Search Results for "code library"
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Showing 90 open source projects for "code library"
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MacroTools.jl
MacroTools provides a library of tools for working with Julia code
MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system and code-walking tools that let you do deep transformations of code in a few lines. See the docs for more info. -
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dlib
Toolkit for making machine learning and data analysis applications
...It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. There is no installation or configure step needed before you can use the library. All operating system specific code is isolated inside the OS abstraction layers which are kept as small as possible. -
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KernelAbstractions.jl
Heterogeneous programming in Julia
KernelAbstractions (KA) is a package that enables you to write GPU-like kernels targetting different execution backends. KA is intended to be a minimal and performant library that explores ways to write heterogeneous code. -
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PDFIO.jl
PDF Reader Library for Native Julia.
...A script-based language makes it easier for the consumers to quickly modify the code and enhance to their specific needs. -
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Malli
High-performance data-driven data specification library
Malli is a powerful, data-driven schema library for Clojure and ClojureScript, offering rich support for specification, validation, parsing, error reporting, and generative testing. Designed for performance, Malli leverages efficient runtime representations and code generation, seamlessly integrating with Clojure’s data-oriented architecture. It supports function schemas, JSON transformation, and OpenAPI generation for strong API contracts. -
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CxxWrap
Package to make C++ libraries available in Julia
This package aims to provide a Boost. Python-like wrapping for C++ types and functions to Julia. The idea is to write the code for the Julia wrapper in C++, and then use a one-liner on the Julia side to make the wrapped C++ library available there. The mechanism behind this package is that functions and types are registered in C++ code that is compiled into a dynamic library. This dynamic library is then loaded into Julia, where the Julia part of this package uses the data provided through a C interface to generate functions accessible from Julia. ... -
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oneAPI.jl
Julia support for the oneAPI programming toolkit.
Julia support for the oneAPI programming toolkit. oneAPI.jl provides support for working with the oneAPI unified programming model. The package is verified to work with the (currently) only implementation of this interface that is part of the Intel Compute Runtime, only available on Linux. This package is still under significant development, so expect bugs and missing features. -
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XCharts
A charting and data visualization library for Unity
A charting and data visualization library for Unity. Unity data visualization chart plugin. A UGUIpowerful, easy-to-use, parameter-configurable data visualization chart plug-in. It supports ten built-in charts. A powerful, easy-to-use, configurable charting and data visualization library for Unity. Visual configuration of parameters, real-time preview of effects, and pure code drawing without additional resources. -
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NVIDIA Merlin
Library providing end-to-end GPU-accelerated recommender systems
NVIDIA Merlin is an open-source library that accelerates recommender systems on NVIDIA GPUs. The library enables data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools to address common feature engineering, training, and inference challenges. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, which is all accessible through easy-to-use APIs. -
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Cytoscape.js
Graph theory library for visualization and analysis
...Browsers with partial but sufficient ES5 support also work, such as IE9 and Firefox 4. The documentation and examples are not optimized for old browsers, although the library itself is. Some demos may not work in old browsers in order to keep the demo code simple. -
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Kestra
Kestra is an infinitely scalable orchestration and scheduling platform
Build reliable workflows, blazingly fast, deploy in just a few clicks. Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate... -
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NBInclude.jl
import code from IJulia Jupyter notebooks into Julia programs
NBInclude is a package for the Julia language that allows you to include and execute IJulia (Julia-language Jupyter) notebook files just as you would include an ordinary Julia file. The goal of this package is to make notebook files just as easy to incorporate into Julia programs as ordinary Julia (.jl) files, giving you the advantages of a notebook (integrated code, formatted text, equations, graphics, and other results) while retaining the modularity and re-usability of .jl files. -
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DynamicalSystems.jl
Award winning software library for nonlinear dynamics timeseries
DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear time series analysis. To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems"). To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms... -
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Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a... -
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can... -
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PGFPlotsX.jl
Plots in Julia using the PGFPlots LaTeX package
PGFPlotsX is a Julia package to generate publication quality figures using the LaTeX library PGFPlots. It is similar in spirit to the package PGFPlots.jl but it tries to have a very close mapping to the PGFPlots API as well as minimize the number of dependencies. The fact that the syntax is similar to the TeX version means that examples from Stack Overflow and the PGFPlots manual can easily be incorporated in the Julia code. -
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plotly
An interactive graphing library for R
This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of... -
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patat
Terminal-based presentations using Pandoc
...Experimental images support. Supports evaluating code snippets and showing the result. Written in Haskell. -
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Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several... -
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Quadratic
Data science spreadsheet with Python & SQL
...Quadratic has no environment to configure. The grid runs entirely in the browser with no backend service. This makes our grids completely portable and very easy to share. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. Quickly write code and see the output in full detail. No more squinting into a tiny terminal to see your data output. -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
...You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime 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. ... -
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Dask
Parallel computing with task scheduling
Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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Chokidar
Minimal and efficient cross-platform file watching library
Chokidar is a solution for all the users of Node.js fs.watch who are tired of it not reporting filenames on MacOS and events at all when using editors like Sublime on MacOS. Node.js fs.watch often reports events twice, emits most changes as rename, and it does not provide an easy way to recursively watch file trees nor supports recursive watching on Linux. Same as with Node.js fs.watchFile. Therefore, Chokidar resolves these problems. Initially made for Brunch (an ultra-swift web app build... -
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cuDF
GPU DataFrame Library
Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. cuDF provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming. For additional examples, browse our complete API documentation, or check out our more detailed notebooks. cuDF can be installed... -
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AWS SDK for pandas
Easy integration with Athena, Glue, Redshift, Timestream, Neptune
aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. ...
