Skip to main content

VPython for Jupyter Notebook

Project description

# VPython

This package enables one to run VPython in a browser, using the GlowScript
VPython API, documented in the Help at http://glowscript.org. If the code is
in a cell in a Jupyter notebook, the 3D scene appears in the Jupyter notebook.
If the code is launched outside a notebook (e.g. from the command line), a
browser window will open displaying the scene.

VPython makes it unusually easy to create navigable real-time 3D animations.
The one-line program "sphere()" produces a 3D sphere with appropriate lighting
and with the camera positioned so that the scene fills the view. It also
activates mouse interactions to zoom and rotate the camera view. This
implementation of VPython was begun by John Coady in May 2014. Ruth Chabay and
Bruce Sherwood are assisting in its further development. The repository for
the source code is at https://github.com/BruceSherwood/vpython-jupyter.

## Installation

For more detailed instructions on how to install vpython, see http://vpython.org.

Briefly:

+ If you use the [anaconda python distribution](https://www.continuum.io/anaconda-overview), install like this: `conda install -c vpython vpython`
+ If you use any other python distribution, install this way: `pip install vpython`

## Sample program

Here is a simple example:

```python
from vpython import *
sphere()
```

This will create a canvas containing a 3D sphere, with mouse and touch
controls available to zoom and rotate the camera:

Right button drag or Ctrl-drag to rotate "camera" to view scene.
To zoom, drag with middle button or Alt/Option depressed, or use scroll wheel.
On a two-button mouse, middle is left + right.
Touch screen: pinch/extend to zoom, swipe or two-finger rotate.

Run example VPython programs: [![Binder](http://mybinder.org/badge.svg)](http://mybinder.org/repo/BruceSherwood/vpython-jupyter)

## vpython build status (for the vpython developers)

[![Build Status](https://travis-ci.org/BruceSherwood/vpython-jupyter.svg?branch=master)](https://travis-ci.org/BruceSherwood/vpython-jupyter) [![Build status](https://ci.appveyor.com/api/projects/status/wsdjmh8aehd1o0qg?svg=true)](https://ci.appveyor.com/project/mwcraig/vpython-jupyter)

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

vpython-7.0.1.tar.gz (2.5 MB view details)

Uploaded Source

Built Distributions

vpython-7.0.1-cp36-cp36m-win_amd64.whl (2.5 MB view details)

Uploaded CPython 3.6mWindows x86-64

vpython-7.0.1-cp36-cp36m-win32.whl (2.5 MB view details)

Uploaded CPython 3.6mWindows x86

vpython-7.0.1-cp36-cp36m-macosx_10_7_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.6mmacOS 10.7+ x86-64

vpython-7.0.1-cp35-cp35m-win_amd64.whl (2.5 MB view details)

Uploaded CPython 3.5mWindows x86-64

vpython-7.0.1-cp35-cp35m-win32.whl (2.5 MB view details)

Uploaded CPython 3.5mWindows x86

vpython-7.0.1-cp35-cp35m-macosx_10_7_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.5mmacOS 10.7+ x86-64

vpython-7.0.1-cp34-cp34m-win_amd64.whl (2.5 MB view details)

Uploaded CPython 3.4mWindows x86-64

vpython-7.0.1-cp34-cp34m-win32.whl (2.5 MB view details)

Uploaded CPython 3.4mWindows x86

vpython-7.0.1-cp34-cp34m-macosx_10_6_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.4mmacOS 10.6+ x86-64

vpython-7.0.1-cp27-cp27m-win_amd64.whl (2.5 MB view details)

Uploaded CPython 2.7mWindows x86-64

vpython-7.0.1-cp27-cp27m-win32.whl (2.5 MB view details)

Uploaded CPython 2.7mWindows x86

vpython-7.0.1-cp27-cp27m-macosx_10_7_x86_64.whl (2.5 MB view details)

Uploaded CPython 2.7mmacOS 10.7+ x86-64

File details

Details for the file vpython-7.0.1.tar.gz.

