Showing 2935 open source projects for "python software foundation license"

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  • 1
    namedtupledefs2

    namedtupledefs2

    Pacthed namedtuple for field defaults.

    The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python3 see namedtupledefs3 or namedtupledefs
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  • 2
    platformids

    platformids

    OS and Distribution Release Enumeration

    The ‘platformids‘ package provides the categorization and enumeration of OS platforms and distributions. This enables the development of portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The introduced hierarchical bitmask vectors enable for fast and efficient platform specific code and data selection for OS and distributions with routines for specific platform releases. The supported...
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  • 3
    TensorFlow Haskell

    TensorFlow Haskell

    Haskell bindings for TensorFlow

    The tensorflow-haskell package provides Haskell-language bindings for TensorFlow, giving Haskell developers the ability to build and run computation graphs, machine learning models, and leverage TensorFlow's ecosystem—though it is not an official Google release. As an expedient we use docker for building. Once you have docker working, the following commands will compile and run the tests. Run the install_macos_dependencies.sh script in the tools/ directory. The script installs dependencies...
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  • 4
    hug

    hug

    Embrace the APIs of the future. For developing APIs

    hug aims to make developing Python-driven APIs as simple as possible, but no simpler. As a result, it drastically simplifies Python API development. Make developing a Python-driven API as succinct as a written definition. The framework should encourage code that self-documents. It should be fast. A developer should never feel the need to look somewhere else for performance reasons. Writing tests for APIs written on-top of hug should be easy and intuitive. Magic done once, in an API...
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  • 5
    TF Quant Finance

    TF Quant Finance

    High-performance TensorFlow library for quantitative finance

    TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The...
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  • 6
    I3D models trained on Kinetics

    I3D models trained on Kinetics

    Convolutional neural network model for video classification

    Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with...
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  • 7
    AES Everywhere

    AES Everywhere

    Cross Language AES 256 Encryption Library

    AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt.
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  • 8
    MLBox

    MLBox

    MLBox is a powerful Automated Machine Learning python library

    MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to...
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  • 9
    WALKOFF

    WALKOFF

    A flexible, easy to use, automation framework

    Faster, smarter, cheaper operations through automation. WALKOFF puts the tools in your hands to easily automate the tedious repetitive tasks dragging your operations down. Act smarter with WALKOFF by automatically gathering data, analyzing data, or visualizing data customized to your requirements. Act faster with WALKOFF by integrating the capabilities you already own to dynamically respond on your terms to your fast-moving environment. Drag and drop workflow editor. Sharable apps and...
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  • 10
    NativeScript Documentation

    NativeScript Documentation

    Documentation, API reference, and code snippets for NativeScript

    NativeScript provides platform APIs directly to the JavaScript runtime (with strong types) for a rich TypeScript development experience. Building Web, iOS, Android, and Vision Pro apps with a shared codebase (aka, cross-platform apps) Building native platform apps with portable JavaScript skills. Augmenting JavaScript projects with platform API capabilities. AndroidTV and Watch development watchOS development. Learning native platforms through JavaScript understanding. Exploring platform...
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  • 11
    Nebula docs

    Nebula docs

    Documentation repo of nebula orchestration system

    Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are appliances\virtual...
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  • 12
    MMF

    MMF

    A modular framework for vision & language multimodal research

    MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that...
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  • 13
    Nebula worker

    Nebula worker

    The worker node manager container which manages nebula nodes

    Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are IoT devices,...
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  • 14
    Nebula reporter

    Nebula reporter

    The optional reporter container which reads nebula reports from Kafka

    Nebula is an open source-distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking effect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe. Ever wandered how your going to push an update...
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  • 15
    Django Celery

    Django Celery

    Old Celery integration project for Django

    Celery is a simple, flexible, and reliable distributed system to process vast amounts of messages, while providing operations with the tools required to maintain such a system. It’s a task queue with focus on real-time processing, while also supporting task scheduling. Celery has a large and diverse community of users and contributors, you should come join us on IRC or our mailing-list. Celery is Open Source and licensed under the BSD License. A task queue’s input is a unit of work called a...
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  • 16
    Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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  • 17
    Microsoft Python Language Server

    Microsoft Python Language Server

    Microsoft Language Server for Python

    Microsoft Python Language Server implements the Language Server Protocol. Its primary clients are the Python extension for VS Code and Python Tools for Visual Studio. Feel free to file issues or ask questions on our issue tracker, and we welcome code contributions. Linting can be controlled via the user configuration. In VS Code, this is settings.json. To control the visibility and severity of the diagnotics, there are a number of lists that can be set in the user configuration which make...
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  • 18

    proofs

    Only proofs and tests

    Only proofs and tests...
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  • 19
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments...
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  • 20

    TestLink-API-Python-client

    Python XML-RPC client for TestLink

    TestLink-API-Python-client is a Python XML-RPC client for TestLink Initially based on James Stock testlink-api-python-client R7 and Olivier Renault JinFeng idea - an interaction of TestLink, Robot Framework and Jenkins. TestLink-API-Python-client delivers two main classes - TestlinkAPIGeneric - Implements the Testlink API methods as generic PY methods with error handling - TestlinkAPIClient - Inherits from TestlinkAPIGeneric and defines service methods like "copyTCnewVersion" and...
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  • 21
    pybag

    pybag

    Crossplatform files synchronization and backup portable tool.

    PYBAG implements a portable bag and is intended for fast synchronization and backup. It lets you use a portable digital storage device to carry your electronic documents similar to the way you can use a bag to carry paper documents. You can synchronize the bag with your original files easily. If a synchronization conflict occurs, it will be reported. You can specify rules for automatic conflict resolution. With PYBAG, you can backup files and synchronize any changes made to the...
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  • 22
    The Google Cloud Developer's Cheat Sheet

    The Google Cloud Developer's Cheat Sheet

    Cheat sheet for Google Cloud developers

    Every product in the Google Cloud family described in <=4 words (with liberal use of hyphens and slashes) by the Google Developer Relations Team. This list only includes products that are publicly available. There are several products in pre-release/private-alpha that will not be included until they go public beta or GA. Many of these products have a free tier. There is also a free trial that will enable you try almost everything. API platforms and ecosystems, developer and management tools,...
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  • 23
    pytorch-examples

    pytorch-examples

    Simple examples to introduce PyTorch

    The pytorch-examples project is a collection of concise and practical examples demonstrating how to use PyTorch for machine learning and deep learning tasks. It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners...
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  • 24
    Climate Modeling Courseware

    Climate Modeling Courseware

    Interactive lecture notes and assignments in Jupyter notebook format

    A collection of interactive lecture notes and assignments for a graduate-level climate modeling course. ATM 623 Climate Modeling is an advanced graduate course on climate dynamics and climate modeling. The focus of the course is on the hands-on use of both simple and complex climate models to build an understanding of the processes that control the planetary energy budget. The course makes extensive use of Python code and the Jupyter notebook for reproducible, self-describing calculations...
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  • 25
    pipupgrade

    pipupgrade

    Like yarn outdated/upgrade, but for pip

    pipupgrade is a command-line utility designed to streamline the management of Python package dependencies. It automates the process of identifying and upgrading outdated packages across various Python environments, including system-wide installations, virtual environments, and project-specific setups. By analyzing semantic versioning, pipupgrade categorizes updates into major, minor, and patch changes, allowing developers to make informed decisions about which packages to upgrade....
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