Great Expectations Python Packages

great-expectations-cloud

Great Expectations Cloud

lakehouse-engine

The Lakehouse Engine is a configuration driven Spark framework, written in Python, serving as a scalable and distributed engine for several lakehouse algorithms, data flows and utilities for Data Products.

great-assertions

This library is inspired by the Great Expectations library. The library has made the various expectations found in Great Expectations available when using the inbuilt python unittest assertions.

koality

Library for data quality monitoring based on duckdb.

prefect-great-expectations

Prefect integrations for interacting with Great Expectations

dbt-gx

Run your dbt tests using Great Expectations as the execution engine!

dqbench

The standard benchmark for data quality tools — detection, transformation, entity resolution, and pipeline orchestration. 4 categories, 12 tiers, 161 tests.

correlator-ge

Accelerate Great Expectations incident resolution with automated correlation. Links validation failures to upstream data issues and provides direct navigation from incident to root cause.