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Command killed due to excessive memory consumption #6412
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Hi @lukelbd! The main problem here is that I enabled two flags in your project that could help with this (the most important one, is to update conda at startup, since the latest conda release has some memory consumptions improvements). I triggered a build already. Let's see how it goes. |
That didn't help too much. I had to increase the memory limit to 2.5Gb to make the The build is still failing because your |
Thanks a lot! I fixed the failed build by adding proplot to dependencies:
- pip:
.. # relative path for installing current proplot master branch But now it fails because I've renamed some classes and class methods. I think it will run if I can call |
It seems this error is related to #208 (which was posted by the astropy developers). Astropy released the little-known sphinx-automodapi plugin that I also use for ProPlot -- it imports your package and automatically figures out which classes + functions need to be documented, but when the class + function names change and you still have the auto-generated stub pages with the old names, you get errors.
Actually it's probably better to just "wipe" the build as described in #208 every time this happens. The main API changes quite rarely. Just triggered another build, hopefully it goes through. |
Perfect, it's live! Thanks for the help. Luckily it seems the |
@humitos I've been getting a lot of "Build exited due to time out" errors lately. The build is successful maybe ~10-20% of the time, seemingly randomly. I have to keep manually re-building. You'll notice a ton of failed builds in my build history. Would it be possible to increase my maximum compile time? |
I increased the time for your project and triggered a build at https://readthedocs.org/projects/proplot/builds/10567203/. Feel free to reopen if it does not work. |
Details
Expected Result
Successful build.
Actual Result
Failed build. The conda environment solve step causes excess memory consumption.
I also have
python.system_packages = True
in my yaml. Maybe I can reduce the environment solve complexity by using the shared packages? Currently the contents ofenvironment.yml
are:But I'm also worried about memory consumption for the
nbsphinx
steps, which generate some fairly high resolution figures. Before this merge I usednbconvert
to manually generate RST files and synced those.The text was updated successfully, but these errors were encountered: