How to include optional dependencies that are instrument specific? #14
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This is done in Xarray: https://docs.xarray.dev/en/stable/getting-started-guide/installing.html#id1 How could we implement something like this in PyOpia if needed? We would like to keep the complexity of dependencies to the minimum needed. i.e. if we wanted to build a light system to just process fast and give us size distributions (and no classification), we could skip installing tensorflow, for example. Do you have any experience / ideas on this @dbuscombe-usgs ? |
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I have some thoughts on this, but will need a few days to compose them. For clarification, you want different 'profiles' that install subset of dependencies depending on the user's needs? Also, is tensorflow-lite planned to be used for mobile/edge devices, or regular tensorflow? |
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This can be done by added [options.extras_require] into setup.cfg if we merge #108 That would then eventually allow optional dependencies that would be installed with, for example: the the contents of setup.cfg would have something like:
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See #140 |
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i.e fftpack is needed for holography, but not UVP or SilCam
@nepstad I think you had some thoughts about optional dependencies in setuptools?
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