File metadata

  • Download URL: vpython-7.0.1.tar.gz
  • Upload date:
  • Size: 2.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for vpython-7.0.1.tar.gz
Algorithm Hash digest
SHA256 896cc5c3bc4c1221f70d607ad99870d4247828f512a4320b56de5f46f070c29f
MD5 f3c12bdbf15a2322e380adc57890dfe5
BLAKE2b-256 103a3f90a6471805c51e1243c6b7d71c05139fa3fc21a3aaf5df467162cb9b85

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 6c9e5803e781aa36e5a6612915cf6a3ddec6671088f75dbcdc28852a7ffbf554
MD5 31ed86462aa83e52b776f6fa1b6f164b
BLAKE2b-256 67bdc69e730eb06e91621b3c1eb29f3cb98094827f13c96bc8ed6a62d4960e9b

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp36-cp36m-win32.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 38b466b525d36f9323ce1f0ae02340ad608e395a7d1ec71a2cb892f7e5382784
MD5 98c261402752179291db423b19221ee3
BLAKE2b-256 3764406428d9df717e50fb36c43bcd9c0fca596667bb34464a53d358df4d4a1d

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp36-cp36m-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp36-cp36m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 074687bd68517c14873e1ca25b8b480f1fdf48adf9ef962dd16932382d5f393b
MD5 29b6a325d544910404cb884492c59967
BLAKE2b-256 a4ebcdb4e40778ad0f39399f434759f3e5777cab7ccbb0cb1c39e2812a0ed2fe

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp35-cp35m-win_amd64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 a8ecb8032b1cb00429b49975402475dffbd4367f502725f78cdd4a161709bc87
MD5 756f6bfc6384c160bd11efc1cdcb2cad
BLAKE2b-256 f3374f2affdb7d243b24a942242613f07a19749c46ec2bbd2e6da28b3806ce10

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp35-cp35m-win32.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp35-cp35m-win32.whl
Algorithm Hash digest
SHA256 44913ef553e6f31bcefc021c5d73920dc4a0f52d1a33d90e8fce66b369b1b16f
MD5 c8ba986acf2d329a519eb8036d0ab784
BLAKE2b-256 4104af9b31755767bd4c59fa97e385c8c16ca80f7f5f6ae36b37c261c5b1dce2

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp35-cp35m-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp35-cp35m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 acbc1c98c855d111bc9669bc316fa2fe7367d4d0f1883bef6bfeeaef12aba9a1
MD5 16e1b032dd17f18c58194456c7d7e55f
BLAKE2b-256 e8f3c3dd591d0dd71c5d4688f40f7f8e944c91f145c3f83db7780468cb767214

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp34-cp34m-win_amd64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp34-cp34m-win_amd64.whl
Algorithm Hash digest
SHA256 d5b0ac2b570176629ff62dfbf78a59f1a98eaf368b1a99ec26be2a7e7daa28e5
MD5 8d1bef015e94137b61302210a165853d
BLAKE2b-256 f315814455faad3ccf60bae58de5bcacc773edf4d5394f7e9a1ce422bae761af

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp34-cp34m-win32.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp34-cp34m-win32.whl
Algorithm Hash digest
SHA256 17cb2f235119aac728df6decc5cc9d3e8a128ee4ce346a9b00d01cbe09f0a290
MD5 bf1227b7d614ce9fe71c41d76723b1b0
BLAKE2b-256 b698884a80eca9cc884711d017719aab11dc971d6e1bea21d35ebdd69c9ee04e

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp34-cp34m-macosx_10_6_x86_64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp34-cp34m-macosx_10_6_x86_64.whl
Algorithm Hash digest
SHA256 88ed9da349d9ff96732a6ac70742d668b61d37b1af87160f650e139494cb6e83
MD5 418fdb3ba6638558bdd8b2a1031b91f9
BLAKE2b-256 0498ba313236b185326269b1278465850506427d57749ef01451f4ead10802b2

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp27-cp27m-win_amd64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 42ae1fedc1b30478174092cf2b299cb7155a7c89d2da7878ae01d4d35869e0aa
MD5 712f816f15d8d3652909b41d9fb0cd70
BLAKE2b-256 e1d1dfc3989b2884f0e7725dd390dbc2df0ba108962c46d1fbbb34bf69579b9a

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp27-cp27m-win32.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 41d016251d0754de45ac8132e0bf726e42d9b49fce0318d077dc6a99a7e528f3
MD5 7bfc1c3adf32eca474e1121469feb185
BLAKE2b-256 aaa155160455bb6f491dccd67b748c8a2dccd82d94c303fb4e54130f7fb204c9

See more details on using hashes here.

File details

Details for the file vpython-7.0.1-cp27-cp27m-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for vpython-7.0.1-cp27-cp27m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 0816774eafe082a9ab32492ff312ccaa4afc535e2f1e840fb266f4b7b2842827
MD5 791ab9f35e62c600685e6b3c43ce1a9f
BLAKE2b-256 c635f8b8878d551f9bd95b1b985cfd426413e22064f2983210c5e12892836389

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