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Showing 15846 open source projects for "compiler python linux"
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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
pomegranate is a library for probabilistic modeling defined by its modular implementation and treatment of all models as the probability distributions they are. The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution,... -
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Pymunk
Pymunk is a easy-to-use pythonic 2d physics library
Pymunk is an easy-to-use Pythonic 2D physics library that can be used whenever you need 2D rigid body physics from Python. Perfect when you need 2D physics in your game, demo or simulation! It is built on top of the very capable 2D physics library Chipmunk2D. The first version was released in 2007 and Pymunk is still actively developed and maintained today, more than 15 years of active development. Pymunk has been used with success in many projects, big and small. For example: 3 Pyweek game... -
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Perceval
An open source framework for programming photonic quantum computers
An open-source framework for programming photonic quantum computers. Through a simple object-oriented Python API, Perceval provides tools for composing circuits from linear optical components, defining single-photon sources, manipulating Fock states, running simulations, reproducing published experimental papers and experimenting with a new generation of quantum algorithms. It aims to be a companion tool for developing photonic circuits – for simulating and optimizing their design, modeling... -
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Copulas
A library to model multivariate data using copulas
Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D... -
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IVRE
Open source framework for large scale network reconnaissance and analy
IVRE is an open source network reconnaissance framework designed to collect, process, and analyze intelligence gathered from network scans and traffic data. It provides tools for both active and passive reconnaissance, enabling users to understand how networks behave and identify exposed services or infrastructure. The framework integrates with well known security and scanning tools such as Nmap, Masscan, ZGrab2, ZDNS, and Zeek to gather large amounts of network intelligence. IVRE stores the... -
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MiniMax-MCP
Official MiniMax Model Context Protocol (MCP) server
MiniMax-MCP is the official Model Context Protocol (MCP) server for accessing MiniMax’s multimodal generative APIs from MCP-compatible clients. It acts as a bridge between tools like Claude Desktop, Cursor, Windsurf, OpenAI Agents, and the MiniMax platform, exposing capabilities such as text-to-speech, voice cloning, image generation, text-to-image, video generation, image-to-video, text-to-video, and music generation. The server is written in Python and distributed under the MIT license,... -
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UCO3D
Uncommon Objects in 3D dataset
uCO3D is a large-scale 3D vision dataset and toolkit centered on turn-table videos of everyday objects drawn from the LVIS taxonomy. It provides about 170,000 full videos per object instance rather than still frames, along with per-video annotations including object masks, calibrated camera poses, and multiple flavors of point clouds. Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based... -
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SuperDuperDB
Integrate, train and manage any AI models and APIs with your database
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on... -
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ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
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Audiomentations
A Python library for audio data augmentation
A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products. Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where... -
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GRR
GRR Rapid Response, remote live forensics for incident response
GRR Rapid Response is an incident response framework focused on remote live forensics. It consists of a python client (agent) that is installed on target systems, and python server infrastructure that can manage and talk to clients. The goal of GRR is to support forensics and investigations in a fast, scalable manner to allow analysts to quickly triage attacks and perform analysis remotely. GRR client is deployed on systems that one might want to investigate. On every such system, once... -
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HunyuanWorld-Voyager
RGBD video generation model conditioned on camera input
HunyuanWorld-Voyager is a next-generation video diffusion framework developed by Tencent-Hunyuan for generating world-consistent 3D scene videos from a single input image. By leveraging user-defined camera paths, it enables immersive scene exploration and supports controllable video synthesis with high realism. The system jointly produces aligned RGB and depth video sequences, making it directly applicable to 3D reconstruction tasks. At its core, Voyager integrates a world-consistent video... -
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HACS Integration
HACS gives you a UI to handle downloads of all your custom needs
HACS is an integration for Home Assistant that simplifies the management of custom components, themes, and other community-driven content. It provides a user-friendly interface within Home Assistant for browsing, installing, and updating custom add-ons, enhancing the customization and extensibility of Home Assistant setups. -
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Dev-template
A template for development with the open-autonomy framework
Dev Template is a starting point for developing autonomous agents using the Autonolas framework by Valory. It provides a modular and extensible codebase to accelerate the development of agents that act autonomously in decentralized networks. This template includes tooling for building, testing, and deploying agents in real-world decentralized applications (dApps). -
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Tensorforce
A TensorFlow library for applied reinforcement learning
Tensorforce is an open-source deep reinforcement learning framework built on TensorFlow, emphasizing modularized design and straightforward usability for applied research and practice. -
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OpenLLMetry
Open-source observability for your LLM application
The repo contains standard OpenTelemetry instrumentations for LLM providers and Vector DBs, as well as a Traceloop SDK that makes it easy to get started with OpenLLMetry, while still outputting standard OpenTelemetry data that can be connected to your observability stack. If you already have OpenTelemetry instrumented, you can just add any of our instrumentations directly. -
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Hummingbird
Hummingbird compiles trained ML models into tensor computation
Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to seamlessly leverage neural network frameworks (such as PyTorch) to accelerate traditional ML models. Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of... -
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Superstaq
Quantum software platform that is optimized across the quantum stack
This repository is the home of the Superstaq development team's open-source work. Our quantum software platform is optimized across the quantum stack and enables users to write quantum programs in Cirq or Qiskit and target a variety of quantum computers and simulators. -
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Pybris
B language compiler written in Python targeting RISVM
Pybris is a compiler written in Python using Pyparsing for the B Programming Language. The compiler emits a variant of Bitmario RISVM assembly. The practical goal of the project is to provide a way to develop digital signal processing (DSP) effects for the Competent Audio library that is a friendlier alternative to writing RISVM assembly by hand. -
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MCP Teams Server
An MCP (Model Context Protocol) server implementation
An MCP server implementation for Microsoft Teams integration, providing capabilities to read messages, create messages, reply to messages, and mention members, facilitating AI-driven interactions within Teams. -
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DI-engine
OpenDILab Decision AI Engine
DI-engine is a unified reinforcement learning (RL) platform for reproducible and scalable RL research. It offers modular pipelines for various RL algorithms, with an emphasis on production-level training and evaluation. -
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BioNeMo
BioNeMo Framework: For building and adapting AI models
BioNeMo is an AI-powered framework developed by NVIDIA for protein and molecular generation using deep learning models. It provides researchers and developers with tools to design, analyze, and optimize biological molecules, aiding in drug discovery and synthetic biology applications. -
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Quod Libet
Music player and music library manager for Linux, Windows, and macOS
Quod Libet is a cross-platform audio/music management program. It provides many ways to view your local library, and supports streaming audio and feeds (podcasts, etc). It has extremely flexible metadata editing and searching capabilities. With over 90 plugins included, you can extend and integrate with almost anything, or write your own! Ex Falso is a bare-bones tag editor with the same editing interface as Quod Libet. Quod Libet is a GTK+-based audio player written in Python, using the... -
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Agentic Context Engine
Make your agents learn from experience
Agentic Context Engine (ACE) is an open-source framework designed to help AI agents improve their performance by learning from their own execution history. Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and... -
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Open Wearables
Self-hosted platform to unify wearable health data
Open Wearables is an open-source initiative that aims to provide a community-driven ecosystem for wearable device software and interoperability by connecting sensor data, activity tracking, and health insights across multiple platforms and devices. Instead of relying on closed vendor ecosystems, the project provides standardized data models and APIs that let developers and hobbyists collect, sync, and analyze biometric and environmental data from wearables, DIY sensors, and open hardware...
