Skip to main content

An analysis and visualization toolkit for volumetric data

Project description

The yt Project

PyPI Supported Python Versions Latest Documentation Users' Mailing List Devel Mailing List Data Hub Powered by NumFOCUS Sponsor our Project

Build and Test CI (bleeding edge) pre-commit.ci status Ruff

yt is an open-source, permissively-licensed Python library for analyzing and visualizing volumetric data.

yt supports structured, variable-resolution meshes, unstructured meshes, and discrete or sampled data such as particles. Focused on driving physically-meaningful inquiry, yt has been applied in domains such as astrophysics, seismology, nuclear engineering, molecular dynamics, and oceanography. Composed of a friendly community of users and developers, we want to make it easy to use and develop - we'd love it if you got involved!

We've written a method paper you may be interested in; if you use yt in the preparation of a publication, please consider citing it.

Code of Conduct

yt abides by a code of conduct partially modified from the PSF code of conduct, and is found in our contributing guide.

Installation

You can install the most recent stable version of yt either with conda from conda-forge:

conda install -c conda-forge yt

or with pip:

python -m pip install yt

More information on the various ways to install yt, and in particular to install from source, can be found on the project's website.

Getting Started

yt is designed to provide meaningful analysis of data. We have some Quickstart example notebooks in the repository:

If you'd like to try these online, you can visit our yt Hub and run a notebook next to some of our example data.

Contributing

We love contributions! yt is open source, built on open source, and we'd love to have you hang out in our community.

We have developed some guidelines for contributing to yt.

Imposter syndrome disclaimer: We want your help. No, really.

There may be a little voice inside your head that is telling you that you're not ready to be an open source contributor; that your skills aren't nearly good enough to contribute. What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong. If you can write code at all, you can contribute code to open source. Contributing to open source projects is a fantastic way to advance one's coding skills. Writing perfect code isn't the measure of a good developer (that would disqualify all of us!); it's trying to create something, making mistakes, and learning from those mistakes. That's how we all improve, and we are happy to help others learn.

Being an open source contributor doesn't just mean writing code, either. You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process). Some of these contributions may be the most valuable to the project as a whole, because you're coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.

(This disclaimer was originally written by Adrienne Lowe for a PyCon talk, and was adapted by yt based on its use in the README file for the MetPy project)

Resources

We have some community and documentation resources available.

Is your code compatible with yt ? Great ! Please consider giving us a shoutout as a shiny badge in your README

  • markdown
[![yt-project](https://img.shields.io/static/v1?label="works%20with"&message="yt"&color="blueviolet")](https://yt-project.org)
  • rst
|yt-project|

.. |yt-project| image:: https://img.shields.io/static/v1?label="works%20with"&message="yt"&color="blueviolet"
   :target: https://yt-project.org

Powered by NumFOCUS

yt is a fiscally sponsored project of NumFOCUS. If you're interested in supporting the active maintenance and development of this project, consider donating to the project.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

yt-4.4.0.tar.gz (4.9 MB view details)

Uploaded Source

Built Distributions

yt-4.4.0-cp313-cp313-win_amd64.whl (16.1 MB view details)

Uploaded CPython 3.13 Windows x86-64

yt-4.4.0-cp313-cp313-musllinux_1_2_x86_64.whl (36.0 MB view details)

Uploaded CPython 3.13 musllinux: musl 1.2+ x86-64

yt-4.4.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.2 MB view details)

Uploaded CPython 3.13 manylinux: glibc 2.17+ x86-64

yt-4.4.0-cp313-cp313-macosx_11_0_arm64.whl (6.9 MB view details)

Uploaded CPython 3.13 macOS 11.0+ ARM64

yt-4.4.0-cp313-cp313-macosx_10_13_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.13 macOS 10.13+ x86-64

yt-4.4.0-cp312-cp312-win_amd64.whl (16.1 MB view details)

Uploaded CPython 3.12 Windows x86-64

yt-4.4.0-cp312-cp312-musllinux_1_2_x86_64.whl (36.2 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.2+ x86-64

yt-4.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.5 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

yt-4.4.0-cp312-cp312-macosx_11_0_arm64.whl (7.0 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

yt-4.4.0-cp312-cp312-macosx_10_13_x86_64.whl (7.4 MB view details)

