10 content recommendations for aiohttp-Python Tutorial-php.cn

Home

Backend Development

Python Tutorial

10 content recommendations for aiohttp

巴扎黑

Jun 12, 2017 pm 02:13 PM

This article mainly introduces the relevant knowledge of Python to implement asynchronous proxy crawlers and proxy pools. It has a very good reference value. Let’s take a look at it with the editor. Using python asyncio to implement an asynchronous proxy pool, crawl the proxy according to the rules. Free proxies on the website are stored in redis after verifying their validity. The number of proxies is regularly expanded, the validity of proxies in the pool is checked, and invalid proxies are removed. At the same time, a server is implemented using aiohttp, and other programs can obtain the proxy from the proxy pool by accessing the corresponding URL. Source code Github environment Python 3.5 + RedisPhantomJS (optional) Supervisord (optional) Because the code uses a lot of asyncio's async and await syntax, which are only provided in Python 3.5, so it is best to use Python 3.5 and above. Version, I am using Python3.6. Dependence on redisaiohttpbs4lxmlrequestsseleniumselenium package is mainly used to operate PhantomJS. Below

1. Recommend 7 articles about proxy pool

10 content recommendations for aiohttp

##Introduction: This article mainly introduces the relevant knowledge of Python to implement asynchronous proxy crawlers and proxy pools. It has a good reference value. Let’s take a look at it using python asyncio to implement an asynchronous proxy pool and crawl according to the rules. Get free proxies from the proxy website, store them in redis after verifying their validity, regularly expand the number of proxies, check the validity of proxies in the pool, and remove invalid proxies. At the same time, a server is implemented using aiohttp, and other programs can obtain the proxy from the proxy pool by accessing the corresponding URL. Source code Github...

2. About aiohttp method of adding static resource path

10 content recommendations for aiohttp

Introduction: This article introduces the method of adding static resource paths about aiohttp

[Related Q&A recommendations]:

python3.x - Under what circumstances does the python aiohttp.errors.ServerDisconnectedError error occur?

node.js - Python has asyncio and aiohttp. Is it necessary for multi-threading/multi-process to exist in crawler IO tasks?

python - Why are the cookies in aiohttp's response different from the cookies automatically printed by the library when a program error occurs?

The above is the detailed content of 10 content recommendations for aiohttp. For more information, please follow other related articles on the PHP Chinese website!

Statement

The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

How to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Mathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PM

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AM

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

How to Create Command-Line Interfaces (CLIs) with Python?Mar 10, 2025 pm 06:48 PM

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.

See all articles