150 lines
5.8 KiB
Markdown
150 lines
5.8 KiB
Markdown
# tradein-mvp/backend/scripts/
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Ops scripts that touch the production database directly. Run via `python -m
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scripts.<name>` from the `backend/` working directory after `uv sync`.
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All scripts are idempotent / resumable where they write — re-running the same
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`--batch` label skips already-processed rows (UNIQUE constraints in target
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tables). Failures inside a per-row loop never roll back the outer transaction;
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each row is wrapped in a SAVEPOINT (`db.begin_nested()`) per `.claude/rules/backend.md`.
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---
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## Production usage (canonical)
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Scripts ship inside the `tradein-backend` image (PR F — `COPY scripts ./scripts`
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в `backend/Dockerfile`). На VPS они уже в `/app/scripts/` — никаких manual
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`docker cp` не нужно.
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`YANDEX_GEOCODER_API_KEY` подтягивается из `/opt/gendesign/tradein-mvp/backend/
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.env.runtime` через `env_file:` в `docker-compose.prod.yml` — никакого `-e` в
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`docker exec` не нужно.
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```bash
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# Backfill (forward geocode 4170 houses без coords)
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ssh gendesign 'docker exec tradein-backend python -m scripts.backfill_house_coords --batch 2026-05-27_backfill'
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# Audit-only (reverse geocode проверка для уже geocoded houses)
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ssh gendesign 'docker exec tradein-backend python -m scripts.backfill_house_coords --audit-only --batch 2026-05-27_audit'
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# Canary first
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ssh gendesign 'docker exec tradein-backend python -m scripts.backfill_house_coords --limit 100 --batch canary_$(date +%F)'
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```
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После изменения `backend/.env.runtime` нужен `--force-recreate` контейнера
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(см. `.claude/rules/deploy.md`):
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```bash
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ssh gendesign 'cd /opt/gendesign/tradein-mvp && docker compose -p gendesign-tradein -f docker-compose.prod.yml up -d --force-recreate --no-deps backend'
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```
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---
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## Address audit + backfill (issue #582)
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End-to-end address quality pipeline. Three scripts, two helpers, two SQL files.
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> Локальные примеры ниже — для dev-машины с `uv run` и переменными в shell.
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> На prod используй canonical `docker exec` команды из секции выше — там
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> `YANDEX_GEOCODER_API_KEY` уже подгружен из `backend/.env.runtime`.
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### `audit_address_mismatch.py` — Phase 1 baseline (PR #583)
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Stratified-sample audit (200 EKB houses) comparing `houses.address` vs
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Yandex Geocoder reverse lookup. Writes one row per house into
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`address_mismatch_audit` with the snapped point + canonical address + distance.
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```bash
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DATABASE_URL=postgresql+psycopg://... \
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YANDEX_GEOCODER_API_KEY=... \
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uv run python -m scripts.audit_address_mismatch \
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--batch 2026-05-25_run1 \
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--limit-per-district 25
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```
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Mode `auto` picks API if the key is set, otherwise Playwright (CAPTCHA-aware,
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4-7s sleep between calls). API tier free is 25k req/day → 200-row sample
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takes ~10s with no quota concern.
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Report:
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```bash
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psql "$DATABASE_URL" -v batch='2026-05-25_run1' \
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-f scripts/address_audit_report.sql
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```
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### `backfill_house_coords.py` — Phase 2-3 (PR for #582)
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Two modes (`--audit-only` flag switches between them):
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**Backfill (default)** — forward-geocode `houses.address` for the ~4141 rows
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WHERE `lat IS NULL OR lon IS NULL`. Only writes back if Yandex returns
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`precision='exact'` or `'number'` (skips street-only / locality matches).
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Each processed row gets an `address_mismatch_audit` entry with status
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`backfill` / `imprecise` / `no_match` / `error`.
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```bash
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DATABASE_URL=postgresql+psycopg://... \
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YANDEX_GEOCODER_API_KEY=... \
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uv run python -m scripts.backfill_house_coords \
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--batch 2026-05-27_backfill
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```
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Expected duration (~4141 rows, 50ms between calls, ~250ms RTT per request):
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20-25 min. Expected output split (rough baseline from Phase 1 numbers):
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| Status | Approx rows | What it means |
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|-------------|-------------|-----------------------------------------------------|
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| `backfill` | ~3.3k–3.7k | UPDATE landed, lat/lon now populated |
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| `imprecise` | ~300–500 | Match returned but precision too low — needs review |
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| `no_match` | ~100–300 | Yandex couldn't resolve; address probably mangled |
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| `error` | <50 | HTTP errors / timeouts — re-run picks them up |
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**Audit-only** — reverse-geocode the ~4452 houses WITH coords, write
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audit rows with status `ok` (≤50m) / `mismatch` (>50m) / `no_match` / `error`.
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Does NOT modify the `houses` table.
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```bash
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uv run python -m scripts.backfill_house_coords \
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--batch 2026-05-27_audit --audit-only
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```
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Combined budget for both phases (~8.6k requests) is well under the 25k/day
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Geocoder free tier.
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### Common ops
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Canary first — run with `--limit 100` and inspect the audit table before
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letting the full job loose:
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```bash
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uv run python -m scripts.backfill_house_coords \
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--batch canary_$(date +%F) --limit 100
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psql "$DATABASE_URL" -c "
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SELECT audit_status, COUNT(*)
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FROM address_mismatch_audit
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WHERE audit_batch = 'canary_$(date +%F)'
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GROUP BY audit_status;
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"
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```
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Resume after crash / quota hit — same `--batch` label, the UNIQUE
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`(house_id, audit_batch)` index skips finished rows:
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```bash
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uv run python -m scripts.backfill_house_coords --batch 2026-05-27_backfill
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# ... interruption ...
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uv run python -m scripts.backfill_house_coords --batch 2026-05-27_backfill
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# logs: "resuming batch 2026-05-27_backfill: N rows already processed"
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```
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### Helpers (not entry points)
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- `_yandex_reverse.py` — `forward_via_api()`, `reverse_via_api()`,
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`reverse_via_playwright()`, `YandexReverseResult` dataclass. Both API
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paths share `_parse_api_payload` because Yandex's forward/reverse
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envelopes have the same shape.
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- `audit_address_sample.sql` — random sample for the Phase 1 audit (used
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by `audit_address_mismatch.py`).
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- `address_audit_report.sql` — psql-driven post-run summary (p50/p75/p95
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distance, top-20 outliers, per-district breakdown).
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