Following sets of tests:
- Open source MLflow tests.
- Launches a source and destination tracking server and then runs tests to ensure that the exported MLflow objects (runs, experiments and registered models) are correctly imported.
- Numerous tests - 100+.
- Databricks tests.
- Remote tests using the Databricks MLflow REST API.
- WIP.
- Databricks MLflow notebook tests.
- Simple smoke tests for Databricks notebooks. Launches Databricks jobs to ensure that Databricks export-import notebooks execute properly.
pip install -e ..[tests] --upgrade
The test script creates the folowing files:
- run_tests.log - log of the entire test run.
- run_tests_junit.xml - report for all tests in standard JUnit XML format.
- run_tests_report.html - report for all tests in HTML format.
Sample reports
Open Source Tests:
Databricks Tests:
Failed Databricks Tests: