feat(datasource): implement get_dataframe_by_tag for drift metric reference data

[SudipSinha]

Summary

All drift metric endpoints call data_source.get_dataframe_by_tag(model_id, reference_tag) to retrieve reference data, but the method doesn't exist on DataSource. Every drift computation fails with AttributeError and HTTP 500.

Root cause

The drift endpoints were written to call get_dataframe_by_tag (matching the Java service's filterRowsByTagEquals pattern), but the method was never implemented on the Python DataSource class.

How it works

The method reads all stored data for a model, then filters rows by tag:

1. Read input data and metadata via ModelData.data()
2. Find the tags column in metadata (column index 3, contains list[str] per row)
3. Build a boolean mask: tag in row_tags for each row
4. Apply the mask to the input data array
5. Return a pandas DataFrame with input columns only

Returns input columns only because drift metrics iterate over request.fit_columns (input feature names) and access reference_df[feature_name].

Reads all rows (no batch size) because reference data tagged e.g. "TRAINING" could be anywhere in the dataset, not just the last N rows.

Handles numpy arrays from column_names() — ModelData.column_names() returns numpy arrays, not Python lists. The implementation converts to list() before calling .index("tags") to avoid AttributeError. Test mocks use np.array() to match the real return type and catch this class of bug.

Files changed

File	Change
src/service/data/datasources/data_source.py	Add get_dataframe_by_tag method
tests/service/data/datasources/test_datasource.py	3 tests: matching rows, non-existent tag, missing data (mocks use numpy arrays)

Test plan

• All 24 datasource tests pass (3 new)
• Test mocks use np.array() for column_names() return values, matching real ModelData behavior
• ruff check clean
• ruff format clean
• pyrefly check clean
• Rebuild container image and verify drift metric computation succeeds with tagged reference data

🤖 Generated with Claude Code

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ℹ️ Review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

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Run ID: df0f7ded-78ac-4b65-8ec4-fa6441353484

📥 Commits

Reviewing files that changed from the base of the PR and between eeca7e6 and bd48cc2.

📒 Files selected for processing (2)

• src/service/data/datasources/data_source.py
• tests/service/data/datasources/test_datasource.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch fix/missing-get-dataframe-by-tag

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[github-actions]

PR image build and manifest generation completed successfully!

📦 PR image: quay.io/trustyai/trustyai-service-python-ci:bd48cc2ceed2620c6cc32cec7de2576227246d04

🗂️ CI manifests

devFlags:
  manifests:
    - contextDir: config
      sourcePath: ''
      uri: https://api.github.com/repos/trustyai-explainability/trustyai-service-operator-ci/tarball/service-python-bd48cc2ceed2620c6cc32cec7de2576227246d04

[RobGeada]

Is there no need to get output_data here?