stock-recognizer 0.1.1

High-precision stock ticker and company recognition for social media.

Stock Recognizer 📈

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Introduction

A lightweight, hybrid Python library for extracting stock tickers and company names from messy social media text (Reddit, Twitter, etc.).

Table of Contents 🗂

• Key Features
• Installation
• Usage
• Citation
• Contributing
• License

Key Features 🔑

• Hybrid Engine: Combines Regex, financedatabase (Market Data), and GLiNER2 (AI).
• Context Aware: Distinguishes between "DD" (Due Diligence) and "DD" (DuPont).
• Yelling Protection: Smart filters for posts written in ALL CAPS.
• Auto-Mapping: Automatically converts "Apple" or "TSMC" to AAPL and TSM.

Installation ⚙️

Installation can be done via pip:

pip install stock-recognizer

Usage ⌨️

from stock_recognizer import StockRecognizer

# Initialize (Market Data only for speed)
recognizer = StockRecognizer(use_ai=False)

text = "$PLAB DD: easy to understand TSMC supplier"
tickers = recognizer.recognize(text)
print(tickers) # ['PLAB'] (TSMC needs AI mapping)

# Initialize with AI for deep extraction
recognizer_ai = StockRecognizer(use_ai=True)
tickers_ai = recognizer_ai.recognize_ai(text)
print(tickers_ai) # ['PLAB', 'TSM']

Citation ✍️

If you use this project in your research, please cite as follows:

@misc{project_name,
  author  = {Stephan Akkerman},
  title   = {Stock Recognizer},
  year    = {2026},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/StephanAkkerman/stock-recognizer}}
}

Contributing 🛠

Contributions are welcome! If you have a feature request, bug report, or proposal for code refactoring, please feel free to open an issue on GitHub. We appreciate your help in improving this project.

License 📜

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