feat: BigQuery loading and GCS integration for Python pipeline

[Copilot]

• Implement GCS storage client (src/a4d/gcp/storage.py)
• Implement BigQuery loading client (src/a4d/gcp/bigquery.py)
• Update src/a4d/gcp/__init__.py with re-exports and __all__
• Add upload-tables, download-trackers, upload-output CLI commands
• Add 18 unit tests for GCP modules (all mocked, all passing)
• Update .env.example with GCP authentication documentation
• Fix all 109 ruff linter warnings across the entire codebase (0 remaining)
• All 239 tests passing

Original prompt

wir sind in der Mitte einer Migration von R zu Python. eigentlich testen wir gerade noch aber das ist gerade ohne Daten nicht möglich. daher würde ich gerne die nächsten Schritte planen und die Pipeline fertigstellen. wir müssten bereits die Tabellen erstellt haben, das nächste Ziel wäre also die Daten nach Big Query zu laden und die Pipeline dann auch Mal in Google cloud zu testen, was wäre dafür notwendig bzw welche Dienste müssten aufgesetzt werden?

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[pmayd]

We also need to check and allow running the pipeline locally as well as within GCP, so locally we need to somehow authenticate against GCP I guess and when running inside a container on GCP I guess the tools like gcloud are already available but this needs to be considered when writing the client code for Google storage and big Query

[pmayd]

I allowed astral.sh for agents, you can try again @copilot

[Copilot]

Pull request overview

This PR implements GCP integration for the Python pipeline migration, enabling BigQuery table loading and Google Cloud Storage operations that were previously handled by R scripts using CLI tools (bq and gsutil).

Changes:

• Added a4d.gcp.bigquery module with table loading functions and clustering configurations matching the R pipeline
• Added a4d.gcp.storage module for downloading tracker files and uploading pipeline output to GCS
• Added three new CLI commands: upload-tables, download-trackers, and upload-output

Reviewed changes

Copilot reviewed 7 out of 8 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
src/a4d/gcp/bigquery.py	Implements BigQuery table loading with clustering configs for patient_data_monthly, patient_data_annual, patient_data_static, and logs tables
src/a4d/gcp/storage.py	Implements GCS operations for downloading tracker files and uploading pipeline output
src/a4d/gcp/__init__.py	Exports public API for the GCP module
src/a4d/cli.py	Adds three new commands for BigQuery upload and GCS interactions
.env.example	Documents GCP authentication options using Application Default Credentials
tests/test_gcp/test_bigquery.py	18 unit tests covering table loading, clustering configs, and error handling
tests/test_gcp/test_storage.py	Tests for GCS download/upload with mocked clients
tests/test_gcp/__init__.py	Empty init file for test package

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[pmayd]

Fix the ci errors, tests will fail for now but fix the ruff linter warnings

[pmayd]

@copilot Fix the ci errors, tests will fail for now but fix the ruff linter warnings

[Copilot]

@copilot Fix the ci errors, tests will fail for now but fix the ruff linter warnings

Fixed all 109 ruff linting errors in commit ac2fa23. This includes:

• 46 E501 (line too long) - wrapped comments, f-strings, and docstrings; added # noqa: E501 for file path literals in scripts/
• Auto-fixed UP035, F841, I001, PT006, B007, PT018 via ruff --fix
• 3 N806 (variable naming) - renamed uppercase variables to lowercase inside functions
• 2 B904 (raise from) - added from e to raise statements in except blocks

All 239 tests pass, 0 ruff errors remain.

We also need to check and allow running the pipeline locally as well as within GCP, so locally we need to somehow authenticate against GCP I guess and when running inside a container on GCP I guess th...

The GCP client code (gcp/bigquery.py and gcp/storage.py) already uses Application Default Credentials (ADC), which handles both scenarios:

• Locally: Authenticate with gcloud auth application-default login - no service account key file needed
• In GCP (Cloud Run/GCE): Authentication is automatic via the metadata server - no extra setup
• CI/CD or VMs: Set GOOGLE_APPLICATION_CREDENTIALS=/path/to/key.json environment variable

The .env.example documents these options. No gcloud CLI is needed at runtime - the Python client libraries (google-cloud-bigquery, google-cloud-storage) handle auth natively through ADC.