{"id":1069286,"date":"2024-12-31T16:50:40","date_gmt":"2024-12-31T08:50:40","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1069286.html"},"modified":"2024-12-31T16:50:42","modified_gmt":"2024-12-31T08:50:42","slug":"python%e7%b1%bb%e4%b8%ad%e7%9a%84%e6%96%b9%e6%b3%95%e5%a6%82%e4%bd%95%e8%b0%83%e7%94%a8%e5%a4%9a%e7%ba%bf%e7%a8%8b","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1069286.html","title":{"rendered":"python\u7c7b\u4e2d\u7684\u65b9\u6cd5\u5982\u4f55\u8c03\u7528\u591a\u7ebf\u7a0b"},"content":{"rendered":"

\"python\u7c7b\u4e2d\u7684\u65b9\u6cd5\u5982\u4f55\u8c03\u7528\u591a\u7ebf\u7a0b\"<\/p>\n

Python\u7c7b\u4e2d\u7684\u65b9\u6cd5\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u8c03\u7528\u591a\u7ebf\u7a0b<\/strong>\uff0c\u5982\u4f7f\u7528threading<\/code>\u6a21\u5757\u3001concurrent.futures.ThreadPoolExecutor<\/code>\u3001\u4ee5\u53camultiprocessing<\/code>\u6a21\u5757\u7b49\u3002\u5728\u7c7b\u4e2d\u8c03\u7528\u591a\u7ebf\u7a0b\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528threading.Thread<\/code>\u521b\u5efa\u7ebf\u7a0b\u3001\u4f7f\u7528ThreadPoolExecutor<\/code>\u7ba1\u7406\u7ebf\u7a0b\u6c60\u3001\u4ee5\u53ca\u901a\u8fc7\u5b50\u7c7b\u5316\u7ebf\u7a0b\u7c7b\u6765\u521b\u5efa\u548c\u7ba1\u7406\u7ebf\u7a0b<\/strong>\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\u2014\u2014\u4f7f\u7528threading.Thread<\/code>\u521b\u5efa\u7ebf\u7a0b\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528 threading.Thread<\/code> \u521b\u5efa\u7ebf\u7a0b<\/h3>\n<\/p>\n
    \n
  1. \u5f15\u5165 threading<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 threading<\/code> \u6a21\u5757\u4ee5\u4fbf\u4f7f\u7528\u591a\u7ebf\u7a0b\u529f\u80fd\u3002<\/li>\n
  2. \u5b9a\u4e49\u7c7b\u548c\u65b9\u6cd5<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u65b9\u6cd5\u3002<\/li>\n
  3. \u521b\u5efa\u7ebf\u7a0b<\/strong>\uff1a\u4f7f\u7528 threading.Thread<\/code> \u521b\u5efa\u7ebf\u7a0b\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u7ebf\u7a0b\u3002<\/li>\n
  4. \u542f\u52a8\u7ebf\u7a0b<\/strong>\uff1a\u8c03\u7528\u7ebf\u7a0b\u5bf9\u8c61\u7684 start()<\/code> \u65b9\u6cd5\u542f\u52a8\u7ebf\u7a0b\u3002<\/li>\n
  5. \u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210<\/strong>\uff1a\u4f7f\u7528 join()<\/code> \u65b9\u6cd5\u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210\u6267\u884c\u3002<\/li>\n<\/ol>\n

    import threading<\/p>\n
    class MyClass:<\/p>\n
        def __init__(self):<\/p>\n
            self.data = []<\/p>\n
        def process_data(self, value):<\/p>\n
            """Simulate a time-consuming task."""<\/p>\n
            print(f"Processing value: {value}")<\/p>\n
            self.data.append(value * 2)<\/p>\n
        def run_in_threads(self, values):<\/p>\n
            threads = []<\/p>\n
            for value in values:<\/p>\n
                thread = threading.Thread(target=self.process_data, args=(value,))<\/p>\n
                threads.append(thread)<\/p>\n
                thread.start()<\/p>\n
            for thread in threads:<\/p>\n
                thread.join()<\/p>\n
    \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
    if __name__ == "__mAI<\/a>n__":<\/p>\n
        obj = MyClass()<\/p>\n
        obj.run_in_threads([1, 2, 3, 4, 5])<\/p>\n
        print(obj.data)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e8c\u3001\u4f7f\u7528 concurrent.futures.ThreadPoolExecutor<\/code><\/h3>\n<\/p>\n
      \n
    1. \u5f15\u5165 concurrent.futures<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 concurrent.futures<\/code> \u6a21\u5757\u3002<\/li>\n
