- 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>
extract: wrap response.content in BytesIO before passing to
normalize_zipped_csv, and call .read() on the returned BytesIO before
write_bytes (two bugs: wrong type in, wrong type out)
sqlmesh: {{ var() }} inside SQL string literals is not substituted by
SQLMesh's Jinja (SQL parser treats them as opaque strings). Replace with
a @psd_glob() macro that evaluates LANDING_DIR at render time and returns
a quoted glob path string.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Remove distributed R2/Iceberg/SSH pipeline architecture in favor of
local subprocess execution with NVMe storage. Landing data backed up
to R2 via rclone timer.
- Strip Iceberg catalog, httpfs, boto3, paramiko, prefect, pyarrow
- Pipelines run via subprocess.run() with bounded timeouts
- Extract writes to {LANDING_DIR}/psd/{year}/{month}/{etag}.csv.gzip
- SQLMesh reads LANDING_DIR variable, writes to DUCKDB_PATH
- Delete unused provider stubs (ovh, scaleway, oracle)
- Add rclone systemd timer for R2 backup every 6h
- Update supervisor to run pipelines with env vars
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
## Key Changes
1. **Simplified extraction logic**
- Changed from downloading 220+ historical archives to checking only latest available month
- Tries current month and falls back up to 3 months (handles USDA publication lag)
- Architecture advisor insight: ETags naturally deduplicate, historical year/month structure was unnecessary
2. **Flat storage structure**
- Old: `data/{year}/{month}/{etag}.zip`
- New: `data/{etag}.zip` (local) or `psd/{etag}.zip` (R2)
- Migrated 226 existing files to flat structure
3. **Dual storage modes**
- **Local mode**: Downloads to local directory (development)
- **R2 mode**: Uploads to Cloudflare R2 (production)
- Mode determined by presence of R2 environment variables
- Added boto3 dependency for S3-compatible R2 API
4. **Updated raw SQLMesh model**
- Changed pattern from `**/*.zip` to `*.zip` to match flat structure
## Benefits
- Simpler: Single file check instead of 220+ URL attempts
- Efficient: ETag-based deduplication works naturally
- Flexible: Supports both local dev and production R2 storage
- Maintainable: Removed unnecessary complexity
## Testing
- ✅ Local extraction works and respects ETags
- ✅ Falls back correctly when current month unavailable
- ✅ Linting passes
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
