Tested full refresh pipeline end-to-end with real Snowflake data:
- Fixed trust filter to read Name column from defaultTrusts.csv
- Fixed Decimal type handling in calculate_cost_per_patient_per_annum
- Fixed array handling in convert_to_records for average_administered
- Added required reference CSV files to data/ directory
- Configured Snowflake connection (account, warehouse, user)
Results:
- Snowflake fetch: 656,695 records in ~7s
- Transformations: 519,848 records after UPID/drug/directory
- Pathway nodes: 293 for all_6mo (8 trusts, 14 directories)
- Total processing time: ~6.2 minutes
Add cli/refresh_pathways.py with:
- refresh_pathways() main function for full pipeline orchestration
- insert_pathway_records() for SQLite insertion
- log_refresh_start/complete/failed() for refresh tracking
- CLI with --minimum-patients, --provider-codes, --dry-run, --verbose
Uses existing pipeline functions:
- fetch_and_transform_data() from pathway_pipeline.py
- process_all_date_filters() for 6 date filter combinations
- Schema helpers from data_processing/schema.py
Andrew Charlwood