Question: 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:  Cancel all futures (both running and unexecuted) when a task fails. 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:  Is this the correct way to handle task cancellation in ThreadPoolExecutor and ProcessPoolExecutor? Are there any better approaches to achieve this functionality? How can I ensure that the raised exception is not silently ignored? How can I free up all resources used by concurrent.futures after an exception?  Thank you!

Answer: 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:  executor.shutdown(wait=False) only prevents new tasks from being submitted. It doesn't actually cancel the running tasks. The tasks that have already started executing will continue until completion. future.cancel() only cancels tasks that are still in the queue (not started). If a task has already started, future.cancel() won't stop it.  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:  Graceful task cancellation: Your tasks should periodically check for a flag or signal to cancel themselves. handling exceptions properly: You can use a try/except block with the worker function(copy_from) itself to detect failure and propagate it.  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:  Always call f.result() in the for f in as_completed(futures) loop. This will raise any exceptions that occurred during task execution. Propagate the exception using raise a after canceling other tasks, as you have done.  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:  Tasks that haven't started should be canceled with future.cancel(). Tasks that have already started will be stopped by setting the cancellation flag, and when all tasks finish, the context manager will clean up the pool and free up resources.  I hope this will help you a little.