Open Source Windows Libraries - Page 20
Sort By:
Libraries for Windows
View 56 business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
2
Alpakka Kafka
Alpakka is a Reactive Enterprise Integration library for Java
The Alpakka project is an open source initiative to implement stream-aware and reactive integration pipelines for Java and Scala. It is built on top of Akka Streams and has been designed from the ground up to understand streaming natively and provide a DSL for reactive and stream-oriented programming, with built-in support for backpressure. Akka Streams is a Reactive Stream and JDK 9+ java.util.concurrent.Flow-compliant implementation and therefore fully interoperable with other implementations. As Kafka’s client protocol negotiates the version to use with the Kafka broker, you may use a Kafka client version that is different than the Kafka broker’s version. -
3
Amazon Braket Python Schemas
A library that contains schemas for Amazon Braket
Amazon Braket Python Schemas is an open source library that contains the schemas for Braket, including intermediate representations (IR) for Amazon Braket quantum tasks and offers serialization and deserialization of those IR payloads. Think of the IR as the contract between the Amazon Braket SDK and Amazon Braket API for quantum programs. Schemas for the S3 results of each quantum task. Schemas for the device capabilities of each device. The preferred way to get Amazon Braket Python Schemas is by installing the Amazon Braket Python SDK, which will pull in the schemas. You can install from source by cloning this repository and running a pip install command in the root directory of the repository. There are currently two types of IR, including jaqcd (JsonAwsQuantumCircuitDescription) and annealing. -
4
Amazon EC2 Instance Selector
A CLI tool and go library which recommends instance types
A CLI tool and go library which recommends instance types based on resource criteria like vcpus and memory. There are over 270 different instance types available on EC2 which can make the process of selecting appropriate instance types difficult. Instance Selector helps you select compatible instance types for your application to run on. The command-line interface can be passed resource criteria like vcpus, memory, network performance, and much more and then return the available, matching instance types. If you are using spot instances to save on costs, it is a best practice to use multiple instances types within your auto-scaling group (ASG) to ensure your application doesn't experience downtime due to one instance type being interrupted. Instance Selector will help to find a set of instance types that your application can run on. -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
-
5
Ansible Examples
A few starter examples of ansible playbooks, to show features
This repository collects practical, real-world examples of using Ansible to automate infrastructure, deployments, and configurations. Each directory demonstrates a specific use case—ranging from setting up web servers, load balancers, and databases to orchestrating multi-tier applications in cloud environments. The examples highlight common Ansible practices such as organizing inventories, writing reusable playbooks, using roles, and handling variables and templates. They’re designed to be adapted directly into your own infrastructure or to serve as reference blueprints when learning how to structure automation projects. Whether you’re managing a handful of servers or deploying at scale, this repo provides starting points that illustrate how Ansible can streamline repetitive operational tasks. -
6
Anthony's VS Code Settings
My VS Code settings and extensions
Anthony's VS Code Settings contains the personal VS Code settings, extensions list and snippets of Anthony Fu— essentially his curated development environment configuration. It provides the settings.json, extensions.json, and other snippet files under .vscode/. The idea is for others to inspect, adopt, clone, or adapt his settings for a more consistent VS Code experience. The settings cover font, icons, product icons, theme, file-nesting config (via the other project), linting integration, and other productivity shortcuts. It's not a typical library but rather a shareable developer setup. Because the settings are openly published, it helps anyone to quickly replicate a well-tuned VS Code environment. The repository is under MIT license and includes 2.2k stars, showing community interest. -
7
Appyx
Model-driven navigation + UI components with gesture control
Appyx is a modern navigation and UI framework for Jetpack Compose and Compose Multiplatform that introduces a model-driven approach to building application navigation and interactive interfaces. Unlike traditional navigation libraries that rely on predefined patterns such as back stacks, Appyx allows developers to define their own navigation models, giving them full control over how screens and UI elements transition and interact. This model-driven paradigm separates navigation logic from UI rendering, making navigation state testable, reusable, and easier to maintain in large applications. The framework also supports advanced transition animations and gesture-driven interactions, enabling developers to create highly dynamic and visually rich user experiences beyond standard navigation flows. -
8
Article Extractor
To extract main article from given URL with Node.js
