C2W4 Assignment 4: DAG Import Errors in Airflow

[oemfitment]

It seems like there is an issue with the great expectations package/library in the Airflow environment. Is this an issue on my end or the Airflow Environment?

[TheHappyIrishman]

Hello, having this same issue. I have tried importing great_expectations_provider with pip but it just returns this.

I have the lab completed other than this issue so hoping someone reaches out soon. Thanks.

[juliak]

@TheHappyIrishman
pip install airflow-provider-great-expectations

[jeanleeb]

In my case, checking the Airflow providers showed that the airflow-provider-great-expectations was v1.0.0, which no longer has the GreatExpectationsOperator…

Migrating to v1.0.0 compatibility fixed the DAG import errors: Migration guide - Great Expectations Airflow Provider

[gael.blf]

Still seeing this issue as of Feb 16, 2026.

It seems like the Airflow instance might have airflow-provider-great-expectations v1.0.0 installed, which would no longer include the GreatExpectationsOperator used in the lab code — hence the ModuleNotFoundError on all three DAGs.

Possible fixes could include:

• Pinning the provider to v0.2.7 on the Airflow instance
• Migrating the lab code to use the v1.0.0 API (GXValidateDataFrameOperator)

This has been reported for over two weeks now. It would be really appreciated if the team could take a look — the lab grader passes without the DAGs actually running, which kind of defeats the purpose of the assignment. Would be great to get this fixed so students can actually see the pipeline work end to end.

Generated by Claude, after I tried to fix this myself and gave up after way too many wasted minutes.

[juliak]

Thank you, @gael.blf and @jeanleeb !
I forwarded this issue to the tech team.

[juliak]

@gael.blf I was able to reproduce the issue and agree with your suggested solution. Thank you for digging into this! The tech team is aware of the mismatch, so hopefully we’ll see an update to the lab soon.

[TheHappyIrishman]

I took some time to focus on some of my other courses. (I’m doing some pre-reqs to pursue a masters) Now my AWS is broken and not working on this lab when I attempt to open it to see if any progress has been made. Airflow just goes here. Is there a way to return to factory settings, wondering if I messed something up in my attempts to version control the lab myself.

[magdalena.bouza]

Hey @oemfitment @TheHappyIrishman @jeanleeb @gael.blf @juliak . Thanks for reporting this issue and looking into possible solutions.
The lab is now fixed, having updated the code to work on v1.0.0

[jeanleeb]

Thank you!