Open Source Web Scrapers
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Web Scrapers
View 179 business solutionsBrowse free open source Web Scrapers and projects below. Use the toggles on the left to filter open source Web Scrapers by OS, license, language, programming language, and project status.
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WFDownloader App
Free batch downloader for image, wallpaper, video, audio, document,
Use as an image gallery, wallpaper, audio/music, video, document, and other media bulk downloader from supported websites. Also use to download sequential website urls that have a certain pattern (e.g. image01.png to image100.png). Also use app's built-in site crawler for advanced link search or extraction. There is also special support for forum media and open directory downloading. It's a programmable downloader and also works with password protected sites. Say goodbye to downloading one by one. Go to the Help menu or check out website to get started. Note that this cross-platform version requires Java (minimum version Java 8) to be installed on your Operating System. For non-java required OS specific versions, check app's website. -
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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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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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UI.Vision RPA
Open-Source RPA Software (formerly Kantu)
The UI Vision RPA software is the tool for visual process automation, codeless UI test automation, web scraping and screen scraping. Automate tasks on Windows, Mac and Linux. The UI Vision RPA core is open-source with enterprise security. The free and open-source browser extension can be extended with local apps for desktop UI automation. UI.Vision RPA's computer-vision visual UI testing commands allow you to write automated visual tests with UI.Vision RPA - this makes UI.Vision RPA the first and only Chrome and Firefox extension (and Selenium IDE) that has "👁👁 eyes". A huge benefit of doing visual tests is that you are not just checking one element or two elements at a time, you’re checking a whole section or page in one visual assertion. The visual UI testing and browser automation commands of UI.Vision RPA help web designers and developers to verify and validate the layout of websites and canvas elements. -
No-Nonsense Code-to-Cloud Security for Devs | AikidoAikido provides a unified security platform for developers, combining 12 powerful scans like SAST, DAST, and CSPM. AI-driven AutoFix and AutoTriage streamline vulnerability management, while runtime protection blocks attacks.
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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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EasySpider
A visual no-code/code-free web crawler/spider
A visual code-free/no-code web crawler/spider, supporting both Chinese and English. -
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CEF Python
Python bindings for the Chromium Embedded Framework (CEF)
Python bindings for the Chromium Embedded Framework (CEF). CEF Python is an open source project founded by Czarek Tomczak in 2012 to provide Python bindings for the Chromium Embedded Framework (CEF). The Chromium project focuses mainly on Google Chrome application development while CEF focuses on facilitating embedded browser use cases in third-party applications. Lots of applications use CEF control, there are more than 100 million CEF instances installed around the world. There are numerous use cases for CEF. Use it as a modern HTML5 based rendering engine that can act as a replacement for classic desktop GUI frameworks. Think of it as Electron for Python. Embed a web browser widget in a classic Qt / GTK / wxPython desktop application. Use it for automated testing of web applications with more advanced capabilities than Selenium web browser automation due to CEF low level programming APIs. -
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miniblink49
Lighter, faster browser kernel of blink to integrate HTML UI in apps
miniblink is an open source, one file, small browser widget based on chromium. By using C interface, you can create a browser with just some line code. miniblink is an open source, single-file, and currently the smallest known chromium-based browser control. Through its exported pure C interface, a browser control can be created in a few lines of code. C++, C#, Delphi and other language calls (support C++, C#, Delphi language to call). Embedded Nodejs, support electron (with Nodejs, can run electron). Customize as you wish, simulate another browser environment. Perfect HTML5 support, friendly to various front-end libraries (support HTML5, and friendly to front framework). After turning off the cross-domain switch, you can use various cross-domain functions (support cross-domain). Headless mode, which greatly saves resources and is suitable for crawlers (headless mode, be suitable for Web Crawler). -
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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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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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Ulixee Hero
The web browser built for scraping
It's the first modern headless browsers designed specifically for scraping instead of just automated testing. Hero provides access to the W3C DOM specification without the need for Puppeteer's complicated evaluate callbacks and multi-context switching. We've recreated a fully compliant DOM directly in NodeJS allowing you bypass the headaches of previous scraper tools. The powerful Chrome engine sits under the hood, allowing for lightning fast rendering. Emulators make it easy to disguise your script as practically any browser. -
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crawlee
A web scraping and browser automation library for Node.js
Crawlee is a web scraping and browser automation library. It helps you build reliable crawlers. Fast. Crawlee won't fix broken selectors for you (yet), but it helps you build and maintain your crawlers faster. When a website adds JavaScript rendering, you don't have to rewrite everything, only switch to one of the browser crawlers. When you later find a great API to speed up your crawls, flip the switch back. It keeps your proxies healthy by rotating them smartly with good fingerprints that make your crawlers look human-like. It's not unblockable, but it will save you money in the long run. Crawlee is built by people who scrape for a living and use it every day to scrape millions of pages. Meet our community on Discord. We believe websites are best scraped in the language they're written in. Crawlee runs on Node.js and it's built in TypeScript to improve code completion in your IDE, even if you don't use TypeScript yourself. -