A Node.js library for extracting main content from web articles, removing unnecessary clutter like ads and navigation elements. -
9
Azure Data SQL Samples
Official Microsoft repository containing code samples for SQL Server
This GitHub repository contains code samples that demonstrate how to use Microsoft's Azure Data products including SQL Server, Azure SQL Database, Azure Synapse, and Azure SQL Edge. Each sample includes a README file that explains how to run and use the sample. Note that certain features like In-Memory OLTP are edition specific for SQL Server and would be possible to implement if the edition which supports that feature is being used to run the sample. Releases allow you to conveniently download sample databases or applications without the need to build them from source code. Wide World Importers sample database v1.0 is the main sample for SQL Server 2016 and Azure SQL Database. It contains both an OLTP and an OLAP database. In-Memory OLTP Performance Demo v1.0 illustrates the performance benefits of the In-Memory OLTP technology built into SQL Server and Azure SQL Database. IoT Smart Grid sample v1.0 illustrates how SQL Server can be leveraged to ingest data from IoT devices. -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
10
Benchmark
A microbenchmark support library
A library to benchmark code snippets, similar to unit tests. -
11
Boltons
250+ constructs, recipes, and snippets which extend the Python library
Boltons is a set of pure-Python utilities in the same spirit as, and yet conspicuously missing from, the standard library. Due to the nature of utilities, application developers might want to consider other integration options. Boltons is tested against Python 2.6-2.7, 3.4-3.7, and PyPy. The majority of boltons strive to be “good enough” for a wide range of basic uses, leaving advanced use cases to Python’s myriad specialized 3rd-party libraries. In many cases the respective boltons module will describe 3rd-party alternatives worth investigating when use cases outgrow boltons. If you’ve found a natural “next-step” library worth mentioning, consider filing an issue! boltons has a minimalist architecture, remain as consistent, and self-contained as possible, with an eye toward maintaining its range of use cases and usage patterns as wide as possible. The boltons package depends on no packages, making it easy for inclusion into a project. -
12
Brave
Java distributed tracing implementation compatible with Zipkin backend
Brave is a distributed tracing instrumentation library. Brave typically intercepts production requests to gather timing data, correlate and propagate trace contexts. While typically trace data is sent to Zipkin server, third-party plugins are available to send to alternate services such as Amazon X-Ray. This repository includes dependency-free Java libraries and instrumentation for common components used in production services. For example, this includes trace filters for Servlet and log correlation for Apache Log4J. Brave's dependency-free tracer library works against JRE6+. This is the underlying api that instrumentation use to time operations and add tags that describe them. This library also includes code that parses X-B3-TraceId headers. -
13
CFD Python
Sequence of Jupyter notebooks featuring the 12 Steps to Navier-Stokes
CFD Python, a.k.a. the 12 steps to Navier-Stokes, is a practical module for learning the foundations of Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow. The module was part of a course taught by Prof. Lorena Barba between 2009 and 2013 in the Mechanical Engineering department at Boston University (Prof. Barba since moved to George Washington University). The module assumes only basic programming knowledge (in any language) and some background in partial differential equations and fluid mechanics. The "steps" were inspired by the ideas of Dr. Rio Yokota, who was a post-doc in Prof. Barba's lab until 2011, and the lessons were refined by Prof. Barba and her students over several semesters teaching the CFD course. We wrote this set of Jupyter notebooks in 2013 to teach an intensive two-day course in Mendoza, Argentina. -
14
Caffe
A fast open framework for deep learning
Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. It’s been used in numerous projects, from startup prototypes and academic research projects, to large scale industrial applications. -
15
Calf
Calf is a library that allows you to easily create adaptive UIs
Calf is a library that allows you to easily create adaptive UIs for your Compose Multiplatform apps. -
16
Cats Effect
The pure asynchronous runtime for Scala
Cats-Effect is a high-quality functional programming library for Scala that provides a principled way to represent and manage side effects, particularly asynchronous and concurrent computations. It is part of the broader Typelevel ecosystem and builds on the abstractions from Cats (such as Functor, Monad, etc.). The core abstraction is the IO type (or effect types more generally), which encodes effectful computations in a pure, referentially transparent way. Cats-Effect offers capabilities like deferred execution, cancellation, resource safety (Resource), fiber concurrency (lightweight threads), and interoperation with underlying runtime platforms (JVM, Java concurrency, etc.). It enables developers to write effectful code while preserving composability, purity, and modular reasoning about side effects. -
17
Chumsky
Write expressive, high-performance parsers with ease.
