performance bottleneck
Despite the nominal 1-2 second response, the delay may be exacerbated in actual use due to network environment or parameter settings.
Key optimization measures
- Compression of request data: Remove non-essential parameters, e.g., the default number may not be passed as num.
- local access: Test server latency in different locales (api.eu.serper.dev, etc.)
- parallel processing: Python can use asyncio+aiohttp to implement concurrent queries
Code-Level Optimization
import aiohttp
async def fetch(session, params):
async with session.get(API_URL, params=params) as response:
return await response.json()
# 建立连接池
conn = aiohttp.TCPConnector(limit=10)
async with aiohttp.ClientSession(connector=conn) as session:
tasks = [fetch(session, p) for p in params_list]
results = await asyncio.gather(*tasks)take note of: Free accounts are limited to 10 requests per second, overdoing it will result in a 429 error
This answer comes from the articleSerper: the API tool for 2,500 free uses of Google search resultsThe
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