MatGraphDB Docs!¶
MatGraphDB is a Python package designed to simplify graph-based data management and analysis in materials and molecular science. It enables researchers to efficiently transform complex theoretical data into structured graph representations, leveraging:
High-performance storage: Utilizes Apache Parquet for scalable and rapid data access.
Automated workflows: Converts theoretical and computational data into graph structures seamlessly.
Robust data operations: Offers comprehensive CRUD functionality and custom generators to maintain consistent relationships between entities.
By streamlining these processes, MatGraphDB makes advanced graph analysis more accessible, helping users model and predict material properties with ease.
Installation¶
If you’re new to MatGraphDB, you’re in the right place!
pip install matgraphdb
What Next?¶
Now that you have successfully installed MatGraphDB, here are some recommended next steps:
Tutorials Visit the Tutorials section for a hands-on tutorial covering the basics of creating, reading, and querying MatGraphDB files.
Learn the Inner Details Visit the MatGraphDB Internals section to dive deeper into MatGraphDB’s internals to understand how it wraps PyArrow, processes different data types, and performs efficient read/write operations.
Example Gallery Visit the Example Gallery section real use cases of MatGraphDB.
Explore PyArrow MatGraphDB relies on PyArrow for powerful data type handling and filtering mechanisms. For more in-depth information on PyArrow’s Table structure, filtering, and other features, refer to the PyArrow Documentation.
Citing MatGraphDB¶
To be added.