Uploaded CPython 3.12 macOS 10.13+ x86-64

yt-4.4.0-cp311-cp311-win_amd64.whl (16.1 MB view details)

Uploaded CPython 3.11 Windows x86-64

yt-4.4.0-cp311-cp311-musllinux_1_2_x86_64.whl (36.6 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.2+ x86-64

yt-4.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

yt-4.4.0-cp311-cp311-macosx_11_0_arm64.whl (6.9 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

yt-4.4.0-cp311-cp311-macosx_10_9_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

yt-4.4.0-cp310-cp310-win_amd64.whl (16.1 MB view details)

Uploaded CPython 3.10 Windows x86-64

yt-4.4.0-cp310-cp310-musllinux_1_2_x86_64.whl (34.1 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.2+ x86-64

yt-4.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (32.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

yt-4.4.0-cp310-cp310-macosx_11_0_arm64.whl (6.9 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

yt-4.4.0-cp310-cp310-macosx_10_9_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

File details

Details for the file yt-4.4.0.tar.gz.

File metadata

  • Download URL: yt-4.4.0.tar.gz
  • Upload date:
  • Size: 4.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for yt-4.4.0.tar.gz
Algorithm Hash digest
SHA256 0e15df9cb21abe582f8128bf0705a3bc0f4805f97efd6b4f883073703941c0d5
MD5 55e2633f815af6a237c84d5c15e4eb6e
BLAKE2b-256 953d83c89a1afb13b7baff5769b572a36528ce4b8aa047215a73412a3a57f74b

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: yt-4.4.0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for yt-4.4.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 6bdf89fbb8229b8a2263867ae940e22c4a5c42265dc87b1edf184d0fab6d82e5
MD5 b69b50d8eee4c909c48f0a79dc0bbee0
BLAKE2b-256 6d592e8abd97f3ed4cbce75e4758e871e916fb1eabd82f6538c260632319b058

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp313-cp313-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp313-cp313-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 f2242f9b303cf0934fcbdb062dc4a5da045e06f7b1b2ced9771f13580f3815ba
MD5 ea860e3c2dc587f167af565f1682d63f
BLAKE2b-256 0b7e14bbe388678d2dfabcf41c93b9c24459e6ec5420d6817686753340f17929

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 26281fc21b4f73dfdab5d7ffe897215709e9d1bb060e98a3a16cbc354e1fcf8a
MD5 2bf269bf612b3235dfe615ababb81da0
BLAKE2b-256 aafa133cf5f035d3bcff511f5c198cc64326fcf6372e054f926c5ee9d5625d60

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b0aeefc7a39b2ac27ed0bca3ca1849c1e71d52a03b40365314ef44a5764bd991
MD5 a06a7d411e146994def8d2299e75b456
BLAKE2b-256 90963eb47396a031fd9c038db83896578db197cec233dbcbb7b040c9ba96ec9c

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp313-cp313-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp313-cp313-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 7f509e4a92e9fb0af4891aec56447823dd895a9f6d53e4eb9bbef1b21fc64cc3
MD5 d1897b41de4a4822748a94fd1d4a39f9
BLAKE2b-256 34dda73b414f167164383ac479ef6395578eab193a43553ea1cdfd45ac5dda32

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: yt-4.4.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for yt-4.4.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 51da47acff803db663c5d1d063a48898c235db9ef06f246e5f60be2d192427d5
MD5 64425c25bb87426ab727595de09760f4
BLAKE2b-256 66a6a6952abedafe9c9c22328793a65e1ffa3081995429d801372cdbd15926c9

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 b710cfbc36ea99932c6a1357c12698bed508f3a3a2455fc9a73bdee64111ea66
MD5 34b7b9bdf71bd950bcfdff840491b73a
BLAKE2b-256 df627a8f1fadb4bedc67337ad978c5c0edf7f4c19290e3cb104637f8d9bf0cda

