Showing 93 open source projects for "hibernate-distribution"

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  • 1
    brython

    brython

    Implementation of Python 3 running in the browser

    ...The most simple way to get started, without anything to install, is to use the distribution available online through jsDelivr.
    Downloads: 2 This Week
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  • 2
    AutoPkg

    AutoPkg

    Automating packaging and software distribution on macOS

    AutoPkg is a system that automatically prepares software for distribution to managed clients. Recipes allow you to specify a series of simple actions which combined together can perform complex tasks, similar to Automator workflows or Unix pipes.
    Downloads: 0 This Week
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  • 3
    Otter-Grader

    Otter-Grader

    A Python and R autograding solution

    Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope.
    Downloads: 0 This Week
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  • 4
    troposphere

    troposphere

    Python library to create AWS CloudFormation descriptions

    The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes.
    Downloads: 2 This Week
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    Pyro

    Pyro

    Deep universal probabilistic programming with Python and PyTorch

    ...It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable abstractions that make it both agile and maintainable. Lastly, Pyro gives you the flexibility of automation when you want it, and control when you need it.
    Downloads: 3 This Week
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  • 6
    Google Fonts

    Google Fonts

    Font files available from Google Fonts, and a public issue tracker

    This is the central GitHub repository for Google Fonts, containing font binaries, metadata, and tools for uploading new typeface families. It serves as the staging area for fonts and follows stringent licensing structures. The top-level directories indicate the license of all files found within them. Subdirectories are named according to the family name of the fonts within. The /catalog subdirectory contains additional metadata, such as profile texts and portrait/avatar images of font...
    Downloads: 17 This Week
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  • 7
    Bottle

    Bottle

    bottle.py is a fast and simple micro-framework for python applications

    Bottle is a minimalist web framework for building small web applications and APIs in Python. It is distributed as a single file with no external dependencies, making it perfect for rapid development, prototyping, or embedded use. Despite its small size, Bottle supports routing, templates, request handling, and plugin support, offering a full-featured toolkit in an extremely compact package.
    Downloads: 0 This Week
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  • 8
    PyJNIus

    PyJNIus

    Access Java classes from Python

    Pyjnius is a Python library for accessing Java classes. A Python module to access Java classes as Python classes using the Java Native Interface (JNI). Warning: the pypi name is now pyjnius instead of jnius. When you use autoclass, it will discover all the methods and fields of the class and resolve them. You can use the signatures method of JavaMethod and JavaMultipleMethod, to inspect the discovered signatures of a method of an object.
    Downloads: 1 This Week
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  • 9
    PyMC3

    PyMC3

    Probabilistic programming in Python

    ...Sometimes an unknown parameter or variable in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets.
    Downloads: 3 This Week
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  • 10
    TradingAgents

    TradingAgents

    Chinese Financial Trading Framework Based on Multi-Agent LLM

    ...The project is oriented toward practical usage, including a stack that can be run in a modern development environment and commonly paired with containerized backends, configuration files, and service components. It also pays attention to distribution and misuse risks, clearly warning users about unauthorized commercial repackaging and stating that commercial use requires explicit authorization while personal use is open.
    Downloads: 1 This Week
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  • 11
    Copulas

    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 histograms, 2D scatterplots and 3D scatterplots. ...
    Downloads: 0 This Week
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  • 12
    Uncertainty Baselines

    Uncertainty Baselines

    High-quality implementations of standard and SOTA methods

    ...The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. Each baseline emphasizes reproducibility: fixed seeds, standard splits, and strong metrics such as calibration error, AUROC for OOD, and accuracy under shift.
    Downloads: 0 This Week
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  • 13
    Ansible Molecule

    Ansible Molecule

    Molecule aids in the development and testing of Ansible roles

    ...See INSTALL.rst, which is created when initializing a new scenario. Ansible is not listed as a direct dependency of molecule package because we only call it as a command-line tool. You may want to install it using your distribution package installer. It is your responsibility to assure that soft dependencies of Ansible are available on your controller or host machines.
    Downloads: 0 This Week
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  • 14
    WinPython

    WinPython

    Portable Scientific Python 2/3 32/64bit Distribution for Windows

    WinPython is a free open-source portable distribution of the Python programming language for Windows XP/7/8, designed for scientists, supporting both 32bit and 64bit versions of Python 2 and Python 3. Since September 2014, Developpement has moved to https://winpython.github.io/
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    Downloads: 3,363 This Week
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  • 15
    Sonnet

