A Cookiecutter template for creating Python packages in computational molecular sciences with pre-configured CI, testing, and documentation.
MolSSI Cookiecutter CMS is a template generator for creating Python packages in computational molecular sciences. It automates the setup of project structure, continuous integration, testing, and documentation, allowing researchers to quickly start developing scientific software. The template includes modern Python packaging tools and cross-platform CI/CD workflows tailored for scientific computing needs.
Computational chemists, molecular scientists, and Python developers building research software in fields like quantum chemistry, molecular dynamics, or cheminformatics. It's ideal for academic labs, research institutions, and open-source scientific projects.
Developers choose this template because it provides domain-specific defaults for scientific Python packages, reduces initial setup time from days to minutes, and incorporates best practices from the molecular sciences community. Unlike generic cookiecutters, it includes specialized features like Conda environment management, scientific testing patterns, and integration with computational chemistry ecosystems.
Python-centric Cookiecutter for Molecular Computational Chemistry Packages
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Tailors defaults for computational molecular sciences, including Conda environment management and scientific testing patterns, reducing setup time from days to minutes.
Uses pyproject.toml and setup.cfg for PEP 517/518 compliance, ensuring up-to-date Python packaging standards without legacy setup.py files.
Pre-configures GitHub Actions for Linux, macOS, and Windows with support for both Conda and pip, facilitating robust testing across environments.
Integrates Versioningit to automatically generate version strings from Git tags, simplifying release management and reducing manual errors.
The README admits generated GitHub Actions cannot be fully tested in real-time due to GitHub constraints, relying on reference comparisons that might miss edge cases.
Includes niche features for molecular sciences, such as Conda build files and scientific data packaging, adding unnecessary overhead for general Python projects.
Requires pre-installed Cookiecutter and Git, adding extra steps before project generation compared to simpler CLI tools or templates.