{"id":1070674,"date":"2025-01-08T11:00:24","date_gmt":"2025-01-08T03:00:24","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1070674.html"},"modified":"2025-01-08T11:00:26","modified_gmt":"2025-01-08T03:00:26","slug":"python%e4%b8%ad%e5%a6%82%e4%bd%95%e5%81%9a%e5%b9%b6%e8%a1%8c%e8%ae%a1%e7%ae%97-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1070674.html","title":{"rendered":"python\u4e2d\u5982\u4f55\u505a\u5e76\u884c\u8ba1\u7b97"},"content":{"rendered":"

\"python\u4e2d\u5982\u4f55\u505a\u5e76\u884c\u8ba1\u7b97\"<\/p>\n

\u5728Python\u4e2d\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\uff1a\u4f7f\u7528\u591a\u7ebf\u7a0b\u3001\u591a\u8fdb\u7a0b\u4ee5\u53ca\u7b2c\u4e09\u65b9\u5e93\u5982Dask\u548cJoblib<\/strong>\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u5229\u7528\u5b83\u4eec\u6765\u63d0\u5347\u8ba1\u7b97\u6548\u7387\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u591a\u7ebf\u7a0b<\/h3>\n<\/p>\n

\u5728Python\u4e2d\uff0c\u591a\u7ebf\u7a0b\u5e76\u884c\u8ba1\u7b97\u53ef\u4ee5\u901a\u8fc7threading<\/code>\u5e93\u5b9e\u73b0\u3002\u867d\u7136Python\u7684\u5168\u5c40\u89e3\u91ca\u5668\u9501\uff08GIL\uff09\u9650\u5236\u4e86\u591a\u7ebf\u7a0b\u7684\u5e76\u884c\u6267\u884c\u80fd\u529b\uff0c\u4f46\u5bf9\u4e8eI\/O\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u591a\u7ebf\u7a0b\u4f9d\u7136\u662f\u4e00\u4e2a\u6709\u6548\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n<\/p>\n

1.1\u3001\u521b\u5efa\u548c\u4f7f\u7528\u7ebf\u7a0b<\/h4>\n<\/p>\n

import threading<\/p>\n
def print_numbers():<\/p>\n
    for i in range(5):<\/p>\n
        print(i)<\/p>\n
threads = []<\/p>\n
for i in range(3):<\/p>\n
    thread = threading.Thread(target=print_numbers)<\/p>\n
    threads.append(thread)<\/p>\n
    thread.start()<\/p>\n
for thread in threads:<\/p>\n
    thread.join()<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.2\u3001\u7ebf\u7a0b\u540c\u6b65<\/h4>\n<\/p>\n
\u591a\u7ebf\u7a0b\u73af\u5883\u4e2d\uff0c\u591a\u4e2a\u7ebf\u7a0b\u53ef\u80fd\u4f1a\u8bbf\u95ee\u5171\u4eab\u8d44\u6e90\uff0c\u8fd9\u53ef\u80fd\u5bfc\u81f4\u6570\u636e\u4e0d\u4e00\u81f4\u7684\u95ee\u9898\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528threading.Lock<\/code>\u6765\u540c\u6b65\u7ebf\u7a0b\u3002<\/p>\n<\/p>\n
import threading<\/p>\n
lock = threading.Lock()<\/p>\n
def print_numbers():<\/p>\n
    lock.acquire()<\/p>\n
    try:<\/p>\n
        for i in range(5):<\/p>\n
            print(i)<\/p>\n
    finally:<\/p>\n
        lock.release()<\/p>\n
threads = []<\/p>\n
for i in range(3):<\/p>\n
    thread = threading.Thread(target=print_numbers)<\/p>\n
    threads.append(thread)<\/p>\n