    2. \u5b9a\u4e49\u7c7b\u548c\u65b9\u6cd5<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u65b9\u6cd5\u3002<\/li>\n
    3. \u521b\u5efa\u7ebf\u7a0b\u6c60<\/strong>\uff1a\u4f7f\u7528 ThreadPoolExecutor<\/code> \u521b\u5efa\u7ebf\u7a0b\u6c60\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u63d0\u4ea4\u7ed9\u7ebf\u7a0b\u6c60\u6267\u884c\u3002<\/li>\n
    4. \u7b49\u5f85\u7ed3\u679c<\/strong>\uff1a\u4f7f\u7528 as_completed()<\/code> \u65b9\u6cd5\u7b49\u5f85\u6240\u6709\u7ebf\u7a0b\u5b8c\u6210\uff0c\u5e76\u6536\u96c6\u7ed3\u679c\u3002<\/li>\n<\/ol>\n
      from concurrent.futures import ThreadPoolExecutor<\/p>\n
      class MyClass:<\/p>\n
          def __init__(self):<\/p>\n
              self.data = []<\/p>\n
          def process_data(self, value):<\/p>\n
              """Simulate a time-consuming task."""<\/p>\n
              print(f"Processing value: {value}")<\/p>\n
              return value * 2<\/p>\n
          def run_in_threads(self, values):<\/p>\n
              with ThreadPoolExecutor(max_workers=5) as executor:<\/p>\n
                  futures = [executor.submit(self.process_data, value) for value in values]<\/p>\n
                  for future in futures:<\/p>\n
                      result = future.result()<\/p>\n
                      self.data.append(result)<\/p>\n
      \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
      if __name__ == "__main__":<\/p>\n
          obj = MyClass()<\/p>\n
          obj.run_in_threads([1, 2, 3, 4, 5])<\/p>\n
          print(obj.data)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u4e09\u3001\u4f7f\u7528 multiprocessing<\/code> \u6a21\u5757<\/h3>\n<\/p>\n
        \n
      1. \u5f15\u5165 multiprocessing<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 multiprocessing<\/code> \u6a21\u5757\u3002<\/li>\n
      2. \u5b9a\u4e49\u7c7b\u548c\u65b9\u6cd5<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u65b9\u6cd5\u3002<\/li>\n
      3. \u521b\u5efa\u8fdb\u7a0b<\/strong>\uff1a\u4f7f\u7528 multiprocessing.Process<\/code> \u521b\u5efa\u8fdb\u7a0b\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u8fdb\u7a0b\u3002<\/li>\n
      4. \u542f\u52a8\u8fdb\u7a0b<\/strong>\uff1a\u8c03\u7528\u8fdb\u7a0b\u5bf9\u8c61\u7684 start()<\/code> \u65b9\u6cd5\u542f\u52a8\u8fdb\u7a0b\u3002<\/li>\n
      5. \u7b49\u5f85\u8fdb\u7a0b\u5b8c\u6210<\/strong>\uff1a\u4f7f\u7528 join()<\/code> \u65b9\u6cd5\u7b49\u5f85\u8fdb\u7a0b\u5b8c\u6210\u6267\u884c\u3002<\/li>\n<\/ol>\n
        import multiprocessing<\/p>\n
        class MyClass:<\/p>\n
            def __init__(self):<\/p>\n
                self.data = multiprocessing.Manager().list()<\/p>\n
            def process_data(self, value):<\/p>\n
                """Simulate a time-consuming task."""<\/p>\n
                print(f"Processing value: {value}")<\/p>\n
                self.data.append(value * 2)<\/p>\n
            def run_in_processes(self, values):<\/p>\n
                processes = []<\/p>\n
                for value in values:<\/p>\n
                    process = multiprocessing.Process(target=self.process_data, args=(value,))<\/p>\n
                    processes.append(process)<\/p>\n
                    process.start()<\/p>\n
                for process in processes:<\/p>\n
                    process.join()<\/p>\n
        \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
        if __name__ == "__main__":<\/p>\n
            obj = MyClass()<\/p>\n
            obj.run_in_processes([1, 2, 3, 4, 5])<\/p>\n
