Python Library for Indian Stock Market Analysis 📈
| Documentation | Features | Quick Start |
Tickersnap provides streamlined access to comprehensive Indian stock market data from Tickertape IN, enabling powerful financial analysis, automated screening, and market sentiment tracking.
Important
- This library heavily relies on the (unofficial) public APIs from Tickertape IN.
- Using this library is same as using some of the public features of the Tickertape website or app (but in a pythonic way).
- I am not affiliated with Tickertape or any stock exchange or financial services in any way.
- Tickertape has been my go to platform, and I am grateful for the work they do and tools they provide to the community!
Warning
- All results from this library are for informational purposes only and should not be considered as financial advice.
- Always consult qualified financial advisors before making investment decisions – I am not a financial expert.
- I am an enthusiast, not a certified finance professional. Use your discretion and do your own research.
- Use this library at your own risk. I assume no responsibility for any financial losses or consequences arising from its use.
Caution
- This library is intended for personal, individual use only. It's not an official Tickertape product.
- Please ensure your usage adheres to tickertape's terms, privacy policy, and any other applicable rules to avoid violations.
- This project was created with genuine, honest intent for personal analysis and automation of manual efforts.
- I do not encourage or support any misuse of this library that breaches official Tickertape terms or causes harm.
🔗 Essential Tickertape Links: About | Info | Terms | Privacy | Disclosures | Guidelines
- 📊 Complete Market Coverage - Access 5,000+ stocks and 270+ ETFs from Indian exchanges
- 🎯 Stock Scorecard Analysis - 6-category evaluation (Performance, Valuation, Growth, Profitability, Entry Point, Red Flags)
- 📈 Market Mood Index (MMI) - Real-time sentiment tracking with Fear/Greed zones
- ⚡ High Performance - Concurrent processing with progress tracking for large datasets
- 🛡️ Robust & Reliable - Comprehensive error handling and extensive test coverage
- 🔧 Developer Friendly - Clean APIs with intuitive method names and comprehensive documentation
- Python 3.10+
pip install tickersnapfrom tickersnap.mmi import MarketMoodIndex
from tickersnap.stock import StockScorecard
from tickersnap.lists import Assets
# Check market sentiment
mmi = MarketMoodIndex()
mood = mmi.get_current_mmi()
print(f"Market Mood: {mood.value:.1f} ({mood.zone.value})")
# Analyze a stock
scorecard = StockScorecard()
analysis = scorecard.get_scorecard("TCS")
if analysis.performance:
print(f"TCS Performance: {analysis.performance.rating.value}")
# Get all stocks
assets = Assets()
all_stocks = assets.get_all_stocks()
print(f"Total stocks available: {len(all_stocks)}")👉 Complete Quick Start Guide - Learn with real examples!
| Module | Description | Use Case |
|---|---|---|
| 📋 Assets | Complete list of stocks & ETFs | Portfolio building, universe selection |
| 📊 Stock Scorecard | 6-category stock analysis | Investment screening, due diligence |
| 📈 Market Mood Index | Sentiment tracking (0-100 scale) | Market timing, contrarian investing |
👉 see documentation for more details! | MMI | Assets | Stocks |
- 📊 Stock Screeners - Find quality stocks automatically
- 📈 Portfolio Trackers - Monitor your investments daily
- 🎯 Market Alerts - Get notified of sentiment extremes
- 🔍 Research Tools - Comprehensive market analysis
- 🤖 Trading Bots - Automated analysis and signals
- 🧠 LLM Agents - Build agents to get live financial data
👉 see documentation, every module is filled with usage examples!
Licensed under the Apache License 2.0
Contributions are welcome!
(contribution guidelines are coming soon.)
Made with ❤️ for Fin Lovers in India