    Sonnet

    TensorFlow-based neural network library

    Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already...
    Downloads: 0 This Week
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  • 16

    OPSI UPDATER

    Check and Update Products on OPSI Server

    This OPSI SERVER Command line Tool (Opsi Updater) will check for available OPSI Product Updates on official Servers (example Mozilla) and will allow to Download and Update older Product Versions on OPSI Repository and distribute them on clients having older versions. readme: http://svn.code.sourceforge.net/p/opsiupdater/code-0/trunk/readme.txt
    Downloads: 1 This Week
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  • 17

    MUNKI UPDATER

    Auto Update munki products

    Automatically Get Official Product Updates on munki Server. This MUNKI SERVER Command line Tool (Munki Updater) will check for available MUNKI Product Updates on official Servers (example Mozilla) and will allow to Download and Update older Product Versions on MUNKI Repository and distribute them on clients having older versions. munki updater readme: http://svn.code.sourceforge.net/p/munkiupdater/code-0/trunk/readme.txt ############# managed software centre installer...
    Downloads: 0 This Week
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  • 18
    KaNaPi

    KaNaPi

    Educational Linux Distribution

    Main goals: * Prepare operating system based on Linux kernel and free software for use at home from scratch by building sources. Binary packages/images are also available. * Each package is installed in separate directory, so you can use different versions of applications and libraries by design. * There is only one user 'kanapi' with root permissions, so you don't have to login, remember passwords, etc. * Simple configuration * Automatic compilation.
    Downloads: 33 This Week
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  • 19
    PyAppExec

    PyAppExec

    Launcher that prepares Python/deps and runs your app like OS-native

    PyAppExec is a cross‑platform open-source launcher and installer that makes Python apps feel native. It locates or installs the required Python runtime, provisions an isolated virtual environment, installs your project’s pip requirements, and handles any external tools requirements or dependencies (e.g., FFmpeg) with version checks and auto-download/extract on Windows/macOS/Linux. The Qt-based installer can scaffold pyappexec.ini, copy/rename the launcher, and (on macOS) bundle a...
    Downloads: 1 This Week
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  • 20
    Basic Website Studio (Tkinter Edition)

    Basic Website Studio (Tkinter Edition)

    Basic Website Studio (Tkinter Edition)

    A simple, lightweight code editor for basic web development, written in Python using the standard Tkinter GUI toolkit. This application is designed to run without any external Python libraries (like PySide6 or PyQt), making it ideal for easy distribution on Linux systems, such as in a .deb package.
    Downloads: 0 This Week
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  • 21
    Neural Tangents

    Neural Tangents

    Fast and Easy Infinite Neural Networks in Python

    Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,...
    Downloads: 1 This Week
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  • 22
    DIG

    DIG

    A library for graph deep learning research

    The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. ...
    Downloads: 0 This Week
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  • 23
    Debreate - Debian Package Builder

    Debreate - Debian Package Builder

    A utility for creating Debian packages (.deb)

    ...Currently it only supports binary packaging (note that the term "binary package" is used loosely, as such packages can contain scripts & non-code items such as media images, audio, & more) for personal distribution. Plans for using backends such as dh_make & debuild for creating source packages are in the works. But source packaging can be quite different & is a must if you want to get your packages into a distribution's official repositories or a Launchpad Personal Package Archive (PPA). The latter from which Debreate is available.
    Downloads: 3 This Week
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  • 24
    Termux APT Repo

    Termux APT Repo

    Script to create Termux apt repositories

    termux-apt-repo is a script designed to create APT repositories for Termux, allowing users to publish and distribute their own packages. It supports cross-compiled packages created using the Termux build setup or on-device packages created with termux-create-package. This tool facilitates the sharing and installation of custom packages within the Termux environment.​
    Downloads: 1 This Week
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  • 25
    Twinify

    Twinify

    Privacy-preserving generation of a synthetic twin to a data set

    twinify is a software package for the privacy-preserving generation of a synthetic twin to a given sensitive tabular data set. On a high level, twinify follows the differentially private data-sharing process introduced by Jälkö et al.. Depending on the nature of your data, twinify implements either the NAPSU-MQ approach described by Räisä et al. or finds an approximate parameter posterior for any probabilistic model you formulated using differentially private variational inference (DPVI)....
    Downloads: 0 This Week
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