This article introduces ten practical Python-based web scraping methods—including requests, Selenium, Scrapy, Crawley, PySpider, aiohttp, asks, vibora, Pyppeteer, and Fiddler‑plus‑Node reverse engineering—explaining their use cases, advantages, and code examples for efficiently gathering e‑commerce and app data.
This article demonstrates how to use Python's asyncio library together with the aiohttp package to perform asynchronous HTTP requests, covering installation, concurrent request execution, GET and POST examples, error handling, timeouts, SSL verification, and proxy usage, with complete code snippets.
This article introduces ten practical Python techniques—including requests, Selenium, Scrapy, Crawley, PySpider, aiohttp, asks, vibora, Pyppeteer, and Fiddler‑based reverse engineering—to efficiently collect e‑commerce and app data while addressing common challenges such as IP blocking, captchas, and authentication.
This tutorial walks you through creating a simple aiohttp web application that fetches random Mars rover photos from the NASA API, validates image quality using Pillow, and serves the images directly, covering environment setup, async code, and deployment options.
This tutorial demonstrates how to build a simple aiohttp web server in Python, install required dependencies, retrieve random Mars photos from the NASA API, validate image size and color mode using Pillow, and serve the selected image directly to the browser.
This article explains Python coroutines, their advantages over threads, demonstrates producer‑consumer patterns, introduces the asyncio event loop, shows how to use async/await syntax, and provides examples of asynchronous network requests and a simple aiohttp server for high‑concurrency I/O.
This article demonstrates how to configure Python's logging module for console and file output, extend it with HTTPHandler for remote logging, and improve performance by using custom handlers, threading, thread pools, and asynchronous aiohttp calls to avoid blocking the main program.
This article explains the limitations of Python's GIL, compares synchronous and asynchronous execution models, introduces asyncio and aiohttp, provides concrete code examples for single and multiple concurrent HTTP requests, and offers solutions for common concurrency errors such as too many file descriptors.
This article explains Python coroutine fundamentals, async/await syntax, and demonstrates how to use aiohttp with an event loop and semaphore to dramatically speed up I/O‑bound network requests, providing practical code and performance results.
This guide introduces the most important Python libraries for web scraping—including requests, urllib3, Selenium, aiohttp, BeautifulSoup, lxml, pyquery, PyMySQL, PyMongo, and redisdump—explaining their core features, typical use cases, and providing concise code examples to help beginners get started quickly.
This tutorial demonstrates how to use asynchronous Python (aiohttp, motor, asyncio) to scrape all comments from a popular Bilibili video, store them in MongoDB, and generate a Chinese word‑cloud analysis to reveal why the video went viral.
This article explains the fundamentals of asynchronous programming, contrasting blocking, non‑blocking, synchronous and asynchronous execution, and demonstrates how to implement async behavior in Python using Tornado, asyncio, and aiohttp, including coroutine definitions, yield usage, and practical code examples.
This article walks through creating a Python blog website, covering project structure, HTTP workflow, ORM implementation, aiohttp web framework integration, and showcases the final UI screenshots, while reflecting on lessons learned and future learning needs.
This tutorial explains Python's asynchronous programming model—including coroutines, the yield‑from syntax, async/await keywords, and event‑loop management—while providing a complete, runnable example that fetches Reddit JSON data concurrently using aiohttp.
