git clone 3b1b-manim_-_2019-04-21_21-27-58.bundle -b master
Manim is an animation engine for explanatory math videos. It's used to create precise animations programmatically.
shgit clone https://github.com/3b1b/manim.gitcd manimpython3 -m pip install -r requirements.txtpython3 -m manim example_scenes.py SquareToCircle -pl
pycairo‑1.18.0‑cp37‑cp37m‑win32.whlwill do fine.
shpip3 install C:\path\to\wheel\pycairo‑1.18.0‑cp37‑cp37m‑win32.whl
Install a LaTeX distibution. MiKTeX is recommended.
Install the remaining Python packages. Make sure that
pycairo==1.17.1 is changed to
pycairo==1.18.0 in requirements.txt.
shgit clone https://github.com/3b1b/manim.gitcd manimpip3 install -r requirements.txtpython3 manim.py example_scenes.py SquareToCircle -pl
shgit clone https://github.com/3b1b/manim.gitmkvirtualenv -a manim -r requirements.txt manimpython3 -m manim example_scenes.py SquareToCircle -pl
Since it's a bit tricky to get all the dependencies set up just right, there is a Dockerfile and Compose file provided in this repo as well as a premade image on Docker Hub. The Dockerfile contains instructions on how to build a manim image, while the Compose file contains instructions on how to run the image.
The image does not contain a copy of the repo. This is intentional, as it allows you to either bind mount a repo that you've cloned locally or clone any fork/branch you want. In order to do this with the Compose file, you must set the
MANIM_PATH environment variable to the absolute path to the manim repo.
shMANIM_PATH=/absolute/path/to/manim/repo docker-compose run manim example_scenes.py SquareToCircle -lThe first time you execute the above command, Docker will pull the image from Docker Hub and cache it. Any subsequent runs until the image is evicted will use the cached image.Note that the image doesn't have any development tools installed and can't preview animations. Its purpose is building and testing only.
Try running the following:
shpython3 -m manim example_scenes.py SquareToCircle -plThe -p is for previewing, meaning the video file will automatically open when it is done rendering.Use -l for a faster rendering at a lower quality.Use -s to skip to the end and just show the final frame.Use -n (number) to skip ahead to the n'th animation of a scene.Use -f to show the file in finder (for osx)
Set MEDIA_DIR environment variable to determine where image and animation files will be written.
Look through the oldprojects folder to see the code for previous 3b1b videos. Note, however, that developments are often made to the library without considering backwards compatibility on those oldprojects. To run them with a guarantee that they will work, you will have to go back to the commit which complete that project.
While developing a scene, the
-sp flags are helpful to just see what things look like at the end without having to generate the full animation. It can also be helpful to use the
-n flag to skip over some number of animations.
Documentation is in progress at manim.readthedocs.io.
Todd Zimmerman put together a tutorial on getting started with manim, which has been updated to run on python 3.7.
To live stream your animations, simply run manim with the
python -m manim --livestream Writing to media/videos/scene/scene/1080p30/LiveStreamTemp.mp4
Manim is now running in streaming mode. Stream animations by passingthem to manim.play(), e.g.
c = Circle() manim.play(ShowCreation(c))
It is also possible to stream directly to Twitch. To do that simply pass--livestream and --to-twitch to manim and specify the stream key with--with-key. Then when you follow the above example the stream will directlystart on your Twitch channel (with no audio support).
Is always welcome. In particular, there is a dire need for tests and documentation.
All files in the directories activeprojects and oldprojects, which by and large generate the visuals for 3b1b videos, are copyright 3Blue1Brown.
The general purpose animation code found in the remainder of the repository, on the other hand, is under the MIT license.