pythonerror-handlingconcurrencymultiprocessingconcurrent.futures

Cancelling All Tasks on Failure with `concurrent.futures` in Python


I am using Python's concurrent.futures library with ThreadPoolExecutor and ProcessPoolExecutor. I want to implement a mechanism to cancel all running or unexecuted tasks if any one of the tasks fails. Specifically, I want to:

  1. Cancel all futures (both running and unexecuted) when a task fails.
  2. Raise the error that caused the first task to fail if that error is silently ignored; otherwise, let Python raise it naturally.

Here is the approach I have tried:

from concurrent.futures import ProcessPoolExecutor, as_completed
from functools import partial

copy_func = partial(copy_from, table_name=table_name, column_string=column_string)
with ProcessPoolExecutor(max_workers=cores_to_use) as executor:
    futures = {executor.submit(copy_func, file_path): file_path for file_path in file_path_list}
    for f in as_completed(futures):
        try:
            f.result()
        except Exception as e:
            executor.shutdown(wait=False)  # Attempt to stop the executor
            for future in futures:
                future.cancel()  # Cancel all futures
            raise e  # Raise the exception

Questions:

Thank you!


Solution

  • Is this the correct way to handle task cancellation in ThreadPoolExecutor and ProcessPoolExecutor?

    Your approach is almost correct, but there are some important things to note:

    To cancel the running tasks effectively, you need to handle it in a way that your tasks can be interrupted by checking a flag or catching an exception.

    Are there any better approach to achieve this functionality?

    A better approach would be to use a combination of:

    Here's the code:

    from concurrent.futures import ProcessPoolExecutor, as_completed
    from functools import partial
    import threading
    
    # Cancellation event that worker tasks can check
    cancel_event = threading.Event()
    
    def copy_from(file_path, table_name, column_string):
        if cancel_event.is_set():
            print(f"Task {file_path} cancelled.")
            return
        # Simulate some work or copying logic
        try:
            # Your actual copy operation here
            if file_path == "some_bad_file":
                raise ValueError("Simulated task failure")
            print(f"Processing {file_path}")
        except Exception as e:
            cancel_event.set()  # Set the cancellation flag
            raise e
    
    # Function to handle task execution
    def run_tasks(file_path_list, table_name, column_string, cores_to_use):
        copy_func = partial(copy_from, table_name=table_name, column_string=column_string)
    
        with ProcessPoolExecutor(max_workers=cores_to_use) as executor:
            futures = {executor.submit(copy_func, file_path): file_path for file_path in file_path_list}
    
            try:
                for f in as_completed(futures):
                    if cancel_event.is_set():
                        # If cancellation has been triggered, skip waiting for further results
                        break
                    # Attempt to get the result and raise any exception if task failed
                    f.result()
            except Exception as e:
                cancel_event.set()  # Cancel all tasks
                for future in futures:
                    future.cancel()  # Attempt to cancel futures that haven't started yet
                raise e  # Re-raise the exception
    
    file_path_list = ["file1", "file2", "some_bad_file", "file4"]
    table_name = "my_table"
    column_string = "col1, col2"
    
    try:
        run_tasks(file_path_list, table_name, column_string, cores_to_use=4)
    except Exception as ex:
        print(f"An error occurred: {ex}")
    

    How can I ensure that the raised exception is not silently ignored?

    To ensure that the exception is not silently ignored, it is critical to:

    How can I free up all resources used by concurrent.futures after an exception?

    By default, when the with ProcessPoolExecutor block exists, it calls executor.shutdown(), which releases resources. This is handled automatically by Python's context manager. However, adding executor.shutdown(wait=False) is unnecessary, as you don't need to prematurely shut down the executor if you've handled cancellation properly.

    To ensure resources are properly cleaned:

    I hope this will help you a little.