Installing stardist-napari downgrades numpy - any ideas why?

[haesleinhuepf]

Hi Uwe and Martin @uschmidt83 @maweigert ,

I had repeatedly issues with installing stardist-napari because it downgraded numpy and then breaks environments. I'm not 100%ly sure if the breaking-environment issue is related to numpy, but I'm quite sure that it happens when installing stardist-napari.

Do you have any idea which dependency pins numpy to 1.19.5 and would it maybe be possible to upgrade that dependency and/or create an issue there? Closing this issue because it's not related directly to stardist-napari would also be fine. Anyway, any hint is welcome!

Thanks!
Robert

Here's the log of a recent installation in a new environment. All I did after setting up a fresh conda environment was 'pip install napari[all]' and then the following output is produced by 'pip install stardist-napari':

(bio_38) C:\Users\rober>pip install stardist-napari
Collecting stardist-napari
  Using cached stardist_napari-2021.6.28-py3-none-any.whl (28 kB)
Collecting stardist>=0.7.0
  Using cached stardist-0.7.3-cp38-cp38-win_amd64.whl (757 kB)
Requirement already satisfied: napari>=0.4.8 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from stardist-napari) (0.4.12)
Requirement already satisfied: magicgui>=0.2.9 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from stardist-napari) (0.3.2)
Collecting tensorflow
  Using cached tensorflow-2.6.0-cp38-cp38-win_amd64.whl (423.2 MB)
Requirement already satisfied: qtpy>=1.7.0 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from magicgui>=0.2.9->stardist-napari) (1.11.2)
Requirement already satisfied: psygnal>=0.1.3 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from magicgui>=0.2.9->stardist-napari) (0.1.4)
Requirement already satisfied: docstring-parser in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from magicgui>=0.2.9->stardist-napari) (0.12)
Requirement already satisfied: typing-extensions in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from magicgui>=0.2.9->stardist-napari) (3.10.0.2)
Requirement already satisfied: tifffile>=2020.2.16 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (2021.10.12)
Requirement already satisfied: appdirs>=1.4.4 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (1.4.4)
Requirement already satisfied: pydantic>=1.8.1 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (1.8.2)
Requirement already satisfied: napari-console>=0.0.4 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (0.0.4)
Requirement already satisfied: toolz>=0.10.0 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (0.11.1)
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Requirement already satisfied: wrapt>=1.11.1 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (1.13.2)
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Requirement already satisfied: scipy>=1.2.0 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (1.7.1)
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Requirement already satisfied: tqdm>=4.56.0 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from napari>=0.4.8->stardist-napari) (4.62.3)
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Requirement already satisfied: scikit-image in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from stardist>=0.7.0->stardist-napari) (0.18.3)
Collecting numba
  Using cached numba-0.54.1-cp38-cp38-win_amd64.whl (2.3 MB)
Collecting csbdeep>=0.6.3
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Collecting clang~=5.0
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  Preparing metadata (setup.py) ... done
Collecting tensorflow-estimator~=2.6
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Collecting wrapt>=1.11.1
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Collecting typing-extensions
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Collecting protobuf>=3.9.2
  Downloading protobuf-3.19.0-cp38-cp38-win_amd64.whl (895 kB)
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Collecting keras~=2.6
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Collecting absl-py~=0.10
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Collecting astunparse~=1.6.3
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Collecting grpcio<2.0,>=1.37.0
  Downloading grpcio-1.41.0-cp38-cp38-win_amd64.whl (3.2 MB)
     |████████████████████████████████| 3.2 MB ...
Collecting six~=1.15.0
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Collecting keras-preprocessing~=1.1.2
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Requirement already satisfied: heapdict in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from cachey>=0.2.1->napari>=0.4.8->stardist-napari) (1.0.1)
INFO: pip is looking at multiple versions of clang to determine which version is compatible with other requirements. This could take a while.
INFO: pip is looking at multiple versions of certifi to determine which version is compatible with other requirements. This could take a while.
Collecting certifi>=2018.1.18
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INFO: pip is looking at multiple versions of astunparse to determine which version is compatible with other requirements. This could take a while.
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Collecting absl-py~=0.10
  Using cached absl_py-0.14.1-py3-none-any.whl (131 kB)
INFO: pip is looking at multiple versions of gast to determine which version is compatible with other requirements. This could take a while.
INFO: pip is looking at multiple versions of tensorflow to determine which version is compatible with other requirements. This could take a while.
Collecting tensorflow
  Using cached tensorflow-2.5.1-cp38-cp38-win_amd64.whl (422.6 MB)
Collecting keras-nightly~=2.5.0.dev
  Using cached keras_nightly-2.5.0.dev2021032900-py2.py3-none-any.whl (1.2 MB)
Collecting grpcio~=1.34.0
  Using cached grpcio-1.34.1-cp38-cp38-win_amd64.whl (2.9 MB)
Collecting tensorflow-estimator<2.6.0,>=2.5.0
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Collecting tensorflow-estimator<2.5.0,>=2.4.0
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Collecting h5py~=2.10.0
  Using cached h5py-2.10.0-cp38-cp38-win_amd64.whl (2.5 MB)
Collecting gast==0.3.3
  Using cached gast-0.3.3-py2.py3-none-any.whl (9.7 kB)
Collecting grpcio~=1.32.0
  Using cached grpcio-1.32.0-cp38-cp38-win_amd64.whl (2.6 MB)
Requirement already satisfied: matplotlib in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from csbdeep>=0.6.3->stardist>=0.7.0->stardist-napari) (3.4.3)
Requirement already satisfied: cloudpickle>=1.1.1 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from dask[array]!=2.28.0,>=2.15.0->napari>=0.4.8->stardist-napari) (2.0.0)
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Requirement already satisfied: packaging>=20.0 in c:\users\rober\miniconda3\envs\bio_38\lib\site-packages (from dask[array]!=2.28.0,>=2.15.0->napari>=0.4.8->stardist-napari) (21.0)
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Collecting google-auth<3,>=1.6.3
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Collecting markdown>=2.6.8
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ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
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Successfully installed absl-py-0.15.0 astunparse-1.6.3 cachetools-4.2.4 csbdeep-0.6.3 flatbuffers-1.12 gast-0.3.3 google-auth-2.3.0 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.32.0 h5py-2.10.0 keras-preprocessing-1.1.2 llvmlite-0.37.0 markdown-3.3.4 numba-0.54.1 numpy-1.19.5 oauthlib-3.1.1 opt-einsum-3.3.0 protobuf-3.19.0 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-oauthlib-1.3.0 rsa-4.7.2 six-1.15.0 stardist-0.7.3 stardist-napari-2021.6.28 tensorboard-2.7.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.0 tensorflow-2.4.3 tensorflow-estimator-2.4.0 termcolor-1.1.0 typing-extensions-3.7.4.3 werkzeug-2.0.2 wrapt-1.12.1