    thread.start()<\/p>\n
for thread in threads:<\/p>\n
    thread.join()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u591a\u8fdb\u7a0b<\/h3>\n<\/p>\n
\u5bf9\u4e8eCPU\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u4f7f\u7528\u591a\u8fdb\u7a0b\u53ef\u4ee5\u66f4\u6709\u6548\u5730\u5229\u7528\u591a\u6838CPU\u3002Python\u7684multiprocessing<\/code>\u5e93\u63d0\u4f9b\u4e86\u591a\u8fdb\u7a0b\u5e76\u884c\u8ba1\u7b97\u7684\u80fd\u529b\u3002<\/p>\n<\/p>\n
2.1\u3001\u521b\u5efa\u548c\u4f7f\u7528\u8fdb\u7a0b<\/h4>\n<\/p>\n
from multiprocessing import Process<\/p>\n
def print_numbers():<\/p>\n
    for i in range(5):<\/p>\n
        print(i)<\/p>\n
processes = []<\/p>\n
for i in range(3):<\/p>\n
    process = Process(target=print_numbers)<\/p>\n
    processes.append(process)<\/p>\n
    process.start()<\/p>\n
for process in processes:<\/p>\n
    process.join()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2.2\u3001\u8fdb\u7a0b\u95f4\u901a\u4fe1<\/h4>\n<\/p>\n
\u591a\u8fdb\u7a0b\u73af\u5883\u4e2d\uff0c\u8fdb\u7a0b\u95f4\u53ef\u4ee5\u901a\u8fc7\u961f\u5217\uff08Queue<\/code>\uff09\u6216\u7ba1\u9053\uff08Pipe<\/code>\uff09\u8fdb\u884c\u901a\u4fe1\u3002<\/p>\n<\/p>\n
from multiprocessing import Process, Queue<\/p>\n
def print_numbers(queue):<\/p>\n
    for i in range(5):<\/p>\n
        queue.put(i)<\/p>\n
queue = Queue()<\/p>\n
processes = []<\/p>\n
for i in range(3):<\/p>\n
    process = Process(target=print_numbers, args=(queue,))<\/p>\n
    processes.append(process)<\/p>\n
    process.start()<\/p>\n
for process in processes:<\/p>\n
    process.join()<\/p>\n
while not queue.empty():<\/p>\n
    print(queue.get())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528\u7b2c\u4e09\u65b9\u5e93<\/h3>\n<\/p>\n
\u9664\u4e86Python\u6807\u51c6\u5e93\u5916\uff0c\u8fd8\u6709\u4e00\u4e9b\u7b2c\u4e09\u65b9\u5e93\u53ef\u4ee5\u7528\u4e8e\u5e76\u884c\u8ba1\u7b97\uff0c\u4f8b\u5982Dask\u548cJoblib\u3002<\/p>\n<\/p>\n
3.1\u3001Dask<\/h4>\n<\/p>\n
Dask\u662f\u4e00\u4e2a\u7075\u6d3b\u7684\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u9002\u7528\u4e8e\u5927\u6570\u636e\u96c6\u548c\u590d\u6742\u8ba1\u7b97\u3002\u5b83\u652f\u6301\u591a\u7ebf\u7a0b\u3001\u591a\u8fdb\u7a0b\u548c\u5206\u5e03\u5f0f\u8ba1\u7b97\u3002<\/p>\n<\/p>\n
import dask.array as da<\/p>\n
\u521b\u5efa\u4e00\u4e2aDask\u6570\u7ec4<\/strong><\/h2>\n
x = da.random.random((10000, 10000), chunks=(1000, 1000))<\/p>\n
\u6267\u884c\u5e76\u884c\u8ba1\u7b97<\/strong><\/h2>\n
result = x.mean().compute()<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3.2\u3001Joblib<\/h4>\n<\/p>\n
