Skip to main content

Interactive visualization in Python

Project description

VisPy: interactive scientific visualization in Python

Main website: http://vispy.org

Build Status Appveyor Status Coverage Status Zenodo Link


VisPy is a high-performance interactive 2D/3D data visualization library. VisPy leverages the computational power of modern Graphics Processing Units (GPUs) through the OpenGL library to display very large datasets. Applications of VisPy include:

  • High-quality interactive scientific plots with millions of points.

  • Direct visualization of real-time data.

  • Fast interactive visualization of 3D models (meshes, volume rendering).

  • OpenGL visualization demos.

  • Scientific GUIs with fast, scalable visualization widgets (Qt or IPython notebook with WebGL).

Announcements

  • Release! Version 0.6.4, December 13, 2019

  • Release! Version 0.6.3, November 27, 2019

  • Release! Version 0.6.2, November 4, 2019

  • Release! Version 0.6.1, July 28, 2019

  • Release! Version 0.6.0, July 11, 2019

  • Release! Version 0.5.3, March 28, 2018

  • Release! Version 0.5.2, December 11, 2017

  • Release! Version 0.5.1, November 4, 2017

  • Release! Version 0.5, October 24, 2017

  • Release! Version 0.4, May 22, 2015

  • VisPy tutorial in the IPython Cookbook

  • Release! Version 0.3, August 29, 2014

  • EuroSciPy 2014: talk at Saturday 30, and sprint at Sunday 31, August 2014

  • Article in Linux Magazine, French Edition, July 2014

  • GSoC 2014: two GSoC students are currently working on VisPy under the PSF umbrella

  • Release!, Version 0.2.1 04-11-2013

  • Presentation at BI forum, Budapest, 6 November 2013

  • Presentation at Euroscipy, Belgium, August 2013

  • EuroSciPy Sprint, Belgium, August 2013

  • Release! Version 0.1.0 14-08-2013

Using VisPy

VisPy is a young library under heavy development at this time. It targets two categories of users:

  1. Users knowing OpenGL, or willing to learn OpenGL, who want to create beautiful and fast interactive 2D/3D visualizations in Python as easily as possible.

  2. Scientists without any knowledge of OpenGL, who are seeking a high-level, high-performance plotting toolkit.

If you’re in the first category, you can already start using VisPy. VisPy offers a Pythonic, NumPy-aware, user-friendly interface for OpenGL ES 2.0 called gloo. You can focus on writing your GLSL code instead of dealing with the complicated OpenGL API - VisPy takes care of that automatically for you.

If you’re in the second category, we’re starting to build experimental high-level plotting interfaces. Notably, VisPy now ships a very basic and experimental OpenGL backend for matplotlib.

Installation

VisPy runs on Python 2.7+ and Python 3.3+ and depends on NumPy. You also need a backend (PyQt4/PySide, PyQt5/PySide2, glfw, pyglet, SDL, or wx).

PyQt5/PySide2 should be considered more experimental than PyQt4/PySide.

VisPy can be installed either via pip:

` pip install vispy `

or within the Anaconda Python distribution. Anaconda provides a convenient package management system. Installing VisPy can then easily be achieved by adding conda-forge to the channels with:

` conda config --add channels conda-forge `

Once the conda-forge channel has been enabled, vispy can be installed with:

` conda install vispy `

Development Installation

As VisPy is under heavy development at this time, we highly recommend developers to use the development version on Github (master branch). You need to clone the repository and install VisPy with python setup.py install.

As a one-liner, assuming git is installed:

git clone --recurse-submodules https://github.com/vispy/vispy.git && cd vispy && python setup.py install --user

This will automatically install the latest version of vispy.

If you already have vispy cloned, you may need to update the git submodules to make sure you have the newest code:

git pull
git submodule update --init --recursive

Structure of VisPy

Currently, the main subpackages are:

  • app: integrates an event system and offers a unified interface on top of many window backends (Qt4, wx, glfw, IPython notebook with/without WebGL, and others). Relatively stable API.

  • gloo: a Pythonic, object-oriented interface to OpenGL. Relatively stable API.

  • scene: this is the system underlying our upcoming high level visualization interfaces. Under heavy development and still experimental, it contains several modules.

    • Visuals are graphical abstractions representing 2D shapes, 3D meshes, text, etc.

    • Transforms implement 2D/3D transformations implemented on both CPU and GPU.

    • Shaders implements a shader composition system for plumbing together snippets of GLSL code.

