awesome-repositories.com
博客
awesome-repositories.com

通过 AI 驱动的搜索,发现最优秀的开源仓库。

探索精选搜索开源替代品自托管软件博客网站地图
项目关于排名机制媒体报道MCP 服务器
法律隐私政策服务条款
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

41 个仓库

Awesome GitHub RepositoriesConcurrent Task Execution

Executing multiple operations simultaneously using concurrency models to improve throughput.

Distinct from Parallel Task Execution: Focuses on general concurrent execution of logic, distinct from build/test task parallelism in dev tools.

Explore 41 awesome GitHub repositories matching development tools & productivity · Concurrent Task Execution. Refine with filters or upvote what's useful.

Awesome Concurrent Task Execution GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • scala/scalascala 的头像

    scala/scala

    14,548在 GitHub 上查看↗

    Scala is a statically typed programming language and compiler that combines object-oriented and functional programming paradigms. It serves as a cross-platform runtime language capable of targeting the Java Virtual Machine and JavaScript to share logic between backend servers and web frontends. The project provides a functional programming framework with immutable data structures and higher-order functions to build reliable concurrent and distributed applications. It distinguishes itself through deep interoperability with Java and JavaScript ecosystems and the ability to transform code into n

    Manages asynchronous computations and concurrent task execution to improve throughput.

    Scalafunctional-programmingjvm-languagesobject-oriented-programming
    在 GitHub 上查看↗14,548
  • morvanzhou/tutorialsMorvanZhou 的头像

    MorvanZhou/tutorials

    12,952在 GitHub 上查看↗

    This repository is a comprehensive collection of instructional guides and practical examples for Python development, focusing on machine learning, data science, and web scraping. It provides implementations for neural networks, reinforcement learning algorithms, and deep learning architectures using PyTorch, alongside detailed manuals for scientific computing and data visualization. The project distinguishes itself by offering specialized tutorials on concurrent programming to optimize CPU performance and guides for setting up Linux development environments. It covers the implementation of ad

    Executes multiple operations simultaneously using concurrency models to handle several tasks without sequential blocking.

    Pythonmachine-learningmultiprocessingneural-network
    在 GitHub 上查看↗12,952
  • adambard/learnxinyminutes-docsadambard 的头像

    adambard/learnxinyminutes-docs

    12,287在 GitHub 上查看↗

    This project is a collection of programming language references and syntax cheat sheets designed for rapid developer onboarding. It serves as a library of code-based documentation that uses valid source code files to provide whirlwind tours of various language specifications. The project focuses on programming language learning by providing concise, commented code examples that explain core features and syntax in place. This approach enables developers to quickly grasp language-specific patterns, data types, and execution flow through a consistent reference format. The content covers a broad

    Shows how to execute multiple operations simultaneously using various concurrency models.

    Markdown
    在 GitHub 上查看↗12,287
  • tj/coT

    tj/co

    11,856在 GitHub 上查看↗

    co is a JavaScript generator control flow library and non-blocking workflow engine. It manages asynchronous logic by using generators and promises to simulate a synchronous coding style. The project transforms generator functions into standard functions that return promises, ensuring compatibility with non-generator interfaces. It also functions as a promise-based asynchronous orchestrator that executes multiple operations concurrently through the recursive resolution of nested promise collections. The library provides high-level primitives for asynchronous flow control and non-blocking work

    Executes multiple asynchronous operations simultaneously to improve throughput and minimize wait time.

    JavaScript
    在 GitHub 上查看↗11,856
  • xianhu/learnpythonxianhu 的头像

    xianhu/LearnPython

    8,484在 GitHub 上查看↗

    LearnPython is a programming tutorial consisting of a collection of practical code examples used to demonstrate Python language features and programming patterns. It serves as a comprehensive learning resource that implements core language concepts through functional code. The project provides specialized guides and samples covering several key domains. These include asynchronous network programming with event loops and coroutines, data visualization using numerical datasets for 2D and 3D plots, and web scraping for fetching content and automating login flows. It also features instructions on

    Shows how to run multiple functions in parallel using threads and processes to improve performance.

