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Scrapy (/ ˈ s k r eɪ p aɪ / [2] SKRAY-peye) is a free and open-source web-crawling framework written in Python. Originally designed for web scraping, it can also be used to extract data using APIs or as a general-purpose web crawler. [3] It is currently maintained by Zyte (formerly Scrapinghub), a web-scraping development and services company.
Beautiful Soup is a Python package for parsing HTML and XML documents, including those with malformed markup. It creates a parse tree for documents that can be used to extract data from HTML, [3] which is useful for web scraping. [2] [4]
Because of this, tool kits that scrape web content were created. A web scraper is an API or tool to extract data from a website. [6] Companies like Amazon AWS and Google provide web scraping tools, services, and public data available free of cost to end-users. Newer forms of web scraping involve listening to data feeds from web servers.
Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions.
Scrapy, an open source webcrawler framework, written in python (licensed under BSD). Seeks, a free distributed search engine (licensed under AGPL). StormCrawler, a collection of resources for building low-latency, scalable web crawlers on Apache Storm (Apache License). tkWWW Robot, a crawler based on the tkWWW web browser (licensed under GPL).
PHP is a commonly used language to write scraping scripts for websites or backend services, since it has powerful capabilities built-in (DOM parsers, libcURL); however, its memory usage is typically 10 times the factor of a similar C/C++ code. Ruby on Rails as well as Python are also frequently used to automated scraping jobs.
The APIs provide functionality like analytics, machine learning as a service (the Prediction API) or access to user data (when permission to read the data is given). Another important example is an embedded Google map on a website, which can be achieved using the Static Maps API, [1] Places API [2] or Google Earth API. [3]
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.