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721–744 of 4,294 · Most stars

Swiss-army tool for scraping and extracting data from online assets, made for hackers

  • css
  • curl
  • gjson
  • json

Twitter API Scraper | Without an API key | Twitter Internal API | Free | Twitter scraper | Twitter Bot

  • python
  • bot
  • client
  • python3

Translated📈📊🚀🚀🚀An elegant modern declarative data visualization chart framework for iOS, iPadOS and macOS. Extremely powerful, supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types. It also supports donut charts, radar charts and mixed charts, among dozens of types of infographic charts, fully meeting work needs.

  • chart
  • column-chart
  • line-charts
  • pie-chart

Drop-in replacement of Django admin comes with lots of goodies, fully extensible with plugin support, pretty UI based on Twitter Bootstrap.

Jobs scraper library for LinkedIn, Indeed, Glassdoor, ZipRecruiter, Bayt, Naukri, BDJobs & HelloWork

  • indeed
  • linkedin
  • ziprecruiter
  • jobs-scraper

RuVector provides High Performance, Real-Time decisions and agent memory , Self-Learning Ai, Vector GNN DB built in Rust.

  • ai
  • ai-ocr
  • gnn
  • graph

Adminator is easy to use and well design admin dashboard template with dark mode for web apps, websites, services and more

  • admin-dashboard
  • admin-panel
  • admin-template
  • bootstrap5

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.