python-youtube
Scrapy
| python-youtube | Scrapy | |
|---|---|---|
| 2 | 182 | |
| 291 | 51,399 | |
| 1.7% | 0.9% | |
| 7.0 | 9.6 | |
| 23 days ago | 2 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
python-youtube
Scrapy
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Scrapy Vs. Crawlee
Scrapy is an open-source Python-based web scraping framework that extracts data from websites. With Scrapy, you create spiders, which are autonomous scripts to download and process web content. The limitation of Scrapy is that it does not work very well with JavaScript rendered websites, as it was designed for static HTML pages. We will do a comparison later in the article about this.
- Claude is now available in Europe
- Scrapy: A Fast and Powerful Scraping and Web Crawling Framework
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Seven Python Projects to Elevate Your Coding Skills
BeautifulSoup4 Scrapy
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What is SERP? Meaning, Use Cases and Approaches
While there is no specific library for SERP, there are some web scraping libraries that can do the Google Search Page Ranking. One of them which is quite famous is Scrapy - It is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It offers rich developer community support and has been used by more than 50+ projects.
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Creating an advanced search engine with PostgreSQL
If you're looking for a turn-key solution, I'd have to dig a little. I generally write a scraper in python that dumps into a database or flat file (depending on number of records I'm hunting).
Scraping is a separate subject, but once you write one you can generally reuse relevant portions for many others. If you can get adept at a scraping framework like Scrapy you can do it fairly quickly, but there aren't many tools that work out of the box for every site you'll encounter.
Once you've written the spider, it's generally able to be rerun for updates unless the site code is dramatically altered. It really comes down to how brittle the spider is coded (i.e. hunting for specific heading sizes or fonts or something) instead of grabbing the underlying JSON/XHR that doesn't usually change frequently.
1. https://scrapy.org
- Turning webpages into pdf
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Implementing case sensitive headers in Scrapy (not through `_caseMappings`)
Scrapy capitalizes headers for request
- Dicas para projetos usando web scraping
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Best tools to use for web scraping ??
Scrapy is a web scraping toolkit
What are some alternatives?
dacite - Simple creation of data classes from dictionaries.
requests-html - Pythonic HTML Parsing for Humans™
mashumaro - Fast and well tested serialization library
pyspider - A Powerful Spider(Web Crawler) System in Python.
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
colly - Elegant Scraper and Crawler Framework for Golang
dataclasses-json - Easily serialize Data Classes to and from JSON
MechanicalSoup - A Python library for automating interaction with websites.
apischema - JSON (de)serialization, GraphQL and JSON schema generation using Python typing.
playwright-python - Python version of the Playwright testing and automation library.
djangorestframework-dataclasses - Dataclasses serializer for Django REST framework
undetected-chromedriver - Custom Selenium Chromedriver | Zero-Config | Passes ALL bot mitigation systems (like Distil / Imperva/ Datadadome / CloudFlare IUAM)