.. _development: Installation and Guide for Developers ================================================================================= This section describes how to install *eta_nexus* using *poetry* and how to contribute to development. Contributing to development ----------------------------- If you would like to contribute, please create an issue in the repository to discuss your suggestions. Once the general idea has been agreed upon, you can create a merge request from the issue and implement your changes there. If you are planning to develop on this package, based on the requirements of another package, you might want to import directly from a local git repository. To do this, uninstall eta_nexus from the other project's virtual environment and add the path to the local *eta_nexus* repository to the other project's main file: .. code-block:: sys.path.append("") .. _install_poetry: Installing Poetry -------------------- This project is being managed by `Poetry `_. It's a tool for Python dependency management and packaging. In order to install the development environment, you need to install Poetry first. Open a terminal for the next steps (such as PowerShell). .. note:: Depending on where the relevant folders for the installation are located on your OS, the terminal may need to be executed as administrator / root. It's recommended to install Poetry with pipx. This will install Poetry in an isolated environment. If you don't have pipx installed, you can install it with pip: .. code-block:: console $ python -m pip install pipx $ python -m pipx ensurepath Then install Poetry with pipx: .. code-block:: console $ pipx install poetry==2.1.2 .. note:: Poetry will initially use the Python version that it has been installed with. To change the Python version, see :ref:`managing_environments_poetry`. By default, Poetry will create its own virtual environment for each project. Only if there is already a virtual environment called ".venv" in the project folder, Poetry will use it. The virtual environments will be installed in: .. code-block:: none C:\Users\\AppData\Local\pypoetry\Cache\virtualenvs\ For more information, see the `Poetry documentation `_. Installation of eta_nexus ------------------------------------- First, clone the repository to a directory of your choosing. You can use a git GUI for this or execute the following command. .. code-block:: console $ git clone https://git.ptw.maschinenbau.tu-darmstadt.de/eta-fabrik/public/eta-nexus You might be asked for your git login credentials. .. figure:: figures/10_GitLogin.png :width: 300 :alt: git login Git login window. After this, navigate to the root directory **eta-nexus** .. code-block:: console $ cd eta-nexus \.. and install the project via poetry. This includes main and development dependencies: .. code-block:: console $ poetry sync .. note:: Updating the project dependencies is done with the same command. We use pre-commit to check code before committing. Therefore, after the installation completes, please install pre-commit before performing the first commits to the repository. This ensures that your commits will be checked and formatted automatically. .. code-block:: console $ poetry run pre-commit install .. figure:: figures/11_PreCommit.png :width: 600 :alt: pre-commit installed successfully Confirmation of correct pre-commit installation. .. note:: When using pre-commit for the first time, it will take longer as it will install all the hooks. | When using an IDE or code editor, make sure that it uses the virtual environment managed by Poetry. | For PyCharm, see: https://www.jetbrains.com/help/pycharm/poetry.html#poetry-env | For VS Code, see: https://code.visualstudio.com/docs/python/environments .. _managinv_environments_poetry: Managing Environments with Poetry ----------------------------------- You can run commands in the virtual environment by using the following command: .. code-block:: console $ poetry run To check which Python version Poetry is using and get the path of that environment, execute the following command: .. code-block:: console $ poetry env info You can change the Python version Poetry uses with: .. code-block:: console $ poetry env use Windows users can list available Python versions with: .. code-block:: console $ py -0p For *pyenv* users: ensure `python` points to your desired version, then: .. code-block:: console $ poetry env use python For more information, see the `Poetry docs `_. .. _testing_your_code: Testing your code ------------------------------- Please always execute the tests before committing changes. You can do this by navigating to the main folder of the *eta_nexus* repository and executing the following command in a terminal. .. code-block:: console $ poetry run pytest Or if you