Awesome GitHub RepositoriesSet Data Structures

Dragonfly is a high-performance, multi-model in-memory data store designed to serve as a drop-in replacement for existing database infrastructures. By utilizing a multi-threaded, shared-nothing architecture and a fiber-based concurrency model, it maximizes CPU utilization and minimizes latency for read and write operations. The system supports a wide range of data structures, including strings, hashes, lists, sets, sorted sets, and JSON documents, while maintaining full compatibility with standard industry wire protocols and client libraries. What distinguishes Dragonfly is its focus on effic

This project is a computer science educational resource and a library of common data structures and algorithms implemented in Swift. It serves as a practical reference for studying complexity and efficiency through solved algorithmic problems and conceptual guides. The collection includes implementations of linear and hierarchical data structures, such as stacks, queues, linked lists, and trees. It covers a wide range of computational patterns, including graph and pathfinding implementations, mathematical numerical methods, and data compression techniques. The project also provides implement

This project is a comprehensive collection of common computer science algorithms and data structures implemented in Swift. It serves as an educational reference and library for studying computational complexity, algorithmic logic, and data structure engineering through practical code examples. The repository provides a wide suite of data structure implementations, including various types of linked lists, heaps, hash tables, and an extensive range of hierarchical trees such as Red-Black, B-Tree, and Splay trees. It also covers diverse sorting and searching techniques, from basic bubble sort to

Python is a high-level, interpreted programming language designed for readability and versatility. It operates via a bytecode-based virtual machine and manages memory automatically through reference-counting garbage collection. The language supports multiple programming paradigms, including object-oriented, imperative, and functional styles, and provides a comprehensive standard library for system operations, networking, and data handling. The language is distinguished by its dynamic nature, allowing for runtime object introspection and metaclass-driven class creation. It utilizes protocol-ba

This project is a comprehensive, community-maintained knowledge base and toolkit designed for competitive programming. It serves as a centralized repository for algorithmic theory, data structures, and mathematical techniques, providing a structured reference for informatics and collegiate programming competitions. The project distinguishes itself by integrating educational content with a robust suite of automation utilities. It provides a complete workflow for competitive programming, including tools for automated test case generation, solution verification, and direct interaction with onlin

core-js is a comprehensive compatibility layer and standard library polyfill that implements ECMAScript proposals and stable language features across diverse JavaScript runtimes. It serves as a runtime environment shim to ensure consistent execution of global objects, iteration protocols, and standard library methods in older browsers or non-browser environments. The project is distinguished by its delivery models, offering both prototype-based global polyfilling and a pure-module implementation. This allows for the integration of modern functionality without modifying global prototypes to pr

This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha

This project is an educational resource designed for learning the Python programming language. It serves as a tutorial repository and programming guide, providing a collection of annotated scripts, code examples, and cheatsheets to help users master syntax and core fundamentals. The resource focuses on moving from basic language syntax to advanced implementation, with a particular emphasis on object-oriented programming, the use of the Python standard library, and scripting automation for business workflows. The content covers a broad range of programming capabilities, including control flow

Cayley is a graph database engine designed for storing and querying interconnected data using a quad-based data model. It functions as an RDF quad store, managing information through subjects, predicates, objects, and labels. The system features a modular graph store architecture with pluggable backends, allowing it to swap between in-memory storage and various external persistent databases. It includes a GraphQL-inspired API and a dedicated data visualizer for the interactive exploration of nodes and edges. Query capabilities cover bidirectional path traversal and multi-syntax execution usi

Rete is a framework for building interactive, node-based visual interfaces and dataflow programming environments. It provides a core engine that processes directed graphs, allowing developers to define modular logic where nodes represent operations and connections represent the flow of data or control. By decoupling the graph logic from the user interface, the framework enables the creation of custom visual editors that can be integrated into various frontend component libraries. The project distinguishes itself through a highly extensible, signal-driven architecture that supports complex req

Garnet is a multi-threaded in-memory database and distributed key-value store. It functions as a high-performance remote cache store that implements the RESP wire protocol to maintain compatibility with existing Redis clients and libraries. The project is distinguished by a shared-memory architecture that enables parallel request processing across multiple cores for sub-millisecond latency. It features a tiered storage system that automatically offloads colder data from system memory to SSD or cloud storage layers, and includes a specialized vector search database for high-dimensional similar

phpredis is a C-based native extension that bridges PHP applications with Redis servers for high-performance data storage and retrieval. It serves as an interface for manipulating strings, hashes, lists, sets, and sorted sets while providing a direct path for executing Redis commands and server-side scripts. The extension provides comprehensive support for distributed environments and high availability. It interfaces with Redis Cluster to distribute data across multiple nodes using hash slots and manages Redis Sentinel for service discovery and automatic failover. It also enables shared state

