da3f5faa91
FastAPI + React + PostgreSQL salary benchmarking tool with AI research pipeline. - Seed data for 25+ New York roles (junior/mid/senior levels) - Single + bulk lookup with location alias mapping (NYC -> New York, etc.) - Research pipeline: Serper -> Firecrawl -> Cohere Rerank -> Claude analysis - Editable validation UI for AI-proposed benchmarks - CSV export, Montserrat font, black/white/#FFC407 design - Fully Dockerized (app + db + frontend) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
import httpx
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from app.config import settings
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async def search_salaries(title: str, location: str) -> dict:
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queries = [
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f'"{title}" salary range {location} 2025 2026',
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f'"{title}" compensation {location} glassdoor levels.fyi',
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]
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all_results = []
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seen_urls = set()
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async with httpx.AsyncClient(timeout=30) as client:
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for query in queries:
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resp = await client.post(
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"https://google.serper.dev/search",
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headers={"X-API-KEY": settings.serper_api_key},
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json={"q": query, "num": 10},
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)
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resp.raise_for_status()
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data = resp.json()
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for item in data.get("organic", []):
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url = item.get("link", "")
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if url not in seen_urls:
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seen_urls.add(url)
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all_results.append(
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{
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"title": item.get("title", ""),
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"link": url,
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"snippet": item.get("snippet", ""),
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}
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)
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return {"results": all_results[:15]}
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