Welcome to Great Expectations.
Always know what to expect from your data
What is great_expectations?
Great Expectations helps teams save time and promote analytic integrity by offering a unique approach to automated testing: pipeline tests. Pipeline tests are applied to data (instead of code) and at batch time (instead of compile or deploy time). Pipeline tests are like unit tests for datasets: they help you guard against upstream data changes and monitor data quality.
Software developers have long known that automated testing is essential for managing complex codebases. Great Expectations brings the same discipline, confidence, and acceleration to data science and engineering teams.
How do I get started?
It is super easy...
Just use pip install:
$ pip install great_expectationsYou can also clone the repository, which includes examples of using great_expectations.
$ git clone https://github.com/great-expectations/great_expectations.git
$ pip install great_expectations/Learn it live with us!
To make this project more accessible to all data practitioners, we are looking for user testers to help make the onboarding experience better! If you are new to Great Expectations, in return for your time we’d love to help you get up and running!
Schedule a 1 hr session here!Great Expectations users are enjoying their experience.
We dont' like to brag, but we don't mind letting the Great Expectations user base do it for us. Here are a few nice things folks have said about GE.
"Now that we're using Great Expectations we get notified ahead of time when data does not look right, giving us time to investigate and alert data users before they find out themselves"
Join our community!
Start a converstation on Slack
We are very active on Slack. This is the best way to quickly get help from us and to be in on all the new improvements and features before anyone else.
Join Slack!
Be a part of the discussion
We learn a lot our conversations with users on slack so we made a place to share what we’ve learned! Join us on our discussion platform to see how our users incorporate GE into their data stack and everything else the GE crowd is chatting about.
Join Discuss!
Be a contributor!
We are very lucky to have an active community of contributors who are finding ways to improve GE for all sorts of use cases. Jump into our github issues or make a PR and become a part of our contributor community.
Check out our Github!Still want more?
Watch our walkthroughs
For a quick, hands-on introductions to Great Expectations' key features, check out our walkthrough videos: Introduction to Great Expectations and Using Distributional Expectations
Read our core philoshophy
Read Down with Pipeline Debt! explains the core philosophy behind Great Expectations. Please give it a read, and clap, follow, and share while you're at it.
Read about a new feature!
One of our engineers just wrote an awesome blog teaching you how to build a self-updating data dictionary by extending Great Expectations' data dictionary (a new shiny feature)
Read about it!