Chat text cleaning library (slang → meaningful text)
Project description
BlobChat
A lightweight Python library for transforming raw chat text into structured, meaningful data.
BlobChat helps you clean, analyze, and convert chat conversations (like WhatsApp, Messenger, etc.) into useful insights — similar to how pandas works with tabular data.
🚀 Features
-
🧹 Clean and normalize chat text
-
🔥 Remove emojis and unwanted symbols
-
📊 Word count and basic text analysis
-
🧠 Simple, chainable API (like pandas)
-
⚡ Lightweight and easy to use
📦 Installation
pip install blobchat
⚠️ Currently under development. For latest version:
git clone https://github.com/p4prince2/blobchat.git
cd blobchat
pip install -e .
🧪 Quick Example
from blobchat import Chat
chat = Chat("Hello BRO!!! 😄🔥 How are you?")
chat.clean().remove_symbols()
print(chat.text)
print(chat.word_count())
Output:
hello bro how are you
5
🧠 Planned Features
-
📂 Read chat files (WhatsApp, etc.)
-
👥 Detect users and messages
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📅 Extract timestamps
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📊 Convert chats to DataFrame
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📈 Analytics (top users, word frequency, etc.)
-
😊 Sentiment analysis
🏗️ Project Structure
blobchat/
├── src/blobchat/
│ ├── __init__.py
│ └── core.py
├── tests/
├── README.md
├── pyproject.toml
🧑💻 Development
Clone the repo and install in editable mode:
git clone https://github.com/p4prince2/blobchat.git
cd blobchat
pip install -e .
Run tests:
pytest
🤝 Contributing
Contributions are welcome!
Feel free to open issues or submit pull requests.
📄 License
MIT License
👨💻 Author
Prince Kushwaha
GitHub: https://github.com/p4prince2
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