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crawley
The unix-way web crawler
Crawls web pages and prints any link it can find. Fast HTML SAX-parser (powered by golang.org/x/net/html) Small (below 1500 SLOC), idiomatic, 100% test-covered codebase. Grabs most of useful resources URLs (pics, videos, audios, forms, etc...) Found URLs are streamed to stdout and guaranteed to be unique (with fragments omitted) Scan depth (limited by starting host and path, by default - 0) can be configured. Can crawl rules and sitemaps from robots.txt. Brute mode - scan HTML comments for URLs (this can lead to bogus results) Make use of HTTP_PROXY / HTTPS_PROXY environment values + handle proxy auth. Directory-only scan mode (aka fast-scan) -
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rvest
Simple web scraping for R
rvest helps you scrape (or harvest) data from web pages. It is designed to work with magrittr to make it easy to express common web scraping tasks, inspired by libraries like beautiful soup and RoboBrowser. If you’re scraping multiple pages, I highly recommend using rvest in concert with polite. The polite package ensures that you’re respecting the robots.txt and not hammering the site with too many requests. -
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The archive-crawler project is building Heritrix: a flexible, extensible, robust, and scalable web crawler capable of fetching, archiving, and analyzing the full diversity and breadth of internet-accesible content.
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BrowserBox
Remote isolated browser API for security
Remote isolated browser API for security, automation visibility and interactivity. Run-on our cloud, or bring your own. Full scope double reverse web proxy with a multi-tab, mobile-ready browser UI frontend. Plus co-browsing, advanced adaptive streaming, secure document viewing and more! But only in the Pro version. BrowserBox is a full-stack component for a web browser that runs on a remote server, with a UI you can embed on the web. BrowserBox lets your provide controllable access to web resources in a way that's both more sandboxed than, and less restricted than, traditional web <iframe> elements. Build applications that need cross-origin access, while delivering complex user stories that benefit from an encapsulated browser abstraction. Since the whole stack is written in JavaScript you can easily extend it to suit your needs. The technology that puts unrestricted browser capabilities within reach of a web app has never before existed in the open. -
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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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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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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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crawler4j
Open source web crawler for Java
crawler4j is an open source web crawler for Java which provides a simple interface for crawling the Web. Using it, you can setup a multi-threaded web crawler in few minutes. You need to create a crawler class that extends WebCrawler. This class decides which URLs should be crawled and handles the downloaded page. shouldVisit function decides whether the given URL should be crawled or not. In the above example, this example is not allowing .css, .js and media files and only allows pages within ics domain. visit function is called after the content of a URL is downloaded successfully. You can easily get the url, text, links, html, and unique id of the downloaded page. You should also implement a controller class which specifies the seeds of the crawl, the folder in which intermediate crawl data should be stored and the number of concurrent threads. -
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ACHE Focused Crawler
ACHE is a web crawler for domain-specific search
ACHE is a focused web crawler. It collects web pages that satisfy some specific criteria, e.g., pages that belong to a given domain or that contain a user-specified pattern. ACHE differs from generic crawlers in sense that it uses page classifiers to distinguish between relevant and irrelevant pages in a given domain. A page classifier can be defined as a simple regular expression (e.g., that matches every page that contains a specific word) or a machine-learning-based classification model. ACHE also automatically learns how to prioritize links in order to efficiently locate relevant content while avoiding the retrieval of irrelevant pages. While ACHE was originally designed to perform focused crawls, it also supports other crawling tasks, including crawling all pages in a given web site and crawling Dark Web sites (using the TOR protocol). -
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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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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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Ferret
Declarative web scraping
A web scraping system aiming to simplify data extraction from the web. ferret has a declarative query language that makes it easy to focus on the data that you need to get. ferret has the ability to scrape JS rendered pages, handle all page events, and emulate user interactions. the ferret was designed as a library from the ground up. it can be easily embedded into any Go application. ferret helps you to focus on the data you need using an easy-to-learn declarative language. ferret uses Chrome/Chromium via Chrome Devtools Protocol to handle dynamically rendered web pages. ferret is extremely extensible, and creating custom functions and types is super easy. ferret allows users to focus on the data. It abstracts away the technical details and complexity of underlying technologies using its own declarative language. It is extremely portable, extensible, and fast. -
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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.
