▼ Click the card below to follow me ▲ Click the card above to follow me Aiohttp: Making Asynchronous Network Programming in Python Super Easy! In modern web applications and web scraping development, efficient network request handling is crucial. Aiohttp is a powerful tool that makes asynchronous network programming effortless. Based on Python’s asyncio framework, … Read more
▼ Click the card below to follow me ▲ Click the card above to follow me Aiohttp: The Magic Wand for Asynchronous HTTP Requests! In the world of Python, there are many libraries for handling HTTP requests, but today I want to introduce you to a truly amazing asynchronous tool – Aiohttp. This library allows … Read more
▼ Click the card below to follow me ▲ Click the card above to follow me Httpx: A Cool New Way to Make HTTP Requests in Python! HTTP requests have always been a common requirement in Python development, and the traditional requests library has been with us for a long time. But today, I want … Read more
Embedded system development has always faced numerous challenges: high code complexity, strict real-time requirements, limited resources, and debugging difficulties. The Rust language, with its features of memory safety, concurrency safety, and high performance, brings new hope for embedded development. Embassy is a next-generation embedded application framework built on the Rust language, aimed at simplifying the … Read more
▼ Click the card below to follow me ▲ Click the card above to follow me Httpx, an asynchronous HTTP client, is a powerful tool for Python! When it comes to making network requests, it truly excels. Think about it, previously when you used the requests library, you had to wait for one request to … Read more
1. Why is Concurrency Programming the Key to Breaking Python’s Performance Bottleneck? In the 2025 Python Developer Survey, 82% of performance optimization cases involved concurrency programming. Faced with I/O-intensive tasks (such as network requests and file operations) and CPU-intensive tasks (such as image processing and data analysis), the combination of asynchronous/multiprocessing/multithreading can bring astonishing performance … Read more
Analyzing Matrices with Python: Achieving 509 Times Data Processing Throughput with Requests Last year, I did something amusing; I ran a single-threaded crawler for an entire day just to scrape data from a small e-commerce website. My boss saw the progress bar on my desktop and laughed, “At this rate, you’ll be delivering the report … Read more
This article is based on a thorough review of relevant authoritative literature and materials, forming professional and reliable content. All data in the article is verifiable and traceable. Special statement: The data and materials have been authorized. The content of this article does not involve any biased views and objectively describes the facts with a … Read more
1. Essential Differences Between Synchronous and Asynchronous (Comparative Understanding) 1.1 Waiter Model Synchronous Mode: The waiter serves only one table of guests at a time (thread blocking) Asynchronous Mode: The waiter serves other guests while waiting for dishes to be served (event loop) # Synchronous request example import requests resp = requests.get('http://example.com') # Blocks until … Read more
AliMei Guide: As a very practical language in daily development and production, it is necessary to master some Python usages, such as web scraping, network requests, etc. However, Python is single-threaded, and how to improve Python’s processing speed is a very important issue. A key technology to address this issue is called coroutines. This article … Read more