Open Source Python Web Scrapers
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Python Web Scrapers
View 179 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 is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
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Our xDM platform turns business users into data champions.It empowers organizations of any size to build trusted data applications quickly, with fast time to value using a single software platform for governance, master data, reference data, data quality, enrichment, and workflows.
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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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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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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. -
Outplacement, Executive Coaching and Career Development | CareermindsBy helping to avoid the potential risks of RIFs or layoffs through our global outplacement services, companies can move forward with their goals while preserving their internal culture, employer brand, and bottom lines.
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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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finvizfinance
Finviz analysis python library
finvizfinance is a package that collects financial information from FinViz website. Stock charts, fundamental & technical information, insider information and stock news. Forex charts and performance. Crypto charts and performance. Screener and Group provide data frames for comparing stocks according to different filters and trading signals. Getting information (fundament, description, outer rating, stock news, inside trader) of an individual stock. -
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img2dataset
Easily turn large sets of image urls to an image dataset
Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine. Also supports saving captions for url+caption datasets. Opt-out directives: Websites can pass the http headers X-Robots-Tag: noai, X-Robots-Tag: noindex , X-Robots-Tag: noimageai and X-Robots-Tag: noimageindex By default img2dataset will ignore images with such headers. -
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ScrapeGraphAI
Python scraper based on AI
Extracting content from websites and local documents using LLM. ScrapeGraphAI is a web scraping python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.). Just say which information you want to extract and the library will do it for you. -
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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. -
Accounting practice management softwareCanopy is a cloud-based practice management software for accounting and tax firms, offering tools for client engagement, document management, workflow automation, and time & billing. Its Client Engagement platform centralizes interactions with a secure portal, customizable branding, and email integration, while the Document Management system enables organized, paperless file storage. The Workflow module enhances visibility into tasks and projects through templates, task assignments, and automation, reducing human error. Additionally, the Time & Billing feature tracks billable hours, generates invoices, and processes payments, ensuring accurate financial management. With its comprehensive features, Canopy streamlines operations, reduces stress, and enhances client experiences.
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Crawl4AI
Open-source LLM Friendly Web Crawler & Scraper
Crawl4AI is a high-performance, AI‑ready web crawler tailored for LLM data ingestion and RAG pipelines. It supports adaptive crawling heuristics (stopping when enough info is gathered), structured markdown output, and high-speed parallel execution. Designed to operate at scale with optional Docker deployment and framework integrations. -
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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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ScrapydWeb
Web app for Scrapyd cluster management
Web app for Scrapyd cluster management, with support for Scrapy log analysis & visualization. Make sure that Scrapyd has been installed and started on all of your hosts. Start ScrapydWeb via command scrapydweb. (a config file would be generated for customizing settings on the first startup.) Add your Scrapyd servers, both formats of string and tuple are supported, you can attach basic auth for accessing the Scrapyd server, as well as a string for grouping or labeling. You can select any number of Scrapyd servers by grouping and filtering, and then invoke the HTTP JSON API of Scrapyd on the cluster with just a few clicks. -
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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. -
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changedetection.io
The best free open source website change detection and restock service
Loved by smart shoppers, data journalists, research engineers, data scientists, security researchers, and more. From simply monitoring website pages that have a change (such as watching prices, and restocking notifications), to deep inspection such as PDF text support, JSON and XML monitoring, and extensive text triggers. Monitor out-of-stock products and get alerts when those products are back in stock, get restock alerts via Discord, Slack, email, and many other platforms. Using the browser steps configuration, add basic steps before performing change detection, such as logging into websites, adding a product to a cart, accepting cookie logins, entering dates, and refining searches. Monitor and track PDF file changes, and know when a PDF file has text changes. Know when your favourite product is on sale, or other special deals are announced before anyone else. Detect and monitor changes in JSON API responses. -
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django-dynamic-scraper
Creating Scrapy scrapers via the Django admin interface
Django Dynamic Scraper (DDS) is an app for Django build on top of the scraping framework Scrapy. While preserving many of the features of Scrapy it lets you dynamically create and manage spiders via the Django admin interface. With Django Dynamic Scraper (DDS) you can define your Scrapy scrapers dynamically via the Django admin interface and save your scraped items in the database you defined for your Django project. Since it simplifies things DDS is not usable for all kinds of scrapers, but it is well suited for the relatively common case of regularly scraping a website with a list of updated items (e.g. news, events, etc.) and then dig into the detail page to scrape some more infos for each item. Django Dynamic Scraper tries to keep its data structure in the database as separated as possible from the models in your app, so it comes with its own Django model classes for defining scrapers, runtime information related to your scraper runs and classes. -
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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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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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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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It is a powerful data scraping tool that helps you extract information from various online sources. Easily collect data from Google SERP, Maps, Shopify, Zillow, and more. With a user-friendly interface, you can scrape and save data in JSON or Excel formats. Unlock insights from the web effortlessly with scrape-it.cloud API.
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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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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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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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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.