col: simulator auto-adjusts spending to local prices via Numbeo+Expatistan

The Monte Carlo used to compare jurisdictions at a flat London-equivalent
spend, which silently overstated the cost-of-living for any move to a
cheaper region. Now every cross-jurisdiction simulation auto-scales
spending_gbp by the real Numbeo/Expatistan ratio between the user's
baseline city and the target city.

Architecture:
- fire_planner/col/baseline.py — 22 cities with headline Numbeo data
  (source URLs + snapshot dates embedded) — fallback when scraper fails
- col/numbeo.py + col/expatistan.py — httpx async scrapers, regex-parsed,
  polite 1.1s rate-limit, EUR/USD anchored
- col/cache.py — PG-backed cache (col_snapshot table, 1-year TTL)
- col/service.py — sync compute_col_ratio() for the simulator; async
  lookup_city_cached() with source reconciliation for the refresh CronJob
- alembic 0005 — col_snapshot table, UNIQUE(city_slug, source_name)

Simulator wiring:
- SimulateRequest gains col_auto_adjust=True (default), col_baseline_city,
  col_target_city. Defaults pick the jurisdiction's representative city.
- _resolve_col_adjustment scales spending_gbp before path-building.
- SimulateResult surfaces col_multiplier_applied + col_adjusted_spending_gbp.

CLIs:
- python -m fire_planner col-seed — loads BASELINES into col_snapshot
  (post-migration seed step)
- python -m fire_planner col-refresh-stale --within-days 7 — used by the
  weekly fire-planner-col-refresh CronJob

268 tests pass. Mypy strict + ruff clean.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

fire_planner/col/__init__.py

@@ -0,0 +1,36 @@
+"""Cost-of-living module — feeds the simulator with real per-city spend ratios.
+
+The simulator's `spending_gbp` is denominated in the user's BASELINE city
+(typically London). When a scenario moves the user to a different TARGET
+city, this module returns the ratio `target_total / baseline_total` so
+the simulator can scale `spending_gbp` to local prices before running
+paths.
+
+Phase 1 (current): hand-curated baselines from Numbeo public pages, with
+source URLs and fetch dates embedded so future-us can refresh by hand.
+Phase 2 (planned): live scrapers for Numbeo + Expatistan, DB cache with
+30-day TTL, nightly refresh CronJob.
+"""
+from __future__ import annotations
+
+from fire_planner.col.models import CategoryBreakdown, CityCostIndex, ColSource
+from fire_planner.col.service import (
+    JURISDICTION_REPRESENTATIVE_CITY,
+    compute_col_ratio,
+    lookup_city,
+    lookup_city_cached,
+    reconcile_sources,
+    representative_city_for,
+)
+
+__all__ = [
+    "CategoryBreakdown",
+    "CityCostIndex",
+    "ColSource",
+    "JURISDICTION_REPRESENTATIVE_CITY",
+    "compute_col_ratio",
+    "lookup_city",
+    "lookup_city_cached",
+    "reconcile_sources",
+    "representative_city_for",
+]