pysheeet es una biblioteca de referencia técnica que proporciona una colección curada de fragmentos de código y patrones de implementación para el desarrollo avanzado en Python, integración de sistemas y computación de alto rendimiento. Sirve como una guía completa para implementar programación de red de bajo nivel, extensiones nativas en C y programación asíncrona y concurrente. El proyecto proporciona frameworks especializados para el desarrollo y despliegue de modelos de lenguaje de gran tamaño, incluyendo herramientas para inferencia distribuida en GPU y servicio de alto rendimiento. También incluye patrones detallados para la orquestación de clústeres de computación de alto rendimiento, cubriendo la asignación de recursos de GPU y la gestión de cargas de trabajo en múltiples nodos. La biblioteca cubre una amplia superficie de capacidades, incluyendo comunicación de red segura y criptografía, mapeo objeto-relacional y gestión de bases de datos, y la implementación de estructuras de datos y algoritmos complejos. También proporciona utilidades para la gestión de memoria, interoperabilidad nativa a través de interfaces de funciones externas e integración de sistemas operativos a nivel de sistema.

This project is a comprehensive library of practical Python code examples and patterns. It provides a collection of scripts and snippets designed to demonstrate a wide range of programming tasks, from basic syntax to advanced implementation patterns. The repository focuses on several core domains, including the implementation of concurrency and multithreading examples, data analysis snippets for cleaning and manipulating tabular data, and various data visualization examples. It also covers automation scripts for file system management and a variety of general programming patterns. Additional

JimuReport is an open-source reporting and dashboard engine designed to be embedded directly into Spring Boot applications. Its core identity centers on generating data reports and full-screen dashboards from natural language descriptions, eliminating the need for manual design. The platform also provides a conversational query interface that translates plain-language questions into database queries, returning results as tables and charts without requiring SQL knowledge. What distinguishes JimuReport is its integration of AI skills that can be installed with a single command, enabling report

go-datastructures is a collection of thread-safe and lock-free data structures designed for high-performance concurrent applications in Go. It provides a modular library of specialized algorithmic toolsets, including a lock-free collection library and an immutable data structure library. The project distinguishes itself through a suite of persistent AVL trees and hash array mapped tries that use branch-copying to preserve previous versions. It also implements non-blocking hash maps, queues, and tries that enable linearizable snapshots and concurrent updates without the use of mutual exclusion

Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

This project provides a curated collection of high-frequency, non-informative Chinese words sourced from academic and industry standards. It serves as a reference dataset and a stopword collection designed for use in natural language processing tasks. The repository focuses on Chinese text preprocessing to reduce noise and improve the accuracy of machine learning models. It provides filtered datasets specifically for Chinese information retrieval, sentiment analysis preparation, and general data cleaning. The project utilizes pre-compiled lexicons and flat-file storage to enable efficient st

Este proyecto es una implementación en TensorFlow de un framework de traducción de imagen a imagen basado en redes generativas adversarias condicionales (cGAN). Proporciona las herramientas para entrenar modelos que mapean imágenes de entrada a imágenes de salida basadas en patrones visuales aprendidos, así como un servidor para procesar solicitudes de traducción de imágenes y servir puntos de control (checkpoints) de modelos entrenados a clientes web. El framework incluye un sistema para convertir pesos de modelos entrenados en un formato portátil para inferencia basada en navegador. También cuenta con un proceso de validación que genera informes comparativos analizando conjuntos de imágenes de entrada, salida y destino utilizando un punto de control entrenado. El código base cubre todo el pipeline desde la ingeniería de datos, incluyendo la preparación de conjuntos de datos de imágenes y el pipelining basado en pares, hasta el entrenamiento adversarial condicional. Admite transformaciones visuales específicas como la colorización de imágenes en escala de grises y la generación de imágenes sintéticas.

dplyr es una librería de manipulación de datos en R que proporciona una gramática para transformar data frames tabulares. Funciona como un procesador de data frames en memoria y una herramienta de álgebra de datos relacionales, utilizando un conjunto consistente de verbos para filtrar, seleccionar y resumir datos. El proyecto incluye un motor de traducción SQL que convierte expresiones de manipulación de datos de alto nivel en consultas optimizadas. Esto permite a los usuarios realizar transformaciones directamente en bases de datos relacionales remotas y almacenamiento en la nube sin necesidad de descargar los datos localmente. La librería cubre una amplia gama de operaciones tabulares, incluyendo la mutación de columnas, el subconjunto de filas y la unión de datos relacionales. También proporciona capacidades para el análisis de datos agrupados, permitiendo particionar conjuntos de datos para realizar agregaciones y resúmenes independientes.