- 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>
- serving/ice_aging_stocks.sql: pass-through from foundation, parses age
bucket string to start/end days ints for correct sort order
- serving/ice_warehouse_stocks_by_port.sql: monthly by-port since 1996,
adds MoM change, MoM %, 12-month rolling average
- analytics.py: get_ice_aging_latest(), get_ice_aging_trend(),
get_ice_stocks_by_port_trend(), get_ice_stocks_by_port_latest()
- api/routes.py: GET /commodities/<code>/stocks/aging and
GET /commodities/<code>/stocks/by-port with auth + rate limiting
- dashboard/routes.py: add 3 new queries to asyncio.gather(), pass to template
- index.html: aging stacked bar chart (age buckets × port) with 4 metric
cards; by-port stacked area chart (30-year history) with 4 metric cards
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Replace brittle ICE_STOCKS_URL env var with API-based URL discovery via
the private ICE Report Center JSON API (no auth required)
- Add rolling CSV → XLS fallback in extract_ice_stocks() using
find_latest_report() from ice_api.py
- Add ice_api.py: fetch_report_listings(), find_latest_report() with
pagination up to MAX_API_PAGES
- Add xls_parse.py: detect_file_format() (magic bytes), xls_to_rows()
using xlrd for OLE2/BIFF XLS files
- Add extract_ice_aging(): monthly certified stock aging report by
age bucket × port → ice_aging/ landing dir
- Add extract_ice_historical(): 30-year EOM by-port stocks from static
ICE URL → ice_stocks_by_port/ landing dir
- Add xlrd>=2.0.1 (parse XLS), xlwt>=1.3.0 (dev, test fixtures)
- Add SQLMesh raw + foundation models for both new datasets
- Add ice_aging_glob(), ice_stocks_by_port_glob() macros
- Add extract_ice_aging + extract_ice_historical pipeline entries
- Add 12 unit tests (format detection, XLS roundtrip, API mock, CSV output)
Seed files (data/landing/ice_aging/seed/ and ice_stocks_by_port/seed/)
must be created locally — data/ is gitignored.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- 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>
