grabowski
0005f7dce1
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Retrained on the gap-filled DB (592k -> 976k rows) and re-examined the flood backtests, now reproducible via scripts/backtest_render.py (renders the three docs/img charts and gates on a >=12h 2024 first-alert lead — currently failing by design and documented as such). Findings, all documented in FLOOD_FORECASTING.md: the true 2024 crossing was 24 Sep 17:00 (8h earlier than recorded; confirmed against the independent HII sensor), the historical 24h-warning claim was partly a missing-data artifact, and retrained warn classifiers collapse on the filled grid (P.1 24h PR-AUC 0.900 -> 0.288) while regression MAE improves (11.3 -> 10.5 cm). Serving therefore becomes max(classifier, sigmoid(regression)) so alerting is never worse than the regression path; metrics table, head-gating tiers, honest-limits and runbook expectations all updated to the current model (hgb-v1+d2d0e65). Perf, from Locust load testing (scripts/locustfile.py + load_test.py): single-flight lock around /forecast inference (concurrent cache misses previously each ran ~18s inference and starved the shared thread pool; 200-user run after: 105 rps, 0.01% errors), and /measurements/latest + /health moved off the event loop (synchronous DB/network calls in async handlers were stalling every request under load).
94 lines
2.6 KiB
Python
94 lines
2.6 KiB
Python
"""Locust load profile for the Ping River Monitor API + dashboard.
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Two user types mirror real traffic: dashboard visitors (page + the API calls
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the page makes, polling like the auto-refresh does) and API consumers
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(direct endpoint hits, including heavy history queries).
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Full stress against a LOCAL instance (never full-stress production — it hosts
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live flood monitoring):
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# separate shell: python -m uvicorn src.web_api:app --port 8125
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.venv/Scripts/python.exe -m locust -f scripts/locustfile.py \
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--host http://localhost:8125 --headless \
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--users 200 --spawn-rate 20 --run-time 2m \
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--html load-report.html
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Interactive UI instead: drop --headless and open http://localhost:8089.
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"""
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import random
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from locust import FastHttpUser, between, task
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class DashboardVisitor(FastHttpUser):
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"""A browser session: initial page load, then periodic refresh polling."""
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weight = 3
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wait_time = between(2, 6)
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def on_start(self):
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# What one real page load requests
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self.client.get("/")
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self.client.get("/stations")
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self.client.get("/measurements/latest?limit=500")
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self.client.get("/api/hii/waterlevel/latest")
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self.client.get("/api/hii/rainfall/latest")
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@task(4)
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def poll_latest(self):
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self.client.get("/measurements/latest?limit=500")
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@task(2)
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def poll_forecast(self):
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self.client.get("/forecast")
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@task(2)
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def poll_rain(self):
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self.client.get("/api/hii/rainfall/latest")
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@task(1)
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def view_history(self):
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station = random.choice(["P.1", "P.67", "P.103", "P.75", "P.20"])
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hours = random.choice([24, 168, 720])
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self.client.get(
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f"/measurements/history/{station}?hours={hours}",
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name="/measurements/history/[station]",
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)
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@task(1)
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def stats(self):
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self.client.get("/api/stats")
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class ApiConsumer(FastHttpUser):
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"""A script/integration hitting the JSON API directly, no think time."""
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weight = 1
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wait_time = between(0.1, 1)
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@task(3)
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def latest(self):
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self.client.get("/measurements/latest?limit=100")
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@task(3)
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def hii_feeds(self):
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self.client.get(random.choice(
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["/api/hii/waterlevel/latest", "/api/hii/rainfall/latest"]
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), name="/api/hii/[feed]/latest")
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@task(2)
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def forecast(self):
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self.client.get("/forecast")
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@task(2)
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def heavy_history(self):
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self.client.get(
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"/measurements/history/P.1?hours=8760",
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name="/measurements/history/P.1 [heavy]",
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)
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@task(1)
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def health(self):
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self.client.get("/health")
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