Search Results for "python-gtksourceview2" - Page 11
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Showing 713 open source projects for "python-gtksourceview2"
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Computer Science Flash Cards
Mini website for testing both general CS knowledge and enforce coding
This repository collects concise flash cards that cover the core ideas of a traditional computer science curriculum with a focus on interview readiness. The cards distill topics like time and space complexity, classic data structures, algorithmic paradigms, operating systems, networking, and databases into short, testable prompts. They are designed for spaced-repetition style study so you can cycle frequently through fundamentals until recall feels automatic. Many cards point at canonical... -
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Double Conversion
Efficient binary-decimal & decimal-binary conversion routines for IEEE
Double Conversion is a high-performance C++ library that provides precise and efficient binary-decimal and decimal-binary conversion routines for IEEE 754 double-precision floating-point numbers. Originally extracted from the V8 JavaScript engine, it was refactored into a standalone library to make its robust number conversion algorithms easily reusable in other projects. The library ensures consistent and accurate results for converting between double values and their string... -
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TensorStore
Library for reading and writing large multi-dimensional arrays
...The library is engineered for scalability—background caching, chunk sharding, and retryable operations keep throughput high even over unreliable networks. With language bindings, it fits into Python-heavy analysis pipelines while retaining a fast C++ core. -
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RLax
Library of JAX-based building blocks for reinforcement learning agents
RLax (pronounced “relax”) is a JAX-based library developed by Google DeepMind that provides reusable mathematical building blocks for constructing reinforcement learning (RL) agents. Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as... -
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MuJoCo Playground
An open source library for GPU-accelerated robot learning
MuJoCo Playground, developed by Google DeepMind, is a GPU-accelerated suite of simulation environments for robot learning and sim-to-real research, built on top of MuJoCo MJX. It unifies a range of control, locomotion, and manipulation tasks into a consistent and scalable framework optimized for JAX and Warp backends. The project includes classic control benchmarks from dm_control, advanced quadruped and bipedal locomotion systems, and dexterous as well as non-prehensile manipulation setups.... -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained... -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference... -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost... -
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DeepEP
DeepEP: an efficient expert-parallel communication library
DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP... -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
...Agile development experience with SQL-like query language and graphical drag-and-drop editor supporting event simulation. Lightweight runtime that can natively run on Kubernetes, Docker, VM, or bare metal, and embedded in any Java or Python application. Scalable, and highly available distributed event processing on Kubernetes, with NATS Streaming and Siddhi Kubernetes Operator. -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major... -
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Opacus
Training PyTorch models with differential privacy
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,... -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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Venom
Venom is the most complete javascript library for Whatsapp
...It uses a set of well-defined operations that apply to all information resources, HTTP itself defines a small set of operations, the most important being post, get, put and delete. Use it in your favorite language like PHP, Python, C# and others. as long as your language is supported with the HTTP protocol, you will save time and money. you don't need to know how Venom works, we have the complete API documentation, in a professional way! -
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ccapi
A header-only C++ library for interacting with crypto exchanges
A header-only C++ library for streaming market data and executing trades directly from cryptocurrency exchanges (i.e. the connections are between your server and the exchange server without anything in-between). -
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QR Code generator library
High-quality QR Code generator library in Java, TypeScript/JavaScript
...I believe that my library has a more intuitive API and shorter code length than competing libraries out there. The library is designed first in Java and then ported to TypeScript, Python, Rust, C++, and C. It is open source under the MIT License. For each language, the codebase is roughly 1000 lines of code and has no dependencies other than the respective language’s standard library. -
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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. -
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Top Deep Learning Projects
A list of popular github projects related to deep learning
TopDeepLearning is a curated index of the most popular GitHub projects related to deep learning, ranked by their star count. Rather than being a library itself, it serves as a curated roadmap and reference guide for anyone exploring the deep learning ecosystem — from beginners to experienced practitioners. By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly... -
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Professional Programming
A collection of learning resources for curious software engineers
Professional Programming is a long-running, curated collection of learning resources aimed at helping software engineers grow into well-rounded professionals. It goes far beyond basic “learn to code” material and covers topics like system design, debugging, testing, performance, security, architecture, and software craftsmanship. The list is organized by themes such as coding, design, operations, communication, and career, making it easy to dive into specific aspects of engineering practice.... -
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. CO3Dv2 enables research... -
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fvcore
Collection of common code shared among different research projects
fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A... -
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging... -
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nghttp2
HTTP/2 C Library and tools
...We offer HPACK encoder and decoder are available as public API. nghttp2 library itself is a bit low-level. The experimental high-level C++ API is also available. We have Python binding of this library, but we have not covered everything yet. -
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Google Style Guides
Style guides for Google-originated open source projects
Google Styleguide is a comprehensive collection of coding style guides created and maintained by Google to ensure consistency, readability, and maintainability across its vast array of software projects. These guides define best practices and conventions for writing code in multiple programming languages, from C++ and Python to JavaScript, Go, and Swift. By adhering to these standards, developers can more easily collaborate, review code, and maintain high-quality software across teams and open source contributions. Each guide covers a wide range of topics, including naming conventions, file organization, indentation, documentation, and usage of specific language features. ... -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations,...