docs: Rust rewrite assessment + forecast parity spike

spikes/rust-forecast ports build_features (P.1 path) and HistGradientBoosting
inference to Rust and checks them against the pandas/sklearn output on two
fixtures (2024 record flood, summer 2026): 244,800 feature cells and every
regression prediction bit-identical, classifier heads to the last ulp;
0.25 ms vs 158 ms per station. docs/RUST_REWRITE.md: what a rewrite would
mean (Rust service, Python training), costs, phased plan, Python alternative.

spikes/rust-forecast/export/time_python.py

@@ -0,0 +1,38 @@
+"""Python timing for the same serving-shaped work as the Rust spike."""
+
+import sys
+import time
+from pathlib import Path
+
+import joblib
+import numpy as np
+import pandas as pd
+
+REPO = Path(__file__).resolve().parents[3]  # repo root
+sys.path.insert(0, str(REPO))
+from src.ml import features  # noqa: E402
+
+bundle = joblib.load(REPO / "models" / "flood_P.1.joblib")
+stations = ["P.1"] + [u for u, _ in features.UPSTREAM_LEADS["P.1"]]
+long = pd.concat(
+    pd.read_csv(REPO / "models" / "cache" / f"{s}.csv.gz", parse_dates=["timestamp"])
+    for s in stations
+)
+df = long[(long.timestamp >= "2026-07-30") & (long.timestamp < "2026-08-13")]
+rain_all = pd.read_csv(REPO / "models" / "cache" / "rain_openmeteo.csv.gz", parse_dates=["timestamp"])
+rain_all = rain_all.set_index("timestamp")["chiang_dao"].astype(float)
+
+reps = 20
+t = time.perf_counter()
+for _ in range(reps):
+    grid = features.make_hourly_grid(df)
+    rain = rain_all.reindex(grid.observed.index)
+    row = features.build_features(grid, "P.1", rain=rain)[bundle["feature_names"]].iloc[[-1]]
+    out = {
+        k: (h.predict_proba(row)[0, 1] if hasattr(h, "predict_proba") else h.predict(row)[0])
+        for k, h in bundle["heads"].items()
+    }
+print(f"python: grid + features + 9 heads for the last hour: {(time.perf_counter() - t) / reps * 1000:.1f} ms per station")
+t = time.perf_counter()
+joblib.load(REPO / "models" / "flood_P.1.joblib")
+print(f"python: bundle load {(time.perf_counter() - t) * 1000:.0f} ms")