Through the PyAnsys project, Ansys provides Python libraries that expose Ansys technologies to the Python ecosystem. These libraries are more than reusable scripts. They are clear, concise, and maintainable APIs and interfaces. Their useful functions, classes, and plugins eliminate the need to write scripts interfacing with low level APIs, allowing you to now interact with the product or service at a high level in an object-orientated manner.
These libraries play a vital role in:
Data manipulation and export
The libraries also include plugins and interfaces to the vast Python ecosystem. Examples include:
Arrays using NumPy
Data structures and tables with pandas
2D visualization using Matplotlib
3D visualization using PyVista
Advanced scientific computing using SciPy
Machine learning using TensorFlow
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Contributing to this guide#
If you would like to contribute to this development guide, maintainers gladly review your pull requests. Feel free to submit them, following the Documentation style.
This repository uses the pre-commit library to automate style checking. To use it, enter your Python environment and install it with:
pip install pre-commit
You can then run it manually with:
pre-commit run --all-files
This performs various style and spelling checks to ensure your contributions meet minimum coding style and documentation standards.
You can make sure that these checks are always run prior to
git commit by
installing a pre-commit as a git hook with:
Now, each time you run
git commit, your commit is only created if it
passes the minimum style checks that also run on the GitHub CI/CD.