have the virtual environment already activated: .. code-block:: console $ pytest Running tests in parallel ^^^^^^^^^^^^^^^^^^^^^^^^^^ The test suite is configured to support parallel execution using `pytest-xdist `_. This significantly reduces test duration by distributing tests across multiple CPU cores. To run tests in parallel: .. code-block:: console $ pytest -n auto The ``-n auto`` option automatically detects the number of available CPU cores. You can also specify a fixed number of workers: .. code-block:: console $ pytest -n 4 For tests that require fixture isolation (e.g., server tests), use the ``loadscope`` distribution strategy: .. code-block:: console $ pytest -n logical --dist loadscope This is the configuration used in the CI/CD pipeline and ensures that tests with class or module-scoped fixtures are properly isolated. .. note:: Some tests that make real network requests may be slower or flakier when run in parallel. If you encounter issues, try running those tests sequentially or using the ``loadscope`` distribution. For more information, see the `pytest-xdist documentation `_. Measuring test coverage ^^^^^^^^^^^^^^^^^^^^^^^^ To measure code coverage, use `pytest-cov `_. The project has coverage configured in ``pyproject.toml``, so you can simply run: .. code-block:: console $ pytest --cov This generates a terminal summary and saves the coverage data to a ``.coverage`` file. To generate an HTML report from the saved coverage data: .. code-block:: console $ coverage html This creates an HTML coverage report in the ``htmlcov/`` directory. Open ``htmlcov/index.html`` in a browser to view detailed coverage information showing which lines of code are covered by tests. For a detailed terminal report: .. code-block:: console $ coverage report You can combine coverage with parallel execution: .. code-block:: console $ pytest -n auto --cov .. note:: The ``.coverage`` file persists between test runs. You can regenerate reports using ``coverage html`` or ``coverage report`` without re-running tests. For more coverage options, see the `pytest-cov documentation `_. Editing this documentation ----------------------------- Sphinx is used as a documentation-generator. The relevant files are located in the *docs* folder of the repository. If you correctly installed *eta_nexus* with the develop extension, sphinx should already be installed. You can edit the *.rst-files* in the *docs* folder. A simple text editor is sufficient for this. For test purposes, navigate to the *docs* folder and execute the following command: .. code-block:: console $ poetry run make html This creates a folder named *_build* (inside the *docs* folder) which allows the HTML pages to be previewed locally. This folder will not be committed to git. Re-execute this command each time you edit the documentation to see the changes (you may have to refresh the HTML page). If you have problems using sphinx see :ref:`sphinx_not_found`. GitLab - CI/CD -------------------------------------- Your contribution via pull request can only be merged if the steps from the CI/CD are approved. The stages are: - *check*: verify the check-style - *test*: check all tests - *deploy*: verify correct documentation deploy All the CI/CD instructions are listed in the *.gitlab-ci.yml* file. GitLab - Docker containers ----------------------------- The directory *.gitlab* contains the dockerfiles which define the images that the jobs of the CI/CD run on. Currently there are two main dockerfiles, one to describe Python-Julia environment and another just for Python. All the dockerfiles contain a corresponding image stored in **Packages & Registries > Container Registry**. In which the image will be used in a container to execute the jobs. To update the containers, first you need to log in to GitLab through docker. .. code-block:: console $ docker login git-reg.ptw.maschinenbau.tu-darmstadt.de Then you build and upload the image from the dockerfile. For example, for the pyjulia image use the following command inside the project folder: .. code-block:: console $ docker build -t git-reg.ptw.maschinenbau.tu-darmstadt.de/eta-fabrik/public/eta-nexus/pyjulia:py3.9-jl1.9 -f .gitlab/docker/pyjulia-39-19.dockerfile . Using tags for the images is a good practice to differentiate image versions, in case it's not used, it's automatically labeled as *latest*. Currently there are three images for Python environments called *python*, with Python versions differentiated by tags (py3.9, py3.10 and py3.11) and there is an image with combined Python and Julia installations. The last step is to upload the images to the private docker registry. .. code-block:: console $ docker push git-reg.ptw.maschinenbau.tu-darmstadt.de/eta-fabrik/public/eta-nexus/pyjulia:py3.9-jl1.9