with mamba though... As for ways to improve this, maybe the requirements file should be trimmed down? Satpy has hard requirements on pyresample, dask and xarray at least, so these can go.
As for ways to improve this, maybe the requirements file should be trimmed down?
That helped a lot! Now at 6 minutes max :slightly_smiling_face:
@ninahakansson From my point of view this is ready to merge now.
Update MSG-4 visible calibration coefficients to latest version from May 2023: https://msgcpp.knmi.nl/solar-channel-calibration.html
Edit 1
For some reason creating the conda environment on macos failed (see https://github.com/foua-pps/level1c4pps/actions/runs/5785938956):
Switching to mambaforge seems to solve the problem.
Edit 2
Now creating the conda env with Python-3.8 takes forever...
I noticed some warnings about deprecated node 12 (https://github.blog/changelog/2023-06-13-github-actions-all-actions-will-run-on-node16-instead-of-node12-by-default/) so I updated
actions/checkout
andcodecov/codecov-action
to version 3. But that doesn't speed things up...pytest level1c4pps
flake8