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Astromol

screenshot of Astromol

Github

Overview

Astromol is an innovative Python 3 package specifically designed for astrophysics enthusiasts and researchers interested in the study of molecules detected in space. This database arises from the extensive Census of Interstellar, Circumstellar, Extragalactic, Protoplanetary Disk, and Exoplanetary Molecules compiled by B. McGuire, and it provides not only a comprehensive collection of data but also an object-oriented interface for easy interaction. The intention of Astromol is to facilitate research and exploration in space chemistry, making it a valuable tool for scientists and hobbyists alike.

The package emphasizes accessibility and usability, allowing users to generate figures and tables that are crucial for their astronomical work. With a straightforward setup process and easy access to a wealth of data, Astromol stands out as a unique contribution to the field of astrochemistry.

Features

  • Comprehensive Database: Contains a rich collection of molecules detected in various astronomical settings, catering to a wide range of research needs.

  • Object-Oriented Interface: This design allows users to interact with the database easily, making manipulation of the dataset intuitive and flexible.

  • Version Control System: The package follows a detailed versioning format ensuring users are aware of updates to molecules and the codebase, providing clarity on the changes.

  • Customizable Outputs: Users can generate specific figures and tables tailored to their research, although they remain primarily designed around the Census paper.

  • Easy Installation and Updates: The use of symlinks during installation enables effortless updates to the package without requiring frequent reinstallation.

  • Preloaded Information: The import feature loads all relevant information directly into your Python session, streamlining the research process.

  • Structured Data Classes: Data is categorized into Molecule, Telescope, or Source classes, facilitating organized access to information.

  • Regular Updates: The package is maintained with regular updates to ensure data relevancy and inclusion of new findings in the field.