Open Source Python Web Scrapers - Page 4
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Python Web Scrapers
View 204 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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Scweet
Scrape tweets, profiles, followers and following from Twitter/X
Scweet is a Python-based Twitter/X scraping library and CLI designed to collect tweets, profile timelines, followers, following lists, and user profile data without requiring the official Twitter/X API or a developer account. Instead of depending on deprecated unauthenticated scraping methods, it works by using X’s web GraphQL API together with authenticated browser cookies, which gives it a more current and practical approach for data extraction. The project supports a broad set of collection patterns, including searches by keyword, hashtag, user, date range, engagement thresholds, language, and location, making it useful for research, monitoring, and data gathering workflows. It is built for both local use and higher-volume runs, with support for proxies, dedicated accounts, and multi-account cookie handling to improve reliability at scale. Scweet also includes asynchronous method variants, a command-line interface, automatic credential persistence in a local database, etc. -
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Twitter Intelligence
Twitter Intelligence OSINT project performs tracking and analysis
A project written in Python for Twitter tracking and analysis without using Twitter API. This project is a Python 3.x application. The package dependencies are in the file requirements.txt. Run that command to install the dependencies. SQLite is used as the database. Tweet data is stored on the Tweet, User, Location, Hashtag, HashtagTweet tables. The database is created automatically. analysis.py performs analysis processing. User, hashtag, and location analyzes are performed. You must write Google Map API Key in setting.py to display Google Maps. -
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VIT Marks Display
A small program that accesses VIT marks of a specific student
A small attempt while learning interfacing with the web while learning python to get the marks of a specific valid VIT student using basic web scraping techniques -
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Web Link Collector 1000
Automatically collect all links from websites to a clean txt file
## About Easily and automatically collect all your links into a neat txt list from a particular website or an entire section of a multi-page website network! Web Link Collector 1000 is a simple tool for gathering links from websites with minimal effort. It helps you collect resources for research, create reference lists, or save useful links without manual copying and pasting. ## Features - Two Collection Modes: Single page or multiple pages of specific website section, or even the entire domain! - Smart Filtering: Include only same-domain links or gather external links too - Duplicate Prevention: Automatically removes duplicate links - Website-Friendly: Uses respectful delays between requests - Custom File Naming: Save your collections with custom meaningful names - Modern Interface: Clean design with status updates - Link Normalization: Standardizes URLs for proper formatting -
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YouTube video web scraper 2 [ISA]
YouTube video web scraper 2 [Improved.Simplified.Alternative]
'YouTube video web scraper 2' is an desktop application developed using python 3.11.4 and other add-on libaries. Finds YouTube video based on user request and view as table. Export the table as excel. Compatible only for windows OS. -
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crawler
Collection of JS reverse engineering examples for web scraping study
crawler is a collection of web scraping and JavaScript reverse engineering examples designed for learning how modern websites protect their data and how those protections can be analyzed. It contains many case studies that demonstrate how to analyze and replicate request parameters, cookies, and encryption logic used by real websites. Each directory in the project focuses on a specific target service or scenario, showing how browser network requests and JavaScript code can be studied to reproduce API calls programmatically. Many examples illustrate techniques such as debugging scripts, intercepting requests, analyzing encrypted parameters, and understanding authentication flows. crawler also explores common anti-scraping defenses and demonstrates how developers can examine them through debugging tools and reverse engineering techniques. -
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diskover-community
Open source file indexing & storage analytics powered by Elasticsearch
Diskover Community Edition is an open source file system indexing and storage analytics platform designed to help organizations understand and manage large volumes of file data. It crawls file systems and indexes metadata using Elasticsearch, enabling fast search, analysis, and organization of files stored across different storage systems. It allows administrators and users to explore file structures, monitor storage usage, and gain insights into how data is distributed across infrastructure. By indexing file metadata from sources such as local file systems, network shares like NFS and SMB, and cloud storage, the tool provides a centralized way to analyze heterogeneous storage environments. Diskover also helps identify outdated or unused files, duplicate data, and inefficient storage usage that can waste resources or increase operational costs. A Python-based indexing engine performs the scanning and indexing tasks. -
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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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dorker-py
Descubre archivos, rutas escondidas realizando busquedas avanzadas
Dorking Google - Dorker Py Descubre archivos, rutas escondidas realizando busquedas avanzadas (ES) Discover files, hidden paths by performing advanced searches (EN) -
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dxy-covid-19-crawler
Realtime crawler for COVID-19 outbreak statistics from DXY data
DXY-COVID-19-Crawler is a Python-based project designed to collect real-time COVID-19 infection data from the public dataset provided by Ding Xiang Yuan (DXY). The crawler periodically retrieves pandemic statistics and stores them in a database so that historical changes in the outbreak can be preserved and analyzed later. It was created to make up-to-date infection data more accessible for developers, researchers, and analysts who wanted to build visualizations or conduct data analysis during the early stages of the pandemic. DXY-COVID-19-Crawler automatically crawls data at regular intervals, typically every minute, ensuring that newly published statistics are captured as quickly as possible. Retrieved data is stored in MongoDB and archived so that the entire progression of the outbreak can be traced over time. It also provided an API that allowed developers to easily access the collected data for building dashboards, visualizations, and other analytical tools. -
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This plug-in for Google Desktop is a simple web spider (Könguló is Icelandic for spider) that crawls websites you specify, e.g. intranet websites, and dumps them into Google Desktop. You must install Google Desktop prior to installing the plug-in.
