from concurrent import futures
时间: 2023-11-14 07:06:52 浏览: 41
As an AI language model, I do not have access to the `concurrent` module or any other modules of Python. However, I can provide a brief explanation of what the `concurrent` module is and what it is used for.
The `concurrent` module is a built-in Python module that provides a high-level interface for asynchronously executing functions using threads or processes. It includes the `futures` module, which provides a way to execute a function asynchronously and retrieve its result later. The `concurrent.futures` module is typically used to speed up IO-bound tasks, such as network requests, by allowing multiple requests to be executed in parallel.
The `concurrent.futures` module provides two classes for submitting tasks: `ThreadPoolExecutor` and `ProcessPoolExecutor`. Both classes provide a `submit()` method that takes a function and its arguments as input and returns a `Future` object. A `Future` object represents the result of an asynchronous computation that has not yet completed. The `Future` object can be used to check if the computation is complete and retrieve the result when it is.
The `concurrent.futures` module also provides a `wait()` function that can be used to wait for multiple `Future` objects to complete. The `wait()` function takes a list of `Future` objects and blocks until all of them have completed.
Overall, the `concurrent.futures` module provides a simple and convenient way to execute functions asynchronously and retrieve their results. It can be a useful tool for speeding up IO-bound tasks and improving the performance of Python applications.