## TubeLearns: YouTube Video Transcript Extractor
TubeLearns 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.
- 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.
- New Feature: Tokenization and Punctuation Removal for text preprocessing and cleaning.
## Installation
You can install TubeLearns using pip:
```bash
pip install tubelearns
```
## Usage
### Playlist Grabbing
```python
from tubelearns import Acquisition
# Initialize the Acquisition class
model = Acquisition()
# Grab transcripts from a YouTube playlist
playlist_url = 'https://www.youtube.com/your_playlist_url'
model.PlaylistGrab(playlist_url, name="raw_data")
```
### Extract Video Links from Playlist
```python
# Extract video links from a YouTube playlist
playlist_url = 'https://www.youtube.com/your_playlist_url'
model.Play2Text(playlist_url)
```
### Tokenization and Cleaning
```python
from tubelearns.tokenizers import Tokenization, Cleaning
# Initialize the Tokenization class
tokenizer = Tokenization()
cleaner = Cleaning()
# Tokenize text data
text_data = "Your input text here."
tokenized_data = tokenizer.TokenizeRaw(text_data)
cleaned_data = tokenizer.PunctList(tokenized_data)
```
Refer to the [TubeLearns documentation](https://github.com/KabilPreethamK/tubelearns/blob/main/Documentation.md) for detailed usage instructions and examples.
## Contributing
If you'd like to contribute to TubeLearns or report issues, please check out the [GitHub repository](https://github.com/KabilPreethamK/tubelearns).
## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.
## Acknowledgments
- [YouTube Transcript API](https://github.com/jdepoix/youtube-transcript-api)
- [PyTube](https://github.com/pytube/pytube)
- [spaCy](https://spacy.io/)
- [num2words](https://github.com/savoirfairelinux/num2words)
---
Enjoy using TubeLearns! If you have any questions or encounter issues, please don't hesitate to [get in touch](mailto:tubelearnsofficial@gmail.com).
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"description": "\n\n## TubeLearns: YouTube Video Transcript Extractor\n\nTubeLearns 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.\n\n## Features\n\n- Extracts video transcripts from YouTube videos.\n- Saves cleaned transcripts into separate text files.\n- Supports individual video URLs, batch processing from a list of URLs, and entire playlists.\n- Streamlines the dataset collection process for machine learning applications.\n- New Feature: Tokenization and Punctuation Removal for text preprocessing and cleaning.\n\n## Installation\n\nYou can install TubeLearns using pip:\n\n```bash\npip install tubelearns\n```\n\n## Usage\n\n### Playlist Grabbing\n\n```python\nfrom tubelearns import Acquisition\n\n# Initialize the Acquisition class\nmodel = Acquisition()\n\n# Grab transcripts from a YouTube playlist\nplaylist_url = 'https://www.youtube.com/your_playlist_url'\nmodel.PlaylistGrab(playlist_url, name=\"raw_data\")\n```\n\n### Extract Video Links from Playlist\n\n```python\n# Extract video links from a YouTube playlist\nplaylist_url = 'https://www.youtube.com/your_playlist_url'\nmodel.Play2Text(playlist_url)\n```\n\n### Tokenization and Cleaning\n\n```python\nfrom tubelearns.tokenizers import Tokenization, Cleaning\n\n# Initialize the Tokenization class\ntokenizer = Tokenization()\ncleaner = Cleaning()\n\n# Tokenize text data\ntext_data = \"Your input text here.\"\ntokenized_data = tokenizer.TokenizeRaw(text_data)\ncleaned_data = tokenizer.PunctList(tokenized_data)\n```\n\nRefer to the [TubeLearns documentation](https://github.com/KabilPreethamK/tubelearns/blob/main/Documentation.md) for detailed usage instructions and examples.\n\n## Contributing\n\nIf you'd like to contribute to TubeLearns or report issues, please check out the [GitHub repository](https://github.com/KabilPreethamK/tubelearns).\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.\n\n## Acknowledgments\n\n- [YouTube Transcript API](https://github.com/jdepoix/youtube-transcript-api)\n- [PyTube](https://github.com/pytube/pytube)\n- [spaCy](https://spacy.io/)\n- [num2words](https://github.com/savoirfairelinux/num2words)\n\n---\n\n\nEnjoy using TubeLearns! If you have any questions or encounter issues, please don't hesitate to [get in touch](mailto:tubelearnsofficial@gmail.com).\n\n\n\n",
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