[FR] Use pytest custom markers to target platform specific tests

[loomlike]

Willingness to contribute

Yes. I would be willing to contribute a fix for this bug with guidance from the Feathr community.

Feature Request Proposal

We may use custom markers such as "databricks", "synapse", "local" to specify target platform for platform-specific tests and run them for each github workflow.

Motivation

What is the use case for this feature?

Currently databricks and synapse test workflow run all the tests:

# under databricks_test section, 
pytest -n 6 feathr_project/test/

# under azure_synapse_test section
pytest -n 6 feathr_project/test/

Details

We may define custom markers, add at pyproject.toml like:

[tool.pytest.ini_options]
markers = [
    "databricks: test Databricks functions",
    "synapse: test Azure Synapse functions",
    "local :test Local Spark functions",
    "integration: test e2e"
]

Use it at pytest files:

@pytest.mark.databricks
def test_databricks_some_functions(...) {...}

@pytest.mark.databricks
@pytest.mark.integration
def test_databricks_e2e(...) {...}

And run them at github workflow:

# For PR-triggered tests
pytest -n 6 feathr_project/test/ -m "databricks and not integration"

# For nightly tests
pytest -n 6 feathr_project/test/ -m "databricks"

What component(s) does this feature request affect?

• [ ] Python Client: This is the client users use to interact with most of our API. Mostly written in Python.
• [ ] Computation Engine: The computation engine that execute the actual feature join and generation work. Mostly in Scala and Spark.
• [ ] Feature Registry API: The frontend API layer supports SQL, Purview(Atlas) as storage. The API layer is in Python(FAST API)
• [ ] Feature Registry Web UI: The Web UI for feature registry. Written in React