Scrape all the media from an OnlyFans account - Updated regularly

This repository helps you learn Python and Machine Learning from scratch.

Easy to use fansly.com content downloading tool. Written in python, but ships as a standalone Executable App for Windows too. Enjoy your Fansly content offline anytime, anywhere in the highest possible content resolution! Fully customizable to download in bulk or single: photos, videos & audio from timeline, messages, collection & specific posts 👍

A completely revamped and redesigned fork, reimagined from scratch based on the original onlyfans-scraper

Scalable Python web scraping scripts for +40 popular domains

Command line tool to download and extract data from HTML/XML pages or JSON-APIs, using CSS, XPath 3.0, XQuery 3.0, JSONiq or pattern matching. It can also create new or transformed XML/HTML/JSON documents.

C# console app to download DRM protected videos from Onlyfans accounts

Raspagem de dados para iniciante usando Scrapy e outras libs básicas

This is a tool to scrape/download images and data from Vinted & Depop using the API and stores the data in a SQLite database.

Scrape OnlyFans #onlyfans -- #of-scr -- #onlyfans scrape -- #onlyfans-dl -- OnlyFans content downloader -- #of scrap -- #onlysnap - OnlyFans Scrape

A minimum-dependency ECMAScript client library and CLI tool for Parler – a "free speech" social network that accepts real money to buy "influence" points to boost organic non-advertising content

Open-source database of all Funko Pop data.

A tool that allows you to scrape media from any Onlyfans account and more

Official version of rusquant package for R

Build web scraping agents using AI to auto-extract the data from websites, capture screenshot, generate pdf from URL and web crawling with Agenty

Evaluate JavaScript on a URL through headless Chrome browser.

Data Scraping using Python BeautifulSoup

Record fansly streams live and upload to remote using rclone

Scrape Airbnb, Booking, Hotels.com from a single JavaScript module. ❗No longer maintained.

Web scraping examples with Scrape.do 😎

The python module can be used to scrape data and process data from different sources. The python module can output data as either as a dataframe in the country year format or it will output data in excel files This module has primarily been created for processing data for the International Futures (IFs) Project however, it can be used to process data in general. The module can be used to process data from the following sources, 1) World Bank World Development Indicators (WDI) 2) UNESCO Education indicators(UIS) 3) FAO Food Balance Sheets (FAO) 4) IMF Global Finance Statistics (IMF GFS) 5) Health data from the Institute for Health and Metric Evaluation (IHME) 6) Water data from FAO AQUASTAT 7) Energy data from EIA Currently this module can be run as is on Windows. For usage on Macs, the user may have to make changes to the code lines which specify paths.

DataReaper is a powerful Python tool designed to harvest data from publicly accessible HTTP servers. It combines the capabilities of Shodan search with web scraping techniques to efficiently gather information from targeted websites.

#DataPipeLine #ETL - Created is a Facebook data extraction utility to extract the publicly available data on Facebook. Used Facebook Graph API and Python to extract the data and loaded the data into the CSV files for further analysis.

This is demo repo to demostrate how to scrape apps review data from Google Play Store by Python with library Google-Play-Scraper. And then use Azure Text Analytics to perform sentiment analysis for reviews content (aka comments).

Node script that will use Selenium to scrape card information from NBA Topshot including card names, rarity, and lowest cost at the moment. Data is scraped once per day.

archiving community contributions on YouTube: unpublished captions, title and description translations and caption credits

This holds all my personal data-related project's (Automation, Modelling, Analysis)

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Social Media Scraping – Scrapes data from TikTok, LinkedIn, Facebook, and Twitter (X.com), including user profiles, posts, engagement metrics, and comments.

I developed a sophisticated movie recommendation system using Python, leveraging key libraries such as Pandas, NumPy, Scikit-Learn, and Natural Language Toolkit (NLTK). The system utilizes data scraping techniques to gather movie information and employs advanced data visualization techniques for insightful analysis.