snippet-cast
Turn an annotated Python snippet into a narrated screencast video.
Narration is written as trailing #: comments on the snippet's own lines, so
the input stays valid, runnable Python:
def fib(n): #: We define fib, taking one argument, n.
a, b = 0, 1 #: Start from the first two Fibonacci numbers.
for _ in range(n): #: Loop n times.
a, b = b, a + b #: Advance the pair; b becomes the running sum.
return a #: Return a — the nth Fibonacci number.
Each #: line becomes one "beat": the code is revealed up to that line, the
line is highlighted, and its narration is spoken. snippet-cast renders
syntax-highlighted code frames with a progressive reveal, a Python-Tutor-style
live variable panel, optional burned-in captions and a typing-in animation,
synthesises speech per line, and stitches everything into an MP4 with ffmpeg.
Installation
Requires Python 3.10+ and ffmpeg (with ffprobe) on PATH.
pip install snippet-cast
# or
pixi add snippet-cast
# or
conda install -c munch-group snippet-cast
Usage
snippet-cast snippet.py -o out.mp4 --tts silent --subtitles # fast, voiceless proof
snippet-cast snippet.py -o out.mp4 --typing --subtitles # type each new line in
snippet-cast loop.py -o out.mp4 --every --subtitles # animate each loop iteration
Or from Python:
from snippet_cast import build
build("snippet.py", "out.mp4", tts="silent", subtitles=True)
Or in a Jupyter notebook — write the snippet directly in a cell instead of a
separate .py file:
pip install snippet-cast[jupyter]
%load_ext snippet_cast.magic
%%snippet-cast -o out.mp4 --tts silent --subtitles
def fib(n): #: We define fib, taking one argument, n.
a, b = 0, 1 #: Start from the first two Fibonacci numbers.
for _ in range(n): #: Loop n times.
a, b = b, a + b #: Advance the pair; b becomes the running sum.
return a #: Return a — the nth Fibonacci number.
result = fib(7) #: Call fib with seven; result becomes {result}.
The cell magic takes the same flags as the CLI and displays the rendered MP4 inline.
%%snippet-cast has to be the cell's first line — and so do Quarto's #|
directives, so they cannot share a cell. snippet_cast.video() is the same
notebook front end as a plain function call, taking the snippet as a string:
#| fig-column: margin
#| echo: false
from snippet_cast import video
video("""
def fib(n): #: We define fib, taking one argument, n.
a, b = 0, 1 #: Start from the first two Fibonacci numbers.
for _ in range(n): #: Loop n times.
a, b = b, a + b #: Advance the pair; b becomes the running sum.
return a #: Return a — the nth Fibonacci number.
result = fib(7) #: Call fib with seven; result becomes {result}.
""", tts="silent", subtitles=True)
Every parameter is the same-named flag (trace=False for --no-trace),
resolved the same way — argument, then SNIPPET_CAST_<NAME>, then the
default — and it returns the video to display, so leave it as the cell's last
expression. Don't make the snippet an f-string: {result} is snippet-cast's
own interpolation. Given no out/name/output_dir, the video goes to
.snippet-cast/<hash of the snippet>.mp4, so re-running an unchanged cell
reuses its file. build() above is the equivalent for a snippet that already
lives in its own .py file.
See SETUP.md for all TTS backends — the zero-setup say (macOS)
and manual (your own recordings, including --record for recording live
via the microphone) backends, plus configuring Piper (local) and ElevenLabs
(cloud) — and snippet-cast --help for all options.
Configuration
-o/--output sets an explicit path; without it, -n/--name (default
out) and -d/--output-dir (default .snippet-cast, created if missing)
build one as output-dir/name.mp4:
snippet-cast snippet.py --tts silent # -> ./.snippet-cast/out.mp4
snippet-cast snippet.py --tts silent -n intro # -> ./.snippet-cast/intro.mp4
snippet-cast snippet.py --tts silent -n intro -d ./videos # -> ./videos/intro.mp4
.snippet-cast/ is a hidden directory beside your work that ignores itself in
git, so renders don't scatter out.mp4 through your folder or your history.
%%snippet-cast cells write there too (under a name hashed from the cell), so
both front ends keep their videos in one place. -d . puts them back in the
current directory.
Every option (except -o/--output) also has a SNIPPET_CAST_<NAME>
environment variable default — an explicit flag always wins over its env
var:
import os
os.environ["SNIPPET_CAST_TTS"] = "say"
os.environ["SNIPPET_CAST_SUBTITLES"] = "1"
os.environ["SNIPPET_CAST_PAUSE"] = "0.6"
os.environ["SNIPPET_CAST_OUTPUT_DIR"] = "./videos"
set in one notebook cell, applies to every %%snippet-cast cell after it
(picked up fresh each time, so setting it in a later cell still works).
Runs are quiet by default — the per-beat progress and every note: need
-v/--verbose. A snippet that won't compile or raises part-way still
reports on stderr, as do errors. The other shipped defaults are --tts say
(macOS; pass --tts silent elsewhere) and --order exec, which highlights
each line on the way in and again on the way out, in the order Python visits
them; --order source gives the plain top-to-bottom playback.
Toggle flags (--every, --subtitles, --typing, --record,
--export-script) accept --no-X to override an env-var-forced default back
off for one run.
Development
This repository is built from the munch-group library template.
Initial set up
pixi run init
Get updates to upstream fork
Add upstream if not already added
git remote add upstream https://github.com/munch-group/snippet-cast.git
Fetch upstream changes
git fetch upstream
Either rebase your changes on top of upstream (cleaner history)
git rebase upstream/main
Or, merge upstream into your fork (preserves history)
git merge upstream/main
If you want to see what's changed upstream before applying:
git log HEAD..upstream/main
See the actual diff
git diff HEAD...upstream/main
Then push your updated fork:
git push origin main
If you rebased and need to force push
git push origin main --force-with-lease
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