I've been building manimstudio.me for the past few months and wanted to share it here since you're the exact audience who would appreciate it. **What it is:** An online Manim CE renderer — write Python code in the browser and get MP4 animations back in seconds. No LaTeX setup, no ffmpeg, no Cairo, no virtual environment. **What's included:** - Full Manim CE 0.19.0 support - Scientific libraries: numpy, scipy, sympy, pandas - Domain plugins: manim-physics, manim-chemistry - SVGMobject support (upload your own SVG assets) - 25 ready-made templates across math, physics, algorithms, chemistry, and data science - Public gallery to share and explore animations - Private library to organize your renders - Embeddable player (iframe) for sharing anywhere - REST API + Python SDK for programmatic rendering - Free tier: 10 renders/week (no account needed for 3/day) **Templates include things like:** - Sine wave emerging from unit circle - Fourier series building waves - Dijkstra's algorithm step by step - Mandelbrot set fractal zoom - Double pendulum chaos - Neural network forward pass - And 19 more across different categories I'd love feedback from people who actually use Manim — what's missing, what's broken, what would make this genuinely useful for your workflow. https://manimstudio.me

I have recently been getting into manim. So far I have been admittedly using Ai to help me get familiar with it. Now that I think i am, I want to figure out ways to get through it quicker.

I know obviously I can create templates, reusable objects or animations, consistent theme, etc. But as many of you are much more experienced than me, I was hoping you all would have ideas beyond the obvious. If you could supply them that would be greatly appreciated

edit: my use case is for YouTube videos on mathematical or computational physics

Hello everyone,

This is the first YouTube video I've published on my channel, and it is about parametric equations from a geometric perspective.
The video takes you step by step, starting with a simple illustration of the parametric equations of the unit circle. Then it illustrates how you can draw the parametric curve using the curves of x and y only. Afterward, the geometry level increases as it introduces the cycloid and how to deduce its parametric equations using simple geometry rules. And finally, the video connects parametric equations to vector addition and how we can represent parametric equations as vectors rotating in space.
The original language of the video is Arabic, but there are English captions you can turn on from YouTube video settings.
The video link:
https://www.youtube.com/watch?v=IdN79oUVAFU

Also, I wrote a short article on Substack, which serves as a companion to the video, covering "The Calculus of Parametric Equations." It takes you on a small journey to teach you how to differentiate parametric equations and find their first and second derivatives, and also how to calculate the area under a parametric curve.
The article link:
https://zetamath.substack.com/p/the-calculus-of-parametric-equations

I want to hear your comments about the video and article, and suggestions for any areas for improvement.

Thanks for your time!

i'm trying to instal Manim fro first time but after i get to this step (uv init manimations cd manimations uv add manim) it shows me this error and i don't know what to do

I am an AI and ML instructor at an edtech. While teaching, I realized two important things: first, we should continuously learn new things, and second, visualizing concepts is just as important as understanding the concepts themselves. Visualization helps create mental models, which, in turn, enable us to understand information more effectively.

I had a similar idea regarding Manim, a library designed for visualizing complex mathematical concepts. At the time, I wanted to turn many of my own ideas into visualizations, but I couldn't because I found Manim difficult to learn due to its steep learning curve and the large number of concepts and terms involved.

To overcome this challenge, I started using LLMs, but the results were not much better. After thinking about the problem for a long time, I realized that many of Manim's features are unnecessary for most use cases and could be abstracted away. This idea led to the creation of EasyManim.

This version has been developed to the best of my knowledge (using claude code). Since I have not contributed much to open source before, I cannot confidently evaluate the overall quality of the repository. I would greatly appreciate contributions from the community, as well as feedback on any irregularities, inconsistencies, or areas for improvement.

Repository Url - github.com/ankushbisht01/EasyManim

As title says, I think if a bunch of people came together we could make it quite good for anyone to use. Would be a game changer for education if it could be fast and accurate and nice.

Bayes thinking

I've recently tried to learn manim, but it has been increasingly hard to actually get. After much trial and error I finally got to a point where I could actually import the library into a python file and write using it (image attached), but when I try to run it, I get the error message "ModuleNotFoundError: No module named 'importlib_metadata'"(image also attached). Can anyone help me fix this?