            print(list(obj.data))<\/p>\n
        <\/code><\/pre>\n<\/p>\n
        \u56db\u3001\u4f7f\u7528 concurrent.futures.ProcessPoolExecutor<\/code><\/h3>\n<\/p>\n
          \n
        1. \u5f15\u5165 concurrent.futures<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 concurrent.futures<\/code> \u6a21\u5757\u3002<\/li>\n
        2. \u5b9a\u4e49\u7c7b\u548c\u65b9\u6cd5<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u65b9\u6cd5\u3002<\/li>\n
        3. \u521b\u5efa\u8fdb\u7a0b\u6c60<\/strong>\uff1a\u4f7f\u7528 ProcessPoolExecutor<\/code> \u521b\u5efa\u8fdb\u7a0b\u6c60\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u63d0\u4ea4\u7ed9\u8fdb\u7a0b\u6c60\u6267\u884c\u3002<\/li>\n
        4. \u7b49\u5f85\u7ed3\u679c<\/strong>\uff1a\u4f7f\u7528 as_completed()<\/code> \u65b9\u6cd5\u7b49\u5f85\u6240\u6709\u8fdb\u7a0b\u5b8c\u6210\uff0c\u5e76\u6536\u96c6\u7ed3\u679c\u3002<\/li>\n<\/ol>\n
          from concurrent.futures import ProcessPoolExecutor<\/p>\n
          class MyClass:<\/p>\n
              def __init__(self):<\/p>\n
                  self.data = []<\/p>\n
              def process_data(self, value):<\/p>\n
                  """Simulate a time-consuming task."""<\/p>\n
                  print(f"Processing value: {value}")<\/p>\n
                  return value * 2<\/p>\n
              def run_in_processes(self, values):<\/p>\n
                  with ProcessPoolExecutor(max_workers=5) as executor:<\/p>\n
                      futures = [executor.submit(self.process_data, value) for value in values]<\/p>\n
                      for future in futures:<\/p>\n
                          result = future.result()<\/p>\n
                          self.data.append(result)<\/p>\n
          \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
          if __name__ == "__main__":<\/p>\n
              obj = MyClass()<\/p>\n
              obj.run_in_processes([1, 2, 3, 4, 5])<\/p>\n
              print(obj.data)<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u4e94\u3001\u4f7f\u7528 asyncio<\/code> \u6a21\u5757<\/h3>\n<\/p>\n
            \n
          1. \u5f15\u5165 asyncio<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 asyncio<\/code> \u6a21\u5757\u3002<\/li>\n
          2. \u5b9a\u4e49\u7c7b\u548c\u5f02\u6b65\u65b9\u6cd5<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u5f02\u6b65\u65b9\u6cd5\u3002<\/li>\n
          3. \u521b\u5efa\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 asyncio.create_task<\/code> \u521b\u5efa\u4efb\u52a1\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u5f02\u6b65\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u4efb\u52a1\u3002<\/li>\n
          4. \u8fd0\u884c\u4e8b\u4ef6\u5faa\u73af<\/strong>\uff1a\u4f7f\u7528 asyncio.run<\/code> \u8fd0\u884c\u4e8b\u4ef6\u5faa\u73af\u3002<\/li>\n<\/ol>\n
            import asyncio<\/p>\n
            class MyClass:<\/p>\n
                def __init__(self):<\/p>\n
                    self.data = []<\/p>\n
                async def process_data(self, value):<\/p>\n
                    """Simulate a time-consuming task."""<\/p>\n
                    print(f"Processing value: {value}")<\/p>\n
                    await asyncio.sleep(1)<\/p>\n
                    self.data.append(value * 2)<\/p>\n
                async def run_in_tasks(self, values):<\/p>\n
                    tasks = [self.process_data(value) for value in values]<\/p>\n
                    await asyncio.gather(*tasks)<\/p>\n
            \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
            if __name__ == "__main__":<\/p>\n
