alxmrs commented on issue #22349:
URL: https://github.com/apache/beam/issues/22349#issuecomment-1190736973

   >  it invokes system Python, whereas for this use case we want Python 
processes to run from conda Python
   
   Interesting – I haven't hit this problem. I use the docker image in the 
issue description (or [see 
here](https://github.com/google/weather-tools/blob/main/weather_mv/Dockerfile)) 
along with [build step in a setup.py file to install conda 
dependencies](https://github.com/google/weather-tools/blob/0ca1a39eb1057acf9b9a663bd122b5fb7d408228/weather_mv/setup.py#L93).
 
   
   I just took a look at the pangeo Dockerfile that compiles sources with go. I 
think this step is unnecessary; rather, I believe that there are other 
strategies to set up conda python on the image. This works by installing deps 
into the base conda environment instead of a named conda env – maybe that's the 
source of the problem?
   
   On @yuvipanda's suggestions: I think the status quo offers enough hooks to 
accomplish a lot of what Yuvi is asking for. For example, the boot sequence for 
Beam will eventually call `setup.py install`  (and `setup.py build`). From 
there, you can install required dependencies, or use distutils to perform 
sophisticated build actions, including running [raw linux 
commands](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/complete/juliaset/setup.py#L75).
 Having said all this, I actually don't really know what problem Yuvi / the 
`forge` container is trying to solve in the first place. Thus, I am probably 
totally off base. @cisaacstern or @yuvipanda can you help me understand the 
infrastructure? 
   
   To add a high level note on my proposal: I think of this Beam/conda docker 
image (with the boot entrypoint) as the runtime environment, from which we can 
add further dependencies at startup time. This is unlike the typical docker 
approach, where we include all dependencies at the image build time. 


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