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Beginner

Using yfinance and NSEpy to Pull Indian Market Data

A hands-on guide to pulling real Indian market data with Python. Covers yfinance for NSE and BSE tickers (historical OHLCV, adjusted close, corporate actions) and NSEpy for NSE-specific data that yfinance doesn't cover, including F&O and delivery percentage. Built for engineering graduates, coders, and systematizing traders who want a working data pipeline, not just theory, with every example run against real Nifty 50 and F&O tickers.

MODULES

3

DURATION

4 Hours

TRACK

Python for Finance

Access Level

LEARNER

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Full Text Playbooks

Actionable Exercises

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Curriculum Breakdown

Chapter 1: Getting Set Up

3 Lessons

Why Python for Indian Market Data: yfinance, NSEpy, and Paid APIs Compared8 min read

Setting Up Your Environment: Python, pip, and a Clean Virtualenv7 min read

Your First Pull: NIFTY 50 Daily OHLC with yfinance9 min read

Chapter 2: yfinance for Indian Tickers

3 Lessons

NSE and BSE Ticker Conventions in yfinance: .NS, .BO, and Common Pitfalls9 min read

Historical OHLCV, Adjusted Close, and Corporate Actions10 min read

Bulk-Fetching a Watchlist: The Nifty 50 Without Getting Rate-Limited10 min read

Chapter 3: NSEpy for NSE-Specific Data

3 Lessons

What NSEpy Gives You That yfinance Doesn't: F&O, Index, and Delivery Data9 min read

Pulling Options Chain and Futures Data with NSEpy11 min read

Handling NSEpy's Reliability Quirks: Endpoint Changes, Retries, and Fallbacks10 min read