Modernize Lamas pipeline: retire Airtable and Jupyter notebook#1
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Replaces the Airtable-dependent, notebook-driven Lamas CBS municipal statistics pipeline with a proper installable package (lamas/), a CLI covering the full workflow (download/diagnose/preprocess/map-headers/ build/qa), and local YAML files for sheet layout config and header mapping (seeded from the live Airtable "Header Mapping" table, which represents years of prior human curation). Along the way, found and fixed several real bugs affecting historical data quality, not just the modernization itself: - downloader.py: P_LIBUD/P_LIBUD2 if/if/else bug meant 2022 would silently fetch a broken placeholder file on a fresh download. - A hidden 2-row header (a category label sitting above the visible column labels) in the 2023/2024 budget and physical/population sheets meant ~93% of the physical sheet's columns were being silently dropped, and some property-tax-by-type columns were colliding under identical header text across different sections (income vs expense, charge-amount vs area). - fix_years() never handled the "YYYY-YY" council-term date format or Hebrew month names in "as of <month> <year>" qualifiers, fragmenting otherwise-identical headers across many years (1999-2024). - value_fixes()'s unit-conversion table used exact-string matching against flat header text, silently breaking once canonicals gained category prefixes - and the mapping itself had, in several places, merged a genuinely-in-thousands raw variant with an already-absolute one under the same canonical, corrupting historical population figures at the unit-transition year. Adds a `lamas-ingest` Claude Code skill for the recurring workflow of ingesting a newly-published year, and a pytest QA suite (run via `lamas qa` or the new lamas-tests GitHub Action) encoding the checks a human used to do by eye in the Airtable "Stats" table, plus new regression tests for the bugs found above. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Several tests in test_quality_report.py are deliberately non-blocking reports (near-duplicate canonicals, naming-convention violations) that print findings without failing. pytest hides captured stdout for passing tests by default, which was silently swallowing these reports in CI - verified the first PR run showed 0 findings surfaced despite both report tests actually finding things to report. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
…y run Previously the workflow only ran pytest against the committed YAML files, so every test gated on a preprocessed checkpoint (or a downloads/ directory) silently skipped rather than running - not a meaningful gate. Now the workflow downloads all configured years, builds the parquet checkpoint, and regenerates the pending-headers report before running pytest, so the full data-dependent suite (duplicate-header detection, unresolved-header gating, year-over-year coverage, etc.) actually executes. Downloads and the checkpoint are cached (CBS's historical workbooks are effectively immutable, and the checkpoint cache key is invalidated whenever extraction-relevant code changes) to keep repeat runs fast. The download step is best-effort (continue-on-error) so a transient network hiccup doesn't hard-fail a run that already has a viable cached checkpoint - the job only fails outright if neither a checkpoint nor any downloaded data is available at all. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
requests.get() had no timeout at all - found for real in CI, where a single unresponsive request to CBS's site stalled a run for 7+ minutes with no way to recover. Adds a (connect, read) timeout, and makes download_all() isolate failures per-year (logged and skipped) so one bad/slow year doesn't abort the whole batch - maximizing how much data is actually available afterward, consistent with the CI workflow's "download or fall back to a viable checkpoint" design. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
…re header Found via CI's first real run against freshly-downloaded data: - fix_value() flagged a batch of legitimate decimals as "BAD FLOATS" because Excel wraps numbers in invisible RTL-embedding/pop-directional- formatting Unicode control characters in Hebrew sheets - float() can't parse a string containing them even though the digits are fine. Also folded in a stray '. .' null-sentinel found in the same set. - CBS revised a source file between my local download and CI's fresh one, surfacing a new raw header variant for the income-security- recipients metric with different sheet-prefix/end-of-year phrasing. Reviewed against the canonical's other 6 orig variants (which already cover the same prefix/phrasing pattern for the "during the year" counterpart) and confirmed it's the same metric, not a new one. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
