{"id":2516,"library":"futures","title":"futures (Python 2 Backport of concurrent.futures)","description":"The `futures` library is a backport of the `concurrent.futures` module from Python 3, providing a high-level interface for asynchronously executing callables using thread or process pools. It is designed exclusively for Python 2 environments (specifically 2.6 and 2.7), offering a structured way to manage concurrent tasks in older Python runtimes. The current version is 3.4.0, released in October 2022.","status":"maintenance","version":"3.4.0","language":"en","source_language":"en","source_url":"https://github.com/agronholm/pythonfutures","tags":["python2","backport","concurrency","futures","threading","multiprocessing"],"install":[{"cmd":"pip install futures","lang":"bash","label":"Install for Python 2"}],"dependencies":[],"imports":[{"symbol":"ThreadPoolExecutor","correct":"from concurrent.futures import ThreadPoolExecutor"},{"symbol":"ProcessPoolExecutor","correct":"from concurrent.futures import ProcessPoolExecutor"},{"note":"The top-level 'futures' package is an internal implementation detail; direct import of `concurrent.futures` is the correct pattern.","wrong":"import futures","symbol":"Future","correct":"from concurrent.futures import Future"}],"quickstart":{"code":"import time\nfrom concurrent.futures import ThreadPoolExecutor\n\ndef my_task(name):\n    print \"Starting task %s\" % name # Python 2 print statement\n    time.sleep(1) # Simulate work\n    print \"Finished task %s\" % name # Python 2 print statement\n    return \"Result from %s\" % name\n\nif __name__ == '__main__':\n    # Create a thread pool with 2 workers\n    with ThreadPoolExecutor(max_workers=2) as executor:\n        # Submit tasks\n        future1 = executor.submit(my_task, \"Alpha\")\n        future2 = executor.submit(my_task, \"Beta\")\n\n        # Get results (blocks until complete)\n        print future1.result()\n        print future2.result()\n\n    print \"All concurrent tasks completed.\" # Python 2 print statement","lang":"python","description":"Demonstrates basic usage of `ThreadPoolExecutor` to run two simple tasks concurrently and retrieve their results. The `with` statement ensures proper shutdown of the executor. This code is designed for Python 2."},"warnings":[{"message":"This library is a backport specifically for Python 2.6/2.7. It is *not* compatible with Python 3, where `concurrent.futures` is part of the standard library. Attempting to install or use this package on Python 3 will lead to syntax errors or other runtime issues.","severity":"breaking","affected_versions":"All versions of `futures` on Python 3"},{"message":"The `ProcessPoolExecutor` class in this Python 2 backport has known, unfixable problems and should not be relied upon for mission-critical work. Consider `ThreadPoolExecutor` for I/O-bound tasks or alternative multiprocessing solutions for CPU-bound tasks.","severity":"gotcha","affected_versions":"All versions"},{"message":"Exceptions raised within tasks submitted to an executor are stored in the `Future` object, not immediately re-raised. They will only be re-raised when `future.result()` is called or when iterating over results from `executor.map()` or `as_completed()`. If `future.result()` is never called for a future that failed, the exception may be silently ignored.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Ensure `max_workers` is sufficiently large or avoid circular dependencies between tasks within the same executor.","message":"When using `ThreadPoolExecutor`, be cautious of deadlocks if tasks wait on the results of other tasks submitted to the *same* executor, especially if the pool size (`max_workers`) is insufficient to prevent all workers from becoming blocked simultaneously.","severity":"gotcha","affected_versions":"All versions"}],"env_vars":null,"last_verified":"2026-04-10T00:00:00.000Z","next_check":"2026-07-09T00:00:00.000Z"}