Guide to Open Source Web Scrapers
Open source web scrapers are automated programs that extract data from websites. They typically "scrape" structured datasets from websites, often using automated queries and tools to access specified content. Open source web scrapers are written in programming languages such as Python, JavaScript, Ruby and Perl, and rely on the use of APIs or scripting techniques to get the data they need. The main advantage of an open source approach is that it gives developers unrestricted access to the codebase, allowing them to modify existing features or build new ones with relative ease.
Open source web scrapers can be used for a variety of legitimate purposes such as research, archiving or creating mashups (combinations of different sources). They allow visitors to access content which would otherwise be difficult to obtain due to restrictions imposed by website owners who do not want their material used outside their own sites. Scraping is also used by entrepreneurs looking for market intelligence; marketers engaging in lead generation efforts; competitors comparing prices; and data journalists producing stories based upon publicly available materials.
However, open source web scrapers have also been misused for unethical practices such as scraping personal information without permission or illegally copying copyrighted material without authorization. This has led important companies and organizations like Google, Twitter and eBay take legal action against perpetrators using these tools for malicious activities. Consequently, many governments worldwide have implemented laws requiring users of open source scraping services to seek permission before collecting certain types of private data from websites ownership by third parties.
Open Source Web Scrapers Features
- Easy to Install: Open source web scrapers are often easy to install and require minimal setup. Many open source web scrapers come with pre-packaged code which makes them simple to get up and running quickly.
- Cost Free: The great thing about open source software is that it is free, meaning you are not required to make any payments for its use. This provides a significant cost benefit as compared to commercial programs which can be quite costly.
- Flexible: Another great feature of open source web scrapers is their flexibility in terms of what they can do. Open source programs typically give the user full control over how they want the scraping process to run, allowing the user to customize and tailor the scraper according to their specific needs.
- Secure: Because these programs are open source, developers have access to all aspects of the program’s code, allowing them more control over security measures such as authentication and authorization protocols. This means that using an open source web scraper has additional benefits when it comes to safety, since issues can be addressed quickly by developers directly rather than having waiting for official updates from manufacturers of closed-source software solutions.
- Scalable: Many open-source web scraping tools allow users the capability to easily scale their usage up or down depending upon their needs at any given time without having purchase new licenses or upgrades each time they need more resources or capabilities added on.
What Types of Open Source Web Scrapers Are There?
- Web Crawlers: A web crawler, sometimes referred to as a spider or bot, is an automated script that allows a computer system to traverse the web by reading HTML tags and other web-page components. The crawler will automatically find and collect data from different websites, allowing for information extraction and storage.
- Scrapy: Scrapy is an open source framework designed to make it easier for developers to write code for scraping websites. It provides users with a built-in library of tools for traversing the DOM of any website, extracting data along the way.
- Selenium: Selenium is an open source browser automation tool that supports multiple languages such as Python and Java. It allows users to control a browser in order to executing specific tasks like simulating user interactions on a web page or filling out forms on a website with pre-defined values.
- Beautiful Soup: Beautiful Soup is another type of open source web scraper written in Python. It helps developers parse HTML documents more easily by providing methods like find_all() which can be used to search for specific element types within the document structure.
- PhantomJS: PhantomJS is an open source headless browser which makes it easier to scrape websites without going through the hassle of setting up a browser window each time you need the data. It also offers various features such as validation checks and page timeout settings that help create robust scripts capable of retrieving complex data from any webpage with ease.
- Mechanize: Mechanize is an open-source Python library that enables programmatic interaction with websites via scriptable browsers, making it easy for developers to automate tasks traditionally done manually such as filling out forms or downloading files directly from pages without needing any extra libraries or programs installed on your machine first.
Benefits of Open Source Web Scrapers
- Cost Saving: Open source web scrapers are free to use as compared to buying expensive software. This helps businesses save cost and makes it easier for them to perform web scraping operations without any additional costs.
- Flexibility: The flexibility offered by open source web scrapers is one of the main reasons why they have become so popular in recent times. Users can customize the code according to their needs, which allows them to tailor the scraper according to their specific requirements.
- Automation: Many open source web scrapers provide features which make it easier for users to automate various tedious tasks such as extracting data from websites or collecting prices from multiple ecommerce sites. This helps businesses save time and focus on other important tasks.
- Security: As most open source web scrapers are updated regularly, they do not pose any security risks that other paid versions may present due to outdated versions of software or codebase bugs. Thus, this ensures a secure scraping environment for users and businesses alike.
- Community Support: One of the best advantages of choosing an open source web scraper is having access to a vibrant community of developers who can help you with troubleshooting issues related your project and provide valuable advice when needed.
Who Uses Open Source Web Scrapers?
- Data Scientists: Data scientists leverage web scrapers to extract data from websites and transform that data into analysis-ready datasets.