    • The scene graph tracks all objects within a transformation graph.

  • plot: high-level plotting interfaces.

The API of all public interfaces are subject to change in the future, although app and gloo are relatively stable at this point.

Genesis

VisPy began when four developers with their own visualization libraries decided to team up: Luke Campagnola with PyQtGraph, Almar Klein with Visvis, Cyrille Rossant with Galry, Nicolas Rougier with Glumpy.

Now VisPy looks to build on the expertise of these developers and the broader open-source community to build a high-performance OpenGL library.


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

vispy-0.6.4.tar.gz (13.3 MB view details)

Uploaded Source

Built Distributions

vispy-0.6.4-cp37-cp37m-win_amd64.whl (2.3 MB view details)

Uploaded CPython 3.7mWindows x86-64

vispy-0.6.4-cp37-cp37m-win32.whl (2.2 MB view details)

Uploaded CPython 3.7mWindows x86

vispy-0.6.4-cp37-cp37m-manylinux2010_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

vispy-0.6.4-cp37-cp37m-manylinux2010_i686.whl (2.3 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ i686

vispy-0.6.4-cp37-cp37m-manylinux1_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.7m

vispy-0.6.4-cp37-cp37m-manylinux1_i686.whl (2.3 MB view details)

Uploaded CPython 3.7m

vispy-0.6.4-cp37-cp37m-macosx_10_6_intel.whl (2.3 MB view details)

Uploaded CPython 3.7mmacOS 10.6+ Intel (x86-64, i386)

vispy-0.6.4-cp36-cp36m-win_amd64.whl (2.3 MB view details)

Uploaded CPython 3.6mWindows x86-64

vispy-0.6.4-cp36-cp36m-win32.whl (2.2 MB view details)

Uploaded CPython 3.6mWindows x86

vispy-0.6.4-cp36-cp36m-manylinux2010_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

vispy-0.6.4-cp36-cp36m-manylinux2010_i686.whl (2.3 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ i686

vispy-0.6.4-cp36-cp36m-manylinux1_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.6m

vispy-0.6.4-cp36-cp36m-manylinux1_i686.whl (2.3 MB view details)

Uploaded CPython 3.6m

vispy-0.6.4-cp36-cp36m-macosx_10_6_intel.whl (2.3 MB view details)

Uploaded CPython 3.6mmacOS 10.6+ Intel (x86-64, i386)

vispy-0.6.4-cp35-cp35m-win_amd64.whl (2.3 MB view details)

Uploaded CPython 3.5mWindows x86-64

vispy-0.6.4-cp35-cp35m-win32.whl (2.2 MB view details)

Uploaded CPython 3.5mWindows x86

vispy-0.6.4-cp35-cp35m-manylinux2010_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

vispy-0.6.4-cp35-cp35m-manylinux2010_i686.whl (2.3 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ i686

vispy-0.6.4-cp35-cp35m-manylinux1_x86_64.whl (2.3 MB view details)

Uploaded CPython 3.5m

vispy-0.6.4-cp35-cp35m-manylinux1_i686.whl (2.3 MB view details)

Uploaded CPython 3.5m

vispy-0.6.4-cp35-cp35m-macosx_10_6_intel.whl (2.3 MB view details)

Uploaded CPython 3.5mmacOS 10.6+ Intel (x86-64, i386)

File details

Details for the file vispy-0.6.4.tar.gz.

File metadata

  • Download URL: vispy-0.6.4.tar.gz
  • Upload date:
  • Size: 13.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4.tar.gz
Algorithm Hash digest
SHA256 627b6574b77c86e72a1e6b4522a5c9697c6f4cbb23678d8da9ff55c339264b1f
MD5 e9a1d8f2fe27b0a487a15457f4ecfe24
BLAKE2b-256 02cf3cdfc2edf65578ea44cebfb067e700dcba0303492b43dc35f905b2d7b540

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 6703ccb8f76f403ef536106c5c877e7551bc5097dc567f5fcd1363d55781e550
MD5 0b80584efbd39123545e57f6f1f94c88
BLAKE2b-256 fa3bdaa4bde03d18e19f703f0182e91ef31cd2317e50e945423add176c41c507

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp37-cp37m-win32.whl.