Joblib\u662f\u53e6\u4e00\u4e2a\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5728\u51fd\u6570\u8c03\u7528\u7684\u5c42\u9762\u4e0a\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u3002\u5b83\u5e38\u7528\u4e8e\u673a\u5668\u5b66\u4e60<\/a>\u4e2d\u7684\u5e76\u884c\u5904\u7406\u3002<\/p>\n<\/p>\n
from joblib import Parallel, delayed<\/p>\n
def square(x):<\/p>\n
    return x * x<\/p>\n
results = Parallel(n_jobs=3)(delayed(square)(i) for i in range(10))<\/p>\n
print(results)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u9009\u62e9\u5408\u9002\u7684\u5e76\u884c\u8ba1\u7b97\u65b9\u6cd5<\/h3>\n<\/p>\n
\u9009\u62e9\u5408\u9002\u7684\u5e76\u884c\u8ba1\u7b97\u65b9\u6cd5\u9700\u8981\u8003\u8651\u4efb\u52a1\u7684\u7279\u6027\u548c\u8ba1\u7b97\u8d44\u6e90\u3002<\/p>\n<\/p>\n
4.1\u3001I\/O\u5bc6\u96c6\u578b\u4efb\u52a1<\/h4>\n<\/p>\n
\u5bf9\u4e8eI\/O\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u4f8b\u5982\u7f51\u7edc\u8bf7\u6c42\u3001\u6587\u4ef6\u8bfb\u5199\uff0c\u591a\u7ebf\u7a0b\u901a\u5e38\u662f\u4e00\u4e2a\u8f83\u597d\u7684\u9009\u62e9\u3002\u56e0\u4e3a\u8fd9\u4e9b\u4efb\u52a1\u4e3b\u8981\u53d7\u9650\u4e8eI\/O\u64cd\u4f5c\u7684\u7b49\u5f85\u65f6\u95f4\uff0c\u591a\u7ebf\u7a0b\u53ef\u4ee5\u5728\u7b49\u5f85I\/O\u64cd\u4f5c\u5b8c\u6210\u65f6\u5207\u6362\u5230\u5176\u4ed6\u7ebf\u7a0b\u6267\u884c\u4efb\u52a1\uff0c\u4ece\u800c\u63d0\u9ad8\u6548\u7387\u3002<\/p>\n<\/p>\n
import threading<\/p>\n
import requests<\/p>\n
def fetch_url(url):<\/p>\n
    response = requests.get(url)<\/p>\n
    print(url, response.status_code)<\/p>\n
urls = ['http:\/\/example.com' for _ in range(10)]<\/p>\n
threads = [threading.Thread(target=fetch_url, args=(url,)) for url in urls]<\/p>\n
for thread in threads:<\/p>\n
    thread.start()<\/p>\n
for thread in threads:<\/p>\n
    thread.join()<\/p>\n
<\/code><\/pre>\n<\/p>\n
4.2\u3001CPU\u5bc6\u96c6\u578b\u4efb\u52a1<\/h4>\n<\/p>\n
\u5bf9\u4e8eCPU\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u4f8b\u5982\u6570\u503c\u8ba1\u7b97\u3001\u56fe\u50cf\u5904\u7406\uff0c\u591a\u8fdb\u7a0b\u901a\u5e38\u662f\u66f4\u597d\u7684\u9009\u62e9\u3002\u56e0\u4e3a\u8fd9\u4e9b\u4efb\u52a1\u4e3b\u8981\u53d7\u9650\u4e8eCPU\u8ba1\u7b97\u80fd\u529b\uff0c\u591a\u8fdb\u7a0b\u53ef\u4ee5\u5145\u5206\u5229\u7528\u591a\u6838CPU\u7684\u4f18\u52bf\uff0c\u663e\u8457\u63d0\u9ad8\u8ba1\u7b97\u901f\u5ea6\u3002<\/p>\n<\/p>\n
from multiprocessing import Pool<\/p>\n
def compute_factorial(n):<\/p>\n
    if n == 0:<\/p>\n
        return 1<\/p>\n
    else:<\/p>\n
        return n * compute_factorial(n-1)<\/p>\n
numbers = [5, 7, 10, 15]<\/p>\n
with Pool(processes=4) as pool:<\/p>\n
    results = pool.map(compute_factorial, numbers)<\/p>\n