    Jupyter Notebooklearning-pythonpythonpython-flask
    在 GitHub 上查看↗8,484
  • crazyguitar/pysheeetcrazyguitar 的头像

    crazyguitar/pysheeet

    8,150在 GitHub 上查看↗

    pysheeet 是一个技术参考库,提供了一系列精选的代码片段和实现模式,用于高级 Python 开发、系统集成和高性能计算。它充当实现底层网络编程、原生 C 扩展以及异步和并发编程的综合指南。 该项目为大语言模型的开发和部署提供了专门的框架,包括用于分布式 GPU 推理和高性能服务的工具。它还包括用于高性能计算集群编排的详细模式,涵盖 GPU 资源分配和多节点工作负载管理。 该库涵盖了广泛的功能,包括安全网络通信和加密、对象关系映射和数据库管理,以及复杂数据结构和算法的实现。它还提供用于内存管理、通过外部函数接口(FFI)进行原生互操作以及系统级 OS 集成的实用程序。

    Provides implementation patterns for blocking execution until specific conditions, such as all tasks completing, are met.

    Python
    在 GitHub 上查看↗8,150
  • jackzhenguo/python-small-examplesjackzhenguo 的头像

    jackzhenguo/python-small-examples

    8,132在 GitHub 上查看↗

    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

    Implements the execution of multiple operations in separate threads to share CPU time and process tasks in parallel.

    Pythondata-sciencemachine-learningpython
    在 GitHub 上查看↗8,132
  • yuesong-feng/30daymakecppserveryuesong-feng 的头像

    yuesong-feng/30dayMakeCppServer

    7,040在 GitHub 上查看↗

    This project is a C++ TCP server framework and educational socket programming guide. It provides a high-performance network library focused on event-driven architecture, implementing a reactor pattern to handle thousands of simultaneous client connections. The framework is distinguished by its multi-threaded event loop, which utilizes a main-sub reactor coordination model to distribute network events across a worker thread pool. It includes an abstraction layer for non-blocking socket I/O and event multiplexing via the epoll system call, decoupling network transport from application business

    Supports executing asynchronous functions in a thread pool and retrieving results via futures.

    C++cppcppserverepoll
    在 GitHub 上查看↗7,040
  • autoscrape-labs/pydollautoscrape-labs 的头像

    autoscrape-labs/pydoll

    6,919在 GitHub 上查看↗

    pydoll is a Chrome DevTools Protocol automation library and headless browser controller used for web data extraction and parallel browser automation. It controls Chromium-based browsers via direct WebSocket connections, allowing it to manage isolated browser contexts and tabs while bypassing the overhead and detection associated with WebDriver. The project features an anti-bot evasion framework that mimics natural human behavior, including mouse movements generated via Bezier curves and variable typing patterns. It provides specialized stealth capabilities to bypass behavioral analysis and au

    Executes multiple automation tasks across different browser tabs simultaneously to increase throughput.

    Pythonanti-detectionautomationbrowser-automation
    在 GitHub 上查看↗6,919
  • weiye-jing/datax-webWeiYe-Jing 的头像

    WeiYe-Jing/datax-web

    6,009在 GitHub 上查看↗

    DataX Web is a web-based management platform for scheduling, building, executing, and monitoring distributed data synchronization jobs powered by DataX. It provides a visual console for creating and managing DataX tasks without manual JSON configuration, with a distributed executor cluster that auto-registers worker nodes and supports configurable routing and blocking strategies for task distribution. The platform offers cron-based task scheduling with dynamic start, stop, and immediate status changes, along with incremental sync capabilities that pass dynamic parameters to extract only new o

    Provides routing strategies and blocking policies for managing concurrent task execution across a cluster.

    Java
    在 GitHub 上查看↗6,009
  • rust-lang/futures-rsrust-lang 的头像

    rust-lang/futures-rs

    5,870在 GitHub 上查看↗

    Zero-cost asynchronous programming in Rust

    Spawning and driving multiple futures on executors, including thread pools and thread-local executors.

