Name: Great Expectations Labs
Type: Organization
Bio: Makers of the Great Expectations platform, revolutionizing the speed and integrity of data collaboration.
Twitter: expectgreatdata
Location: United States of America
Blog: https://greatexpectations.io/
Great Expectations Labs's Projects
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Test repo to run the GE Airflow operator with Astronomer
AWS ECR docker registry proxy. Anonymous proxy for AWS ECR
Cookiecutter template for a Python package.
Cooper Pair is a Python library to simplify programmatic access to the Allotrope GraphQL API.
pypi download stats for gx oss
dbt (data build tool) enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Auto-generated data documentation site for dbt projects
A CLI tool to help you run the fewest number of tests to ensure coverage over a given commit or PR.
A toy data project based on the collected works of Charles Dickens.
Simple demo with data + an expectation suite
Notebooks used for demonstrating and replicating Issues
CLI to simplify and automate parts of the OSS Great Expectations release process
Learn how to add data validation and documentation to a data pipeline built with dbt and Airflow.
WIP
Experimental Great Expectations docker
Minimal deployment of Great Expectations on lambda
Apache Superset (incubating) is a modern, enterprise-ready business intelligence web application
Testing Jupyter Binder, which allows notebooks to be interactive
Reference deployment of JupyterHub with docker
Test repo for experimental multibatch profiling
Create HTML profiling reports from pandas DataFrame objects
Load data from redshift into a pandas DataFrame and vice versa.
The easiest way to automate your data
How to write integration tests for data pipelines using Great Expectations and pytest.