screencast-narrator 0.1.2

Turn raw screen recordings + narration text into polished narrated screencasts

screencast-narrator

Turn raw screen recordings + narration text into polished narrated screencasts.

screencast-narrator is a Python library and CLI that takes a Playwright (or any) screen recording together with timestamped narration text and produces a final video with:

• Text-to-speech narration synced to on-screen actions
• QR-code-based frame-accurate synchronization
• Automatic freeze-frame insertion when narration overflows action duration
• Dead-air gap detection and cutting
• Interactive HTML timeline visualizations

Installation

pip install screencast-narrator

For TTS support (Kokoro):

pip install screencast-narrator[tts]

System dependencies:

# macOS
brew install ffmpeg zbar

# Ubuntu/Debian
apt-get install ffmpeg libzbar0

# Windows
winget install GyanDev.FFmpeg
# The pyzbar Python package ships its own libzbar DLL but needs the Visual C++ 2013 runtime:
winget install Microsoft.VCRedist.2013.x64
# Or download manually from https://aka.ms/highdpimfc2013x64enu

Quick Start

As a library with Playwright

from pathlib import Path
from playwright.sync_api import sync_playwright
from screencast_narrator.timeline import ScreencastTimeline
from screencast_narrator.sync_frames import inject_sync_frame
from screencast_narrator.merge import process

output_dir = Path("my-screencast")
output_dir.mkdir(exist_ok=True)

timeline = ScreencastTimeline(output_dir, video_enabled=True)

with sync_playwright() as p:
    browser = p.chromium.launch()
    context = browser.new_context(
        record_video_dir=str(output_dir / "videos"),
        record_video_size={"width": 1920, "height": 1080},
    )
    page = context.new_page()
    timeline.video_recording_started()

    # Narration bracket with sync frames
    timeline.begin_narration_bracket()
    inject_sync_frame(page, timeline.active_narration_id(), "START")

    page.goto("https://example.com")
    timeline.add_action("Navigate to example.com")

    inject_sync_frame(page, timeline.active_narration_id(), "END")
    timeline.add_narration("We open the example website.", start_ms=0, end_ms=2000)
    timeline.end_narration_bracket()

    timeline.video_recording_ended()
    context.close()
    browser.close()

# Produce the final narrated video
process(output_dir)

As a CLI

screencast-narrator /path/to/recording-output/

The directory must contain:

• A timeline.json file (produced by ScreencastTimeline)
• A video file (.webm) in a videos/ subdirectory

Architecture

The pipeline has these stages:

1. Timeline recording (timeline.py) — During your test/recording, track narrations, actions, highlights, and sync frames with timestamps.

2. Sync frame injection (sync_frames.py) — Inject green QR-code overlay frames into the browser at narration bracket boundaries for frame-accurate sync.

3. TTS generation (tts.py) — Convert narration text to speech audio files. Pluggable backend; ships with Kokoro TTS.

4. Sync detection (sync_detect.py) — Extract frames from the recorded video, detect green sync frames, decode QR codes to map video frames to narration events.

5. Freeze frame calculation (freeze_frames.py) — When narration audio is longer than the on-screen action, calculate where to insert freeze frames (paused video) so audio and video stay in sync. Avoids placing freezes during visual highlights.

6. Video merge (merge.py) — Orchestrate FFmpeg to build the final video: insert freeze frames, overlay audio, cut dead air gaps, concatenate segments.

7. Timeline visualization (timeline_html.py) — Generate interactive HTML timelines showing original events, adjusted (post-freeze) positions, and a combined three-column view.

Modules

Module	Purpose
timeline.py	Event recording during screen capture
sync_frames.py	QR code overlay injection for frame-accurate sync
sync_detect.py	Green frame detection and QR decoding from video
freeze_frames.py	Freeze frame calculation algorithm
tts.py	Pluggable TTS backend (Kokoro default)
ffmpeg.py	FFmpeg subprocess helpers
merge.py	Main merge pipeline and CLI entry point
timeline_html.py	HTML timeline visualization generator

Custom TTS Backend

Implement the TTSBackend protocol:

from screencast_narrator.tts import TTSBackend
from pathlib import Path

class MyTTS(TTSBackend):
    def generate(self, text: str, output_path: Path) -> None:
        # Generate audio file at output_path
        ...

# Use it
from screencast_narrator.merge import process
process(target_dir, tts_backend=MyTTS())

Development

git clone https://github.com/mmarinschek/screencast-narrator.git
cd screencast-narrator
pip install -e ".[dev,tts]"

# Run tests
pytest tests/ -v

# On macOS, if pyzbar can't find libzbar:
DYLD_LIBRARY_PATH=/opt/homebrew/lib pytest tests/ -v

License

Apache License 2.0 — see LICENSE.