                obj = MyClass()<\/p>\n
                asyncio.run(obj.run_in_tasks([1, 2, 3, 4, 5]))<\/p>\n
                print(obj.data)<\/p>\n
            <\/code><\/pre>\n<\/p>\n
            \u516d\u3001\u4f7f\u7528 gevent<\/code> \u6a21\u5757<\/h3>\n<\/p>\n
              \n
            1. \u5f15\u5165 gevent<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 gevent<\/code> \u6a21\u5757\u3002<\/li>\n
            2. \u5b9a\u4e49\u7c7b\u548c\u65b9\u6cd5<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u65b9\u6cd5\u3002<\/li>\n
            3. \u521b\u5efa\u7eff\u8272\u7ebf\u7a0b<\/strong>\uff1a\u4f7f\u7528 gevent.spawn<\/code> \u521b\u5efa\u7eff\u8272\u7ebf\u7a0b\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u7eff\u8272\u7ebf\u7a0b\u3002<\/li>\n
            4. \u542f\u52a8\u7eff\u8272\u7ebf\u7a0b<\/strong>\uff1a\u4f7f\u7528 gevent.joinall<\/code> \u542f\u52a8\u7eff\u8272\u7ebf\u7a0b\u5e76\u7b49\u5f85\u5b8c\u6210\u3002<\/li>\n<\/ol>\n
              import gevent<\/p>\n
              from gevent import monkey<\/p>\n
              Monkey patch to make standard library cooperative<\/strong><\/h2>\n
              monkey.patch_all()<\/p>\n
              class MyClass:<\/p>\n
                  def __init__(self):<\/p>\n
                      self.data = []<\/p>\n
                  def process_data(self, value):<\/p>\n
                      """Simulate a time-consuming task."""<\/p>\n
                      print(f"Processing value: {value}")<\/p>\n
                      self.data.append(value * 2)<\/p>\n
                  def run_in_greenlets(self, values):<\/p>\n
                      greenlets = [gevent.spawn(self.process_data, value) for value in values]<\/p>\n
                      gevent.joinall(greenlets)<\/p>\n
              \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
              if __name__ == "__main__":<\/p>\n
                  obj = MyClass()<\/p>\n
                  obj.run_in_greenlets([1, 2, 3, 4, 5])<\/p>\n
                  print(obj.data)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u4e03\u3001\u4f7f\u7528 celery<\/code> \u5206\u5e03\u5f0f\u4efb\u52a1\u961f\u5217<\/h3>\n<\/p>\n
                \n
              1. \u5f15\u5165 celery<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 celery<\/code> \u6a21\u5757\u3002<\/li>\n
              2. \u5b9a\u4e49\u7c7b\u548c\u4efb\u52a1<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u4efb\u52a1\u3002<\/li>\n
              3. \u914d\u7f6e Celery<\/strong>\uff1a\u914d\u7f6e Celery \u4ee5\u4fbf\u4f7f\u7528\u5206\u5e03\u5f0f\u4efb\u52a1\u961f\u5217\u3002<\/li>\n
              4. \u521b\u5efa\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 celery.task<\/code> \u521b\u5efa\u4efb\u52a1\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u4efb\u52a1\u3002<\/li>\n
              5. \u542f\u52a8\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 task.delay<\/code> \u542f\u52a8\u4efb\u52a1\u5e76\u7b49\u5f85\u5b8c\u6210\u3002<\/li>\n<\/ol>\n
                from celery import Celery<\/p>\n
                app = Celery('tasks', broker='pyamqp:\/\/guest@localhost\/\/')<\/p>\n
                class MyClass:<\/p>\n
                    def __init__(self):<\/p>\n
                        self.data = []<\/p>\n
                    @app.task<\/p>\n
                    def process_data(self, value):<\/p>\n
                        """Simulate a time-consuming task."""<\/p>\n
                        print(f"Processing value: {value}")<\/p>\n
                        return value * 2<\/p>\n
