Python crawler can do many things, such as search engine, data collection, advertisement filtering and so on. Python crawler can also be used for data analysis, which can play a huge role in data capture! (Recommended learning: Python video tutorial)
Python crawler architecture composition
1.url manager: manages the url set to be crawled and the crawled url set, and sends the URL to be crawled to the webpage downloader;
2. webpage downloader: grab the webpage corresponding to url, store it as a character string, and send it to webpage parser;
3. Web page parser: parse out valuable data, store it, and supplement url to URL manager.
How Python Crawlers Work
Python crawler judges whether there is a URL to crawl through URL manager. If there is a URL to crawl, it sends it to downloader through scheduler, downloads the URL content, sends it to parser through scheduler, parses the URL content, sends the value data and new URL list to application through scheduler, and outputs the value information.
Common frameworks of Python crawler are:
Grab: web crawler framework (based on pycurl/multicur);
Scrapy: Web crawler framework (based on twisted), which does not support Python 3；;
Pyspider: a powerful reptile system;
Cola: a distributed crawler framework;
Portia: a visual crawler based on Scrapy;
Restkit:Python's HTTP resource package. It allows you to easily access HTTP resources and build objects around it;
Demiurge: a reptile micro-framework based on PyQuery.
Python crawler is widely used and occupies a leading position in the field of web crawler. The application of Scrapy, Request, BeautifuSoap, urlib and other frameworks can realize the function of free crawling. Python crawler can be realized as long as you grasp the idea of data!
For more Python-related technical articles, please visit the Python tutorial section to learn!