Pallas documentation

Pallas makes querying AWS Athena easy.

It is especially valuable for analyses in Jupyter Notebook, but it is designed to be generic and usable in any application.

Main features:

  • Friendly interface to AWS Athena.

  • Caching - local and remote cache for reproducible results.

  • Performance – Large results are downloaded from S3.

  • Pandas integration - Conversion to DataFrame with appropriate dtypes.

  • Optional white space normalization for better caching.

  • Kills queries on KeyboardInterrupt.

import pallas
athena = pallas.environ_setup()
df = athena.execute("SELECT 'Hello world!'").to_df()

Pallas is hosted at GitHub and it can be installed from PyPI.

This documentation is available online at Read the Docs.