    Rustasync-foundations
    在 GitHub 上查看↗5,870
  • ruby-concurrency/concurrent-rubyruby-concurrency 的头像

    ruby-concurrency/concurrent-ruby

    5,830在 GitHub 上查看↗

    Concurrent Ruby is a comprehensive concurrency toolkit for the Ruby language that provides thread-safe data structures, synchronization primitives, and asynchronous execution patterns. It implements core concurrency abstractions including an actor model framework where isolated actors communicate through asynchronous message passing, a future and promise system for composing non-blocking operations, and thread pool executors that manage reusable worker threads for concurrent task execution. The library distinguishes itself through a broad set of coordination mechanisms that go beyond basic th

    Executes blocks in separate threads via thread pools, returning futures for result retrieval.

    Ruby
    在 GitHub 上查看↗5,830
  • angrave/systemprogrammingangrave 的头像

    angrave/SystemProgramming

    5,734在 GitHub 上查看↗

    This is an open-source, crowd-sourced wiki textbook that teaches Linux system programming in C. It covers the core operating system concepts of process management through the fork-exec-wait model, dynamic memory allocation using implicit free list heap allocators, inode-based file systems, inter-process communication via pipes and shared memory, POSIX threads with synchronization primitives, signal-based asynchronous notification, virtual memory with page table translation, and runtime diagnostics using Valgrind and GDB. The textbook distinguishes itself by providing practical, implementation

    Teaches concurrent task execution using POSIX threads across multiple CPU cores.

    在 GitHub 上查看↗5,734
  • lanmaster53/recon-nglanmaster53 的头像

    lanmaster53/recon-ng

    5,698在 GitHub 上查看↗

    recon-ng is an open source intelligence reconnaissance framework designed to automate the collection and aggregation of public information. It is a modular intelligence tool that utilizes a system of pluggable modules to harvest target data, resolve DNS queries, and parse web content. The framework is built as an API-driven tool with a programmatic interface to integrate with other security workflows. It is provided as a containerized application, using Docker to ensure a consistent environment for running reconnaissance tasks and managing a persistent data store. Its capabilities cover exte

    Uses a concurrent execution model to send multiple network requests simultaneously, reducing data gathering time.

    Python
    在 GitHub 上查看↗5,698
  • maiot-io/zenmlmaiot-io 的头像

    maiot-io/zenml

    5,452在 GitHub 上查看↗

    ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself

    Executes multiple pipeline steps concurrently to improve throughput and reduce total runtime.

    Python
    在 GitHub 上查看↗5,452
  • zenml-io/zenmlzenml-io 的头像

    zenml-io/zenml

    5,451在 GitHub 上查看↗

    ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning pipelines and agentic workflows. It provides a unified framework that manages the entire lifecycle of machine learning assets, from data processing and model training to the deployment of persistent inference services. By decoupling pipeline logic from underlying compute and storage, the platform enables teams to transition workflows seamlessly from local development environments to production-grade cloud infrastructure. The platform distinguishes itself through a service-oriented

    Executes independent work units in parallel using asynchronous submission to improve throughput and reduce execution time.

    Pythonagentopsagentsai
    在 GitHub 上查看↗5,451
  • swiftlang/swift-corelibs-foundationswiftlang 的头像

    swiftlang/swift-corelibs-foundation

    5,434在 GitHub 上查看↗

    该项目是一个 Swift 标准库扩展和跨平台系统库。它提供了一系列核心实用类型和基础数据结构,扩展了 Swift 基础语言,并作为处理网络和文件系统等系统操作的独立于操作系统的接口层。 该项目具有专门的 C++ 互操作层,将 C++ 类型和函数映射为兼容的 Swift 接口,以实现跨语言通信。这包括一个处理标准库类型和外部容器的桥接机制,允许将 C++ 类型映射为引用类型或值类型,以同步内存管理和语义。 其广泛的功能包括用于编码和解码 JSON 等结构化数据的序列化,以及用于管理区域感知格式、日历和区域设置的国际化框架。它还提供了用于处理 URL 和原始二进制数据的核心数据管理功能。

    Enables the execution of multiple operations simultaneously across multicore hardware to increase throughput.

