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Information for developers

This page provides general information for developers who want to work on and contribute to the Airinnova Python packages.

1 Repository structure

All repositories have a standardised file structure which closely follows the structure proposed and described here:

Every repository contains commonly used folders:

  • src All source code related to the particular project. The src folder may contain subdirectories to distinguish between library code and executables.

    • lib Library code.
    • bin Executable files. On Linux such file would typically be found in /usr/bin.
  • docs Complete project documentation.

  • tests Complete set of test cases/code verification.

2 Dependencies

Every Python package may depend on external packages which are not part of the Python standard library. Additional packages are also required to build the documentation and to run the testing framework. All external dependencies are listed in a file called requirements.txt located in the repository root folder. All requirements may be simply installed with the Python package installer pip:

pip install -r requirements.txt

See also

Note It is highly recommended to develop each Python package in a separate virtual environment (see below).

3 Development environment

3.1 Version control

Git is used as the version control system and code is hosted on Github.

3.2 Virtual environments

It is highly recommended to develop each Python project in separate so-called virtual environment. A virtual environment basically provides a working environment which is separate from the system-wide Python/Python library installation. All dependencies pertinent to the particular package which is being developed can be installed into the respective virtual environment. For more information on virtual environments see:

4 Testing

4.1 PyTest

Test cases for each package can be found in the tests folder. We use the testing framework pytest which allows to set up test cases with relatively little effort. Test cases are defined in files which must be named test_*.py, so for instance test_some_feature.py. pytest will automatically locate these files and try to evaluate individual test cases. Each test case is defined in a function named test_*().

def test_function_xyz():
    assert always_true() is True

To check all test cases defined in a folder tests we can simply run pytest tests/. More information on pytest:

4.2 Tox

Tox is another tool related to testing. It can be used to bundle various tests defined in a file called tox.ini (root of project directory). See also:

4.3 Travis CI

Test cases defined with PyTest / Tox can be run locally. However, the code can also be tested automatically in the background using the continuous integration service Travis CI. If some test fails, it is possible to get notified with an email. The configuration file for Travis CI is called .travis.yml (root of project directory). See also:

Note Open-source projects are tested on travis-ci.org, not travis-ci.com.

4.4 Code coverage

When testing with pytest it is possible to create a report which shows which parts of the code base have been executed and which have not. This can be a help in identifying parts of the code base which are not yet tested. To generate a coverage report with pytest a plug-in called pytest-cov can be used. Coverage results can also be displayed nicely on Codecov.io.

Note The code coverage in percent is merely an indication of the testing status, but 100% test coverage does not imply that there are not any bugs.

5 Documentation

All documentation is included in the docs folder of the project. Documentation is built using the documentation generator Sphinx. The documentation is mainly written is RST (ReStructuredText). Documentation can be written manually, but API documentation can be generated automatically from Python docstrings.

The documentation can be converted into various format, e.g. PDFs or HTML websites. Project documentation can also be conveniently built and hosted on readthedocs.org.

6 Packaging and code deployment

A Python project can be packaged which makes it easy to install and distribute. Two files, namely setup.py and MANIFEST.in (optional), located in the project root folder define how the package should look like. These files must follow a certain format. If set up correctly, a package may be installed by simply running pip install . in the same directory where setup.py is located.

6.1 Python Package Index (PyPI)

Packaged Python projects can be distributed using the Python Package Index (PyPI). This makes it possible to install a Python package by simply running pip install pkg_name.

7 Miscellaneous

7.1 Licensing

It is good practice to include a license file (LICENSE.txt) in the project root folder. More information on licenses can be found here:

7.2 Code reuse

Some projects make use of some quite general, common routines. To avoid having copies of same functions in different projects, common routines have been factored out and namespaced in the CommonLibs package.

Just beware that changing the interface of functions may affect the packages that use CommonLibs.

7.3 CPACS and Anaconda

The use of CPACS requires two libraries developed by DLR, namely Tigl and Tixi. Unfortunately, these libraries are not available on the official Python Package Index (PyPI). Thus, they cannot be installed via the requirements.txt file. However, the DLR provided packages via Anaconda which creates its own environments separate from the standard Python virtual environments.

For testing and development, the use of Tigl and Tixi via Anaconda has proven itself to be the most reliable option. For testing on Travis CI, there is also a light-weight version of Anaconda called Miniconda.

Currently, only PyTornado uses Tigl and Tixi. See the file environment.yml (Anaconda environment definition analogous to requirements.txt).

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