coursera-transcripts 0.1.0

CLI tool to extract Coursera course transcripts/subtitles

📚 Coursera Transcript Generator

A beautiful CLI tool to bulk-download transcripts and subtitles from any Coursera course you're enrolled in.

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✨ Features

• Interactive prompts — guided step-by-step experience, no need to memorize flags
• Bulk download — grabs every lecture transcript in a course at once
• Organized output — files are neatly sorted into module folders
• Progress tracking — real-time progress bar with download status
• Retry logic — automatic retries with exponential backoff on failures
• Multiple formats — supports both .txt (plain text) and .srt (subtitle) formats
• Multi-language — download transcripts in any available language

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📦 Installation

# Clone the repo
git clone https://github.com/your-username/coursera-transcript-generator.git
cd coursera-transcript-generator

# Install in editable mode
pip install -e .

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🚀 Usage

Interactive Mode (recommended)

Just run the command with no arguments — it will guide you through everything:

coursera-transcripts

You'll be prompted for:

1. CAUTH cookie — your Coursera authentication token
2. Course slug — the identifier from the course URL
3. Options — language, format, and output directory

CLI Mode

Pass everything as flags for scripting / automation:

coursera-transcripts \
  --cookie "YOUR_CAUTH_VALUE" \
  --slug "machine-learning" \
  --language en \
  --format txt \
  --output ./transcripts

All Options

Flag	Short	Default	Description
--cookie	-c	(prompted)	CAUTH cookie value
--slug	-s	(prompted)	Course slug from URL
--language	-l	en	Subtitle language code
--format		txt	Output format (txt or srt)
--output	-o	./output	Parent output directory

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🔑 Getting Your CAUTH Cookie

1. Open coursera.org and log in
2. Open DevTools (F12 or Ctrl+Shift+I)
3. Go to Application → Cookies → https://www.coursera.org
4. Find the cookie named CAUTH
5. Copy its Value

[!IMPORTANT] You must be enrolled in the course to download its transcripts.

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📁 Output Structure

Transcripts are organized by module:

output/
└── machine-learning/
    ├── introduction-to-ml/
    │   ├── Welcome to Machine Learning.txt
    │   ├── What is Machine Learning.txt
    │   └── Supervised Learning.txt
    ├── linear-regression/
    │   ├── Model Representation.txt
    │   └── Cost Function.txt
    └── ...

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🔧 Finding the Course Slug

The slug is the part of the URL after /learn/:

https://www.coursera.org/learn/machine-learning
                                └── this is the slug

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📋 Requirements

• Python 3.10+
• A Coursera account with enrollment in the target course

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📄 License

MIT