    C
    在 GitHub 上查看↗5,434
  • njhu/iosprojectNJHu 的头像

    NJHu/iOSProject

    5,426在 GitHub 上查看↗

    该项目是 Objective-C iOS 应用程序演示和代码示例的集合。它提供了 iOS 环境中核心开发模式和系统级功能的实现。 该仓库专注于 Objective-C 运行时示例,演示了动态方法分发和运行时方法交换(swizzling)以修改对象行为。它还包括一个 Core Animation UI 库以及 iOS 多线程和并发管理的示例。 该项目涵盖了 UI 动画和图形、并发任务协调以及集成第三方服务进行身份验证和社交分享的功能。

    Executes multiple operations simultaneously using queues to prevent main thread blocking.

    Objective-Canimationcoreanimationcoregraphics
    在 GitHub 上查看↗5,426
  • hit-alibaba/interviewHIT-Alibaba 的头像

    HIT-Alibaba/interview

    5,253在 GitHub 上查看↗

    该项目是一个全面的技术面试准备指南和计算机科学知识库。它作为一个结构化的学习资源,旨在帮助软件工程师复习核心工程概念并准备专业编码评估。 该仓库专注于广泛的理论和实践领域,包括移动应用架构和操作系统基础的详细参考。它提供了关于软件架构模式和网络协议分析的精选材料,以支持职业发展。 该内容涵盖了基础能力,如数据结构与算法、并发与多线程以及内存管理。它还深入探讨了系统架构,包括进程调度、进程间通信和 UI 渲染优化。

    Discusses executing multiple units of work in parallel to improve processing throughput.

    Shellinterviewinterview-preparation
    在 GitHub 上查看↗5,253
  • sbt/sbtsbt 的头像

    sbt/sbt

    4,929在 GitHub 上查看↗

    Sbt 是一个专为 Scala 和 Java 设计的 JVM 构建工具和依赖管理系统。它作为一个多项目构建编排器,管理源代码的编译、从远程仓库解析外部库,并打包二进制文件以供分发。 该项目以其交互式构建系统而著称,该系统提供了一个用于实时状态检查和任务执行的读取-求值-打印循环(REPL)。它利用基于依赖图的执行模型来处理任务,并维护一个用于动态构建配置的类型安全键值存储。 其功能涵盖具有增量重编译、模块化项目组织和自动化测试执行的 JVM 构建自动化。该系统还支持跨版本编译、向云存储发布工件,以及用于添加自定义构建逻辑的可扩展插件模型。

    Executes independent build steps in parallel based on a dependency graph to significantly reduce total build time.

    Scala
    在 GitHub 上查看↗4,929
上一个123下一个
  1. Home
  2. Development Tools & Productivity
  3. Concurrent Task Execution

探索子标签

  • Applicative Task CombinationCombining asynchronous tasks for parallel or sequential execution using applicative patterns. **Distinct from Concurrent Task Execution:** Specifically addresses the applicative application of task-wrapped functions to task-wrapped values.
  • Build Task ParallelismExecuting independent build and test steps concurrently to reduce total project execution time. **Distinct from Concurrent Task Execution:** Distinct from general concurrent task execution by focusing specifically on the build-tool task graph
  • Execution BarriersMechanisms that block execution until a set of concurrent tasks all reach completion. **Distinct from Concurrent Task Execution:** Focuses on blocking synchronization barriers rather than general concurrent execution of logic.
  • Routing and Blocking PoliciesProvides routing strategies and blocking policies for managing concurrent task execution across a cluster. **Distinct from Concurrent Task Execution:** Distinct from Concurrent Task Execution: focuses on routing and blocking policies for task distribution rather than general concurrency execution.