Showing 1056 open source projects for "python library"

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  • 1
    AWS ParallelCluster Node

    AWS ParallelCluster Node

    Python package installed on the Amazon EC2 instances

    aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources...
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  • 2
    mlpack

    mlpack

    mlpack: a scalable C++ machine learning library

    mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. Written in C++ and built on the Armadillo linear...
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  • 3
    jCasbin

    jCasbin

    An authorization library that supports access control models

    An authorization library that supports access control models like ACL, RBAC, ABAC for Golang, Java, C/C++, Node.js, Javascript, PHP, Laravel, Python, .NET (C#), Delphi, Rust, Ruby, Swift (Objective-C), Lua (OpenResty), Dart (Flutter) and Elixir. In Casbin, an access control model is abstracted into a CONF file based on the PERM metamodel (Policy, Effect, Request, Matchers). So switching or upgrading the authorization mechanism for a project is just as simple as modifying a configuration...
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  • 4
    Papis

    Papis

    Powerful and highly extensible command-line based document

    Papis is a powerful and highly extensible CLI document and bibliography manager. With Papis, you can search your library for books and papers, add documents and notes, import and export to and from other formats, and much much more. Papis uses a human-readable and easily hackable .yaml file to store each entry's bibliographical data. It strives to be easy to use while providing a wide range of features. And for those who still want more, Papis makes it easy to write scripts that extend its...
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    Airtest

    Airtest

    UI Automation Framework for Games and Apps

    ¿Airtest provides cross-platform APIs, including app installation, simulated input, assertion and so forth. Airtest uses image recognition technology to locate UI elements so that you can automate games and apps without injecting any code. Airtest cases can be easily run on large device farms, using the command line or python API. HTML reports with detailed info and screen recording allow you to quickly locate failure points. NetEase builds Airlab on top of the Airtest Project. AirtestIDE...
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  • 6
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from...
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  • 7
    Django Rules

    Django Rules

    Awesome Django authorization, without the database

    rules is a tiny but powerful app providing object-level permissions to Django, without requiring a database. At its core, it is a generic framework for building rule-based systems, similar to decision trees. It can also be used as a standalone library in other contexts and frameworks. Versatile. Decorate callables to build complex graphs of predicates. Predicates can be any type of callable -- simple functions, lambdas, methods, callable class objects, partial functions, decorated functions...
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  • 8
    django-push-notifications

    django-push-notifications

    Send push notifications to mobile devices through GCM or APNS

    A minimal Django app that implements Device models that can send messages through APNS, FCM/GCM, WNS and WebPush. The app also implements an admin panel, through which you can test single and bulk notifications. Select one or more FCM/GCM, APNS, WNS or WebPush devices and in the action dropdown, select "Send test message" or "Send test message in bulk", accordingly. Note that sending a non-bulk test message to more than one device will just iterate over the devices and send multiple single...
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  • 9
    Opacus

    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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  • 10
    Graph Notebook

    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...
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  • 11
    jsii

    jsii

    jsii allows code in any language to naturally interact with JavaScript

    jsii allows code in any language to naturally interact with JavaScript classes. It is the technology that enables the AWS Cloud Development Kit to deliver polyglot libraries from a single codebase! A class library written in TypeScript can be used in projects authored in TypeScript or Javascript (as usual), but also in C# (and other languages from the .NET family), Go, Java, Python, etc. More languages will be added in the future! Due to JSON marshaling costs and the absence of a distributed...
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  • 12
    Face Alignment

    Face Alignment

    2D and 3D Face alignment library build using pytorch

    Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively use...
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  • 13
    DGL

    DGL

    Python package built to ease deep learning on graph

    Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers....
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  • 14
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    ... of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations.
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  • 15
    Valkey GLIDE

    Valkey GLIDE

    An open source Valkey client library that supports Valkey and Redis

    Valkey General Language Independent Driver for the Enterprise (GLIDE), is an open-source Valkey client library. Valkey GLIDE is one of the official client libraries for Valkey, and it supports all Valkey commands. Valkey GLIDE supports Valkey 7.2 and above, and Redis open-source 6.2, 7.0 and 7.2. Application programmers use Valkey GLIDE to safely and reliably connect their applications to Valkey- and Redis OSS- compatible services. Valkey GLIDE is designed for reliability, optimized performance...
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  • 16
    DALI

    DALI

    A GPU-accelerated library containing highly optimized building blocks

    The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding...
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  • 17
    QuantumOptics.jl

    QuantumOptics.jl

    Library for the numerical simulation of closed as well as open quantum

    QuantumOptics.jl is a numerical framework written in the Julia programming language that makes it easy to simulate various kinds of open quantum systems. It is inspired by the Quantum Optics Toolbox for MATLAB and the Python framework QuTiP. QuantumOptics.jl optimizes processor usage and memory consumption by relying on different ways to store and work with operators. The framework comes with a plethora of pre-defined systems and interactions making it very easy to focus on the physics...
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  • 18
    Siddhi Core Libraries

    Siddhi Core Libraries

    Stream Processing and Complex Event Processing Engine

    ... to various endpoints in real time. 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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  • 19
    DocArray

    DocArray

    The data structure for multimodal data

    DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data...
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  • 20
    Douyin TikTok Download API

    Douyin TikTok Download API

    Douyin TikTok Download API

    ... can deploy or transform this project yourself to achieve more functions, or you can directly call scraper.py in your project or install an existing pip package as a parsing library to easily crawl data, etc. Support input Douyin|TikTokuser homepage to crawl the author [homepage video data (remove watermark link, liked video list (permission must be public), video comment data, background music video list data, etc...).
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  • 21
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 22
    IVY

    IVY

    The Unified Machine Learning Framework

    Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an...
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  • 23
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    ... and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies.
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  • 24
    OpenSpiel

    OpenSpiel

    Environments and algorithms for research in general reinforcement

    ... to analyze learning dynamics and other common evaluation metrics. Games are represented as procedural extensive-form games, with some natural extensions. The core API and games are implemented in C++ and exposed to Python. Algorithms and tools are written both in C++ and Python. To try OpenSpiel in Google Colaboratory, please refer to open_spiel/colabs subdirectory.
    Downloads: 0 This Week
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  • 25
    TensorFlow Model Garden

    TensorFlow Model Garden

    Models and examples built with TensorFlow

    ... are suitable. A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU).
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