Open Source Libraries - Page 96
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Google Weather v1.0
Google Weather v1.0
Google Weather v1.0 -
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GopenPGP V3
A high-level OpenPGP library
GopenPGP V3 is a high-level OpenPGP cryptographic library developed by ProtonMail that provides a user-friendly API for common encryption and signing operations in Go, abstracting the complexity of the underlying OpenPGP standards and golang crypto primitives. This library lets developers perform key generation, message encryption and decryption, digital signing, and signature verification with straightforward functions that hide much of the boilerplate and nuance typically required when working directly with OpenPGP implementations. Built on top of a forked version of the Go crypto library, gopenpgp supports current OpenPGP RFC standards and includes examples for working with password-based encryption and PGP keys, as well as detached and inline signatures. Because it’s designed for broad use, the library also targets go-mobile compatibility, meaning it can support mobile app use cases alongside server and desktop tooling. -
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Gossamer
Go Implementation of the Polkadot Host
Gossamer is a modular blockchain framework implemented in Go, serving as an execution environment for the Polkadot runtime. It allows developers to build and run nodes for various blockchain protocols within the Polkadot ecosystem. Gossamer's design emphasizes modularity and flexibility, enabling customization and integration of different services such as networking, block production, and JSON-RPC servers. -
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GraalPy
A Python 3 implementation built on GraalVM
GraalPy is a high-performance implementation of the Python language for the JVM built on GraalVM. GraalPy is a Python 3.11 compliant runtime. It has first-class support for embedding in Java and can turn Python applications into fast, standalone binaries. GraalPy is ready for production running pure Python code and has experimental support for many popular native extension modules. -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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Grabana
User-friendly Go library for building Grafana dashboards
Grabana provides a developer-friendly way of creating Grafana dashboards. Whether you prefer writing code or YAML, if you are looking for a way to version your dashboard configuration or automate the tedious and error-prone creation of dashboards, this library is meant for you. -
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Gradle Advanced Build Version Plugin
A plugin to generate the Android version code and version name
A plugin to generate the Android version code and version name automatically based on git commits number, date and Semantic Versioning. -
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Gradle Bintray Plugin
The Gradle Bintray Plugin allows you to publish artifacts to Bintray
The Gradle Bintray Plugin allows you to publish artifacts to Bintray. The plugin supports three methods to create groups of artifacts: Configurations, Publications and Copying specific files using filesSpec. One of the methods should be used to group artifacts to be uploaded to Bintray. Using the Configurations approach is the easiest, since this option attempts to infer what artifacts to upload based on the Gradle project and dependencies that are defined. Publications gives more fine-grained control, especially when needing to publish metadata for publishing to Maven Central. Copying specific files can be used as a last option, which provides the ability to define custom rules using the Gradle's CopySpec task. In general, the first two options should be sufficient for your needs. -
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Gradle Libraries Plugin
This plugin allows to specify versions of external libraries
This plugin allows to specify versions of external libraries in a centralized place and use them across the project. It's specifically useful for Gradle multi-projects. This plugin also uses com.github.ben-manes.versions plugin to automatically update libraries once new releases are available. Run ./gradlew syncLibraries to create $rootDir/dependencies.json file with all currently known dependencies. Once dependencies.json file is in place by generating via syncLibraries task or just by manually creating it, all declared in dependencies.json libraries can be used in project files. It's not a secret that it's really hard to keep libraries up to date especially when there are dozens and sometimes hundreds of them. For that purpose, this plugin has update libraries task that will automatically check for available new versions of libraries. -
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Gradle License Plugin
Gradle plugin that provides a task to generate a HTML license report
The Gradle License Plugin helps developers manage and audit software licenses for dependencies in Android and Java projects. It automatically detects third-party libraries and generates a report containing license details. This is particularly useful for ensuring compliance with open-source licenses, making it easier for teams to identify potential legal issues or attribution requirements before releasing software. -
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GradlePluginDevelop
Gradle execution process