print(results)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u6027\u80fd\u4f18\u5316\u548c\u8c03\u8bd5<\/h3>\n<\/p>\n
\u5728\u5e76\u884c\u8ba1\u7b97\u4e2d\uff0c\u6027\u80fd\u4f18\u5316\u548c\u8c03\u8bd5\u662f\u4e24\u4e2a\u91cd\u8981\u7684\u65b9\u9762\u3002<\/p>\n<\/p>\n
5.1\u3001\u6027\u80fd\u4f18\u5316<\/h4>\n<\/p>\n
\u5728\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u6cd5\u8fdb\u884c\u6027\u80fd\u4f18\u5316\uff1a<\/p>\n<\/p>\n
    \n
  • \u4efb\u52a1\u5212\u5206<\/strong>\uff1a\u5c06\u4efb\u52a1\u5212\u5206\u4e3a\u591a\u4e2a\u8f83\u5c0f\u7684\u5b50\u4efb\u52a1\uff0c\u6709\u52a9\u4e8e\u63d0\u9ad8\u5e76\u884c\u8ba1\u7b97\u7684\u6548\u7387\u3002<\/li>\n
  • \u8d1f\u8f7d\u5747\u8861<\/strong>\uff1a\u786e\u4fdd\u6bcf\u4e2a\u7ebf\u7a0b\u6216\u8fdb\u7a0b\u7684\u5de5\u4f5c\u91cf\u5927\u81f4\u76f8\u540c\uff0c\u907f\u514d\u51fa\u73b0\u67d0\u4e9b\u7ebf\u7a0b\u6216\u8fdb\u7a0b\u8fc7\u8f7d\u7684\u60c5\u51b5\u3002<\/li>\n
  • \u51cf\u5c11\u901a\u4fe1\u5f00\u9500<\/strong>\uff1a\u5c3d\u91cf\u51cf\u5c11\u7ebf\u7a0b\u6216\u8fdb\u7a0b\u95f4\u7684\u901a\u4fe1\u5f00\u9500\uff0c\u53ef\u4ee5\u901a\u8fc7\u5408\u5e76\u6570\u636e\u4f20\u8f93\u3001\u51cf\u5c11\u9501\u7684\u4f7f\u7528\u7b49\u65b9\u5f0f\u5b9e\u73b0\u3002<\/li>\n<\/ul>\n
    5.2\u3001\u8c03\u8bd5\u6280\u5de7<\/h4>\n<\/p>\n
    \u5e76\u884c\u8ba1\u7b97\u4e2d\u7684\u8c03\u8bd5\u76f8\u5bf9\u590d\u6742\uff0c\u53ef\u4ee5\u501f\u52a9\u4ee5\u4e0b\u6280\u5de7\u8fdb\u884c\u8c03\u8bd5\uff1a<\/p>\n<\/p>\n
      \n
    • \u65e5\u5fd7\u8bb0\u5f55<\/strong>\uff1a\u5728\u5173\u952e\u6b65\u9aa4\u52a0\u5165\u65e5\u5fd7\u8bb0\u5f55\uff0c\u6709\u52a9\u4e8e\u5b9a\u4f4d\u95ee\u9898\u3002<\/li>\n
    • \u65ad\u70b9\u8c03\u8bd5<\/strong>\uff1a\u4f7f\u7528\u8c03\u8bd5\u5668\u8bbe\u7f6e\u65ad\u70b9\uff0c\u9010\u6b65\u67e5\u770b\u7a0b\u5e8f\u7684\u6267\u884c\u60c5\u51b5\u3002<\/li>\n
    • \u5355\u7ebf\u7a0b\u8c03\u8bd5<\/strong>\uff1a\u5c06\u5e76\u884c\u4ee3\u7801\u6539\u4e3a\u5355\u7ebf\u7a0b\u8fd0\u884c\uff0c\u9a8c\u8bc1\u4ee3\u7801\u903b\u8f91\u662f\u5426\u6b63\u786e\u3002<\/li>\n<\/ul>\n
      \u516d\u3001\u5b9e\u9645\u6848\u4f8b<\/h3>\n<\/p>\n
      \u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u5e76\u884c\u8ba1\u7b97\u7684\u5e94\u7528\uff0c\u6211\u4eec\u6765\u770b\u4e00\u4e2a\u5b9e\u9645\u6848\u4f8b\uff1a\u5bf9\u5927\u89c4\u6a21\u6570\u636e\u8fdb\u884c\u7edf\u8ba1\u5206\u6790\u3002<\/p>\n<\/p>\n
      \u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u6570\u767e\u4e07\u6761\u8bb0\u5f55\u7684\u65e5\u5fd7\u6587\u4ef6\uff0c\u6bcf\u6761\u8bb0\u5f55\u5305\u542b\u4e00\u4e2a\u7528\u6237ID\u548c\u4e00\u4e2a\u64cd\u4f5c\u65f6\u95f4\u6233\u3002\u6211\u4eec\u7684\u4efb\u52a1\u662f\u7edf\u8ba1\u6bcf\u4e2a\u7528\u6237\u7684\u64cd\u4f5c\u6b21\u6570\u3002<\/p>\n<\/p>\n
