Search Results for "gnu/linux" - Page 29
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Showing 13880 open source projects for "gnu/linux"
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Cassandra Spark Connector
Apache Spark to Apache Cassandra connector
The Apache Cassandra Spark Connector allows Spark jobs (RDDs or DataFrames/Datasets) to read from and write to Cassandra tables. Compatible with Apache Cassandra (v2.1+), Spark 1.0–3.5, and Scala 2.11–2.13, it supports mapping Cassandra rows to Scala case classes, saving results back to Cassandra, and executing arbitrary CQL within Spark applications. -
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Stapler
My take on the classic Macintosh app Stapler
The idea is you set up a Stapler Document per project containing related apps, files, folders, etc. Then you can open them all at once by launching the single document. Each document contains a list of aliases that can be managed, inspected, and launched using the app. -
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Automatisch
The open source Zapier alternative. Build workflow automation
Automatisch is an open-source alternative to Zapier and Make.com, aimed at developers and teams who want to automate tasks and integrate APIs with full control over data and workflows. It allows users to build multi-step workflows using a powerful, web-based visual editor. Designed with scalability and extensibility in mind, Automatisch supports numerous built-in integrations while also allowing users to add their own through custom components. Its lightweight architecture and Docker-based... -
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tremor
React components to build charts and dashboards
React components to build charts and dashboards 20+ open-source components built on top of Tailwind CSS to make visualizing data simple again. Fully open-source, accessible, and customizable. Tremor NPM 20+ open-source components built on top of Tailwind CSS to make visualizing data simple again. Fully open-source, made by data scientists and software engineers with a sweet spot for design. -
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miepython
Mie scattering of light by perfect spheres
miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles. -
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ExponentialUtilities.jl
Fast and differentiable implementations of matrix exponentials
ExponentialUtilities is a package of utility functions for matrix functions of exponential type, including functionality for the matrix exponential and phi-functions. These methods are more numerically stable, generic (thus support a wider range of number types), and faster than the matrix exponentiation tools in Julia's Base. The tools are used by the exponential integrators in OrdinaryDiffEq. The package has no external dependencies, so it can also be used independently. -
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AppleAccelerate.jl
Julia interface to the macOS Accelerate framework
Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced... -
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Braket.jl
Experimental Julia implementation of the Amazon Braket SDK
Braket.jl is not an officially supported AWS product. This package is a Julia implementation of the Amazon Braket SDK allowing customers to access Quantum Hardware and Simulators. This is experimental software, and support may be discontinued in the future. For a fully supported SDK, please use the Python SDK. We may change, remove, or deprecate parts of the API when making new releases. Please review the CHANGELOG for information about changes in each release. -
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GDAL.jl
Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library
Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly. -
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JUDI.jl
Julia Devito inversion
JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling... -
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ScientificTypes.jl
An API for dispatching on the "scientific" type of data
This package makes a distinction between machine type and scientific type of a Julia object. The machine type refers to the Julia type being used to represent the object (for instance, Float64). The scientific type is one of the types defined in ScientificTypesBase.jl reflecting how the object should be interpreted (for instance, Continuous or Multiclass). -
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ReTest.jl
Testing framework for Julia
ReTest is a testing framework for Julia allowing defining tests in source files, whose execution is deferred and triggered on demand. This is useful when one likes to have definitions of methods and corresponding tests close to each other. This is also useful for code that is not (yet) organized as a package, and where one doesn't want to maintain a separate set of files for tests. Filtering run testsets with a Regex, which is matched against the descriptions of testsets. This is useful for... -
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ConformalPrediction.jl
Predictive Uncertainty Quantification through Conformal Prediction
ConformalPrediction.jl is a package for Predictive Uncertainty Quantification (UQ) through Conformal Prediction (CP) in Julia. It is designed to work with supervised models trained in MLJ (Blaom et al. 2020). Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use... -
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CBinding.jl
Automatic C interfacing for Julia
