Pycoding

final_tutorial.mp4

Automated Coding Tutorial Generation with Audio Narration

Pycoding is an agentic Python library designed to generate fully automated, natural-looking coding tutorials with real-time or post-processed audio narration. It combines AI-powered code generation, screen recording, and voice synthesis to create engaging programming tutorials.

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Key Features

• AI-Powered Code Generation: Uses Google's Generative AI to create relevant code examples
• Natural Voice Narration: Integrates with ElevenLabs for high-quality voice synthesis
• Real-Time Screen Recording: Captures live coding demonstrations
• Multi-Language Support: Works with multiple programming languages
• Flexible Narration Modes: Supports both real-time and post-processed narration
• Title Slide Generation: Optional title slides for each code segment
• Automated Window Management: Handles Jupyter console and matplotlib windows automatically
• Flowchart Visualizations: Optional flowchart visualizations for code logic

Supported Languages

Pycoding supports generating tutorials in the following programming languages:

• Python (python3)
• C/C++ (xcpp17)
• Julia (julia)
• Rust (rust)
• Bash (bash)
• R (r)

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Prerequisites

Before installing Pycoding, ensure you have the following:

System Requirements

• Linux operating system (currently Linux-only)
• ffmpeg for audio/video processing
• wmctrl and xwininfo for window management
• gnome-terminal for terminal emulation
• Jupyter installation with required language kernels
• graphviz for flowchart generation

API Requirements

• Google Generative AI API key
• ElevenLabs API key and voice ID

Python Dependencies

Core dependencies include:

ffmpeg-python
google-generativeai
pydub
simpleaudio
pyautogui
pynput
rich 
elevenlabs
jupyter
ipython
pycaw
comtypes
pygetwindow
moviepy
opencv-python

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Installation

1. Clone the Repository

git clone https://github.com/your-repo/pycoding.git
cd pycoding

2. Install Dependencies

python3 -m pip install -r requirements.txt

3. Install System Dependencies

# For Ubuntu/Debian
sudo apt-get install ffmpeg graphviz

# For Fedora
sudo dnf install ffmpeg graphviz

# For Arch Linux
sudo pacman -S ffmpeg graphviz

4. Install the Library

python3 -m pip install .

4. Configure Jupyter Kernels See README_kernels.md for detailed instructions on setting up language kernels.

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Usage

Command Line Interface

Generate a coding tutorial using the command line:

python3 -m pycoding \
    --topic "Your Tutorial Topic" \
    --google-api-key YOUR_GOOGLE_API_KEY \
    --elevenlabs-api-key YOUR_ELEVENLABS_API_KEY \
    --elevenlabs-voice-id YOUR_ELEVENLABS_VOICE_ID \
    --narration-type parallel \
    --language python3 \
    --force-approve \
    --add-titles \
    --add-flowchart \
    --io-path /path/to/example/code

Python API

from pycoding import CodingTutorial, GoogleGenAI

# Initialize AI model
model = GoogleGenAI(google_api_key)

# Create tutorial
tutorial = CodingTutorial(
    topic="Your Tutorial Topic",
    eleven_labs_api_key="YOUR_ELEVENLABS_API_KEY",
    eleven_labs_voice_id="YOUR_ELEVENLABS_VOICE_ID",
    model_object=model,
    path_info=[],  # Optional paths for code context
    narration_type="parallel",  # or "after"
    language="python3",
    force_approve=False,  # Set to True to skip manual approvals
    add_titles=True,  # Add title slides
    add_flowchart=True,  # Add flowchart visualization
    io_path="/path/to/example/code"  # Specify paths for code generation context
)

# Generate the tutorial
tutorial.make_tutorial()

Command Line Options

Flag	Description
--topic	Tutorial topic
--google-api-key	Google Generative AI API key
--elevenlabs-api-key	ElevenLabs API key
--elevenlabs-voice-id	ElevenLabs voice ID
--io-path	Paths for code context (optional)
--narration-type	Narration mode: parallel or after
--language	Programming language
--force-approve	Skip manual approvals
--add-titles	Add title slides
--add-flowchart	Add flowchart visualization

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Output

The generated tutorial includes:

• Screen recording of code typing and execution
• AI-generated voice narration
• Optional title slides
• Optional flowchart visualizations
• Synchronized audio and video
• Output files in pycoding_data/ directory

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Examples

Basic Python Tutorial

python3 -m pycoding \
    --topic "Python List Comprehensions in 3 Examples" \
    --google-api-key YOUR_KEY \
    --elevenlabs-api-key YOUR_KEY \
    --elevenlabs-voice-id YOUR_ID \
    --language python3

C++ Tutorial with Titles and Flowchart

python3 -m pycoding \
    --topic "Understanding C++ Templates" \
    --google-api-key YOUR_KEY \
    --elevenlabs-api-key YOUR_KEY \
    --elevenlabs-voice-id YOUR_ID \
    --language xcpp17 \
    --add-titles \
    --add-flowchart

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Limitations

• Currently supports Linux environments only
• Requires specific window management utilities
• API keys needed for AI services
• Language kernels must be properly configured

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Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

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Author

Aadya Chinubhai