      6.1\u3001\u4f7f\u7528\u591a\u7ebf\u7a0b\u8fdb\u884c\u7edf\u8ba1<\/h4>\n<\/p>\n
      import threading<\/p>\n
      from collections import defaultdict<\/p>\n
      def count_user_operations(log_file, start, end, result):<\/p>\n
          user_counts = defaultdict(int)<\/p>\n
          with open(log_file, 'r') as file:<\/p>\n
              file.seek(start)<\/p>\n
              while file.tell() < end:<\/p>\n
                  line = file.readline()<\/p>\n
                  if not line:<\/p>\n
                      break<\/p>\n
                  user_id = line.split()[0]<\/p>\n
                  user_counts[user_id] += 1<\/p>\n
          result.append(user_counts)<\/p>\n
      log_file = 'large_log_file.txt'<\/p>\n
      file_size = os.path.getsize(log_file)<\/p>\n
      chunk_size = file_size \/\/ 4<\/p>\n
      results = []<\/p>\n
      threads = []<\/p>\n
      for i in range(4):<\/p>\n
          start = i * chunk_size<\/p>\n
          end = (i + 1) * chunk_size<\/p>\n
          result = []<\/p>\n
          thread = threading.Thread(target=count_user_operations, args=(log_file, start, end, result))<\/p>\n
          threads.append(thread)<\/p>\n
          thread.start()<\/p>\n
          results.append(result)<\/p>\n
      for thread in threads:<\/p>\n
          thread.join()<\/p>\n
      final_counts = defaultdict(int)<\/p>\n
      for result in results:<\/p>\n
          for user_id, count in result[0].items():<\/p>\n
              final_counts[user_id] += count<\/p>\n
      print(final_counts)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      6.2\u3001\u4f7f\u7528\u591a\u8fdb\u7a0b\u8fdb\u884c\u7edf\u8ba1<\/h4>\n<\/p>\n
      from multiprocessing import Process, Manager<\/p>\n
      from collections import defaultdict<\/p>\n
      def count_user_operations(log_file, start, end, result):<\/p>\n
          user_counts = defaultdict(int)<\/p>\n
          with open(log_file, 'r') as file:<\/p>\n
              file.seek(start)<\/p>\n
              while file.tell() < end:<\/p>\n
                  line = file.readline()<\/p>\n
                  if not line:<\/p>\n
                      break<\/p>\n
                  user_id = line.split()[0]<\/p>\n
                  user_counts[user_id] += 1<\/p>\n
          result.update(user_counts)<\/p>\n
      log_file = 'large_log_file.txt'<\/p>\n
      file_size = os.path.getsize(log_file)<\/p>\n
      chunk_size = file_size \/\/ 4<\/p>\n
      manager = Manager()<\/p>\n
      results = manager.dict()<\/p>\n
      processes = []<\/p>\n
      for i in range(4):<\/p>\n