- Market Researchers: Market researchers use web scrapers to collect massive amounts of online data that can provide insights into consumer behavior, trends, and preferences.
- Freelancers & Consultants: Freelance workers often use web scrapers to automatically retrieve information from the internet for their clients. This allows them to provide more comprehensive services than manually gathering data.
- Journalists & Media Professionals: Journalists often rely on open-source web scrapers when searching for specific information for stories or research projects.
- Software Developers: Software developers can use web scraping tools to access external APIs and make sure their applications stay up-to-date with the latest changes in the market.
- Educators & Students: Students and educators benefit from using open source web scrapers as they allow easier access to a wide range of resources without manual labor or scraping techniques. They can also learn how to develop more sophisticated tools by exploring existing code structures.
How Much Do Open Source Web Scrapers Cost?
Open source web scrapers can be free to use. While they may not have the robust capabilities of a paid option, open source tools are often suitable for basic data extraction needs. Typically, these come in the form of software programs which are available for download at no cost.
The real cost with open source web scrapers is in setting up and managing them. Configuring the software program requires technical expertise and understanding of how web scraping works. Additionally, there is a certain amount of maintenance that needs to be done over time to ensure accuracy and precision in data extraction results. This includes monitoring any changes on the target website as well as writing new scripts if needed.
Overall, open source web scrapers can be great options if you're looking for a low-cost solution that doesn't require a lot of technical know-how or frequent oversight. All that's required is an upfront commitment in terms of time and effort to set it up correctly - then you can start extracting valuable information from websites quickly and easily.
What Software Can Integrate With Open Source Web Scrapers?
Software that can integrate with open source web scrapers includes enterprise applications, content management systems (CMS), big data analytics and visualization tools, and cloud-based services. Enterprise applications such as customer relationship management (CRM) or enterprise resource planning (ERP) systems can use scraped data to provide a better understanding of customers’ needs or to streamline operations. CMS software can be used to input scraped data into websites quickly, easily, and accurately. Big data analytics and visualization tools are capable of taking scraped data from multiple sources and deriving insights from it. Cloud-based services like Google Cloud Storage or Amazon S3 can facilitate storage requirements for large datasets generated by scraping operations.
Open Source Web Scrapers Trends
- Increased Use of Open Source Web Scrapers: Open source web scraping tools are becoming increasingly popular as they are free and relatively easy to use. They can be used to collect large amounts of data quickly, which is useful for businesses that need to track various metrics.
- Growing Popularity: As the use of open source web scrapers has grown, so has their popularity. The open source community provides a wealth of resources and support for users and developers alike, making them more appealing for a wide range of purposes.
- Improved Functionality: Open source web scrapers are constantly being improved and updated, adding new features and making them more efficient. This allows users to customize their scrapers and get the most out of their data-gathering efforts.
- More Security: Open source web scrapers have become more secure as security protocols are continuously being improved. This helps to ensure that private data is protected and that any scraped data is collected in a secure manner.
- Increased Efficiency: With the improved functionality of open source web scrapers, they can usually scrape data faster than traditional solutions. This makes them especially helpful for businesses that need to collect large volumes of data quickly, such as for market research or competitor analysis.
- Lower Cost: Open source web scrapers often require less money than traditional solutions, making them a cost-effective alternative for businesses on a budget. This makes them accessible to smaller companies that may not have the funds to invest in expensive proprietary tools.
How To Get Started With Open Source Web Scrapers
- Getting started with web scraping using open source tools is relatively easy and straightforward. First, you'll want to find an appropriate tool for your specific scraping needs. There is a wide range of scrapping software available in the market, some free and some paid, so it's important to choose one that meets the requirements of your project. Once you have settled on a scraper, the next step is to download and install it on your computer or server. This is usually quite easy as most open-source web scrapers are already packaged in binary formats that make installation a breeze.
- Now it’s time to configure the web scraper. All popular open source web scrapers provide settings to customize how they interact with websites - such as frequency of requests, types of data needed etc. Implementing these settings correctly ensures that information can be collected from target websites without running into issues like getting IP banned or blocked by website owners for excessive requests.
- The next step before actually starting the scraping process is creating a script containing instructions for what websites should be visited (URLs) and how much information from each page should be extracted (CSS selectors). Fortunately, this task can usually be done using point-and-click user interfaces for most open source software options which makes scripting much simpler compared to coding everything manually from scratch every time.
Once your script file is ready, simply run it within the installed web scraper application and wait until all desired data has been harvested. To ensure there are fewer errors while collecting data, you may also have to tweak parameters like crawling speed (number of simultaneous connections), set up proxy rotating services etc. But overall this whole process should not consume more than an hour or two depending on your experience level and familiarity with such scripting tasks.
