Conda is an alternative package manger to PyPi. It comes with many features that PyPi packaging does not handle well such as including compiled libraries and c dependencies.

While traditional Python packages are stored in conda python packages are stored at These steps do not require that you have already deployed a package to PyPi.

First create an account through <>. Unlike PyPi there is no test repo to submit your package to. Anaconda takes a different philosophy where each user has a collection of packages and jupyter notebooks in their repo. The approach I will show you does not require that you have conda installed on your machine. If you would like to experiment with the build tool I would recommend pulling the continuum conda build docker container continuumio/miniconda3. The default continuumio/anaconda3 docker environment is over 3.5 GB unzipped. Why are the continuum docker containers so large?

docker pull continuumio/miniconda3
docker run -i -t continuumio/miniconda3 /bin/bash

Once you start the docker container you can do the following steps for package deployment to conda. These steps will be automated later with a Gitlab build script. In order to upload packages you will either need to login to your account via anaconda login or create an account token will all account access. I would recommend creating an account token so that you can revoke access at any time. To create an account token go to settings->access on when you are logged in.

  1. conda install anaconda-client setuptools conda-build -y
  2. python bdist_conda
  3. anaconda -t $ANACONDA_TOKEN upload -u $ANACONDA_USERNAME /opt/conda/conda-bld/linux-64/<package>-<version>-<pyversion>.tar.bz2

The first step ensures that all packages are the right version and we have the command line anaconda tool. Anaconda has it hidden in their documentation that they have a convenient build tool for python packages that does not require a recipe. When running in a conda environment they have overridden setuptools to include bdist_conda for building conda packages. The build command will build the package, run tests, and check that each command created exits. After your package is built you can now upload to conda. If you are building within a docker container chances are that their is only one conda build so you can shorten the upload command to anaconda upload /opt/conda/conda-bld/linux-64/<package>*.tar.bz2. Otherwise you will have to chose the build that is provided at the end of the python bdist_conda output.

From some of my initial tests I was surprised that many packages available on PyPi are not available on conda and thus made the builds fail. These errors are most likely due to me know understanding the conda tools well. If your build succeeded you should see the package listed on<username>.

Since we are all about automation lets make this process automatic on Gitlab!


 - deploy

  image: continuumio/miniconda3:latest
  stage: deploy
    - conda install anaconda-client setuptools conda-build -y
    - python bdist_conda
    - anaconda -t $ANACONDA_TOKEN upload -u $ANACONDA_USERNAME /opt/conda/conda-bld/linux-64/pypkgtemp*.tar.bz2
    - /^v\d+\.\d+\.\d+([abc]\d*)?$/  # PEP-440 compliant version (tags)