          start = i * chunk_size<\/p>\n
          end = (i + 1) * chunk_size<\/p>\n
          process = Process(target=count_user_operations, args=(log_file, start, end, results))<\/p>\n
          processes.append(process)<\/p>\n
          process.start()<\/p>\n
      for process in processes:<\/p>\n
          process.join()<\/p>\n
      print(results)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u901a\u8fc7\u4ee5\u4e0a\u4e24\u4e2a\u6848\u4f8b\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u591a\u7ebf\u7a0b\u548c\u591a\u8fdb\u7a0b\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u4e0d\u540c\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u9009\u62e9\u5408\u9002\u7684\u5e76\u884c\u8ba1\u7b97\u65b9\u6cd5\uff0c\u53ef\u4ee5\u6709\u6548\u63d0\u5347\u8ba1\u7b97\u6548\u7387\uff0c\u89e3\u51b3\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u95ee\u9898\u3002<\/p>\n<\/p>\n
      \u603b\u7ed3<\/h3>\n<\/p>\n
      \u5728Python\u4e2d\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u4e3b\u8981\u6709\u591a\u7ebf\u7a0b\u3001\u591a\u8fdb\u7a0b\u548c\u7b2c\u4e09\u65b9\u5e93\uff08\u5982Dask\u3001Joblib\uff09\u7b49\u65b9\u6cd5\u3002\u591a\u7ebf\u7a0b\u9002\u7528\u4e8eI\/O\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u591a\u8fdb\u7a0b\u9002\u7528\u4e8eCPU\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u800c\u7b2c\u4e09\u65b9\u5e93\u53ef\u4ee5\u63d0\u4f9b\u66f4\u9ad8\u7ea7\u7684\u5e76\u884c\u8ba1\u7b97\u80fd\u529b\u3002\u901a\u8fc7\u5408\u7406\u9009\u62e9\u5e76\u884c\u8ba1\u7b97\u65b9\u6cd5\u5e76\u8fdb\u884c\u6027\u80fd\u4f18\u5316\u548c\u8c03\u8bd5\uff0c\u53ef\u4ee5\u6709\u6548\u63d0\u5347\u8ba1\u7b97\u6548\u7387\uff0c\u89e3\u51b3\u590d\u6742\u7684\u8ba1\u7b97\u95ee\u9898\u3002<\/p>\n<\/p>\n
      \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
       \u5728Python\u4e2d\uff0c\u4ec0\u4e48\u662f\u5e76\u884c\u8ba1\u7b97\uff0c\u4e3a\u4ec0\u4e48\u8981\u4f7f\u7528\u5b83\uff1f<\/strong>
      \u5e76\u884c\u8ba1\u7b97\u662f\u4e00\u79cd\u540c\u65f6\u6267\u884c\u591a\u4e2a\u8ba1\u7b97\u4efb\u52a1\u7684\u6280\u672f\uff0c\u5b83\u80fd\u591f\u663e\u8457\u63d0\u9ad8\u7a0b\u5e8f\u7684\u8fd0\u884c\u6548\u7387\u3002Python\u4e2d\u7684\u5e76\u884c\u8ba1\u7b97\u4e3b\u8981\u7528\u4e8e\u5904\u7406\u5927\u91cf\u6570\u636e\u6216\u9700\u8981\u8fdb\u884c\u5bc6\u96c6\u8ba1\u7b97\u7684\u4efb\u52a1\u3002\u901a\u8fc7\u5e76\u884c\u8ba1\u7b97\uff0c\u53ef\u4ee5\u5145\u5206\u5229\u7528\u591a\u6838\u5904\u7406\u5668\u7684\u4f18\u52bf\uff0c\u4ece\u800c\u52a0\u901f\u4efb\u52a1\u7684\u5b8c\u6210\u3002<\/p>\n
      Python\u4e2d\u6709\u54ea\u4e9b\u5e38\u7528\u7684\u5e76\u884c\u8ba1\u7b97\u5e93\uff1f<\/strong>
