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Description:

jupytermanim 1.3

Integrates manim (animation engine
for explanatory math videos) with Jupyter displaying the resulting video
when using %%manim cell magic to wrap a scene definition.

Quick preview
The code in the example above comes from the excellent manim
tutorial.
Run a live demo in your browser by clicking
here.

Installation
pip3 install jupyter-manim

Usage
To enable the manim magic please run import jupyter_manim first.
Then, you can use the magic as if it was the manim command: your
arguments will be passed to manim, exactly as if these were command line
options.
For example, to render scene defined with class Shapes(Scene) use
%%manim Shapes
from manimlib.scene.scene import Scene
from manimlib.mobject.geometry import Circle
from manimlib.animation.creation import ShowCreation

class Shapes(Scene):

def construct(self):
circle = Circle()
self.play(ShowCreation(circle))
Since version 1.0, the code is no longer required to be self-contained -
jupyter_manim will attempt to export your variables (and imported
objects) from the notebook into the manim script.
Most variables can be easily exported, however there are limitations; in
short everything which can be
pickled
can be exported. Additionally, variables whose names start with an
underscore will be ommited.
To display manim help and options use:
%%manim -h
pass
The %%manim magic (by default) hides the progress bars as well as
other logging messages generated by manim. You can disable this
behaviour using --verbose flag
In the latest version of manimlib you can import everything at once
using:
from manimlib.imports import *

Video player control options

--no-controls - hides the controls
--no-autoplay - disables the autoplay feature
-r or --resolution - control the height and width of the
video player; this option is shared with manim and requires the
resolution in following format: height,width,
e.g. %%manim Shapes -r 200,1000
--base64 send the video with a data: URL instead of a local
path - useful for remote notebooks like Google Colab, or to embed the
video in notebook (note: the notebook size may increase rapidly)

Compatibility and testing
This package is continuously tested with Python 3.7 on Ubuntu, Mac OS an
Windows.
Tests have to be run with ipython, as the magic relies on IPython
instance being available:
python3 setup.py install
ipython -m pytest -- --cov=.