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scrapyvsautoscraper

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Scrapy is an open-source Python library for web scraping. It allows developers to extract structured data from websites using a simple and consistent interface.

Scrapy provides:

  • A built-in way to follow links and extract data from multiple pages (crawling)
  • Handling common web scraping tasks such as logging in, handling cookies, and handling redirects.

Scrapy is built on top of the Twisted networking engine, which provides a non-blocking way to handle multiple requests at the same time, allowing Scrapy to efficiently scrape large websites.

It also comes with a built-in mechanism for handling common web scraping problems, such as:

  • handling HTTP errors
  • handling broken links

Scrapy also provide these features:

  • Support for storing scraped data in various formats, such as CSV, JSON, and XML.
  • Built-in support for selecting and extracting data using XPath or CSS selectors (through parsel).
  • Built-in support for handling common web scraping problems (like deduplication and url filtering).
  • Ability to easily extend its functionality using middlewares.
  • Ability to easily extend output processing using pipelines.

Autoscraper project is made for automatic web scraping to make scraping easy. It gets a url or the html content of a web page and a list of sample data which we want to scrape from that page. This data can be text, url or any html tag value of that page. It learns the scraping rules and returns the similar elements. Then you can use this learned object with new urls to get similar content or the exact same element of those new pages.

Autoscraper is minimalistic and auto-generative approach to web scraping. For example, here's a scraper that finds all titles on a stackoverflow.com page:

from autoscraper import AutoScraper

url = 'https://stackoverflow.com/questions/2081586/web-scraping-with-python'

# We can add one or multiple candidates here.
# You can also put urls here to retrieve urls.
wanted_list = ["What are metaclasses in Python?"]

scraper = AutoScraper()
result = scraper.build(url, wanted_list)
print(result)

Highlights


popularcss-selectorsxpath-selectorscommunity-toolsoutput-pipelinesmiddlewaresasyncproductionlarge-scale
popularminimalisticauto-generating

Example Use


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