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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-07-30T22:01:10.093Z","updated_at":"2026-03-11T20:02:49.284Z","avatar_url":"https://github.com/libdynd.png","language":"C++","funding_links":[],"categories":["TODO scan for Android support in followings"],"sub_categories":[],"readme":"[![DyND Logo](docs/logo/dynd_logo_320px.png)](http://libdynd.org)\n\nThe DyND Library\n================\n\nTravis CI: [![Build Status](https://api.travis-ci.org/libdynd/libdynd.svg?branch=master)](https://travis-ci.org/libdynd/libdynd) CircleCI: [![CircleCI](https://circleci.com/gh/libdynd/libdynd.svg?style=svg)](https://circleci.com/gh/libdynd/libdynd) Azure Pipelines: [![Build Status](https://dev.azure.com/libdynd/libdynd/_apis/build/status/libdynd.libdynd?branchName=master)](https://dev.azure.com/libdynd/libdynd/_build/latest?definitionId=2?branchName=master)\nGitter: [![Join the chat at https://gitter.im/libdynd/libdynd](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/libdynd/libdynd?utm_source=badge\u0026utm_medium=badge\u0026utm_campaign=pr-badge\u0026utm_content=badge)\n\nDyND is an array library for managing structured and semi-structured data, written with\nC++ as a first-class target and extended to Python with a lightweight binding. It aims\nto be a cross-language platform for data analysis, by bringing the popularity and flexibility\nof the Python data science stack to other languages. It is inspired by [NumPy](http://www.numpy.org/),\nthe Python array programming library at the core of the scientific Python stack, but tries\nto address a number of obstacles encountered by some of NumPy’s users. Examples of these are\nsupport for variable-sized strings, missing values, variable-sized (ragged) array dimensions,\nand versatile tools for creating and manipulating functions that apply generic patterns\nacross containers.\n\nAt a high level, the cornerstones of DyND are its type system, array container, and callable\n(function) objects. These represent the description, storage, and manipulation of dynamic,\nreinterpretable bytes across languages. At a low level, DyND defines an primitive execution\nkernel that brings together computation and data in a compact form that can be executed rapidly\nacross array elements. Where DyND begins to shine is in its support for functional composition.\nFor example, NumPy-like broadcasting is not built into every callable, rather it is made\navailable as a functional transformation applied to a scalar callable.\n\nDyND was created by [Irwin Zaid](https://github.com/izaid) and [Mark Wiebe](https://github.com/mwiebe).\nThe core team consists of [Irwin Zaid](https://github.com/izaid), [Mark Wiebe](https://github.com/mwiebe),\nand [Ian Henriksen](https://github.com/insertinterestingnamehere). Others who made important\ncontributions include [Phillip Cloud](https://github.com/cpcloud), [Michael Droettboom](https://github.com/mdboom),\n[Stefan Krah](https://github.com/skrah), [Travis Oliphant](https://en.wikipedia.org/wiki/Travis_Oliphant), and\n[Andy Terrel](http://andy.terrel.us/). Much of the funding that made this project possible came through [Continuum Analytics](http://continuum.io/)\nand [DARPA-BAA-12-38](https://www.fbo.gov/index?s=opportunity\u0026mode=form\u0026id=7a77846c73ffc5cb22f9295ffe6cdd55\u0026tab=core\u0026_cview=0),\npart of [XDATA](http://www.darpa.mil/Our_Work/I2O/Programs/XDATA.aspx).\n\nWe pronounce DyND as \"dined\", though others refer to it as \"dy-n-d\". It's not something we're picky about.\n\nGetting Started\n===============\n\nThis library is actively developed together with its Python\nbindings. The Python bindings provide a good way to become familiar\nwith the library from a high level perspective. See\n[the github site for the Python bindings](https://github.com/libdynd/dynd-python).\n\nC++ is a first-class target of the library, the intent is that all features should\nbe easily usable in that language. This approach makes it so that DyND can expose\na more uniform interface to C++, Python, and hopefully other languages that eventually\nget bindings to the core DyND library.\n\nDyND is still experimental, so many of the interfaces provided here will continue to change.\nThat said, feedback and bug reports are greatly appreciated.\n\nTo get started as a developer of libdynd, begin by working through the\n[LibDyND Developer Guide](docs/developer-guide.md). To discuss\nthe development of this library, subscribe to the\n[LibDyND Development List](https://groups.google.com/forum/#!forum/libdynd-dev).\n\nHistory Of DyND\n===============\n\nDyND was started as a personal project of [Mark Wiebe](https://github.com/mwiebe)\nin September 2011 to begin dabbling in ideas for how a dynamic, multidimensional\narray library could be structured in C++. See [here](https://github.com/libdynd/libdynd/commit/768ac9a30cdb4619d09f4656bfd895ab2b91185d)\nfor the very first commit. Mark was at the [University of British Columbia](https://www.ubc.ca/),\nthen joined [Continuum Analytics](http://continuum.io/about-continuum) part-time when\nit was founded in January 2012, and later became full-time in the spring of 2012. He parted ways with Continuum at the end of 2014, joining [Thinkbox Software](http://www.thinkboxsoftware.com).\n\nDuring the formation of Continuum, DyND was open-sourced and brought into the company\nas a part of the [Blaze project](http://blaze.pydata.org). Continuum secured funding\nfor the Blaze project through DARPA's [XDATA program](http://www.darpa.mil/Our_Work/I2O/Programs/XDATA.aspx),\ngiving the project space and time to develop as it needed and providing real data sets\nand challenge problems to tackle and measure against. [Travis Oliphant](https://en.wikipedia.org/wiki/Travis_Oliphant)\nhas told the story of the early days at Continuum, and why it supports DyND, on the\nNumPy mailing list - see [here](https://mail.scipy.org/pipermail/numpy-discussion/2015-August/073412.html).\n\n[Irwin Zaid](https://github.com/izaid) joined the project at the beginning of 2014, as\nits first major outside contributor, while he was a research fellow at [Christ Church](http://www.chch.ox.ac.uk),\n[University of Oxford](http://www.ox.ac.uk). He initially added [CUDA](https://developer.nvidia.com/about-cuda)\nsupport to the library, then played a gradually increasing role in the design and goals of the project.\nHe took over development of DyND in the spring of 2015, and was funded by Continuum from June 2015\nuntil April 2016.\n\n[Ian Henriksen](https://github.com/insertinterestingnamehere) began working on DyND through\n[Google Summer of Code](https://developers.google.com/open-source/gsoc/) - under the umbrella\nof [NumFocus](http://www.numfocus.org) - in the summer of 2015. He remained active in the\nproject from then onwards.\n\nDyND is still experimental. Some of its components are mature while others are severely lacking.\nNew contributors are welcome, so if you have the patience to collaborate on a maturing code base, and enjoy C++,\narray-oriented, and numeric programming, DyND might be the the open source project you're looking for.\n\nBuilding\n========\n\nThe build system of this library is based on CMake. See\nthe [build instructions](BUILD.md) for details about how\nto build the library.\n\nDyND requires a C++14 compiler, the minimum versions supported are gcc 4.9,\nMSVC 2015, and Clang 3.6. The last release to support C++98 was DyND 0.6.6.\nC++14 brings several things to the library, including a roughly factor of two\ncompile time improvement and generality with variadic templates.\n\nDocumentation\n=============\n\n[Documentation Index](docs/index.md)\n\nRunning The Tests\n=================\n\nThe tests are built using Google Test. To execute the test suite,\nrun the `test_libdynd` program.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flibdynd%2Flibdynd","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flibdynd%2Flibdynd","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flibdynd%2Flibdynd/lists"}