Chumsky is a parser library for Rust that focuses on expressiveness and performance. It provides developers with tools to write high-performance parsers using combinators, suitable for a wide range of parsing tasks. -
18
ClashN
A clash client for Windows, support Mihomo
clashN is a Windows desktop client for the Clash networking engine, providing a graphical interface to manage proxies, rules, and profiles. It wraps the Clash core in a familiar, configurable UI so users can import subscriptions, switch nodes, and observe connections without editing YAML by hand. The app emphasizes rule-based routing, letting you combine rule providers and policy groups to steer traffic by domain, process, or destination category. System-wide proxy control, including PAC and TUN/TAP options, helps route applications that don’t natively support proxies. Logs, traffic charts, and connection inspectors make troubleshooting and optimization straightforward. For power users, granular profile editing and hot-reloading reduce the friction of iterating on configurations. -
19
Claude Code Projects Index
An index of my Claude Code related repos
Claude Code Projects Index is a curated directory of projects, tools, and resources built around Claude Code and related AI development ecosystems. It functions as a centralized index that helps developers discover useful repositories, workflows, and integrations. The project is organized to make navigation easy, grouping resources by categories such as tooling, frameworks, and use cases. It is particularly valuable for developers exploring the Claude ecosystem and looking for inspiration or best practices. The repository is continuously updated, reflecting the evolving landscape of AI-assisted development. It also serves as a knowledge-sharing platform, highlighting innovative approaches and implementations. Overall, it acts as a discovery hub that accelerates learning and adoption of AI development tools. -
20
Claude Cookbooks
A collection of notebooks/recipes showcasing ways of using Claude
Claude Cookbooks is a curated collection of practical examples, notebooks, and implementation guides that demonstrate how to effectively use Claude’s API across a wide range of tasks. It serves as both a learning resource and a reference library, helping developers understand how to apply AI capabilities such as classification, summarization, and retrieval-augmented generation in real-world scenarios. The repository includes structured examples for integrating Claude with external tools, databases, and APIs, showcasing how to extend its functionality beyond basic text generation. It also covers advanced techniques like sub-agent orchestration, prompt optimization, and automated evaluation workflows. The content is organized into thematic sections, allowing users to explore specific capabilities or integration patterns systematically. Designed with accessibility in mind, the examples are primarily written in Python but can be adapted to other languages. -
21
Comprehensive Python Cheatsheet
Comprehensive Python Cheatsheet
Comprehensive Python Cheatsheet is a comprehensive reference resource that consolidates essential Python syntax, idioms, and best practices into a highly readable and searchable format. The project is designed to help developers quickly recall language features without digging through full documentation, making it especially useful for both beginners and experienced programmers. It covers a broad range of topics including data structures, control flow, functions, object-oriented programming, standard library usage, and common patterns. The repository includes both web and printable versions, allowing users to access the material in multiple formats depending on their workflow. Because it is continuously maintained, the cheatsheet reflects modern Python usage and practical conventions. Overall, it serves as a fast lookup companion for everyday Python development. -
22
Cytoscape.js
Graph theory library for visualization and analysis
A fully featured graph library written in pure JS. Permissive open source license (MIT) for the core Cytoscape.js library and all first-party extensions. Used in commercial projects and open-source projects in production. Designed for users first, for both frontfacing app usecases and developer usecases. Highly optimized. Compatible with All modern browsers. Legacy browsers with ES5 and canvas support. ES5 and canvas support are required, and feature detection is used for optional performance enhancements. Browsers circa 2012 support ES5 fully: IE10, Chrome 23, Firefox 21, Safari 6 (caniuse). Browsers with partial but sufficient ES5 support also work, such as IE9 and Firefox 4. The documentation and examples are not optimized for old browsers, although the library itself is. Some demos may not work in old browsers in order to keep the demo code simple. -
23
Dart
Dart is a client-optimized language for fast apps on any platform
The Dart SDK, including the VM, dart2js, core libraries, and more. Develop with a programming language specialized around the needs of user interface creation. Make changes iteratively, use hot reload to see the result instantly in your running app. Compile to ARM & x64 machine code for mobile, desktop, and backend. Or compile to JavaScript for the web. Mature and complete async-await for user interfaces containing event-driven code, paired with isolate-based concurrency. A programming language optimized for building user interfaces with features such as sound null safety, the spread operator for expanding collections, and collection if for customizing UI for each platform. A programming language that is easy to learn, with a familiar syntax. Make changes to your source code iteratively, using hot reload to instantly see the effect in the running app. -
24
DeepSeed
Deep learning optimization library making distributed training easy
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. Sparse attention of DeepSpeed powers an order-of-magnitude longer input sequence and obtains up to 6x faster execution comparing with dense transformers. -
25
Dependabot
Dependabot's core logic for creating update PR's
Dependabot-Core is the library at the heart of Dependabot security/version updates. Use it to generate automated pull requests updating dependencies for projects written in Ruby, JavaScript, Python, PHP, Dart, Elixir, Elm, Go, Rust, Java and .NET. It can also update git submodules, Docker files, and Terraform files. Check for the latest version of a dependency that's resolvable given a project's other dependencies. Generate updated manifest and lockfiles for a new dependency version. Generate PR descriptions that include the updated dependency's changelogs, release notes, and commits.