                    def run_in_tasks(self, values):<\/p>\n
                        results = [self.process_data.delay(value) for value in values]<\/p>\n
                        for result in results:<\/p>\n
                            self.data.append(result.get())<\/p>\n
                \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
                if __name__ == "__main__":<\/p>\n
                    obj = MyClass()<\/p>\n
                    obj.run_in_tasks([1, 2, 3, 4, 5])<\/p>\n
                    print(obj.data)<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u516b\u3001\u4f7f\u7528 dask<\/code> \u5206\u5e03\u5f0f\u8ba1\u7b97<\/h3>\n<\/p>\n
                  \n
                1. \u5f15\u5165 dask<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 dask<\/code> \u6a21\u5757\u3002<\/li>\n
                2. \u5b9a\u4e49\u7c7b\u548c\u4efb\u52a1<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u4efb\u52a1\u3002<\/li>\n
                3. \u521b\u5efa Dask \u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 dask.delayed<\/code> \u521b\u5efa Dask \u4efb\u52a1\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u4efb\u52a1\u3002<\/li>\n
                4. \u542f\u52a8\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 dask.compute<\/code> \u542f\u52a8\u4efb\u52a1\u5e76\u7b49\u5f85\u5b8c\u6210\u3002<\/li>\n<\/ol>\n
                  import dask<\/p>\n
                  from dask import delayed<\/p>\n
                  class MyClass:<\/p>\n
                      def __init__(self):<\/p>\n
                          self.data = []<\/p>\n
                      def process_data(self, value):<\/p>\n
                          """Simulate a time-consuming task."""<\/p>\n
                          print(f"Processing value: {value}")<\/p>\n
                          return value * 2<\/p>\n
                      def run_in_tasks(self, values):<\/p>\n
                          tasks = [delayed(self.process_data)(value) for value in values]<\/p>\n
                          results = dask.compute(*tasks)<\/p>\n
                          self.data.extend(results)<\/p>\n
                  \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
                  if __name__ == "__main__":<\/p>\n
                      obj = MyClass()<\/p>\n
                      obj.run_in_tasks([1, 2, 3, 4, 5])<\/p>\n
                      print(obj.data)<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u4e5d\u3001\u4f7f\u7528 joblib<\/code> \u5e76\u884c\u8ba1\u7b97<\/h3>\n<\/p>\n
                    \n
                  1. \u5f15\u5165 joblib<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 joblib<\/code> \u6a21\u5757\u3002<\/li>\n
                  2. \u5b9a\u4e49\u7c7b\u548c\u4efb\u52a1<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u4efb\u52a1\u3002<\/li>\n
                  3. \u521b\u5efa\u5e76\u884c\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 joblib.Parallel<\/code> \u521b\u5efa\u5e76\u884c\u4efb\u52a1\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u4efb\u52a1\u3002<\/li>\n
                  4. \u542f\u52a8\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 joblib.Parallel<\/code> \u548c joblib.delayed<\/code> \u542f\u52a8\u4efb\u52a1\u5e76\u7b49\u5f85\u5b8c\u6210\u3002<\/li>\n<\/ol>\n
                    from joblib import Parallel, delayed<\/p>\n
                    class MyClass:<\/p>\n
                        def __init__(self):<\/p>\n
                            self.data = []<\/p>\n
                        def process_data(self, value):<\/p>\n
