Stories from the Web Crawling trenches in parallelism

Making the Most of asyncio: Adding Tasks to Event Loops

Author: Mohan Ganesan

Date: Mar 25, 2024

The asyncio module in Python provides infrastructure for writing asynchronous code using the async/await syntax. The event loop is at the heart of asyncio and manages task execution. Enqueue tasks with loop.create_task() or ensure_future().

Does asyncio use multiple cores python ?

Author: Mohan Ganesan

Date: Mar 17, 2024

Python's asyncio module enables concurrency within a single thread, but not parallelism across multiple threads or processes. However, by utilizing multiprocessing or multithreading, we can achieve true parallelism.

Async IO in Python: When and Why to Use It Over Threads

Author: Mohan Ganesan

Date: Mar 17, 2024

Leverage async I/O for non-CPU bound tasks that deal with network, disk, or user interactions for great performance gains. Stick to threads for intensive computational workloads.

What is the difference between asyncio and time sleep in Python?

Author: Mohan Ganesan

Date: Mar 17, 2024

Python provides asyncio module for concurrency and time.sleep for pausing execution. Use asyncio for parallelism and time.sleep carefully.

Faster Parallel Processing Alternatives to Multithreading in Python

Author: Mohan Ganesan

Date: Mar 17, 2024

Multithreading in Python allows concurrent execution of multiple threads within a process. However, it has limitations due to the GIL. Alternatives like multiprocessing, Numba, and Cython provide better parallelism and performance.

Does asyncio run in parallel python ?

Author: Mohan Ganesan

Date: Mar 17, 2024

Python's asyncio module enables concurrency, not parallelism, by using coroutines and an event loop.

Does asyncio use multiple cores?

Author: Mohan Ganesan

Date: Mar 24, 2024

Asyncio enables concurrency, but not parallelism by default. You can achieve parallelism by integrating thread pools and process pools.

Understanding Multithreading Models: Green, Native, and Pool

Author: Mohan Ganesan

Date: Mar 24, 2024

Multithreading enables parallel execution, with green threads managed by runtime, native threads by OS, and thread pools for task execution.

Is asyncio concurrent or parallel python?

Author: Mohan Ganesan

Date: Mar 17, 2024

Asyncio provides concurrency, not parallelism. It shines for I/O bound work and can achieve high performance. Use multiprocessing for CPU intensive tasks.

Concurrency in Python: Understanding Asyncio and Futures

Author: Mohan Ganesan

Date: Mar 24, 2024

Python provides powerful tools for handling concurrency and parallelism with asyncio and futures. Asyncio enables asynchronous I/O handling in a single thread, while futures handle parallelism across threads/processes.

Achieving Speed with Asyncio in Python

Author: Mohan Ganesan

Date: Mar 24, 2024

Python's asyncio library enables concurrency for improved performance, but not parallelism. It allows efficient use of I/O resources within a single thread.

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