[maweigert]

Hi,

Yes, I these numpy version issues are quite annoying. Almost always they are related to version pins by either tensorflow or numba, see

tensorflow/tensorflow#50204
numba/numba#7176

I normally simply upgrade numpy directly after installing tensorflow, numba, stardist etc and keep my fingers crossed :)

[psobolewskiPhD]

What's really wierd is that stardist installs fine and doesn't do the numpy shenanigans.
edit:
The difference is stardist doesn't depend on tensorflow directly in requirements, so i guess pip doesn't recurse the requirements and downgrade numpy?
If I comment out tensorflow from the plugin setup.py, then pip install . works without messing with numpy.
Likewise, if I manually install stardist and then add tensorflow-macos to the requires, I can install with --no-deps and it also works, because the requirements for stardist-napari are there, and pip doesn't recurse through their mix of requirements.

Edit2: but cellfinder-core which also uses tensorflow and has it in the requirements doesn't have this issue, so 🤷

[uschmidt83]

Edit2: but cellfinder-core which also uses tensorflow and has it in the requirements doesn't have this issue, so 🤷

Maybe tensorflow was already installed at that point?

[psobolewskiPhD]

Yes, in both cases I've got TF installed first, when setting up the environment following Apple instructions.
And because I neglected to mention, this is a branch of cellfinder that has tensorflow-macos and the same for stardist-napari so pip sees the TF. So it must be deeper in.
I'll try the strategy shown here at some point and see if I can find the culprit:
napari/napari#3223 (comment)

[uschmidt83]

Good luck and thanks for working through all of this. I currently keep up with all of it...

[psobolewskiPhD]

Good news!
Apple has bumped the tensorflow-deps conda package and now it has numpy 1.21 etc.
With

        'tensorflow;  platform_system!="Darwin" or platform_machine!="arm64"',
        'tensorflow-macos;  platform_system=="Darwin" and platform_machine=="arm64"',

in setup.py the plugin just installs directly with no issue.

(note stardist required llvmlite from conda, because I (apparently) have llvm 13 which is not yet supported by llvmlite—but will be in the next release numba/llvmlite#802 (comment) )

[kapoorlab]

In mathching.py file there is numba import: from numba import jit and in numba there is a strict numpy requirement pinning it down File ~\anaconda3\envs\vollseg\lib\site-packages\numba\__init__.py:140, in _ensure_critical_deps() 138 raise ImportError("Numba needs NumPy 1.18 or greater") 139 elif numpy_version > (1, 21): --> 140 raise ImportError("Numba needs NumPy 1.21 or less") 142 try: 143 import scipy
So there is no way out of this requirement then or?

[maweigert]

So there is no way out of this requirement then or?

Currently not as we are not in control over numba's numpy dependency. It looks like this will be solved in the next numba release though.

[psobolewskiPhD]

Experimental numba M1 releases work with numpy 1.21.*
StarDist installs fine in the apple TF-metal conda miniforge env.
See: https://numba.discourse.group/t/wheels-for-apple-silicon-m1/1282?u=psobolewskiphd

[maweigert]

Experimental numba M1 releases work with numpy 1.21.*

Sounds good! So the next numba release should at least the current numpy dependency regression problems...

[psobolewskiPhD]

FYI:
numba 0.55.2 has been released, along with llvmlite 0.38.1 which both support numpy 1.22 and have arm64 macOS wheels on pypi.
So at least on macOS and M1 this issue is resolved.

[maweigert]

Nice, thanks for the heads up! :)