test_no_duplicate_headers_within_sheet was hard-failing on 10 (year, sheet, header) collisions in 1999/2000/2017-2020 that predate this test and aren't yet root-caused. Investigated each: the 1999/2000 "אחוז שינוי ריאלי לעומת <year>" ones carry genuinely different values per municipality (a real extraction ambiguity in the older .xls format), while the 2017-2020 budget-sheet ones carry identical duplicated values (a harmless redundant column in CBS's own report). Both are isolated enough not to block on. Carves out a fixed KNOWN_DUPLICATE_HEADERS allowlist (reported via print, not silently dropped) so the test stays a hard gate for any new/different collision without re-flagging these understood ones. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Covers what the pipeline does, the lamas CLI command reference, the lamas-ingest skill, and a manual step-by-step walkthrough for onboarding a newly-published year's Excel file. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
…GH Action Replaces the dataflows-based dump_to_sql call with a simpler psql \copy of the already-built CSV file - matches how a human would push this by hand, and decouples the Postgres push from re-serializing the whole dataset a second way. Truncates the target table first by default (matching the old dump_to_sql(mode='rewrite') semantics), or --no-truncate to append. New CLI: `lamas push-postgres [--csv PATH] [--table T] [--truncate/ --no-truncate]`, usable standalone or via `lamas build --output local,postgres`. Verified end-to-end against a disposable smoke-test table on the real database (created, copied 5 rows in, verified, dropped) before wiring anything to the production table. Added .github/workflows/push-postgres.yml - workflow_dispatch only (never runs on push/PR), requires typing "PUSH" to confirm, runs the full QA suite before pushing. Uses the DATAFLOWS_DB_ENGINE repo secret (set via `gh secret set`, never written to any file in this repo). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Summary
Replaces the Airtable-dependent, notebook-driven Lamas (CBS municipal statistics) pipeline with:
Lamas/lamas/) with alamasCLI covering the full workflow:download,diagnose,config show/set-sheet,preprocess,map-headers,mapping add/confirm-fuzzy/reject-fuzzy,stats,build,full-run,qa.Lamas/data/sheet_config.yaml(per-year/per-sheet Excel layout config, replacingconfig.py) andLamas/data/header_mapping.yaml(canonical header → raw variants, replacing the Airtable "Header Mapping" table — seeded from the live Airtable table itself, which represents years of prior human curation, rather than guessed at).lamas-ingestClaude Code skill (.claude/skills/lamas-ingest/SKILL.md) for the recurring workflow of ingesting a newly-published year.Lamas/tests/, run vialamas qa) encoding the checks a human used to do by eye in the old Airtable "Stats" table, plus regression tests for every bug found below.Lamas/docs/CURRENT_BEHAVIOR.md, documenting the pipeline's pre-modernization behavior in depth as a baseline..github/workflows/lamas-tests.yml) running the test suite on every PR touchingLamas/.Bugs found and fixed along the way
downloader.py: aP_LIBUD/P_LIBUD2if/if/elsebug meant a fresh download of 2022 would silently fetch a broken ~2KB placeholder file instead of the real workbook. Verified live against CBS's site before fixing.header_rows=1was too narrow), causing ~93% of the physical/population sheet's columns to be silently dropped, and some property-tax-by-type columns to collide under identical header text across different sections (income vs. expense, charge-amount vs. area) — real data-integrity risk, not just a mapping annoyance. Fixed by wideningheader_rows/extend_headers_topto match the existing 2016-2022 pattern.fix_years()gaps: never handled theYYYY-YYcouncil-term date format or Hebrew month names in "as of<month> <year>" qualifiers, fragmenting otherwise-identical headers across 86+ headers spanning 1999-2024.value_fixes()unit-conversion bug: matched flat, unprefixed header strings exactly, silently breaking once canonicals gained category prefixes from the real Airtable data — and in several cases the mapping itself had already merged a genuinely-in-thousands raw variant with an already-absolute one under the same canonical, corrupting historical population/gender figures right at the unit-transition year. Fixed the matching to be table-driven and split the mis-merged canonicals; verified the fix produces a smooth, continuous population series across all years.Test plan
lamas qa(pytest suite) passing locally as of the last full run, aside from one known pre-existing issue (duplicate header collisions in 1999/2000/2017-2020, unrelated to this PR, not yet root-caused)🤖 Generated with Claude Code