Crawler is one of the best ways to get started with Python . After mastering Python crawler, it will be more handy to learn other knowledge points of Python. Of course, it is still difficult for friends with zero foundation to use Python crawlers. So friends, do you really know Python crawlers?
Let me give you a brief explanation of the Python crawler. For those who want to improve the actual combat, I have also prepared **"Write a Web Crawler in Python" tutorial**, a total of 212 pages. The content is detailed and the code is clear, which is very suitable for entry-level learning .
[At the end of the article, there is a way to get the information! ! 】
Basic crawler architecture
As can be seen from the figure above, the basic crawler architecture is roughly divided into five categories: crawler scheduler, URL manager, HTML downloader, HTML parser, and data storage.
For the functions of these 5 categories, I will give you a brief explanation:
- **Crawler scheduler,** is mainly to coordinate and call the other four modules. The so-called scheduling is to fetch and call other templates
- The URL manager is responsible for managing URL links. URL links are divided into those that have been crawled and those that have not been crawled. This requires the URL manager to manage them, and it also provides an interface for obtaining new URL links.
- The HTML downloader is to download the HTML of the page to be crawled
- The HTML parser is to get the data to be crawled from the HTML source code, and at the same time send the new URL link to the URL manager and send the processed data to the data storage.
- The data storage is to store the data sent by the HTML downloader locally
Are Python crawlers illegal?
There are different opinions on whether Python is illegal, but so far, Python web crawlers are still within the scope of the law. Of course, if the captured data is used for personal or commercial purposes and causes certain negative effects, it will be condemned of. So please use Python crawlers reasonably.
Why choose Python for crawling?
1. Compared with other static programming languages, the interface of crawling webpage itself is more concise; in addition, sometimes it is necessary to simulate the behavior of a browser to crawl a webpage, and many websites are difficult for blunt crawlers to crawl. Blocked. This is what we need to simulate the behavior of the user agent to construct a suitable request. There are excellent third-party packages in python to help you.
2. Processing after web crawling The captured web pages usually need to be processed, such as filtering html tags, extracting text, etc. Python's beautifulsoap provides a concise document processing function, which can complete most document processing with very short codes.
In fact, many languages and tools can do the above functions, but using python can do it the fastest and cleanest. Life is short, u need python.
NO.1 Fast development, concise language, not so many skills, so it is very clear and easy to read.
NO.2 Cross-platform (due to the open source of python, it can embody "write once and run everywhere" better than java
NO.3 Interpretation (no need to compile, run/debug code directly)
NO.4 There are too many architecture choices (the main GUI architectures are wxPython, tkInter, PyGtk, PyQt.
How to use Python for web crawling?
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"Writing Web Crawlers with Python" has 212 pages and 9 chapters, covering everything from basics to practical applications. The content is detailed and concise, and the code is clear and reproducible.
The 9 chapters are respectively elaborated from the following contents:
Chapter 1 : Introduction to Web Crawlers, introduces what a web crawler is and how to crawl a website.
Chapter 2 : Data Scraping, shows how to use several libraries to extract data from web pages.
Chapter 3 : Download Caching describes how to avoid repeated downloads by caching results.
Chapter 4 : Concurrent Downloads, teaches you how to speed up data scraping by downloading websites in parallel.
Chapter 5 , Dynamic Content, describes how to extract data from dynamic websites in several ways.
Chapter 6 : Form Interaction, shows how to use forms such as input and navigation for search and login.
Chapter 7 : Captcha Handling, explains how to access data protected by captcha images.
Chapter 8 : Scrapy, describes how to use Scrapy for fast parallel scraping and build web crawlers using Portia's web interface.
Chapter 9 : General Applications, summarizes the web crawling techniques you have learned in this book.
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