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update setup #54

Merged
merged 6 commits into from
Jul 30, 2024
Merged

update setup #54

merged 6 commits into from
Jul 30, 2024

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weiqi-tori
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@weiqi-tori weiqi-tori commented Jul 29, 2024

@weiqi-tori weiqi-tori requested review from jterry64 and chrowe July 29, 2024 15:25
setup.py Outdated Show resolved Hide resolved
setup.py Outdated
package_data={
'city_metrix.models.building_classifier': [
'building_classifier.pkl',
'V2-building-class-data.geojson',
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@chrowe was wondering if the user needs this file for running the package? Also, could you rename is to something more like building-class-data-v2.geojson?

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The user needs building_classifier.pkl to generate the SmartSurfaceLULC layer, but the geojson is not necessary. The geojson is the training data for building_classifier.pkl that I got from Elizabeth, I removed it for now.

setup.py Outdated
@@ -21,5 +28,10 @@
"osmnx",
"geopandas",
"s3fs",
"dask==2023.11.0",
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it might not be good to pin a specific version, it will fail if the user has another version. You can set a minimum though, like dask>=2023.11.0

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also, I think the conflict is from odc-stac above, not dask specifically. You can safely remove that, but will need to delete files that reference it

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odc-stac is used in landsat_collection_2.py and sentinel_2_level_2.py. We probably cannot remove that without updating the layers.

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chrowe commented Jul 30, 2024

@weiqi-tori can you also remove cartoframes. I don't think we are using it for anything at this point and it is causing issues in Github Actions when trying to run tests.

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This looks good to me.

@chrowe chrowe marked this pull request as ready for review July 30, 2024 13:40
@chrowe chrowe merged commit ec81280 into main Jul 30, 2024
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@chrowe chrowe deleted the fix/setup_requires branch July 30, 2024 13:41
@chrowe chrowe mentioned this pull request Jul 30, 2024
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chrowe commented Jul 30, 2024

FWIW, a quick search lead me to https://stackoverflow.com/questions/63342686/packaging-libraries-with-ml-models-in-python and not much else on the topic of how to include models in packages. Seems like they are recommending the same basic approach we took.

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3 participants