Showing 3588 open source projects for "linux-debian"

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  • 1
    teslamate

    teslamate

    A self-hosted data logger for your Tesla

    TeslaMate is an open-source self-hosted data logger that collects and visualizes data from Tesla vehicles in real time. It provides detailed insights into driving, charging, efficiency, and battery health through intuitive dashboards powered by Grafana. TeslaMate is ideal for Tesla owners who want full control of their vehicle data, avoid cloud reliance, and access rich analytics for personal tracking or troubleshooting.
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  • 2
    Outerbase

    Outerbase

    A lightweight Database GUI in your browser

    Outerbase Studio is an open-source, browser-based database GUI designed for simplicity and versatility. It supports connecting to various relational databases, providing an intuitive interface for managing and querying data without the need for complex setups.
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  • 3
    Kapacitor

    Kapacitor

    Open source framework for processing, monitoring, and alerting

    Open source framework for processing, monitoring, and alerting on time series data. Kapacitor is a real-time data processing engine for monitoring and alerting, specifically designed to work with time-series data from InfluxDB.
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  • 4
    Arroyo

    Arroyo

    Distributed stream processing engine in Rust

    Arroyo is a distributed stream processing engine written in Rust, designed to efficiently perform stateful computations on streams of data. Unlike traditional batch processing, streaming engines can operate on both bounded and unbounded sources, emitting results as soon as they are available.
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  • 5
    Fluid

    Fluid

    Fluid, elastic data abstraction and acceleration for BigData/AI apps

    Fluid, elastic data abstraction and acceleration for BigData/AI applications in the cloud. Provide DataSet abstraction for underlying heterogeneous data sources with multidimensional management in a cloud environment. Enable dataset warmup and acceleration for data-intensive applications by using a distributed cache in Kubernetes with observability, portability, and scalability. Taking characteristics of application and data into consideration for cloud application/dataset scheduling to...
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  • 6
    GeoInterface.jl

    GeoInterface.jl

    A Julia Protocol for Geospatial Data

    This Package describe a set of traits based on the Simple Features standard (SF) for geospatial vector data, including the SQL/MM extension with support for circular geometry. Using these traits, it should be easy to parse, serialize and use different geometries in the Julia ecosystem, without knowing the specifics of each individual package. In that regard it is similar to Tables.jl, but for geometries instead of tables.
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  • 7
    Bumper.jl

    Bumper.jl

    Bring Your Own Stack

    Bumper.jl is a package that aims to make working with bump allocators (also known as arena allocators) easier and safer. You can dynamically allocate memory to these bump allocators, and reset them at the end of a code block, just like Julia's stack. Allocating to a bump allocator with Bumper.jl can be just as efficient as stack allocation. Bumper.jl is still a young package, and may have bugs. Let me know if you find any.
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  • 8
    ExplainableAI.jl

    ExplainableAI.jl

    Explainable AI in Julia

    This package implements interpretability methods for black box models, with a focus on local explanations and attribution maps in input space. It is similar to Captum and Zennit for PyTorch and iNNvestigate for Keras models. Most of the implemented methods only require the model to be differentiable with Zygote. Layerwise Relevance Propagation (LRP) is implemented for use with Flux.jl models.
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  • 9
    101-0250-00

    101-0250-00

    ETH course - Solving PDEs in parallel on GPUs

    This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering.
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  • 10
    LineSearches.jl

    LineSearches.jl

    Line search methods for optimization and root-finding

    Line search methods for optimization and root-finding. This package provides an interface to line search algorithms implemented in Julia. The code was originally written as part of Optim, but has now been separated out to its own package.
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  • 11
    MultilayerGraphs.jl

    MultilayerGraphs.jl

    Julia package for the creation and analysis of multilayer graphs

    MultilayerGraphs.jl is a Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs. A multilayer graph is a graph consisting of multiple standard subgraphs called layers which can be interconnected through bipartite graphs called interlayers composed of the vertex sets of two different layers and the edges between them. The vertices in each layer represent a single set of nodes, although not all nodes have to be represented in...
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  • 12
    NetCDF.jl

    NetCDF.jl

    NetCDF support for the julia programming language

    NetCDF support for the Julia programming language, there is a high-level and a medium-level interface for writing and reading netcdf files. The dimensions "x1" and "t" of the variable are called "x1" and "t" in this example. If the dimensions do not exist yet in the file, they will be created. The dimension "x1" will be of length 10 and have the values 11..20, and the dimension "t" will have length 20 and the attribute "units" with the value "s".
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  • 13
    LLVM.jl