      Python\u63d0\u4f9b\u4e86\u591a\u4e2a\u5e93\u6765\u5b9e\u73b0\u5e76\u884c\u8ba1\u7b97\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u5305\u62ecmultiprocessing<\/code>\u3001concurrent.futures<\/code>\u548cjoblib<\/code>\u3002multiprocessing<\/code>\u6a21\u5757\u5141\u8bb8\u521b\u5efa\u591a\u4e2a\u8fdb\u7a0b\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u53ef\u4ee5\u5728\u72ec\u7acb\u7684CPU\u6838\u5fc3\u4e0a\u8fd0\u884c\uff1bconcurrent.futures<\/code>\u63d0\u4f9b\u4e86\u7ebf\u7a0b\u6c60\u548c\u8fdb\u7a0b\u6c60\u7684\u9ad8\u5c42\u63a5\u53e3\uff0c\u7b80\u5316\u4e86\u5e76\u884c\u4efb\u52a1\u7684\u7ba1\u7406\uff1b\u800cjoblib<\/code>\u5219\u5e38\u7528\u4e8e\u5e76\u884c\u5316\u6570\u636e\u5904\u7406\u548c\u673a\u5668\u5b66\u4e60\u4efb\u52a1\u3002<\/p>\n
      \u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u5e76\u884c\u8ba1\u7b97\u65b9\u5f0f\uff1f<\/strong>
      \u9009\u62e9\u5e76\u884c\u8ba1\u7b97\u65b9\u5f0f\u65f6\uff0c\u9700\u8981\u8003\u8651\u4efb\u52a1\u7684\u7279\u6027\u548c\u8d44\u6e90\u7684\u4f7f\u7528\u3002\u5bf9\u4e8eI\/O\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u4f7f\u7528\u591a\u7ebf\u7a0b\u53ef\u80fd\u66f4\u6709\u6548\uff0c\u56e0\u4e3a\u5b83\u53ef\u4ee5\u5728\u7b49\u5f85I\/O\u64cd\u4f5c\u65f6\u5207\u6362\u6267\u884c\u5176\u4ed6\u4efb\u52a1\u3002\u800c\u5bf9\u4e8eCPU\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u4f7f\u7528\u591a\u8fdb\u7a0b\u901a\u5e38\u66f4\u4e3a\u5408\u9002\uff0c\u56e0\u4e3a\u5b83\u80fd\u6709\u6548\u5229\u7528\u591a\u6838\u5904\u7406\u5668\u7684\u8ba1\u7b97\u80fd\u529b\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\uff0c\u8bc4\u4f30\u4efb\u52a1\u7684\u6027\u8d28\u5e76\u8fdb\u884c\u9009\u62e9\uff0c\u53ef\u4ee5\u8fbe\u5230\u6700\u4f73\u7684\u6027\u80fd\u4f18\u5316\u6548\u679c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\uff1a\u4f7f\u7528\u591a\u7ebf\u7a0b\u3001\u591a\u8fdb\u7a0b\u4ee5\u53ca\u7b2c\u4e09\u65b9\u5e93\u5982Dask\u548cJoblib\u3002\u672c\u6587\u5c06 […]","protected":false},"author":3,"featured_media":1070681,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1070674"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1070674"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1070674\/revisions"}],"predecessor-version":[{"id":1070683,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1070674\/revisions\/1070683"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1070681"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1070674"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1070674"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1070674"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}