tubelearns 1.1.1

Python script for extracting and cleaning YouTube video transcripts for Pre-Processing in machine learning.

Tube-Data: YouTube Video Transcript Extractor

Tube-Data is a Python script designed for extracting and cleaning YouTube video transcripts for preprocessing in machine learning. This versatile tool streamlines the process of acquiring high-quality text data from YouTube videos, making it ideal for various natural language processing tasks, sentiment analysis, speech recognition, and more.

Features

• Extracts video transcripts from YouTube videos.
• Cleans transcripts by removing unwanted elements like music and applause.
• Saves cleaned transcripts into separate text files.
• Supports individual video URLs, batch processing from a list of URLs, and entire playlists.
• Streamlines the dataset collection process for machine learning applications.

Installation

You can install the required dependencies using pip:

pip install tubelearns

Usage

Extract Transcripts from a List of Video URLs

from tubelearns import text_link

# Provide a path to a text file containing YouTube video URLs.
text_link('path_to_file.txt', name='output_folder_name')

Extract Transcript from a Single Video URL

from tubelearns import url_grab

# Provide a single YouTube video URL.
url_grab('video_url', name='output_folder_name')

Extract Transcripts from a YouTube Playlist

from tubelearns import playlist_grab

# Provide the URL of a YouTube playlist.
playlist_grab('playlist_url', name='output_folder_name')

Convert Playlist Video Links to Text File

from tubelearns import play2text

# Provide the URL of a YouTube playlist.
play2text('playlist_url')

Development Status

This project is currently in the planning stage.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contributions

Contributions are welcome! Please feel free to open issues or submit pull requests.

Contact

For any inquiries or feedback, please contact KabilPreethamK.