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/db.py

@@ -244,6 +244,50 @@ class IncomeStream(Base):
                                                  server_default=func.now())
 
 
+class ColSnapshot(Base):
+    """Cached cost-of-living snapshot per (city_slug, source).
+
+    Phase 2 of the COL subsystem. Replaces the previous "baseline-only"
+    lookup with cache-then-scrape semantics:
+
+      service.lookup_city(slug) → check ColSnapshot, return if fresh
+                                → else scrape Numbeo, upsert, return
+                                → if scrape fails, fall back to baseline.py
+
+    TTL default = 365 days (`expires_at = fetched_at + interval '365 day'`).
+    The user explicitly asked for 1y on 2026-05-21 — Numbeo data doesn't
+    move fast enough to need monthly refresh, and the API/scraper has rate-
+    limit risk we prefer to amortise. Phase-3 CronJob will run a nightly
+    refresh of stale rows so individual user requests never have to scrape.
+
+    `(city_slug, source_name)` is unique — we can store multiple sources
+    per city (Numbeo + Expatistan) and reconcile in service.py.
+    """
+    __tablename__ = "col_snapshot"
+    __table_args__ = {"schema": SCHEMA_NAME}  # noqa: RUF012
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    city_slug: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    city_display: Mapped[str] = mapped_column(String(128), nullable=False)
+    country: Mapped[str] = mapped_column(String(64), nullable=False)
+    source_name: Mapped[str] = mapped_column(String(32), nullable=False)
+    source_url: Mapped[str | None] = mapped_column(String, nullable=True)
+    snapshot_date: Mapped[date] = mapped_column(Date, nullable=False)
+    fetched_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
+                                                 nullable=False,
+                                                 server_default=func.now())
+    expires_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True), nullable=False)
+    total_no_rent_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
+    total_with_rent_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
+    rent_1bed_center_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
+    rent_1bed_outside_gbp: Mapped[Decimal | None] = mapped_column(Numeric(12, 2), nullable=True)
+    raw_currency: Mapped[str] = mapped_column(String(3), nullable=False, server_default="GBP")
+    gbp_per_unit: Mapped[Decimal] = mapped_column(Numeric(12, 8),
+                                                   nullable=False,
+                                                   server_default=text("1"))
+    by_category_json: Mapped[dict[str, Any] | None] = mapped_column(JSON_TYPE, nullable=True)
+
+
 class RetirementGoal(Base):
     """A user-defined success criterion for a scenario.