Jason Brownlee's Blog, page 40

Multiprocessing Pool and the Global Interpreter Lock (GIL)

You can achieve full parallelism in Python with the multiprocessing pool, side-stepping the GIL. In this tutorial you will discover the relationship between the multiprocessing pool and the Global Interpreter Lock in Python. Let’s get started. Multiprocessing Pool Affected By GIL? The multiprocessing pool provides a pool of reusable workers for executing ad hoc tasks […]

Multiprocessing Pool Restarts Workers if Killed

Child worker processes in the multiprocessing pool will be restarted automatically if killed. In this tutorial you will discover what happens if a child worker process is killed in the multiprocessing pool in Python. Let’s get started. What If One Worker is Killed The multiprocessing pool provides a pool of reusable workers for executing ad […]

Multiprocessing Pool When Are Workers Started

Child worker processes are started automatically after creating an instance of the multiprocessing.Pool class. In this tutorial you will discover when the child worker processes are created in the multiprocessing pool in Python. Let’s get started. Multiprocessing Pool Workers The multiprocessing pool provides a pool of reusable workers for executing ad hoc tasks with process-based […]

Does the Multiprocessing Pool Stop Main From Exiting

The multiprocessing pool will be closed automatically by the Python garbage collector, if required. It will not prevent the main process from exiting and the child worker processes will not keep running if the main process exits without closing the pool. In this tutorial, we will explore what happens if you forget or are unable […]

Multiprocessing Pool PEP and History

You can read the PEP for the multiprocessing module and Python release changelogs in order to learn the history of the multiprocessing pool. In this tutorial you will discover the history of the multiprocessing pool in Python. Let’s get started. Multiprocessing Pool Authors The multiprocessing pool was developed by Jesse Noller and Richard Oudkerk. Specifically, […]

How to Configure Multiprocessing Pool.map() Chunksize

You can execute tasks in batches using the “chunksize” argument when using the Pool.map(). In this tutorial you will discover the chunksize argument when executing multiple tasks with the multiprocessing pool in Python. Let’s get started. Problem With Issuing Many Tasks to the Pool The multiprocessing pool allows us to issue many tasks to the […]

Multiprocessing Pool Remaining Tasks

You can report the number of remaining tasks in the multiprocessing pool with Pool.apply_async() and a busy-wait loop, or via the Pool.imap_unordered() function. In this tutorial you will discover how to report the number of remaining tasks in the multiprocessing pool. Let’s get started. Need to Report Remaining Tasks in the Pool The multiprocessing.pool.Pool in […]

Multiprocessing Pool Get Result from Asynchronous Tasks

You can get results from tasks in the multiprocessing pool using a callback or by calling AsyncResult.get(). In this tutorial you will discover how to get results from tasks issued asynchronously to the multiprocessing pool in Python. Let’s get started. Multiprocessing Pool Asynchronous Tasks We can execute tasks asynchronously using the multiprocessing pool. The multiprocessing.Pool […]

Multiprocessing Pool map() Multiple Arguments

The multiprocessing pool map() function cannot be used directly with a target function that takes multiple arguments. Instead, you need to use an alternate function like starmap() or a workaround like a wrapper function. In this tutorial you will discover how to call the multiprocessing pool map() function with multiple arguments indirectly and how to […]

Parallel For-Loop With a Multiprocessing Pool

You can convert a for-loop to be parallel using the multiprocessing.Pool class. In this tutorial you will discover how to convert a for-loop to be parallel using the multiprocessing pool. Let’s get started. Need to Make For-Loop Parallel You have a for-loop and you want to execute each iteration in parallel using a separate CPU […]