Open Source Python Web Scrapers
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Python Web Scrapers
View 174 business solutionsBrowse free open source Python Web Scrapers and projects below. Use the toggles on the left to filter open source Python Web Scrapers by OS, license, language, programming language, and project status.
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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KemonoDownloader
Kemono Downloader - A cross-platform Python app built with PyQt6
Welcome to Kemono Downloader, a versatile Python-based desktop application built with PyQt6, designed to download content from Kemono.su. This tool enables users to archive individual posts or entire creator profiles from services like Patreon, Fanbox, and more, supporting a wide range of file types with customizable settings and advanced features. -
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Scrapy
A fast, high-level web crawling and web scraping framework
Scrapy is a fast, open source, high-level framework for crawling websites and extracting structured data from these websites. Portable and written in Python, it can run on Windows, Linux, macOS and BSD. Scrapy is powerful, fast and simple, and also easily extensible. Simply write the rules to extract the data, and add new functionality if you wish without having to touch the core. Scrapy does the rest, and can be used in a number of applications. It can be used for data mining, monitoring and automated testing. -
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Snoop Project
This is the most powerful software taking into account CIS location
Snoop is an open data intelligence tool (OSINT world). Snoop Project is one of the most promising OSINT tools for finding nicknames. This is the most powerful software taking into account the CIS location. Is your life slideshow? Ask Snoop. Snoop project is developed without taking into account the opinions of the NSA and their friends, that is, it is available to the average user. Snoop is a research work (own database / closed bugbounty) in the field of searching and processing public data on the Internet. In terms of specialized search, Snoop is able to compete with traditional search engines. -
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Selectolax
Python binding to Modest and Lexbor engines
A fast HTML5 parser with CSS selectors using Modest and Lexbor engines. Selectolax supports two backends: Modest and Lexbor. By default, all examples use the Modest backend. Most of the features between backends are almost identical, but there are still some differences. Currently, the Lexbor backend is in beta and missing some of the features. To use lexbor, just import the parser and use it in the similar way to the HTMLParser. -
Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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Crawlab
Distributed web crawler admin platform for spiders management
Golang-based distributed web crawler management platform, supporting various languages including Python, NodeJS, Go, Java, PHP and various web crawler frameworks including Scrapy, Puppeteer, Selenium. Please use docker-compose to one-click to start up. By doing so, you don't even have to configure MongoDB database. The frontend app interacts with the master node, which communicates with other components such as MongoDB, SeaweedFS and worker nodes. Master node and worker nodes communicate with each other via gRPC (a RPC framework). Tasks are scheduled by the task scheduler module in the master node, and received by the task handler module in worker nodes, which executes these tasks in task runners. Task runners are actually processes running spider or crawler programs, and can also send data through gRPC (integrated in SDK) to other data sources, e.g. MongoDB. -
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CyberScraper 2077
A Powerful web scraper powered by LLM | OpenAI, Gemini & Ollama
CyberScraper 2077 is not just another web scraping tool – it's a glimpse into the future of data extraction. Born from the neon-lit streets of a cyberpunk world, this AI-powered scraper uses OpenAI, Gemini and LocalLLM Models to slice through the web's defenses, extracting the data you need with unparalleled precision and style. -
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MechanicalSoup
A Python library for automating interaction with websites
A Python library for automating interaction with websites. MechanicalSoup automatically stores and sends cookies, follows redirects, and can follow links and submit forms. It doesn't do JavaScript. MechanicalSoup was created by M Hickford, who was a fond user of the Mechanize library. Unfortunately, Mechanize was incompatible with Python 3 until 2019 and its development stalled for several years. MechanicalSoup provides a similar API, built on Python giants Requests (for HTTP sessions) and BeautifulSoup (for document navigation). Since 2017 it is a project actively maintained by a small team. -
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Domain Analyzer Security Tool
Finds all the security information for a given domain name
Domain analyzer is a security analysis tool which automatically discovers and reports information about the given domain. Its main purpose is to analyze domains in an unattended way. -
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ApeSmit is a very simple Python module to create XML sitemaps as defined at http://www.sitemaps.org. ApeSmit doesnt contain any web spider or something like that, it just writes the data you provide to a file using the proper syntax.
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Powering the best of the internet | FastlyEnsure your websites, applications and services can effortlessly handle the demands of your users with Fastly. Fastly’s portfolio is designed to be highly performant, personalized and secure while seamlessly scaling to support your growth.
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AutoScraper
A Smart, Automatic, Fast and Lightweight Web Scraper for Python
This 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 that 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 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. -
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Basketball Reference
NBA Stats API via Basketball Reference
Basketball Reference is a great site (especially for a basketball stats nut like me), and hopefully, they don't get too pissed off at me for creating this. I initially wrote this library as an exercise for creating my first PyPi package, hope you find it valuable! This library was created for another Python project where I was trying to estimate an NBA player's productivity. A lot of sports-related APIs are expensive - luckily, Basketball Reference provides a free service which can be scraped and translated into a usable API. -
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify JASP for advanced data editing and RapidMiner for advanced prediction modeling. DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy. License: R, RStudio, NLTK, SciPy, SKLearn, MatPlotLib, Weka, ... each has their own licenses. -
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Webhunter is a distributed, multi-threaded web crawler designed for both general indexing and crawling the web for focused content.
