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.
Documentation in the docs/
directory can be read online at Read the Docs.
Changelog is the CHANGELOG.rst
file. It is also available online in docs.
Copyright 2020 Akamai Technologies, Inc
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you may not use this file except in compliance with the License.
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