Search Results for "collection" - Page 3
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Showing 732 open source projects for "collection"
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Claude Quickstarts
A collection of projects for building deployable applications
Claude Quickstarts is a curated collection of starter projects and templates that help developers quickly begin building applications with the Claude API, making it easier to leverage Anthropic’s Claude models for real use cases. Each quickstart provides a foundational codebase with preconfigured settings and examples for common deployment scenarios, so developers can focus on customizing functionality instead of bootstrapping infrastructure. -
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Natural Language Toolkit
NLTK Source
The Natural Language Toolkit (NLTK) is a widely used open-source Python library designed for working with human language data and building natural language processing (NLP) applications. It provides a comprehensive suite of modules, datasets, and tutorials that support both symbolic and statistical approaches to language processing. The toolkit includes implementations of many foundational NLP algorithms and utilities, enabling developers to perform tasks such as tokenization, stemming,... -
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OpenWPM
A web privacy measurement framework
OpenWPM is a web privacy measurement framework that makes it easy to collect data for privacy studies on a scale of thousands to millions of websites. OpenWPM is built on top of Firefox, with automation provided by Selenium. It includes several hooks for data collection. Check out the instrumentation section below for more details. OpenWPM is tested on Ubuntu 18.04 via TravisCI and is commonly used via the docker container that this repo builds, which is also based on Ubuntu. Although we don't officially support other platforms, conda is a cross-platform utility and the install script can be expected to work on OSX and other Linux distributions. ... -
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BettaFish
Public opinion analysis system
BettaFish is an open-source, multi-agent public opinion analysis system built to automate the collection, deep analysis, and reporting of social media data at scale through conversational queries. It uses a modular architecture of specialized agents that collaborate to crawl mainstream platforms, extract multimodal content like text and short video, and synthesize insights through both statistical and large language model techniques. -
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Parser-Chitai-Gorod
Intelligent parser for catalog «Read-city»
Parser Chitai-Gorod is a Python data-collection tool for extracting structured book information from the Chitai-Gorod online catalog. Its workflow first discovers individual book pages across catalog sections and pagination. A second stage processes those pages and extracts fields such as title, author, ISBN, price, binding, description, page count, publication year, and image URL. -
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TUI apps
Terminal User Interface (TUI) apps
TUI Apps is a collection of terminal applications created mainly for learning, experimentation, and interactive programming practice. Many of the applications are built with Python and the Textual framework. The repository includes a Python regular-expression playground and more than 100 regex exercises. Separate programs provide over 50 grep exercises, over 50 sed exercises, and over 80 GNU awk exercises. -
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CommunityScrapers
This is a public repository containing scrapers
Stash Community Scrapers is a large open-source collection of metadata extraction tools designed to work with the Stash media management platform, enabling automated scraping of content information from various online sources. The repository contains hundreds of scraper definitions written primarily in YAML and Python, each tailored to extract structured metadata such as titles, performers, tags, and media details from specific websites. -
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Claude Code Hooks Mastery
Master Claude Code Hooks
Claude Code Hooks Mastery is a trending community-centric GitHub repository aimed at helping developers master Claude Code hooks — customizable integration points that let users extend, automate, and augment workflows when using Claude Code, an agentic terminal coding assistant. Although the project itself doesn’t include a single coherent application, it functions as a curated collection of advanced hook examples, best practices, and coding patterns that show how to tailor Claude Code to specific use cases such as automated CI workflows, custom command triggers, and integrations with external tools. The repository is part of a larger ecosystem of Claude Code tooling that enables natural-language-driven coding tasks, and the hooks contained here help users go beyond default behaviors to solve real problems efficiently. -
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Perceval
An open source framework for programming photonic quantum computers
An open-source framework for programming photonic quantum computers. Through a simple object-oriented Python API, Perceval provides tools for composing circuits from linear optical components, defining single-photon sources, manipulating Fock states, running simulations, reproducing published experimental papers and experimenting with a new generation of quantum algorithms. It aims to be a companion tool for developing photonic circuits – for simulating and optimizing their design, modeling... -
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OSX-KVM
Run macOS on QEMU/KVM
OSX-KVM is a collection of scripts, firmware files, and documentation for running macOS virtual machines on Linux with QEMU and KVM. It uses OpenCore and OVMF components to create a Virtual Hackintosh without requiring a Mac host. The project can fetch installers for multiple macOS generations, prepare installation media, and guide users through the complete virtual machine setup. -
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Lutris
Lutris desktop client in Python
Lutris is a video game preservation platform aiming to keep your video game collection up and running for the years to come. Over the years, video games have gone through many different hardware and software platforms. By offering the best software available to run your games, Lutris makes it easy to run all your games, old and new. We provide emulators, compatibility layers and game engine re-implementations needed to run games in the most optimal way, often offering an enhanced experience compared to the original platform. ... -
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Terraform Examples and Modules for GC
End-to-end modular samples and landing zones toolkit for Terraform
Terraform Examples and Modules for GC is a comprehensive infrastructure-as-code toolkit built on Terraform that enables organizations to design, deploy, and manage enterprise-grade Google Cloud environments using modular and reusable components. It provides a collection of end-to-end blueprints and composable modules that allow teams to implement standardized cloud architectures such as landing zones, networking configurations, and security frameworks. The project is designed to accelerate cloud adoption by offering opinionated yet flexible patterns aligned with Google Cloud best practices, helping organizations bootstrap their environments quickly while maintaining governance and scalability. ... -
