Contribute

Overall guidance on contributing to a PyAnsys library appears in the Contributing topic in the PyAnsys Developer’s Guide. Ensure that you are thoroughly familiar with this guide before attempting to contribute to the grantami-bomanalytics repository.

The following contribution information is specific to the grantami-bomanalytics repository, which is for the PyGranta BoM Analytics library. This PyAnsys library name is often used in place of the repository name to provide clarity and improve readability.

Clone the source repository

Run the following code to clone and install the latest version of the grantami-bomanalytics repository. It installs the package in editable mode, which ensures changes to the code are immediately visible in the environment. It also installs the required development dependencies to run the tests.

git clone https://github.com/ansys/grantami-bomanalytics
cd grantami-bomanalytics
poetry install

Post issues

Use the Issues page for this repository to submit questions, report bugs, and request new features.

To reach the PyAnsys support team, email pyansys.support@ansys.com.

View PyGranta BoM Analytics documentation

Documentation for the latest stable release of PyGranta BoM Analytics is hosted at PyGranta BoM Analytics Documentation.

View examples

Examples are included in the documentation to give you more context around the core capabilities described in API reference. Additional examples are welcomed, especially if they cover a key use case of the package that has not yet been covered.

The example scripts are placed in the examples directory and are included in the documentation build if the environment variable BUILD_EXAMPLES is set to True. Otherwise, the building of examples is skipped and a placeholder page is inserted in the documentation.

Examples are authored using Jupyter notebooks, but they are converted into Python files before being checked in. As part of the doc build process, the Python files are converted back into Jupyter notebooks and are executed, which populates the output cells.

This conversion between Jupyter notebooks and Python files is performed by nb-convert. For installation instructions, see the nb-convert documentation.