https://github.com/kang-theo/crawlers

Python crawlers used to automate data retrieval from the internet.
https://github.com/kang-theo/crawlers

Last synced: 16 days ago
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Python crawlers used to automate data retrieval from the internet.

• Host: GitHub
• URL: https://github.com/kang-theo/crawlers
• Owner: kang-theo
• License: mit
• Created: 2024-04-07T09:12:28.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-04-11T05:02:29.000Z (10 months ago)
• Last Synced: 2024-11-13T15:55:45.315Z (3 months ago)
• Language: Python
• Size: 65.4 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# crawlers

Python crawlers used to automate data retrieval from the internet.

Python crawlers are typically implemented using third-party libraries, with the most commonly used crawler libraries including:

- Requests: Used for sending HTTP requests and retrieving web content.

- Beautiful Soup: Used for parsing HTML and XML files, extracting information from web pages.

- Scrapy: A comprehensive crawler framework that provides rich functionality and flexible configuration options.

- Selenium: Used for simulating browser operations, supporting dynamic web pages and JavaScript-rendered pages crawling.

The process of developing a Python crawler typically involves the following steps:

- Determine Objectives: Identify the target website or data source to be crawled, clarify objectives and requirements.

- Select Tools: Choose the appropriate crawler tools and libraries based on requirements, such as Requests, Beautiful Soup, Scrapy, or Selenium.

- Write Code: Develop crawler code using the selected tools, implementing data retrieval and processing logic.

- Handle Data: Process, clean, store, or analyze retrieved data as needed.

Regular Updates: Periodically update the crawler program to ensure data timeliness and accuracy.