- extract/cftc_cot: refactor extract_cot_year() to accept url_template and
landing_subdir params; add _extract_cot() shared loop; add extract_cot_combined()
entry point using com_disagg_txt_{year}.zip → landing/cot_combined/
- pyproject.toml: add extract_cot_combined script entry point
- macros/__init__.py: add @cot_combined_glob() for cot_combined/**/*.csv.gzip
- fct_cot_positioning.sql: union cot_glob and cot_combined_glob in src CTE;
add report_type column (FutOnly_or_Combined) to cast_and_clean + deduplicated;
include FutOnly_or_Combined in hkey to avoid key collisions; add report_type to grain
- obt_cot_positioning.sql: add report_type = 'FutOnly' filter to preserve
existing serving behavior
- obt_cot_positioning_combined.sql: new serving model filtered to report_type =
'Combined'; identical analytics (COT index, net %, windows) on combined data
- pipelines.py: register extract_cot_combined; add to extract_all meta-pipeline
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
secrets.py: replace Pulumi ESC (esc CLI) with SOPS decrypt. Reads
.env.prod.sops via `sops --decrypt`, parses dotenv output. Same public
API: get_secret(), list_secrets(), test_connection().
cli.py: update secrets subcommand help text and test command messaging.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
Two bugs fixed:
1. Cross-connection COPY: DuckDB doesn't support referencing another
connection's tables as src.serving.table. Replace with Arrow as
intermediate: src reads to Arrow, dst.register() + CREATE TABLE.
2. Catalog/schema name collision: naming the export file serving.duckdb
made DuckDB assign catalog name "serving" — same as the schema we
create inside it. Every serving.table query became ambiguous. Rename
to analytics.duckdb (catalog "analytics", schema "serving" = no clash).
SERVING_DUCKDB_PATH values updated: serving.duckdb → analytics.duckdb
in supervisor, service, bootstrap, dev_run.sh, .env.example, docker-compose.
3. Temp file: use _export.duckdb (not serving.duckdb.tmp) to avoid
the same catalog collision during the write phase.
Verified: 6 tables exported, serving.* queries work read-only.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Split the single lakehouse.duckdb into two files to eliminate the exclusive
write-lock conflict between SQLMesh (pipeline) and the Quart web app (reader):
lakehouse.duckdb — SQLMesh exclusive (all pipeline layers)
serving.duckdb — web app reads (serving tables only, atomically swapped)
Changes:
web/src/beanflows/analytics.py
- Replace persistent global _conn with per-thread connections (threading.local)
- Add _get_conn(): opens read_only=True on first call per thread, reopens
automatically on inode change (~1μs os.stat) to pick up atomic file swaps
- Switch env var from DUCKDB_PATH → SERVING_DUCKDB_PATH
- Add module docstring documenting architecture + DuckLake migration path
web/src/beanflows/app.py
- Startup check: use SERVING_DUCKDB_PATH
- Health check: use _db_path instead of _conn
src/materia/export_serving.py (new)
- Reads all serving.* tables from lakehouse.duckdb (read_only)
- Writes to serving_new.duckdb, then os.rename → serving.duckdb (atomic)
- ~50 lines; runs after each SQLMesh transform
src/materia/pipelines.py
- Add export_serving pipeline entry (uv run python -c ...)
infra/supervisor/supervisor.sh
- Add SERVING_DUCKDB_PATH env var comment
- Add export step: uv run materia pipeline run export_serving
infra/supervisor/materia-supervisor.service
- Add Environment=SERVING_DUCKDB_PATH=/data/materia/serving.duckdb
infra/bootstrap_supervisor.sh
- Add SERVING_DUCKDB_PATH to .env template
web/.env.example + web/docker-compose.yml
- Document both env vars; switch web service to SERVING_DUCKDB_PATH
web/src/beanflows/dashboard/templates/settings.html
- Minor settings page fix from prior session
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Sequences: extract (PSD) → extract_cot (CFTC) → extract_prices (KC=F) → extract_ice_all (ICE)
Stops and reports on first failure. META_PIPELINES dict makes it easy to
add more meta-pipelines as sources expand.
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>
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>
- Add pytest and pytest-cov for testing
- Add niquests for modern HTTP/2 support (keep requests for hcloud compatibility)
- Create 13 E2E tests covering CLI, workers, pipelines, and secrets (71% coverage)
- Fix Pulumi ESC environment path (beanflows/prod) and secret key names
- Update GitLab CI to run CLI tests with coverage reporting
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
