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pub-search.waow.tech
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zig
blog
atproto
chore: simplify scripts now that logfire handles observability
- remove diagnose-latency.py (logfire shows latency distributions)
- simplify exercise-api to just hit endpoints, point to logfire for results
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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scripts/diagnose-latency.py
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scripts/diagnose-latency.py
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#!/usr/bin/env python3
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"""diagnose search API latency"""
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import time
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import httpx
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BASE_URL = "https://leaflet-search-backend.fly.dev"
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def timed_request(url: str, name: str) -> float:
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start = time.perf_counter()
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resp = httpx.get(url, timeout=30)
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elapsed = time.perf_counter() - start
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print(f"{name}: {elapsed:.3f}s (status={resp.status_code})")
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return elapsed
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def main():
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print("=== latency diagnosis ===\n")
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# warmup
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print("1. warmup request (health):")
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timed_request(f"{BASE_URL}/health", " health")
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print("\n2. first search (cold db?):")
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t1 = timed_request(f"{BASE_URL}/search?q=atproto", " search")
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print("\n3. rapid follow-up searches:")
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times = []
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for i in range(5):
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t = timed_request(f"{BASE_URL}/search?q=blog", f" search {i+1}")
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times.append(t)
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print(f"\n4. stats (single query):")
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timed_request(f"{BASE_URL}/stats", " stats")
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print(f"\n5. dashboard (batched queries):")
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timed_request(f"{BASE_URL}/api/dashboard", " dashboard")
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print("\n=== summary ===")
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print(f"first search: {t1:.3f}s")
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print(f"follow-up avg: {sum(times)/len(times):.3f}s")
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print(f"follow-up min: {min(times):.3f}s")
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print(f"follow-up max: {max(times):.3f}s")
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if t1 > 5:
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print("\n⚠️ first request very slow - likely turso cold start")
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if sum(times)/len(times) > 1:
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print("⚠️ follow-up requests still slow - query optimization needed")
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print(" suggestion: batch the 3 search queries into 1 http request")
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if __name__ == "__main__":
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main()
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scripts/exercise-api
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scripts/exercise-api
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# dependencies = ["httpx"]
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# ///
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"""
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Exercise all leaflet-search API endpoints to generate traffic for stats.
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Exercise all leaflet-search API endpoints to generate traffic.
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Usage:
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./scripts/exercise-api # run with defaults
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./scripts/exercise-api --count 20 # more requests per endpoint
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Check logfire for latency/error data after running.
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"""
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import asyncio
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exercise_popular(client, count),
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)
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print("\nfetching stats...")
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async with httpx.AsyncClient(base_url=BASE_URL, timeout=30) as client:
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resp = await client.get("/api/dashboard")
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data = resp.json()
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timing = data.get("timing", {})
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print("\nendpoint count p50 p95")
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print("-" * 40)
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for name in ["search", "similar", "tags", "popular"]:
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t = timing.get(name, {})
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c = t.get("count", 0)
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p50 = t.get("p50_ms", 0)
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p95 = t.get("p95_ms", 0)
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print(f"{name:<12} {c:<6} {p50:>6.0f}ms {p95:>6.0f}ms")
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print("\ndone - check logfire for results")
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if __name__ == "__main__":