我想提高 Python 脚本的性能,并一直在使用 cProfile 生成性能报告:
ncalls tottime percall cumtime percall filename:lineno(function)
75 23.514 0.314 23.514 0.314 {method 'read' of '_ssl._SSLSocket' objects}
75 8.452 0.113 8.452 0.113 {method 'do_handshake' of '_ssl._SSLSocket' objects}
75 2.113 0.028 2.113 0.028 {method 'load_verify_locations' of '_ssl._SSLContext' objects}
75 1.479 0.020 1.479 0.020 {method 'connect' of '_socket.socket' objects}
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示例代码:
import requests
import json
from collections import defaultdict
#Added for multiprocessing
from urllib.request import urlopen
from multiprocessing.dummy import Pool as ThreadPool
results = defaultdict(list)
# Make the Pool of workers
pool = ThreadPool(4)
# Open the urls in their own threads
# and return the results
results = pool.map(urlopen, requests.post())
#close the pool and wait for the work to finish
pool.close()
pool.join()
for store, data in results.items():
print('Store: {}'.format(store), end=', ')
if data:
for inventory in data:
print(inventory)
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小智 1
您正在有效地测量远程网站的响应时间,这可能不是您想要的。为了最大化吞吐量(每秒发送的 HTTP 请求数或接收的数据数),您应该异步发送许多同时请求。您可以使用aiohttp等异步 HTTP 库或仅使用本机 Python asyncio/asyncore。