                            """Simulate a time-consuming task."""<\/p>\n
                            print(f"Processing value: {value}")<\/p>\n
                            return value * 2<\/p>\n
                        def run_in_tasks(self, values):<\/p>\n
                            results = Parallel(n_jobs=5)(delayed(self.process_data)(value) for value in values)<\/p>\n
                            self.data.extend(results)<\/p>\n
                    \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
                    if __name__ == "__main__":<\/p>\n
                        obj = MyClass()<\/p>\n
                        obj.run_in_tasks([1, 2, 3, 4, 5])<\/p>\n
                        print(obj.data)<\/p>\n
                    <\/code><\/pre>\n<\/p>\n
                    \u5341\u3001\u4f7f\u7528 ray<\/code> \u5206\u5e03\u5f0f\u8ba1\u7b97<\/h3>\n<\/p>\n
                      \n
                    1. \u5f15\u5165 ray<\/code> \u6a21\u5757<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5bfc\u5165 ray<\/code> \u6a21\u5757\u3002<\/li>\n
                    2. \u5b9a\u4e49\u7c7b\u548c\u8fdc\u7a0b\u51fd\u6570<\/strong>\uff1a\u5728\u7c7b\u4e2d\u5b9a\u4e49\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u8fdc\u7a0b\u51fd\u6570\u3002<\/li>\n
                    3. \u521d\u59cb\u5316 Ray<\/strong>\uff1a\u4f7f\u7528 ray.init<\/code> \u521d\u59cb\u5316 Ray\u3002<\/li>\n
                    4. \u521b\u5efa\u8fdc\u7a0b\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 ray.remote<\/code> \u521b\u5efa\u8fdc\u7a0b\u4efb\u52a1\u5bf9\u8c61\uff0c\u5e76\u5c06\u7c7b\u7684\u65b9\u6cd5\u4f5c\u4e3a\u76ee\u6807\u51fd\u6570\u4f20\u9012\u7ed9\u4efb\u52a1\u3002<\/li>\n
                    5. \u542f\u52a8\u4efb\u52a1<\/strong>\uff1a\u4f7f\u7528 task.remote<\/code> \u542f\u52a8\u4efb\u52a1\u5e76\u7b49\u5f85\u5b8c\u6210\u3002<\/li>\n<\/ol>\n
                      import ray<\/p>\n
                      ray.init()<\/p>\n
                      class MyClass:<\/p>\n
                          def __init__(self):<\/p>\n
                              self.data = []<\/p>\n
                          @ray.remote<\/p>\n
                          def process_data(self, value):<\/p>\n
                              """Simulate a time-consuming task."""<\/p>\n
                              print(f"Processing value: {value}")<\/p>\n
                              return value * 2<\/p>\n
                          def run_in_tasks(self, values):<\/p>\n
                              results = ray.get([self.process_data.remote(value) for value in values])<\/p>\n
                              self.data.extend(results)<\/p>\n
                      \u4f7f\u7528\u793a\u4f8b<\/strong><\/h2>\n
                      if __name__ == "__main__":<\/p>\n
                          obj = MyClass()<\/p>\n
                          obj.run_in_tasks([1, 2, 3, 4, 5])<\/p>\n
                          print(obj.data)<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                      \u901a\u8fc7\u4ee5\u4e0a\u591a\u79cd\u65b9\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u5728 Python \u7c7b\u4e2d\u6709\u6548\u5730\u8c03\u7528\u591a\u7ebf\u7a0b\u6216\u591a\u8fdb\u7a0b\uff0c\u4ece\u800c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u5e76\u53d1\u6027\u80fd\u3002\u9009\u62e9\u5408\u9002\u7684\u5e76\u53d1\u6a21\u578b\u548c\u5e93\u53d6\u51b3\u4e8e\u5177\u4f53\u7684\u5e94\u7528\u573a\u666f\u548c\u9700\u6c42\u3002<\/p>\n<\/p>\n
