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Data Science- Scrapy

Scrapy was released for the first time on June 26, 2008, with a BSD license and a version 1.0 of June 2015. Scrapy is a fast, open-source web browser written in Python that uses XPath-based selectors to extract data from a web page.

Features of Scrapy

Scrapy comes with amazing features like-

Scrapy has integrated support for selecting and extracting data from sources with XPath or CSS expressions. Scrapy is a free, open-source to use web crawl framework. Browsing Scrapy allows you to automatically retrieve information from web pages. Scrapy creates the export of feeds in formats such as XML, CSV, and JSON.

Advantages of Scrapy

Scrapy comes with many advantages like-

Scrapy is an integrated service called Scrapyd, that allows uploading projects and control spiders using the JSON web service. Scrapy is easily measurable, fast and strong. Scrapy is a Cross-platform application (Windows, Linux, Mac OS, and BSD). Scrapy suits are planned and processed smoothly.

Disadvantages of Scrapy

There are just a few disadvantages of Scrapy-

There is a problem in installation because for a different operating system its required different way of installation. Scrapy is only available for Python 2.7 and + version.

Use of Scrapy

When we talk about the uses of Scrapy so it is the most important tool for Data Science, some of the uses of Scrapy are-

Scrapy has an integrated mechanism called "Selectors" to extract data from sites. Scrapy processes request asynchronously and are fast. Scrapy is easier to create and scale large indexing projects. Scrapy automatically adjusts the crawl rate using an automatic throttling mechanism.

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