在 Python 中，可以使用多种方法来编写并行程序：
- 使用 Python 的多线程模块
threading，可以创建多个线程来并行执行任务。例如：
import threading
def my_function(arg):
# Do something with 'arg'
print(arg)
threads = []
for i in range(5):
thread = threading.Thread(target=my_function, args=(i,))
thread.start()
threads.append(thread)
# Wait for all threads to complete
for thread in threads:
thread.join()
- 使用 Python 的多进程模块
multiprocessing，您可以创建多个进程来并行执行任务。例如：
import multiprocessing
def my_function(arg):
# Do something with 'arg'
print(arg)
processes = []
for i in range(5):
process = multiprocessing.Process(target=my_function, args=(i,))
process.start()
processes.append(process)
# Wait for all processes to complete
for process in processes:
process.join()
- 使用 Python 的线程池模块
concurrent.futures，您可以使用线程池或进程池来分配任务并行执行。例如：
import concurrent.futures
def my_function(arg):
# Do something with 'arg'
return arg
# Create a thread pool
with concurrent.futures.ThreadPoolExecutor() as executor:
# Submit work to the pool
results = [executor.submit(my_function, i) for i in range(5)]
# Wait for the results to complete
for result in concurrent.futures.as_completed(results):
print(result.result())
# You can also use a process pool by replacing 'ThreadPoolExecutor' with 'ProcessPoolExecutor'
注意，在 Python 中，线程和进程的效率通常不如 C 程序中的线程和进程，因为 Python 的解释器有一个