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douyin
Open source Douyin crawler for collecting and downloading public data
DouyinCrawler is an open source data collection tool designed to gather publicly available information from the Douyin platform. It demonstrates how to build a Python-based web crawler combined with a graphical interface and command line functionality. It allows users to collect data from various types of Douyin content, including user profiles, videos, hashtags, and music pages. -
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Google Toolbox for Mac
Google Toolbox for Mac
Google Toolbox for Mac (GTMSession) is a comprehensive collection of open source Objective-C utilities and frameworks developed by Google to support macOS and iOS application development. It consolidates reusable code components drawn from various internal Google projects, offering developers a wide range of tools for building efficient, maintainable Apple platform software. The library includes modules for networking, logging, testing, data handling, and user interface extensions, helping developers avoid reinventing common functionality. ... -
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System Design Primer
Learn how to design large-scale systems
System Design Primer is a curated, open source collection of resources that helps engineers learn how to design large-scale systems. The project is structured as a comprehensive guide covering core system design concepts, trade-offs, and patterns necessary for building scalable, reliable, and maintainable systems. It offers both theoretical foundations—such as scalability principles, the CAP theorem, and consistency models—and practical exercises, including real-world system design interview questions with sample solutions, diagrams, and code. ... -
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Claude Code Skills & Plugins
232+ Claude Code skills & agent plugins for Claude Code, Codex
Claude Skills is a repository that provides a collection of structured skill definitions designed to enhance the capabilities of Claude-based AI systems. Each skill encapsulates a specific capability, such as coding, analysis, or workflow execution, allowing the model to perform tasks more effectively. The project emphasizes modularity, enabling skills to be combined and reused across different contexts. -
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My Python Eggs
Python Examples
My Python Eggs, commonly associated with the geekcomputers Python repository, is a large collection of practical Python scripts and small programs created primarily for experimentation, automation, and educational purposes. Rather than being a single cohesive application, it functions as a repository of utilities that demonstrate how Python can be used to solve everyday problems and automate repetitive tasks. The scripts cover a wide range of topics, including file management, networking, system monitoring, web scraping, and even simple games, making it a versatile learning resource. ... -
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Google Kubernetes Engine (GKE) Samples
Sample applications for Google Kubernetes Engine (GKE)
Google Kubernetes Engine (GKE) Samples repository is a comprehensive collection of sample applications and reference implementations designed to demonstrate how to build, deploy, and manage workloads on Google Kubernetes Engine (GKE). It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. -
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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. -
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. -
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FEAPDER
Powerful Python crawler framework for scalable web scraping tasks
feapder is a Python-based web crawling framework designed to simplify the process of building scalable and efficient web scrapers. It focuses on providing a developer-friendly environment that makes it easier to create, run, and manage crawlers for a variety of data collection tasks. It includes several built-in spider types, such as AirSpider, Spider, TaskSpider, and BatchSpider, which address different crawling scenarios ranging from lightweight scraping to distributed and batch-based jobs. feapder supports features such as breakpoint resume, allowing crawlers to continue from where they stopped without losing progress. ... -
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DATAGEN
AI-driven multi-agent research assistant automating hypothesis
DATAGEN is an AI-driven multi-agent research and data analysis platform designed to automate complex analytical workflows. The system coordinates multiple specialized AI agents that collaborate to perform tasks such as hypothesis generation, data collection, analysis, visualization, and report creation. Instead of requiring users to manually orchestrate each stage of a research process, the platform allows these agents to coordinate automatically and handle the workflow end-to-end. The project integrates several modern AI frameworks including LangChain, LangGraph, and large language models to manage reasoning and data processing tasks. ... -
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llmware
Unified framework for building enterprise RAG pipelines
...It provides a unified interface for constructing retrieval-augmented generation pipelines, agent workflows, and document intelligence applications. One of the framework’s defining characteristics is its collection of small specialized language models optimized for specific tasks such as summarization, classification, and document analysis. The system supports a wide range of inference backends including PyTorch, OpenVINO, ONNX Runtime, and other optimized runtimes, allowing developers to choose the most efficient execution environment for their hardware. -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
Antigravity Awesome Skills is a playful yet practical repository that curates a set of clever, expressive, and sometimes whimsical AI agent skill templates designed to help users bootstrap agent behavior quickly. Rather than focusing on production-grade systems, it provides creative and high-impact skills that demonstrate how agents can be used to automate tasks, generate content, assist with daily operations, or integrate into larger workflows with minimal configuration. The project... -
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Open Source Vizier
Python-based research interface for blackbox
...Allows a user to setup an OSS Vizier Server, which can host black-box optimization algorithms to serve multiple clients simultaneously in a fault-tolerant manner to tune their objective functions. Defines abstractions and utilities for implementing new optimization algorithms for research and to be hosted in the service. A wide collection of objective functions and methods to benchmark and compare algorithms. Define a problem statement and study configuration. Setup a local server, setup a client to connect to the server, perform a typical tuning loop, and use other client APIs.
