p-pattern 2026.4

Parametric patterns/shapes definition and sampling

Documentation

The documentation is available at https://src.koda.cnrs.fr/eric.debreuve/p-pattern/-/wikis/home.

Installation

This project is published on the Python Package Index (PyPI) at: https://pypi.org/project/p-pattern/. It should be installable from Python distribution platforms or Integrated Development Environments (IDEs). Otherwise, it can be installed from a command console using pip:

	For all users (after acquiring administrative rights)	For the current user (no administrative rights required)
Installation	pip install p-pattern	pip install --user p-pattern
Update	pip install --upgrade p-pattern	pip install --user --upgrade p-pattern

Dependencies

The development relies on several packages:

• Mandatory: logger-36, numpy, scikit-image, scipy

• Optional: None

The mandatory dependencies, if any, are installed automatically by pip, if they are not already, as part of the installation of p-pattern. Python distribution platforms or Integrated Development Environments (IDEs) should also take care of this. The optional dependencies, if any, must be installed independently by following the related instructions, for added functionalities of p-pattern.

Packaging

Missing files for packaging the project from source (notably, documentation/wiki/description.asciidoc, README-template.rst, pyproject.toml, and setup.py) can be found on the Python package template repository and as part of the documentation wiki.

Acknowledgments

The project is developed with PyCharm Community.

The code is formatted by Black, The Uncompromising Code Formatter, or Ruff, An extremely fast Python linter and code formatter, written in Rust.

The imports are ordered by isort… your imports, so you don’t have to, or Ruff, An extremely fast Python linter and code formatter, written in Rust.