Conda-build: pip dependencies in conda recipe

Created on 20 Aug 2015  路  4Comments  路  Source: conda/conda-build

is there a way to include dependencies in a meta.yaml that are not yet available as conda packages?

or is the solution to go and build conda packages for all deps?

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Was there ever any progress on this? In order to have a pip dependency, at the moment it seems like you need to go through your entire dependency tree and make sure every package is available through conda. This seems like a lot of mucking around for what intuitively feels like a simple operation (maybe that's naive).

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What sort of dependencies are you trying to include?

Python? AFAIK, no. I know there use to be an issue for listing PyPI dependencies in a package and for the life of me I can't find it. If it is Python, you can try the following:

  • conda pipbuild <pypi_package> - Builds packages for the package listed and any dependencies it can't find. When it works, it is amazing, but there are edge cases it will fail on.
  • conda skeleton pypi <pypi_package> - Gives a rough start at a Python package. There are variants for some other non-Python languages. Not recursive like conda pipbuild, but a bit more stable.
  • Hunt down a recipe. There are tons here ( https://github.com/conda/conda-recipes ). Not to mention, most people put their recipes in a repo on GitHub and put the least restrictive licenses on them.
  • Finally, write your own. Given the numerous examples and methods to get an easy start. It is pretty easy to tweak something to get what you want.

Is it possible to use --pypi-url to point to a pypi.anaconda.org/username channel because there is a package there I want to use, rather than from pypi.python.org? I can't seem to figure out how to get it to work.

Supporting pip dependencies would be great particularly for conda forge. If you want to add a new recipe you currently need to make sure all dependencies are available via conda.

Was there ever any progress on this? In order to have a pip dependency, at the moment it seems like you need to go through your entire dependency tree and make sure every package is available through conda. This seems like a lot of mucking around for what intuitively feels like a simple operation (maybe that's naive).

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