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haipproxy
Distributed proxy IP pool for web crawlers using Scrapy and Redis
HAipproxy is a distributed proxy IP pool system designed to collect, manage, and provide large numbers of proxy addresses for web crawling tasks. It automatically crawls proxy resources from the internet and aggregates them into a centralized pool that can be accessed by distributed spiders and scraping systems. It is built using Python and relies on Scrapy for high-performance crawling while Redis is used for data storage, communication, and task coordination between components. It includes crawlers that discover proxy servers, validators that test proxy availability and performance, and schedulers that manage crawling and validation tasks. HAipproxy aims to maintain a high availability proxy pool with low latency so that scraping frameworks can rotate proxies efficiently and avoid blocking during large-scale data collection. Its architecture supports distributed deployment, allowing multiple crawler workers and validators to run across different machines. -
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jd-autobuy
Python tool that automates JD.com login and product purchase tasks
jd-autobuy is an open source Python-based automation tool designed to simulate the purchasing process on the JD e-commerce platform. It uses web scraping and HTTP request techniques to log into an account, check product availability, and attempt to purchase specified items automatically. It supports login through methods such as QR code authentication, allowing users to sign in through the platform’s mobile application. Once authenticated, the script can retrieve product details including price, stock status, and item information. It can automatically add items to the shopping cart and prepare an order submission workflow for faster purchasing during high-demand sales or limited stock releases. Users can configure parameters such as the product ID, quantity, refresh interval, and purchase behavior using command-line options. jd-autobuy is intended primarily for learning purposes and demonstrates how automated scripts can interact with web services and online shopping systems . -
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rnet
Python HTTP client with TLS and HTTP/2 fingerprint emulation support
rnet is an ergonomic and modular Python HTTP client designed for developers who need advanced control over network requests and protocol behavior. It provides a flexible API for making HTTP requests while supporting both asynchronous and blocking workflows, allowing it to integrate easily into different Python applications and runtimes. rnet focuses on low-level protocol customization, giving users fine-grained control over TLS and HTTP/2 configuration in order to emulate specific browser behaviors. This includes support for TLS fingerprinting techniques such as JA3 and JA4 as well as detailed HTTP/2 settings, enabling more accurate simulation of real client network traffic. It is powered by the underlying wreq engine and is built with performance and modularity in mind. rnet also supports advanced networking capabilities such as proxy rotation, connection pooling, and streaming transfers, which make it suitable for automation, scraping, and high-performance network. -
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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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xsrfprobe
Advanced toolkit for detecting and exploiting CSRF vulnerabilities
XSRFProbe is an advanced security auditing toolkit designed to detect and analyze Cross Site Request Forgery (CSRF/XSRF) vulnerabilities in web applications. It uses an automated crawling engine that continuously scans a target application, collects forms and endpoints, and evaluates them for potential CSRF weaknesses. XSRFProbe performs numerous systematic checks to determine whether a web endpoint is vulnerable, including inspection of anti-CSRF tokens, cookie validation behavior, and request forgery scenarios. It also analyzes the strength and randomness of security tokens using algorithms such as entropy calculations to determine whether tokens can be predicted or forged. When a vulnerability is discovered, it can automatically generate proof-of-concept payloads that demonstrate how the flaw could be exploited in a real attack scenario. XSRFProbe provides a highly automated workflow while still allowing users to customize scanning behavior and configuration settings. -
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yabasta
Yet Another BAsic Scraper and Text Analysis
YA BASTA! is a Python/R application for Lyrics Web Scraper and Text Analysis. Web scraping is developed in Python, text analysis in R as Python subprocesses. YA BASTA! is only tested on windows OS. To run YA BASTA! just type on window command prompt: python.exe yabasta.py
