A cookiecutter template for conda packages using Python
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A cookiecutter template for conda packages using Python


  • Automatic versioning with versioneer (requires git annotated tags before it'll work)
  • Ready-made conda recipe found in conda.recipe/meta.yaml
  • Pre-configured for Appveyor, Travis CI and Circle CI (you need to activate each of these individually)
  • Coverage report hosted on Codecov.io (activated after first successful CI run, which uploads results)
  • Code analysis with codacy, setup to exclude versioneer and tests (requires activation of project at Codacy)
  • setup.cfg with flake8 opinions and pytest/pytest-cov configuration (including fixed PYTHONHASHSEED)


Prior to installing cookiecutter-conda-python, the cookiecutter package must be installed in your environment. This is achieved via the following command::

$ conda install cookiecutter

With cookiecutter installed, the cookiecutter-conda-python template can be installed with::

$ cookiecutter https://github.com/conda/cookiecutter-conda-python.git

Once cookiecutter clones the template, you will be asked a series of questions related to your project::

$ full_name [Full Name]: Enter your full name.

$ email [Email Address]: Enter your email address.

$ github_username [github_username]: Enter your github username.

$ repo_name [repository_name]: Enter the name of your project's repository.

$ package_name [package_name]: Enter the name of your package.

$ application_name [application]: Enter the name of your GUI application.

$ project_short_description [Short description]: Enter a short description about your project.


After answering the questions asked during installation, a conda Python package will be created in your current working directory. This package will contain a simple CLI script and the conda recipe necessary to build the application into a conda package.

You'll still need to activate the web services you want to use - they won't be active automatically.