Complete pproject workflow, beginning with creation of the project and ending with release and documentation.


Customize the pproject-config-file located at ~/.config/pproject/pproject_config.yml. You should change the default company and the gitlab-settings for your own needs.

Make sure all your groups you want to use are in the following style:
We recommend something like:
ouroboros-products and ouroboros-modules

Also create a gitlab-token (if not already created) and insert the token inside the config-file. Run all steps as described in the configuration section in the pproject-documentation (everything will be much easier if you also enable pproject autoenv with pproject autoenv_toggle like described in this section).

Now all requirements are satisfied.


First you have to decide which kind of project you want to develop.

Now switch to the terminal and inside the folder where your project should be placed. Create the project with the pproject create command.


You want to create a product named dummy which uses python 3.6. You defined example as your companies name in the config-file. Then you would use the following command:

pproject create products -n dummy -v 3.6

You can also create projects connected with your gitlab-instance.


pproject create --remote products -n dummy -v 3.6

pproject collects the related skeleton for this python-version and replaces the template variables with the inputs and the settings as defined in the config-file. Then it creates resulting folder with combined contents and the base conda-environment for this project.

Update and autoenv

Now in terminal change to the created folder. In our example:

cd example-products-dummy

If you activated autoenv in your .bashrc/.zshrc the related conda-environment is activated automatically when entering the project-folder. Else you can set autoenv to be activated with:

pproject autoenv_toggle

You can also activate it manually with:

pproject autoenv

The conda-environment is activated.

List current environment content

You can list currently installed packages with:

conda list

Testing and developing

Now you should write the tests for your project using pytest inside the folder tests. Run them with:

pproject test

They will fail.

Edit your projects code at (rename YOUR_CODE.py to what you like):


Change the code until running the pproject test command succeed.

Dependency handling

Imagine you would need a third-party-package inside your project now. For example, numpy. Add the import to your code. Then add this dependency to the meta.yaml file at the requirements-run-section.

If autoenv is set, pproject detects changes in the meta.yaml (md5sum-comparison of hash.md5 and new md5sum of meta.yaml-file) and automatically trigger your environment to be recreated (using pproject update). This will remove your current environment and rebuild it with the new dependency list. Else (if autoenv is deactivated) you have to run the update manually running:

pproject update

resulting in the same result.

List the packages of the environment again with:

conda list

Now numpy is also listed to be installed in the environment.

Showing details of current project

Perhaps you would like to know some details about your current project at this point. In this time run:

pproject info project

This will list informations about your current project and the pproject-tool itself.

You can also list currrent pproject-configuration with:

pproject info global

Version control and tagging

Continue developing, testing and updating your project using the described commands yet.

Assume your project will be done at this point. Important: make sure all tests pass at this point.

Now add and commit your changes to git.

Lets say the resulting package should be the first major version of your package. Running:

pproject version -m "MESSAGE" major

This will tag your project with the version “1.0.0”.

Now your project is tested, your branch is up to date and also tagged.

We arrive at the final steps: building/releasing and documentation

Converting your project to a conda-package (Building)

You simply can create a conda-package from your project at this point with:

pproject build

This will build your package. Note that the package will only be available local cause it is stored in your local conda-build channel (/var/local/conda/conda-bld/linux-64).

You can either scp it to your conda-repository-server and update the index. scp to the servers conda-bld/linux-64 folder and run:

conda index .


Alternatively you can build the package and publish it there automatically running:

pproject build --publish

In both ways the package is available for you and your colleagues now.


Building a package is only possible if some checks are passed.

These tests are:
  • checking if all tests defined inside the tests-folder pass
  • checking if no uncommited stuff in branch
  • checking if current state is tagged
  • checking if current tag also pushed to origin

Only if these checks pass, the package will be build.

Releasing project (Rollout)

Assuming the package should also be released inside an own conda-environment as a conda-package on either localhost or another host (be sure to add your public ssh-key to the destination host before) you could also run:



pproject release -d localhost

This creates the envrionment PACKAGENAME_env on the destination with the package with all its dependencies in it. If the environment already exists on the destination it will be removed and recreated like using the pproject update command during developing.


For traceability reason releasing a package with pproject release stores information about when which user released what on the server.

These informations are stored inside ~/.pproject.log on the destination server.

The result looks like the following:

2018-03-24T12:49:59.432033 [ektom@gallifrey] CREATE ouroboros-testing-example_env [SOURCE: master 1.0.1]

Document your project

Finally you would like to create a documentation for your project. We support sphinx in this case. Simply run:

pproject sphinx

This will set up all requirements for the documentation assuming you added docstrings either in numpy- or google-documentation-style and creates the resulting html files inside the folder build.

Congratulation you successfully created your first project with pproject.

© Copyright 2018, Simon Kallfass.


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