- CONDA PYTHON VERSION LIST HOW TO
- CONDA PYTHON VERSION LIST INSTALL
- CONDA PYTHON VERSION LIST UPDATE
- CONDA PYTHON VERSION LIST FULL
- CONDA PYTHON VERSION LIST WINDOWS
There are a number of actions in the marketplace that set up Conda environments. The CONDA variable still exists in Windows, I just don’t know PowerShell well enough to use it. The final difference is that an absolute path to Conda is used instead of a relative path from the CONDA environment variable.
CONDA PYTHON VERSION LIST INSTALL
Now that PowerShell knows where to look for Conda environments, the next steps are able to activate an environment, install a package, and use the package without a path from the Conda directory. This line tells the virtual machine to look for Conda information when loading new shells (as it does at the start of each step). There is also an added init powershell line. The differences start at the first line of Install dependencies when it becomes apparent that the shell being used is PowerShell instead of bash.
While the steps and the end results are the same, the implementation is fairly different.
CONDA PYTHON VERSION LIST WINDOWS
This action is a Windows implementation of the action above. count -exit-zero -max-complexity=10 -max-line-length=127 -statisticsĬ:\Miniconda\condabin\conda.bat install pytest count -select=E9,F63,F7,F82 -show-source -statisticsįlake8.
CONDA PYTHON VERSION LIST UPDATE
Windows ActionĬ:\Miniconda\condabin\conda.bat env update -file environment.yml -name baseĬ:\Miniconda\condabin\conda.bat init powershellĬ:\Miniconda\condabin\conda.bat activate baseĬ:\Miniconda\condabin\conda.bat install flake8įlake8. Since it’s discussed in depth in the first section, I’ll avoid going into too much detail here. It is also listed in the Github starter workflows directory as python-package-conda.
The action above is based off the python-package github action. If this were a normal machine you’d be able to call flake8 here without specifying a path.īecause Github Actions runners ignore shell profiles, you have to specify the path from the Conda directory instead.Īlternatively you can use shell: bash -l for the step which should make the path
CONDA PYTHON VERSION LIST FULL
The next line throws errors for specific code issues, then the following line runs the full linter to print any style issues. The first line installs flake8 into the base environment. This step runs the flake8 linter to check the python code in the directory. count -exit-zero -max-complexity=10 -max-line-length=127 -statistics # exit-zero treats all errors as warnings. count -select=E9,F63,F7,F82 -show-source -statistics # stop the build if there are Python syntax errors or undefined names Installing the environment’s packages into the base environment avoids this issue because it makes the packages available by default. Unfortunately, environment variables don’t persist between steps in a workflow, which breaks some things in Conda. Normally we’d use something like conda env create -f environment.yml to install an environment from a file. The CONDA environment variable is present in all environments to point to the Miniconda root directory for the virtual machine. This is also the first Conda specific step. Which shell is being run depends on the operating system for the job, though it can be specified manually with the shell keyword.īecause this action uses Ubuntu, the shell defaults to bash. The first thing to notice is the run keyword, which executes commands in a shell.
$CONDA/bin/conda env update -file environment.yml -name base # $CONDA is an environment variable pointing to the root of the miniconda directory This section lists explains the basic syntax of an action line by line. The only issue is that they don’t currently explain much of the syntax, they just refer you to templates or the full reference document.
The tl dr of it is that you add the file /.github/workflows/.yml to your repository.
CONDA PYTHON VERSION LIST HOW TO
If you’re unfamiliar with how to set up an action, start there. Github does a great job of explaining how to set up a starter workflow. If you are unfamiliar with continuous integration, or want a refresher, you may want to start here. Then it gives examples of how to use Github Actions to run tests on both Windows and Ubuntu virtual machines.įinally it discusses when and how to use actions from the marketplace instead of writing all of the logic yourself. There are several actions in the Marketplace that are designed to perform various tasks with Conda,īut Miniconda is already installed on Github Actions runners so they aren’t strictly necessary.įirst it explains the different parts of a Github Action and what they do. In particular, there are no tutorials of how to use Github Actions in repos that manager their dependencies with Conda environments. While it is nice to have a CI service in the same place as your code, there are fewer guides about how to use it than there are for more established services like Around a year ago Github released a continuous integration (CI) service called Github Actions.