Use CBinding.jl to automatically create C library bindings with Julia at runtime. In order to support the fully automatic conversion and avoid name collisions, the names of C types or functions are mangled a bit to work in Julia. Therefore everything generated by CBinding.jl can be accessed with the c"..." string macro to indicate that it lives in C-land. As an example, the function func above is available in Julia as c"func". It is possible to store the generated bindings to more... -
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CausalityTools.jl
Algorithms for detecting associations, dynamical influences
CausalityTools.jl is a package for quantifying associations and dynamical coupling between datasets, independence testing, and causal inference. Association measures from conventional statistics, information theory, and dynamical systems theory, for example, distance correlation, mutual information, transfer entropy, convergent cross mapping and a lot more. A dedicated API for independence testing, which comes with automatic compatibility with every measure-estimator combination you can... -
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Compat.jl
Compatibility across Julia versions
The Compat package is designed to ease interoperability between older and newer versions of the Julia language. In particular, in cases where it is impossible to write code that works with both the latest Julia master branch and older Julia versions, or impossible to write code that doesn't generate a deprecation warning in some Julia version, the Compat package provides a macro that lets you use the latest syntax in a backward-compatible way. This is primarily intended for use by other... -
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NCDatasets.jl
Load and create NetCDF files in Julia
NCDatasets allows one to read and create netCDF files. NetCDF data set and attribute list behave like Julia dictionaries and variables like Julia arrays. This package implements the CommonDataModel.jl interface, which means that the datasets can be accessed in the same way as GRIB files opened with GRIBDatasets.jl. -
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ChaosTools.jl
Tools for the exploration of chaos and nonlinear dynamics
A Julia module that offers various tools for analyzing nonlinear dynamics and chaotic behavior. It can be used as a standalone package, or as part of DynamicalSystems.jl. All further information is provided in the documentation, which you can either find online or build locally by running the docs/make.jl file. ChaosTools.jl is the jack-of-all-trades package of the DynamicalSystems.jl library: methods that are not extensive enough to be a standalone package are added here. You should see the... -
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LaTeXStrings.jl
convenient input and display of LaTeX equation strings for Julia
This is a small package to make it easier to type LaTeX equations in string literals in the Julia language, written by Steven G. Johnson. With ordinary strings in Julia, to enter a string literal with embedded LaTeX equations you need to manually escape all backslashes and dollar signs: for example, $\alpha^2$ is written \$\\alpha^2\$. Also, even though IJulia is capable of displaying formatted LaTeX equations (via MathJax), an ordinary string will not exploit this. -
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InvoicePrinter
Super simple PDF invoicing
Super simple PDF invoicing. InvoicePrinter is a server, command line program and pure Ruby library to generate PDF invoices in no time. You can use Ruby or JSON as the invoice representation to build the final PDF. -
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ComponentArrays.jl
Arrays with arbitrarily nested named components
The main export of this package is the ComponentArray type. "Components" of ComponentArrays are really just array blocks that can be accessed through a named index. This will create a new ComponentArray whose data is a view into the original, allowing for standalone models to be composed together by simple function composition. In essence, ComponentArrays allow you to do the things you would usually need a modeling language for, but without actually needing a modeling language. The main... -
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ReverseDiff
Reverse Mode Automatic Differentiation for Julia
ReverseDiff is a fast and compile-able tape-based reverse mode automatic differentiation (AD) that implements methods to take gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really). While performance can vary depending on the functions you evaluate, the algorithms implemented by ReverseDiff generally outperform non-AD algorithms in both speed and accuracy. -
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Molly.jl
Molecular simulation in Julia
Much of science can be explained by the movement and interaction of molecules. Molecular dynamics (MD) is a computational technique used to explore these phenomena, from noble gases to biological macromolecules. Molly.jl is a pure Julia package for MD, and for the simulation of physical systems more broadly. The package is described in a talk at Enzyme Conference 2023 and an earlier talk at the JuliaMolSim minisymposium at JuliaCon 2022. Slides are also available for a tutorial in September... -
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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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Literate
Simple package for literate programming in Julia
Literate is a package for Literate Programming. The main purpose is to facilitate writing Julia examples/tutorials that can be included in your package documentation. Literate can generate markdown pages (for e.g. Documenter.jl), and Jupyter notebooks, from the same source file. There is also an option to "clean" the source from all metadata, and produce a pure Julia script. Using a single source file for multiple purposes reduces maintenance, and makes sure your different output formats are...
