Technical Details

Dependencies and Platforms

PyPEEC is entirely programmed in Python 3 and has the following dependencies:

• SciLogger, SciSave, and jsonschema (logging and serialization)

• NumPy, SciPy, and Joblib (basic numerical computing libraries)

• Shapely and Rasterio (only used for the mesher, 2D shape manipulation)

• Pillow (only used for the mesher, 2D image manipulation)

• VTK and PyVista (only used for for the mesher, 3D shape manipulation)

Additionally, the following libraries are used for the plotter and viewer:

• Matplotlib and QtPy (2D plots)

• VTK, PyVista, PyVistaQt, and QtPy (3D plots)

The following optional packages can be used for speeding up the solver:

• PyAMG (Python Algebraic Multigrid)

• MKL/FFT (available through mkl_fft)

• MKL/PARDISO (available through Pydiso)

• FFTW (available through pyFFTW)

• CuPy (using GPUs through CUDA)

The following optional packages are required for Jupyter notebooks:

• JupyterLab

• IPyWidgets

• Trame / ipympl

PyPEEC is known to work with the following platforms:

• Linux on x86/x64/X11/glibc

• Apple macOS on x86/x64

• Apple macOS on ARM64

• MS Windows on x86/x64

Some more details on the supported platforms:

• The main target platform of PyPEEC is Linux on x86/x64/X11/glibc.

• PyPEEC is a pure-python package and should work on any platform.

• Compatible Python versions: 3.10, 3.11, 3.12, and 3.13

• Any CUDA and CuPy compatible GPU is supported.

Logger and Data Serialization

For the logging, PyPEEC is using SciLogger:

• The logger configuration files can be set with the SCILOGGER environment variable.

• More information on the logging module: https://github.com/otvam/scilogger

For the serialization, PyPEEC is using SciSave:

• The input/configuration files are either JSON or YAML files.

• The output/data files are either JSON or Pickle files.

• Pickle is faster than JSON for large output/data files.

• More information on the serialization module: https://github.com/otvam/scisave

Packaging and Environment

The following files are describing the packages and dependencies:

• Definition of the Python package: pyproject.toml

• Dockerfile for building the Docker image: Dockerfile

• Conda feedstock recipe: https://github.com/conda-forge/pypeec-feedstock

The development environment is defined in conda.yaml:

• Contains all the required and optional dependencies.

• Contains the packaging/development tools.

• All the version number are pinned.

• Tested with Linux x86/x64/X11/glibc.

The following scripts are used for the packaging and releasing processes:

• scripts/run_clean.sh: clean the all the autogenerated and temporary data.

• scripts/run_build.sh: build the Python package and build the HTML documentation.

• scripts/run_release.sh: create a release (tag, release, package, and documentation).

Tests and Coverage

PyPEEC is using different tests to check for potential regressions:

• The tests are located in the tests folder.

• The tests are using the unittest framework.

• The tests are covering all the main functionalities.

• The tests are using the examples and the tutorial to check the code.

• Only integration tests are currently implemented (no unit tests).

These files are used to run the code quality checks and the tests:

• scripts/run_ruff.sh: run the code quality checks.

• scripts/run_tests.sh: run all the integration tests.

• scripts/run_coverage.sh: run a code coverage analysis.

The following automated tests are performed:

• Test the latest version of the released Conda and PyPI pakages

• Test the Conda and PyPI environments with the current Git code

The following platforms are considered for the automated tests:

• Linux / Ubuntu on x86/x64

• Microsoft / Windows on x86/x64

• Apple / macOS on ARM64

The following Python versions are considered for the automated tests:

• CPython 3.10

• CPython 3.11

• CPython 3.12

• CPython 3.13

Contributing and Bug Report

PyPEEC is gladly accepting contributions (code, benchmark, packages, or tests). Non-code contributions (documentation, examples, or tutorials) are particularly welcomed. For large contributions, please first discuss the changes in the issue tracker.

For the bug reports, please report the following information:

• The version of PyPEEC and Python.

• The operating system/platform/hardware.

• A clear and concise description of the bug.

• A minimal working example for the bug.

• For PyVista related bugs, please include the pyvista.Report output.

• For NumPy related bugs, please include the numpy.show_config output.

• For SciPy related bugs, please include the scipy.show_config output.