                      \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                       \u5982\u4f55\u5728Python\u7c7b\u4e2d\u521b\u5efa\u548c\u7ba1\u7406\u591a\u7ebf\u7a0b\uff1f<\/strong>
                      \u5728Python\u7c7b\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528threading<\/code>\u6a21\u5757\u6765\u521b\u5efa\u548c\u7ba1\u7406\u591a\u7ebf\u7a0b\u3002\u9996\u5148\uff0c\u9700\u8981\u5728\u7c7b\u4e2d\u5b9a\u4e49\u4e00\u4e2a\u65b9\u6cd5\uff0c\u5e76\u5728\u8be5\u65b9\u6cd5\u4e2d\u5b9e\u73b0\u9700\u8981\u5e76\u53d1\u6267\u884c\u7684\u903b\u8f91\u3002\u63a5\u7740\uff0c\u53ef\u4ee5\u521b\u5efa\u7ebf\u7a0b\u5bf9\u8c61\u5e76\u6307\u5b9a\u76ee\u6807\u51fd\u6570\uff0c\u7136\u540e\u8c03\u7528start()<\/code>\u65b9\u6cd5\u6765\u542f\u52a8\u7ebf\u7a0b\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u7ebf\u7a0b\u7684\u751f\u547d\u5468\u671f\u548c\u6570\u636e\u5171\u4eab\u9700\u8981\u59a5\u5584\u7ba1\u7406\uff0c\u4ee5\u907f\u514d\u7ade\u4e89\u6761\u4ef6\u548c\u6570\u636e\u4e0d\u4e00\u81f4\u7684\u95ee\u9898\u3002<\/p>\n
                      \u5728\u591a\u7ebf\u7a0b\u8c03\u7528\u4e2d\uff0c\u5982\u4f55\u4fdd\u8bc1\u7ebf\u7a0b\u5b89\u5168\uff1f<\/strong>
                      \u786e\u4fdd\u7ebf\u7a0b\u5b89\u5168\u7684\u5e38\u7528\u65b9\u6cd5\u662f\u4f7f\u7528\u9501\u673a\u5236\uff0c\u4f8b\u5982threading.Lock<\/code>\u3002\u5728\u6267\u884c\u9700\u8981\u5171\u4eab\u6570\u636e\u7684\u64cd\u4f5c\u524d\uff0c\u5148\u83b7\u53d6\u9501\uff0c\u64cd\u4f5c\u5b8c\u6210\u540e\u518d\u91ca\u653e\u9501\u3002\u8fd9\u6837\u53ef\u4ee5\u907f\u514d\u591a\u4e2a\u7ebf\u7a0b\u540c\u65f6\u8bbf\u95ee\u540c\u4e00\u8d44\u6e90\u5bfc\u81f4\u7684\u6570\u636e\u51b2\u7a81\u3002\u6b64\u5916\uff0c\u4f7f\u7528threading.RLock<\/code>\u4e5f\u53ef\u4ee5\u66f4\u7075\u6d3b\u5730\u5904\u7406\u5d4c\u5957\u9501\u7684\u60c5\u51b5\u3002<\/p>\n
                      \u5982\u4f55\u5728Python\u7c7b\u4e2d\u5904\u7406\u591a\u7ebf\u7a0b\u7684\u5f02\u5e38\uff1f<\/strong>
                      \u5728\u591a\u7ebf\u7a0b\u73af\u5883\u4e0b\uff0c\u5982\u679c\u7ebf\u7a0b\u6267\u884c\u8fc7\u7a0b\u4e2d\u53d1\u751f\u5f02\u5e38\uff0c\u9ed8\u8ba4\u60c5\u51b5\u4e0b\u8be5\u5f02\u5e38\u4e0d\u4f1a\u5f71\u54cd\u4e3b\u7ebf\u7a0b\u7684\u8fd0\u884c\u3002\u4e3a\u4e86\u6355\u83b7\u548c\u5904\u7406\u7ebf\u7a0b\u4e2d\u7684\u5f02\u5e38\uff0c\u53ef\u4ee5\u5728\u76ee\u6807\u65b9\u6cd5\u5185\u4f7f\u7528try-except<\/code>\u7ed3\u6784\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u8bb0\u5f55\u5f02\u5e38\u4fe1\u606f\u5e76\u91c7\u53d6\u76f8\u5e94\u7684\u63aa\u65bd\uff0c\u6bd4\u5982\u91cd\u542f\u7ebf\u7a0b\u6216\u8bb0\u5f55\u9519\u8bef\u65e5\u5fd7\uff0c\u4ece\u800c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u5065\u58ee\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u7c7b\u4e2d\u7684\u65b9\u6cd5\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u8c03\u7528\u591a\u7ebf\u7a0b\uff0c\u5982\u4f7f\u7528threading\u6a21\u5757\u3001concurrent.futu […]","protected":false},"author":3,"featured_media":1069299,"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\/1069286"}],"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=1069286"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1069286\/revisions"}],"predecessor-version":[{"id":1069302,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1069286\/revisions\/1069302"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1069299"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1069286"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1069286"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1069286"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}