File metadata

  • Download URL: vispy-0.6.4-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 33763666f1857f0dddeed3df19a6f611934df3a26c905e955c9ef9b2a5fb54f0
MD5 5f965a369670914454fc93ccc822e79b
BLAKE2b-256 2c2f997004b211ae0ebbdc0fc261f347b076b71dfd7e54e3f0e3b3bd7ce74df6

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp37-cp37m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.7m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 c29b3973fb3fc756f43af7f9157e42cf8141cd922f3aa250dffe611139458d73
MD5 dac255976cd741a311a5eace551dae5a
BLAKE2b-256 5f7e9e24a986e8fe2ee94588f806e1c4579c8c285e7e42b70189d79db4132e07

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp37-cp37m-manylinux2010_i686.whl.

File metadata

  • Download URL: vispy-0.6.4-cp37-cp37m-manylinux2010_i686.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.7m, manylinux: glibc 2.12+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp37-cp37m-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 7a08fa4578fc5e1e6b0bb52d15525233794a07cf6f80d27d96c76bf9a8a60ceb
MD5 4d02381f2697e3132b661a9f9d99e369
BLAKE2b-256 ab6563644853a1a14ecf2c868a2528b28ce2bacb5b8f417ddf069fa7f8013a3e

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp37-cp37m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 61b6ccbf701f3a022d0081d7c78760a95cb5f5e368c799a9c2294eb15918aa0e
MD5 c4dc1697baf13ee28d49c524b80e4317
BLAKE2b-256 6714928c38a1a48449c34440363e303506b47bea2fab2c90464dd3691431e370

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp37-cp37m-manylinux1_i686.whl.

File metadata

  • Download URL: vispy-0.6.4-cp37-cp37m-manylinux1_i686.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp37-cp37m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 e59590a54f0b15190e0409a7a06ed210dfdc331ea9150c806d51a160df4b2bd3
MD5 26b46788ea8ef1d01188402313118289
BLAKE2b-256 e41dfdfc7ea4fb5cd9a61fae3dbba2aada07a22feb0327ffd0e46686cb51230a

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp37-cp37m-macosx_10_6_intel.whl.

File metadata

  • Download URL: vispy-0.6.4-cp37-cp37m-macosx_10_6_intel.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.7m, macOS 10.6+ Intel (x86-64, i386)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp37-cp37m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 45b44f3f621e4ea0e98d95d70a447a443d04793f9226ac346fb9b25e04e64160
MD5 b958c2724424654e354c262a33a4ca15
BLAKE2b-256 ce0632a354cd6467dcf1afb36dc120e420a4387a681de7316297249f39f673c5

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 dbe1a074d4e8940a150952e22e4e163d4085a6733fa780e228441ce8e4883c2e
MD5 ccd85502b63eb4b981044b977be0151a
BLAKE2b-256 4054dff5cef159fe724e66614cc86bfb885110cc9d27fd75814283fd3d4927b4

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp36-cp36m-win32.whl.

File metadata

  • Download URL: vispy-0.6.4-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 2037341a3e1c6e31a14015a98d9f5a7cdf805900c80058690d31e8ba99fc891d
MD5 d0e0e9a62bde59e5c57d5350598161f4
BLAKE2b-256 59dafd3b958a1fc4a22aa0dbc22e3b1aae4e9218ee6441935fc0d8c2ebcfb89e

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp36-cp36m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.6m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 7c021fa1592b6249197863ac3839e2a8c92c283e194053df225fa94717a7aa14
MD5 1c0f4fa14ea3b617a90ae42bc6a2500e
BLAKE2b-256 cf29899797a9af4446d3ddf594f49b0fbd43076eafa1552e24690cfd99b0e2ff

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp36-cp36m-manylinux2010_i686.whl.

File metadata

  • Download URL: vispy-0.6.4-cp36-cp36m-manylinux2010_i686.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.6m, manylinux: glibc 2.12+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp36-cp36m-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 370fbbd9d398c1ee9c9fc720cfb63cf4b81c9266d1960485b20eb7af1b4083d1
MD5 13a7b157faeef1233e87694864e74653
BLAKE2b-256 89300f567205dcf3d33654d2084bc5b0bb0e590ee77c71475afce72d30aa6236

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp36-cp36m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 26d66815b68df401a4c50beab86cd6141ed315bbb2a12e9759db55a3c6737187
MD5 3de58078931def8db1d81da356602d22
BLAKE2b-256 6ae8c42c520707b00523f45c50dbb305617335df1bda308a5c474eed5e0bbafc

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp36-cp36m-manylinux1_i686.whl.

