pallas 0.6

AWS Athena client

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.

• Performance – Large results are downloaded directly from S3, which is much faster than using Athena API.

• Pandas integration - Results can be converted to Pandas DataFrame with correct data types mapped automatically.

• Local caching – Query results can be cached locally, so no data have to be downloaded when a Jupyter notebook is restarted.

• Remote caching – Query IDs can be cached in S3, so team mates can reproduce results without incurring additional costs.

• Fixes malformed results returned by Athena to DCL (for example DESCRIBE) queries.

• 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

Documentation in the docs/ directory can be read online at Read the Docs.

Changelog

Changelog is the CHANGELOG.rst file. It is also available online in docs.

License

Copyright 2020 Akamai Technologies, Inc

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Contributing

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