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4e64d342e9c4ab70177a5e3f9494c8523bb3354df79c99227adc0872fb9abf85
MD5 1b6960c6507b60dfd5bf6d85d52cb2c3
BLAKE2b-256 83ed21d0172b02555f844ccb0a08531d453afe53ceb5166dafb643f96448b3fb

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 577beb3ab2571126b5d14059fb870e7cf38c0967e6e37c9f578a0a796e72dc64
MD5 285cdc9f3e243fb315ec68a7050fb3b7
BLAKE2b-256 8cf7a14e74ab3974078fa82e4823adf83db8585552295c6dd6520a80ae9db704

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 9ff0be46744c94897c79bd94dd1c762236a7e8b9b23a1aabf2c61c0ab6d68d02
MD5 8d8574c74d68161f79c990d5b3f39e8d
BLAKE2b-256 e5f4dbbbcf13467fd8e0380146f386fb8e89cc86feac40e668fb9eecda882cf9

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: yt-4.4.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for yt-4.4.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 acce425e347e0cfe60d7d55febbd282a57915e07551c957497a882eeaf872892
MD5 3581ccba463eb8f3a53d0a1137d79e9e
BLAKE2b-256 1dbbaf4de6590cc0f0602d1035ee50ab9cf13802a4ae70ab0c9f590728d952b7

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 9ccf3fe5a4ccd24a1673b6852deaa01d8586f9d15d0832f3f8d807fa91261b03
MD5 1e7a2694c4e0de6e654f8fccbae78712
BLAKE2b-256 0a078b57e819e9134d1a78f76491ef964d453b1a645e737f41273e7e5fd07fc4

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1b88b5b4bba59366dd27dd9a9a0c9e4223b80bf7ed7231dbb34146c479fda01a
MD5 d7e755c50e92f65fff0c7387024b4e08
BLAKE2b-256 09c0831b2637e6631d3523405f4cd08ef8204b9ad6e107154ec23eeabd067a2d

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 256573a94059a257c5995f6afd5821505c831d3bf7485fac11f89cb66cf2b715
MD5 bc452f6ee7f98571b9832fd294aec990
BLAKE2b-256 6c633154791e0367fe6a37f1f5888963b2bdf20b74546fecf91cefb4edf0470c

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c1c5118d87f95f9ef126bac85220730668584ba3470c3edb5a2da95c62c95fee
MD5 c1bea5853c7276b91944c2110775e755
BLAKE2b-256 6e4ec75064925403e7aea591169d7608b1ebd602e2708a572d5ed0a6d5fdcd5b

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: yt-4.4.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 16.1 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for yt-4.4.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 247c872251b6d81a6654567125772d4aff8489ae30b1d321dba703918b8d4bbc
MD5 8a268b638319c3b15d1e04e657a63ac7
BLAKE2b-256 495bdb8ead6a3a9d0a98fbf186dd12071466c553ade6ff280012656a8c21189b

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 a927de93fc6166750516335867ef950e24b2beab4f2e09f549b26e4df8d5c680
MD5 1714e2cecf8d21cae9d065bfdba146d8
BLAKE2b-256 1aa59d679541399f4c7039b6eace5773c7ea54ce0bc648e2a3addd50ad80b64e

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f43d55028cab00c231fca37d84c4a9ecce23c217bca02b722a80996c36fe45df
MD5 59a4494f26a15d1be0136a71116e61eb
BLAKE2b-256 6e5794e8d3e0ff981528b5e4c46a67fbc47994ee702ce7b14e4a2dc1dfb36883

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 64c18e6b25741a36f58122e69127119eff7763ceb5ef6fbcf4ea2c90913ceccb
MD5 9ecb209579ae1ff029392f6394a3ccac
BLAKE2b-256 07dc9715711d435448df738731df20e74683ff260c03c67e4651155b1ce807c8

See more details on using hashes here.

File details

Details for the file yt-4.4.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for yt-4.4.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 685c18f23c88c240d9e43ce1a479ad292f8837872ee6051effdf9cf66cabdc92
MD5 551895ab0904cda2e324d76f831bc8a9
BLAKE2b-256 9afc6c7aebcbe2372ec2dd1e093714d81d313ef7b93492564490e27170ade05a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page