A skeleton or demonstration project for developing Gradle plugins. It contains sample plugin code, project structure, examples of applying plugin logic, extension configuration, and build integration for Gradle plugin development. Gradle execution process, what is DSL, domain-specific language, common usage of Gradle, usage of Gradle advanced plug-ins, Gradle optimization for Android, using Javassist to the next floor, and problems encountered in Gradle development. Demonstration of plugin application in other modules. Plugin configuration and metadata. -
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Grafana Operator
An operator for Grafana that installs and manages Grafana instances
The Grafana Operator is a Kubernetes operator built to help you manage your Grafana instances and its resources in and outside of Kubernetes. Whether you’re running one Grafana instance or many, the Grafana Operator simplifies the processes of installing, configuring, and maintaining Grafana and its resources. Additionally, it's perfect for those who prefer to manage resources using infrastructure as code or using GitOps workflows through tools like ArgoCD and Flux CD. -
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Gramine
A library OS for Linux multi-process applications
Gramine is a lightweight library-operating system (Library OS) designed to run unmodified Linux applications with minimal dependencies on the host OS, and to offer enhanced isolation and portability. It was formerly known as Graphene, but the project renamed to Gramine to avoid naming conflicts and to reflect its broader ambition beyond the original research prototype. The idea is that instead of running a full guest OS in a VM, you embed your application inside Gramine, which handles the system-call interface, process and thread management, file system, and network abstractions — everything the application expects — but strips out the overhead and complexity of a full OS stack. One particularly strong use-case is confidential computing: Gramine supports Intel® SGX enclaves, allowing applications to run inside hardware-protected memory regions even while using standard Linux binaries with minimal porting effort. -
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the foundational ideas from DeepMind’s paper “Relational Inductive Biases, Deep Learning, and Graph Networks”, offering tools to explore relational reasoning and message-passing neural networks. Graph Nets supports both TensorFlow 1 and TensorFlow 2, working with CPU and GPU environments, and includes educational Jupyter demos for shortest path finding, sorting, and physical prediction tasks. The codebase emphasizes modularity, allowing users to easily define their own edge, node, and global update functions. -
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Graph Notebook
Library extending Jupyter notebooks to integrate with Apache TinkerPop
The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. This project includes many examples of Jupyter notebooks. It is recommended to explore them. All of the commands and features supported by graph notebook are explained in detail with examples within the sample notebooks. You can find them here. As this project has evolved, many new features have been added. If you are already familiar with graph-notebook but want a quick summary of new features added, a good place to start is the Air-Routes notebooks in the 02-Visualization folder. -
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Graph4NLP
Graph4nlp is the library for the easy use of Graph Neural Networks
Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP). It provides both full implementations of state-of-the-art models for data scientists and also flexible interfaces to build customized models for researchers and developers with whole-pipeline support. Built upon highly-optimized runtime libraries including DGL , Graph4NLP has both high running efficiency and great extensibility. The architecture of Graph4NLP is shown in the following figure, where boxes with dashed lines represent the features under development. Graph4NLP consists of four different layers: 1) Data Layer, 2) Module Layer, 3) Model Layer, and 4) Application Layer. Graph4nlp aims to make it incredibly easy to use GNNs in NLP tasks (check out Graph4NLP Documentation). -
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GraphHopper Routing Engine
Open source routing engine for OpenStreetMap
GraphHopper invests in an active open source community. Our flagships are the GraphHopper routing engine and jsprit, the toolkit for solving rich vehicle routing problems. We promote a fair & diverse mindset. jsprit is a Java based toolkit for solving rich traveling salesman problems (TSP) and vehicle routing problems (VRP). It is lightweight, flexible, easy-to-use, and based on a single all-purpose meta-heuristic. The GraphHopper routing engine is fast and memory-efficient, using Java. It runs server side, offline on Android and iOS. It uses OpenStreetMap data, but can import other data sources as well. GraphHopper is a fast and memory-efficient routing engine released under Apache License 2.0. It can be used as a Java library or standalone web server to calculate the distance, time, turn-by-turn instructions and many road attributes for a route between two or more points. Beyond this "A-to-B" routing it supports "snap to road", Isochrone calculation, mobile navigation and more. -
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GraphQL Java Tools
A schema-first tool for graphql-java inspired by graphql-tools for JS