File metadata

  • Download URL: vispy-0.6.4-cp36-cp36m-manylinux1_i686.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp36-cp36m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 a0e587d826ad0504add75962a2a5e29dcc9fe639156d92ac8384ee2e2be873e8
MD5 4e492ba8a157e991d9d930f1bfbb4948
BLAKE2b-256 49f6ccf9df739de3eb4abc84459ed695419de7d0fa868a95f8938ea9f2d6502b

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp36-cp36m-macosx_10_6_intel.whl.

File metadata

  • Download URL: vispy-0.6.4-cp36-cp36m-macosx_10_6_intel.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.6m, macOS 10.6+ Intel (x86-64, i386)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp36-cp36m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 f5d27453181b4553e1c7f55435a8185effb71c554b1d2b369b8d2865c982fa92
MD5 5f882447893d5884e46b1a36c0599f08
BLAKE2b-256 c3cb8fc9adbd4e6f5e36ff71718e19fbfaa7cdb561ef0683d7a7b3af0a1fefdd

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 e8643285ee0b84dd16ea1c1261bce694454eebd3c6be6c81d10f9a92bd96bea2
MD5 a5d39a19029102cc0dce440bce84d579
BLAKE2b-256 6fb6ede4d8fc8296546cbd587a2472eafa0b6f74e12b5d11f5e82f4e13a8ec3d

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp35-cp35m-win32.whl.

File metadata

  • Download URL: vispy-0.6.4-cp35-cp35m-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.5m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp35-cp35m-win32.whl
Algorithm Hash digest
SHA256 02929e5a2414dae33a64d4177172c0a36a71131cf3674e7d99b48d28e296a300
MD5 554b4c3bd14504ca123b0e83ac30c2fb
BLAKE2b-256 7be647c77cc6d49c41634a0d7ccac4512f4f242dd31536ee72370e132a5144f5

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp35-cp35m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.5m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 85a581e995938ae4e2e6d3613c74add9e5e10448c61fac198b20d2fa18b2a150
MD5 927c330b0709b32a1f96700569e5edd5
BLAKE2b-256 2a58d8654ad4b4c5ffb03adebd880f88181066be722c5ebb4ecefe16c12dc214

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp35-cp35m-manylinux2010_i686.whl.

File metadata

  • Download URL: vispy-0.6.4-cp35-cp35m-manylinux2010_i686.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.5m, manylinux: glibc 2.12+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp35-cp35m-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 a6bb5926c5c4107b77fbfb7ed259e82d7a8e363650b435062aa55c6d1cf9d4df
MD5 45c55e745af9c5368b6ea193eb85d3c7
BLAKE2b-256 3caeb5985c0d77375ec7f643cf8caa4d84b5ebb3742a3037cc2f3c783173284c

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

  • Download URL: vispy-0.6.4-cp35-cp35m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.5m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 ea2891c433e928b30e40f5c128ac7d35ce7964592bfbf579fc02c955f0096564
MD5 7a34874f3f504496c1875ea9f561f56e
BLAKE2b-256 dcfc0c300f4780aec5669c1be99cb016bd3473b813d50a5b760b4334821b8afd

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp35-cp35m-manylinux1_i686.whl.

File metadata

  • Download URL: vispy-0.6.4-cp35-cp35m-manylinux1_i686.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.5m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp35-cp35m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 1cd1ffefb462ea483fcb141deb900ac1e6a002d19338b30758069d3ec783bddd
MD5 ea32f0c26d1d1c8cafd8700be6b2cccf
BLAKE2b-256 f463ba6ee8749ff0947fb10998741ebf3ab4075ffd028dab9eb4e04f0c213262

See more details on using hashes here.

File details

Details for the file vispy-0.6.4-cp35-cp35m-macosx_10_6_intel.whl.

File metadata

  • Download URL: vispy-0.6.4-cp35-cp35m-macosx_10_6_intel.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.5m, macOS 10.6+ Intel (x86-64, i386)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.8.0

File hashes

Hashes for vispy-0.6.4-cp35-cp35m-macosx_10_6_intel.whl
Algorithm Hash digest
SHA256 5645ac825c726cbf751a792802846e5583bf55567d751065df943877768b1de6
MD5 d01f9bb4081528920d8e272bdc8f495e
BLAKE2b-256 611bc36e44433b3c2e1d513a1731f896404f8bbe06cef2addd1fa4e94f245138

See more details on using hashes here.

Supported by

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