Commit Graph

5 Commits

Author SHA1 Message Date
Deeman
4fae358f97 fix(extract,transform): fix COT/prices column name mismatches + OWM rate limit skip
- fct_cot_positioning: quote Swap__Positions_Short_All and Swap__Positions_Spread_All
  (CSV uses double underscore; DuckDB preserves header names exactly)
- fct_cot_positioning: quote Report_Date_as_YYYY-MM-DD (dashes preserved in header)
- fct_coffee_prices: quote "Adj Close" (space in CSV header)
- openmeteo/execute.py: skip API call in backfill when all daily files already exist
  (_count_existing_files pre-check prevents 429 rate limit on re-runs)
- dev_run.sh: open browser as admin@beanflows.coffee instead of pro@

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-26 09:46:34 +01:00
Deeman
08e74665bb feat(extract): add OpenWeatherMap daily weather extractor
Adds extract/openweathermap package with daily weather extraction for 8
coffee-growing regions (Brazil, Vietnam, Colombia, Ethiopia, Honduras,
Guatemala, Indonesia). Feeds crop stress signal for commodity sentiment score.

Extractor:
- OWM One Call API 3.0 / Day Summary — one JSON.gz per (location, date)
- extract_weather: daily, fetches yesterday + today (16 calls max)
- extract_weather_backfill: fills 2020-01-01 to yesterday, capped at 500
  calls/run with resume cursor '{location_id}:{date}' for crash safety
- Full idempotency via file existence check; state tracking via extract_core

SQLMesh:
- seeds.weather_locations (8 regions with lat/lon/variety)
- foundation.fct_weather_daily: INCREMENTAL_BY_TIME_RANGE, grain
  (location_id, observation_date), dedup via hash key, crop stress flags:
  is_frost (<2°C), is_heat_stress (>35°C), is_drought (<1mm), in_growing_season

Landing path: LANDING_DIR/weather/{location_id}/{year}/{date}.json.gz

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-25 22:40:27 +01:00
Deeman
c3c8333407 refactor(transform): remove raw layer, read landing zone directly
- Delete 6 data raw models (coffee_prices, cot_disaggregated, ice_*,
  psd_data) — pure read_csv passthroughs with no added value
- Move 3 PSD seed models raw/ → seeds/, rename schema raw.* → seeds.*
- Update staging.psdalldata__commodity: read_csv(@psd_glob()) directly,
  join seeds.psd_* instead of raw.psd_*
- Update 5 foundation models: inline read_csv() with src CTE, removing
  raw.* dependency (fct_coffee_prices, fct_cot_positioning, fct_ice_*)
- Remove fixture-based SQLMesh test that depended on raw.cot_disaggregated
  (unit tests incompatible with inline read_csv; integration run covers this)
- Update readme.md: 3-layer architecture (staging/foundation → serving)

Landing files are immutable and content-addressed — the landing directory
is the audit trail. A raw SQL layer duplicated file bytes into DuckDB
with no added value.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-22 17:30:18 +01:00
Deeman
2962bf5e3b Fix COT pipeline: TRY_CAST nulls, dim_commodity leading zeros, correct CFTC codes
- config.yaml: remove ambiguousorinvalidcolumn linter rule (false positives on read_csv TVFs)
- fct_cot_positioning: use TRY_CAST throughout — CFTC uses '.' as null in many columns
- raw/cot_disaggregated: add columns() declaration for 33 varchar cols
- dim_commodity: switch from SEED to FULL model with SQL VALUES to preserve leading zeros
  Pandas auto-converts '083' → 83 even with varchar column declarations in SEED models
- seeds/dim_commodity.csv: correct cftc_commodity_code from '083731' (contract market code)
  to '083' (3-digit CFTC commodity code); add CSV quoting
- test_cot_foundation.yaml: fix output key name, vars for time range, partial: true,
  and correct cftc_commodity_code to '083'
- analytics.py: COFFEE_CFTC_CODE '083731' → '083' to match actual data

Result: serving.cot_positioning has 685 rows (2013-01-08 to 2026-02-17), 23/23 tests pass.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 23:28:10 +01:00
Deeman
0a83b2cb74 Add CFTC COT data integration with foundation data model layer
- New extraction package (cftc_cot): downloads yearly Disaggregated Futures ZIPs
  from CFTC, etag-based dedup, dynamic inner filename discovery, gzip normalization
- SQLMesh 3-layer architecture: raw (technical) → foundation (business model) → serving (mart)
- dim_commodity seed: conformed dimension mapping USDA ↔ CFTC codes — the commodity ontology
- fct_cot_positioning: typed, deduplicated weekly positioning facts for all commodities
- obt_cot_positioning: Coffee C mart with COT Index (26w/52w), WoW delta, OI ratios
- Analytics functions + REST API endpoints: /commodities/<code>/positioning[/latest]
- Dashboard widget: Managed Money net, COT Index card, dual-axis Chart.js chart
- 23 passing tests (10 unit + 2 SQLMesh model + existing regression suite)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 23:28:10 +01:00