Scrapy – How to Build Fast, Efficient, and Robust Web Crawlers With Scrapy

Scrapy is a powerful web crawling library written in Python that enables developers to build fast, efficient, and robust crawlers without writing code from scratch. It makes use of spiders, which are self-contained crawlers that are given a set of instructions to perform a task.

It is a robust, highly configurable, and extensible framework for crawling large amounts of data from web pages and storing them in a structured format such as CSV, JSON or SQLite. It is also capable of scraping a large amount of data in less than a minute depending on the number of URLs that are crawled.

The underlying framework of Scrapy uses Twister as its crawling engine, which works asynchronously (non-blocking) to increase efficiency. Even if there are errors or a response is returned, the requests are not interrupted and continue to run.

Besides Twister, Scrapy also uses a number of libraries to provide advanced functionality to its spiders. These include Xpath and regex for selecting and extracting data from locators like CSS selectors, API for scraping data, and file formats such as JSON and CSV.

In addition, Scrapy provides many tools to manage and maintain spiders in the form of a Python shell console. This shell console can be used to debug or write the spider code, as well as check it before running the final spider file.

One of the major advantages of using Scrapy over other crawling such as BeautifulSoup or Python Requests/BeautifulSoup is that it comes with many built-in Spider classes and middlewares, which saves developers from writing their own logic for generating and handling requests and responses.

These Spider classes are simple and easy to use, allowing users to easily get started with a crawler. They come with a lot of standard features, such as rate limits and bot detection, to allow you to build the best web crawler possible.

They can also be configured to retry or delay responses if necessary, to prevent overloading the website and causing problems for the site’s administrators. They can also be enabled with AutoThrottle to automatically adjust delays between scraped pages, depending on the current load on the web server.

It also includes a number of plugins to help you with more complex tasks, such as handling duplicated URLs and a python-shell console. Moreover, the framework comes with brilliant logs that log everything that the spider is doing as well as any data that it returns.

This way, developers can have a clearer understanding of the Scrapy code they are writing. They can also make use of a telnet console for introspection, and an interactive shell for debugging.

In addition, Scrapy allows the creation of item pipelines for avoiding duplicated data and saving it in CSV or SQLite. It also supports multiple output files and multiple data storage methods such as JSON, XML, CSV, and Pickle.

The other big advantage of Scrapy is that it can handle a large number of spiders and can run them in parallel, which is essential for high-performance crawling. It can also manage duplicated URLs, a feature that most other crawlers lack. It can even scrape multiple pages from the same website at once, thereby reducing bandwidth costs and speeding up processing.