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Gerapy
Distributed Crawler Management Framework Based on Scrapy
Distributed Crawler Management Framework Based on Scrapy, Scrapyd, Scrapyd-Client, Scrapyd-API, Django and Vue.js. Someone who has worked as a crawler with Python may use Scrapy. Scrapy is indeed a very powerful crawler framework. It has high crawling efficiency and good scalability. It is basically a necessary tool for developing crawlers using Python. If you use Scrapy as a crawler, then of course we can use our own host to crawl when crawling, but when the crawl is very large, we can’t run the crawler on our own machine, a good one. The method is to deploy Scrapy to a remote server for execution. At this time, you might use Scrapyd. With it, we only need to install Scrapyd on the remote server and start the service. We can deploy the Scrapy project we wrote. Go to the remote host. In addition, Scrapyd provides a variety of operations API, which gives you free control over the operation of the Scrapy project. -
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Grab Framework Project
Web Scraping Framework
Grab is a python framework for building web scrapers. With Grab you can build web scrapers of various complexity, from simple 5-line scripts to complex asynchronous website crawlers processing millions of web pages. Grab provides an API for performing network requests and for handling the received content e.g. interacting with DOM tree of the HTML document. The single request/response API that allows you to build network request, perform it and work with the received content. The API is built on top of urllib3 and lxml libraries. The Spider API to build asynchronous web crawlers. You write classes that define handlers for each type of network request. Each handler is able to spawn new network requests. Network requests are processed concurrently with a pool of asynchronous web sockets. Grab provides interface called Spider to develop multithreaded web-site scrapers. -
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JobFunnel
Scrape job websites into a single spreadsheet with no duplicates.
Scrape job websites into a single spreadsheet with no duplicates. Automated tool for scraping job postings into a .csv file. You can search for jobs with YAML configuration files or by passing command arguments. By performing regular scraping and reviewing, you can cut through the noise of even the busiest job markets. Run funnel with your settings YAML to populate your master CSV file with jobs from available providers. JobFunnel can be easily automated to run nightly with crontab. If you have a job website you'd like to write a scraper for, you are welcome to implement it, Review the Base Scraper for implementation details. JobFunnel supports scraping jobs from the same job website across locales & domains. If you are interested in adding support, you may only need to define session headers and domain strings, Review the Base Scraper for further implementation details. -
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Letterboxd Recommendations
Scraping publicly-accessible Letterboxd data for movie recommendations
Scraping publicly-accessible Letterboxd data and creating a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username. A user's "star" ratings are scraped from their Letterboxd profile and assigned numerical ratings from 1 to 10 (accounting for half stars). Their ratings are then combined with a sample of ratings from the top 4000 most active users on the site to create a collaborative filtering recommender model using singular value decomposition (SVD). All movies in the full dataset that the user has not rated are run through the model for predicted scores and the items with the top predicted scores are returned. Due to constraints in time and computing power, the maximum sample size that a user is allowed to select is 500,000 samples, though there are over five million ratings in the full dataset from the top 4000 Letterboxd users alone. -
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Nomad is tiny but efficient search engine and web crawler. This works very good for searching with in the set of corporate websites on internet and/or intranet's HTML documents or knowledge repositories.
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We are integrating existing communication systems including Wiki, IRC, Instant Messaging, e-mail, and even static web sites. We write web scrapers and servers for managing events, IRC bots, logs, local names, templates, and groups.
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PAMIE
A Python class to allow the user to automate Internet Explorer
Python Automation Module (class) for Internet Explorer (PAM.py). Originally written as a simple Python module. This new Python class starting with 2.0 allows the user to automate Internet Explorer browser for QA testing, development testing, or web scraping. This python class only runs on Windows (only) and automates Internet Explorer using the COM object, there is no support for Firefox, Chrome, Safari or Flex at this time. This is not an Application. Also check out the original "SAMIE" (Perl module) written by Henry Wasserman. -
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Provas aplicadas - Concursos
Baixar provas aplicadas de bancas
Um aplicativo desktop que permite o download de provas aplicadas em concursos públicos no Brasil. O aplicativo oferece filtros personalizáveis para pesquisa de provas e gabaritos de acordo com a banca organizadora, ano e nível de escolaridade. -
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Python Crawler Library
Python Web Crawler Library
A simple library for crawling the web. This library will give you the ability to create macros for crawling web site and preforming simple actions like preforming "log in" and other simple actions in web sites. -
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Requests-HTML
Pythonic HTML Parsing for Humans
This library intends to make parsing HTML (e.g. scraping the web) as simple and intuitive as possible. When using this library you automatically get full JavaScript support! (Using Chromium, thanks to puppeteer) CSS Selectors (a.k.a jQuery-style, thanks to PyQuery). XPath Selectors, for the faint of heart. Mocked user-agent (like a real web browser). Automatic following of redirects. Connection–pooling and cookie persistence. The Requests experience you know and love, with magical parsing abilities, and async support. The rest of the code operates the same way as the synchronous version except that results is a list containing multiple response objects however the same basic processes can be applied as above to extract the data you want. -
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Scrapy-Redis
Redis-based components for Scrapy
You can start multiple spider instances that share a single redis queue. Best suitable for broad multi-domain crawls. Scraped items gets pushed into a redis queued meaning that you can start as many as needed post-processing processes sharing the items queue. Scheduler + Duplication Filter, Item Pipeline, Base Spiders. Default requests serializer is pickle, but it can be changed to any module with loads and dumps functions. Note that pickle is not compatible between python versions. Version 0.3 changed the requests serialization from marshal to cPickle, therefore persisted requests using version 0.2 will not able to work on 0.3. The class scrapy_redis.spiders.RedisSpider enables a spider to read the urls from redis. The urls in the redis queue will be processed one after another, if the first request yields more requests, the spider will process those requests before fetching another url from redis.
