- Add extract/extract_core/ workspace package with three modules:
- state.py: SQLite run tracking (open_state_db, start_run, end_run, get_last_cursor)
- http.py: niquests session factory + etag normalization helpers
- files.py: landing_path, content_hash, write_bytes_atomic (atomic gzip writes)
- State lives at {LANDING_DIR}/.state.sqlite — no extra env var needed
- SQLite chosen over DuckDB: state tracking is OLTP (row inserts/updates), not analytical
- Refactor all 4 extractors (psdonline, cftc_cot, coffee_prices, ice_stocks):
- Replace inline boilerplate with extract_core helpers
- Add start_run/end_run tracking to every extraction entry point
- extract_cot_year returns int (bytes_written) instead of bool
- Update tests: assert result == 0 (not `is False`) for the return type change
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>
- Configure ruff with strict linting rules (pycodestyle, pyflakes, isort, pylint, etc.)
- Exclude notebooks folder from linting
- Set line length to 88 characters and target Python 3.13
- Migrate build backend from hatchling to uv_build for better integration
- Add per-file ignores for __init__.py and scripts
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <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>
