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Awesome

repository·main·Indexed 11 days ago

https://github.com/sindresorhus/awesome

A massive, curated collection of 'awesome' lists covering various programming languages, platforms, and technologies to help developers find high-quality tools and resources.

Tokens
6.8K
Snippets
2
Records
33
Agent score
99%

What's inside Awesome

  2. Explore Back-End Development resources

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    A curated collection of resources for back-end development, including:

    • Languages & Frameworks:
      • Python: Flask, Pyramid, Dash, FastAPI, and Reflex (frontend/backend with no JS).
      • PHP: CakePHP, Symfony, Laravel, Lumen, Phalcon, and Slim.
      • Ruby: Rails.
      • Java: Dropwizard, Apache Wicket, and Vert.x (reactive JVM toolkit).
      • Go: Fiber (built on Fasthttp).
      • Swift: Vapor.
      • .NET: Blazor (WebAssembly).
    • Infrastructure & DevOps:
      • Containerization & Orchestration: Docker, Kubernetes, and Kustomize.
      • Infrastructure as Code (IaC): Terraform, CDK, and OpenTofu.
      • Deployment & Servers: Vagrant, nginx, .htaccess snippets, and Serverless Framework.
    • Cloud & Security:
      • IAM: User accounts, authentication, and authorization.
      • Cloud Infrastructure: Kubernetes and Serverless architectures.

  3. Explore JavaScript resources

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    The JavaScript section provides curated lists for various aspects of the ecosystem, including:

  4. Explore Big Data and Data Engineering resources

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    The Big Data section contains resources for managing and processing large-scale datasets:

    • Core Technologies: Hadoop (distributed storage/processing) and Apache Spark (large-scale data processing engine).
    • Data Management: Data Engineering, Streaming, and Big Data general resources.
    • Analytics & Visualization: Qlik (BI platform) and Splunk (real-time machine-generated data analysis).
    • Datasets & Analysis: Public Datasets and Network Analysis.

  7. Explore Miscellaneous Awesome Lists

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    The awesome repository contains a curated collection of high-quality resources across various domains. The 'Miscellaneous' section includes specialized lists for topics such as:

  9. Explore Game Development and Gaming resources

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    The Gaming section provides resources for both playing and creating games:

    • Game Engines: Godot, Unity, LÖVE, Construct 2, Gideros, PlayCanvas, GameMaker, Babylon.js, and Flame (for Flutter).
    • Development Platforms: PICO-8 (fantasy console), Game Boy Development, Roblox, and CHIP-8 (virtual machine).
    • Specialized Dev: Game Engine Development, Game Production, and Haxe Game Development.
    • Learning & Community: Games of Coding (learn via games), Discord Communities, and Esports.

  10. Explore Front-End Development resources

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    A curated collection of resources for front-end development, including:

    • Core Technologies: HTML5, CSS (Frameworks, Scalability, Critical-Path Tools), SVG, Canvas, WebGL, WebGPU, and WebAssembly.
    • JavaScript Frameworks & Libraries: React (Relay, Hooks, Draft.js), Angular, Vue.js, Svelte, Ember, Backbone, KnockoutJS, Dojo Toolkit, Cycle.js, Preact, and jQuery.
    • Styling & UI: Tailwind CSS, Sass, Less, PostCSS, Material Design, Ant Design, Material-UI, and BEM.
    • State & Data: Redux, Inertia.js, and D3 for data visualization.
    • Modern Architectures: JAMstack, Progressive Web Apps (PWA), Service Workers, and Offline-First development.
    • Specialized Tools: Web Audio, Frontend GIS, Web Typography, and Chrome DevTools.

  11. Explore Computer Science resources

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    The Computer Science section provides curated lists for various specialized fields including:

    • Machine Learning: Includes resources for ML with Ruby, Core ML Models (Apple), H2O (distributed ML in Java/R/Python/Scala), JAX (high-performance research), and XAI (explainable AI).
    • Natural Language Processing (NLP): Covers Speech and NLP, including specific resources for Spanish and NLP with Ruby, as well as Question Answering and Natural Language Generation.
    • Deep Learning: Resources for TensorFlow, TensorFlow.js (web-based ML), and TensorFlow Lite (on-device ML).
    • Other Fields: Cryptography, Computer Vision, Quantum Computing, Functional Programming, and Theoretical Computer Science.