At this month’s meetup, we:
Learned more about how to use GX with AWS S3 and Pandas for data validation
Heard about the v0.16 release, which includes the fluent method of configuring Datasources
Saw a demo of this new fluent way of configureing Datasources
And more!
You can watch the complete recording below:
The Great Expectations community gathers on the third Tuesday of every month: sign up here to join the next one.
Thanks and kudos
The GX community is a key part of our success!
Special recognition this month goes out to Richard O’Hara, Marcin Szymański, Carlos Iguaran, and Luke Dyer for their recent contributions!
[BUGFIX] Use Path().glob Instead of Path(). Issue #7239 (#7327) (thanks Richard O’Hara
[FEATURE] Improve Trino types support (#6588) (thanks Marcin Szymański)
[BUGFIX] Adding exception logging to store-related failures (#7202) (thanks Carlos Iguaran)
[BUGFIX] AssertError Duing GX Installation (#7285) (thanks Richard O’Hara)
[BUGFIX] Allow CLI to work with RuntimeDataConnector (#7187) (thanks Luke Dyer)
And big kudos to our top Slack supporters this month:
Feature demo: Using GX with AWS S3 and Pandas (part II)
Ruben, a developer advocate at GX, covered the second part of how to use our new set of end-to-end integration guides for AWS with a live demo. In today’s demo, Ruben walked us through how to profile data, validate data, and generate the Data Docs site with results in S3:
Product updates
v0.16 Release
GX’s product manager, Tal, shared what’s in this release: fluent-configuration Datasources!
Fluent-config Datasources will make it simpler to get started with GX by making it possible to set up a Datasource with just a couple of lines of code. Benefits include:
Usability improvements
Makes working with multiple batches easy
Building and contributing new Datasources is a pleasure
Compatibility with the current Datasources, no breaking changes
Feature demo: new fluent method of configuring Datasources
Next, Ruben was back to demo the new fluent method of configuring Datasources. He showed how you need just a few lines of code to get started. He shared his Jupyter Notebooks (file system, AWS S3), showing how simple it is to connect a Datasource. Once connected, you can create an expectation suite and add a validator, create a checkpoint and run it, and review the Data Docs. We’re very excited about this new feature and can’t wait for you to try it!
We’re especially interested in hearing about your experience with fluent-config Datasources! If you have thoughts you’d like to share or any questions, please contact @Tal in the GX Slack. Your feedback will be important in prioritizing future work on fluent-config Datasources.
Join the conversation
Aleksei Chumagin posted a tip about how to enable logging for GX in your project.
In honor of Pi Day, GX founders James and Abe debated the usefulness of the pie chart. Watch it here!
Veronica Moi shared that GX is on Bestlist’s “best of” list for data quality with Python!
Additional updates
Next month, we’re meeting on Tuesday, April 18, for another community meetup! Get the invite here.
Catch up on our API documentation improvements and new AWS integration guides…
…and don’t miss our back pocket guide to data quality.
Headed to Data Council? Enjoy a happy hour and an evening of tacos, beverages, networking, and fun! We’re excited to co-host along with Acryl Data and Astronomer.
Interested in learning more about Great Expectations Cloud? If you want to be one of the first to see what we’re building, please fill out this form, and we'll be in touch.
We’re hiring in engineering and developer relations! Check out our open roles.
Have you done something cool with GX that you'd like to share? If you're interested in demoing or have a piece of data quality content you'd like us to feature, DM @Josh Zheng on our Slack.
