# jwkvam/celluloid

:movie_camera: Matplotlib animations made easy

Repository: https://github.com/jwkvam/celluloid
Canonical: https://ross.abutalabs.com/products/jwkvam-celluloid
Language: Python
License: MIT
License Family: permissive
Topics: matplotlib, animation, matplotlib-animation
Last push: 2024-02-16T17:12:46+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2846, "days_push": 929, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1139, forks 42 (observed 2026-08-28T04:03:44.186103+00:00)

## What it is
A tiny Python library that simplifies creating Matplotlib animations by wrapping a figure in a Camera object that snapshots each frame. It adapts existing plotting code into animations with minimal changes and works well in Jupyter notebooks.

## Use cases
- animate matplotlib plots
- create animation from existing plotting code
- make animated gif or mp4 of plots
- animate subplots in matplotlib
- show plot animations in jupyter notebook
- animate image frames with matplotlib

## When to choose
- you already have matplotlib plotting code and want to animate it with minimal changes
- you want a simpler API than matplotlib.animation.FuncAnimation
- you work in Jupyter notebooks and want inline video output

## When to avoid
- you need fine-grained control over animation timing or blitting
- you need interactive or real-time animations
- you use plotting libraries other than matplotlib

## Facets
- artifact type: library
- maturity: maintenance
- function: animation, data-visualization
- domain: data-visualization, data-science
- platform: python
- tags: matplotlib, camera-snapshot, jupyter

## Member repositories
- jwkvam/celluloid (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:44.186103+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:35:52.662880+00:00, confidence not recorded.
  - readme: https://github.com/jwkvam/celluloid (fetched 2026-08-28T04:03:44.186103+00:00, sha 0dd6219245ac)
  - registry_pypi: https://pypi.org/pypi/celluloid/json (fetched 2026-08-29T12:40:58.685631+00:00, sha bd2928d23863)
- Data as of 2026-08-30T08:39:29.467469+00:00.