    LLVM.jl

    Julia wrapper for the LLVM C API

    A Julia wrapper for the LLVM C API. The LLVM.jl package is a Julia wrapper for the LLVM C API, and can be used to work with the LLVM compiler framework from Julia. You can use the package to work with LLVM code generated by Julia, to interoperate with the Julia compiler, or to create your own compiler. It is heavily used by the different GPU compilers for the Julia programming language.
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  • 14
    AbstractAlgebra.jl

    AbstractAlgebra.jl

    Generic abstract algebra functionality in pure Julia

    AbstractAlgebra is a pure Julia package for computational abstract algebra. It grew out of the Nemo project and provides all of the abstract types and generic implementations that Nemo relies on. It was originally developed by William Hart, Tommy Hofmann, Fredrik Johansson and Claus Fieker with contributions from others. Current maintainers are Claus Fieker, Tommy Hofmann and Max Horn.
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  • 15
    Clapeyron

    Clapeyron

    Framework for the development and use of fluid-thermodynamic models

    Welcome to Clapeyron! This module provides both a large library of thermodynamic models and a framework for one to easily implement their own models. Clapeyron provides a framework for the development and use of fluid-thermodynamic models, including SAFT, cubic, activity, multi-parameter, and COSMO-SAC.
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  • 16
    Rocket.jl

    Rocket.jl

    Functional reactive programming extensions library for Julia

    Rocket.jl is a Julia package for reactive programming using Observables, to make it easier to work with asynchronous data. Rocket.jl has been designed with a focus on performance and modularity.
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  • 17
    EvoTrees.jl

    EvoTrees.jl

    Boosted trees in Julia

    A Julia implementation of boosted trees with CPU and GPU support. Efficient histogram-based algorithms with support for multiple loss functions, including various regressions, multi-classification and Gaussian max likelihood.
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  • 18
    BAT.jl

    BAT.jl

    A Bayesian Analysis Toolkit in Julia

    Welcome to BAT, a Bayesian analysis toolkit in Julia. BAT.jl offers a variety of posterior sampling, mode estimation and integration algorithms, supplemented by plotting recipes and I/O functionality. BAT.jl originated as a rewrite/redesign of BAT, the Bayesian Analysis Toolkit in C++. BAT.jl now offer a different set of functionality and a wider variety of algorithms than its C++ predecessor.
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  • 19
    Clang.jl

    Clang.jl

    C binding generator and Julia interface to libclang

    This package provides a Julia language wrapper for libclang: the stable, C-exported interface to the LLVM Clang compiler. The libclang API documentation provides background on the functionality available through libclang, and thus through the Julia wrapper. The repository also hosts related tools built on top of libclang functionality.
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  • 20
    CImGui

    CImGui

    Julia wrapper for cimgui

    This package provides a Julia language wrapper for cimgui: a thin c-api wrapper programmatically generated for the excellent C++ immediate mode gui Dear ImGui. Dear ImGui is mainly for creating content creation tools and visualization / debug tools. You could browse Gallery to get an idea of its use cases.
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  • 21
    Compose.jl

    Compose.jl

    Declarative vector graphics

    Compose is a vector graphics library for Julia. It forms the basis for the statistical graphics system Gadfly. Compose is a declarative vector graphics system written in Julia. It's designed to simplify the creation of complex graphics and serves as the basis of the Gadfly data visualization package.
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  • 22
    OpenCL.jl

    OpenCL.jl

    OpenCL Julia bindings

    Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous.
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  • 23
    Manopt.jl

    Manopt.jl

    Optimization on Manifolds in Julia

    Optimization Algorithm on Riemannian Manifolds. A framework to implement arbitrary optimization algorithms on Riemannian Manifolds. Library of optimization algorithms on Riemannian manifolds. Easy-to-use interface for (debug) output and recording values during an algorithm run. Several tools to investigate the algorithms, gradients, and optimality criteria.
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  • 24
    Metaflow

    Metaflow

    A framework for real-life data science

    Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.
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  • 25
    PythonCall & JuliaCall

    PythonCall & JuliaCall

    Python and Julia in harmony

    Bringing Python® and Julia together in seamless harmony. Call Python code from Julia and Julia code from Python via a symmetric interface. Simple syntax, so the Python code looks like Python and the Julia code looks like Julia. Intuitive and flexible conversions between Julia and Python: anything can be converted, you are in control. Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. bytes, array. array, numpy.ndarray) from Julia or Julia arrays...
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