Ibis: Python Data Analysis Productivity Framework
Ibis is a toolbox to bridge the gap between local Python environments (like pandas and scikit-learn) and remote storage and execution systems like Hadoop components (like HDFS, Impala, Hive, Spark) and SQL databases (Postgres, etc.). Its goal is to simplify analytical workflows and make you more productive.
We have a handful of specific priority focus areas:
- Enable data analysts to translate local, single-node data idioms to scalable computation representations (e.g. SQL or Spark)
- Integration with pandas and other Python data ecosystem components
- Provide high level analytics APIs and workflow tools to enhance productivity and streamline common or tedious tasks.
- Integration with community standard data formats (e.g. Parquet and Avro)
- Abstract away database-specific SQL differences
As the Apache Arrow project develops, we will look to use Arrow to enable computational code written in Python to be executed natively within other systems like Apache Spark and Apache Impala (incubating).
Source code is on GitHub: https://github.com/ibis-project/ibis.