This library allows you to use the GraphQL schema language to build your graphql-java schema. Inspired by graphql-tools, it parses the given GraphQL schema and allows you to BYOO (bring your own object) to fill in the implementations. GraphQL Java Tools works extremely well if you already have domain POJOs that hold your data (e.g. for RPC, ORM, REST, etc) by allowing you to map these magically to GraphQL objects. GraphQL Java Tools aims for seamless integration with Java, but works for any JVM language. Try it with Kotlin. -
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GraphQL Juniper
GraphQL server library for Rust
GraphQL is a data query language developed by Facebook intended to serve mobile and web application frontends. Juniper makes it possible to write GraphQL servers in Rust that are type-safe and blazingly fast. We also try to make declaring and resolving GraphQL schemas as convenient as Rust will allow. Juniper does not include a web server - instead it provides building blocks to make integration with existing servers straightforward. It optionally provides a pre-built integration for the Actix, Hyper, Iron, Rocket, and Warp frameworks, including embedded Graphiql and GraphQL Playground for easy debugging. The best place to get started is the Juniper Book, which contains guides with plenty of examples, covering all features of Juniper. Juniper supports the full GraphQL query language according to the specification (October 2021), including interfaces, unions, schema introspection, and validations. It can also output the schema in the GraphQL Schema Language. -
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GraphQL Kotlin
Libraries for running GraphQL in Kotlin
graphql-java is one of the most popular JVM-based GraphQL implementations. GraphQL Kotlin is built on top of grahpql-java as it can be easily extended with additional functionality and this implementation has been used and tested by many users. The most common way to create the schema in graphql-java is to first manually write the SDL file. Then write the runtime code that matches this schema to build the GraphQLSchema object. This means that there are two sources of truth for your schema and changes in either have to be reflected in both locations. As your schema scales to hundreds of types and many different resolvers, it can get more difficult to track what code needs to be changed if you want to add a new field, deprecate or delete an existing one, or fix a bug in the resolver code. graphql-kotlin-schema-generator aims to simplify this process by using Kotlin reflection to generate the schema for you. All you need to do is write your schema code in a Kotlin class. -
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Grenade
Deep Learning in Haskell
Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only the layers of the network but also the shapes of data that are passed between the layers. To perform back propagation, one can call the eponymous function which takes a network, appropriate input, and target data, and returns the back propagated gradients for the network. The shapes of the gradients are appropriate for each layer and may be trivial for layers like Relu which have no learnable parameters. -
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Grid Alx
Library Grid for Codeigniter
GridAlx es un grid que ayuda a facilitar mostrar datos de tablas y haciendo filtros, mediante tablas con limits. Todo esto con Ajax. Requiere un poco de configuracion pero ya que le entiendas, sera de gran utilidad. ------------------------ GridAlx is a grid that helps facilitate display data from tables and making filters, using tables with limits. All this with Ajax. Requires some settings but since you understand, will be of great use. -
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A Groovy builder for URLConnection
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. This makes it easy to integrate Groq-powered AI capabilities into backend services, data pipelines, research notebooks, or applications written in Python. For those building AI-based tooling, automation scripts, or ML-backed backends, groq-python abstracts away HTTP request plumbing and exposes a clean API, accelerating development and reducing boilerplate. -
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Groq TypeScript / Node.s
The official Node.js / Typescript library for the Groq API
Groq TypeScript / Node.s (also often referred to as “groq-sdk” on npm) is the official Node.js / TypeScript client library for Groq’s REST API, enabling JavaScript/TypeScript developers to integrate LLM and AI-powered services into web backends, serverless functions, or frontend apps. It exports strongly-typed interfaces for models, chat completions, file uploads (e.g. for audio transcription), and other endpoints, allowing for better type safety and developer experience when using Groq from TypeScript. The library also supports passing different input types (file streams, blobs, fetch responses) for media-related endpoints, making it flexible for diverse environments (backend, browser, serverless). With this SDK, developers can call Groq’s models, transcribe audio, perform file uploads — all with minimal boilerplate — which streamlines creation of AI-enabled applications in the JavaScript/TypeScript ecosystem. -
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A shell for the layout manager GroupLayout. It allows to control components' placement using simple 2-dimensional textual schemes. Such approach to GUI creation removes the problem of representing a 2-dimensional GUI by 1-dimensional code.
