NSE Finance - Python Library for NSE India Data

A lightweight Python package to fetch commonly used market data from NSE India and shape it as pandas DataFrames for analysis and trading research.

✨ Features

• End‑of‑day (EOD) bhavcopy for equities & F&O
• Pre‑market snapshots (All, FO, NIFTY categories)
• Index details for multiple market lists (e.g., NIFTY 50, NIFTY AUTO)
• Option chain + optional Greeks computation
• Convenience lists: equities, F&O, ETFs
• FII/DII cash/derivatives activity
• Corporate actions & announcements, insider trades, upcoming results
• Most active (by value/volume, options & futures, OI, etc.)
• Historical data helpers for equities (and indices; see notes)

All functions are designed to return clean pandas.DataFrame objects (unless noted), ready for further transformation and visualization.

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📦 Installation

pip install nsefin

Requirements: Python 3.9+, pandas, requests (and optionally numpy).

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🚀 Quick Start

import datetime as dt
import pandas as pd
import nsefin

nse = nsefin.NSEClient()

# Example: EOD Equity Bhavcopy
bhav = nse.get_equity_bhav_copy(dt.datetime(2025, 8, 14))
print(bhav.head())

# Example: Pre‑market (All)
pm_all = nse.get_pre_market_info(category="All")

# Example: Index details (see available market lists below)
ix = nse.get_index_details(category="NIFTY 50")

# Example: Option Chain + Greeks for NIFTY
oc = nse.get_option_chain("NIFTY")
og = nse.compute_greek(oc, strike_diff=50)

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🔌 API Overview & Examples

1) EOD files

# Equity bhavcopy (EOD)
nse.get_equity_bhav_copy(dt.datetime(2025, 8, 14))

# F&O bhavcopy (EOD)
nse.get_fno_bhav_copy(dt.datetime(2025, 8, 14))

# Optional post‑processing
nse.format_fo_data(df)

Returns: DataFrames with symbol, series, OHLC, volume/turnover, OI (for F&O), etc.

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2) Pre‑Market data

nse.get_pre_market_info(category="All")
nse.get_pre_market_info(category="FO")
nse.get_pre_market_info(category="NIFTY")

Tip: Pre‑market snapshots are most useful before 9:15 IST and during early ticks.

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3) Market Lists & Index Details

# See all supported markets for index details
nse.endpoints.equity_market_list  # -> iterable of valid market names

# Fetch index details
nse.get_index_details(category="NIFTY 50")
nse.get_index_details(category="NIFTY AUTO")

Output: Index‑level stats (LTP, % change, PE/PB/DY, breadth, time‑window returns where available).

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4) Option Chain & Greeks

# Option chain for an index/stock (near‑dated by default; check function signature)
oc = nse.get_option_chain("NIFTY")

# Compute Greeks on a normalized OC DataFrame (requires columns like LTP, strike, etc.)
og = nse.compute_greek(oc, strike_diff=50)

Note: Greeks rely on implied vols/assumptions; read function docstring for parameters and expected columns.

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5) Universe Helpers

nse.get_equity_list()
nse.get_fno_list()
nse.get_etf_list()

Use cases: Screen eligible symbols, build watchlists, or validate tickers.

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6) FII/DII Activity

nse.get_fii_dii_activity()

Common usage: Market breadth and flows dashboard; daily net buy/sell across segments.

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7) Corporate Data

nse.get_corporate_actions()
nse.get_corporate_actions(subject_filter="dividend")  # filter examples: dividend, split, bonus
nse.get_corporate_announcements()
nse.get_insider_trading()
nse.get_upcoming_results()

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8) Most Active & Derivatives Scans

nse.get_most_active_by_volume()
nse.get_most_active_by_value()

nse.get_most_active_index_calls()
nse.get_most_active_index_puts()

nse.get_most_active_stock_calls()
nse.get_most_active_stock_puts()

nse.get_most_active_contracts_by_oi()
nse.get_most_active_contracts_by_volume()

nse.get_most_active_futures_by_volume()
nse.get_most_active_options_by_volume()

Great for: Intraday scanners, dispersion/volatility screens, liquidity checks for strategy filters.

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9) Historical Data

# Equities
nse.get_equity_historical_data("TCS", "15-08-2024", "31-12-2024")  # ~70 rows limit (API cap)

# Convenience wrapper (day_count based)
nse.history("TCS", day_count=200)

# Indices — currently not working (see Known Limitations below)
# nse.get_index_historical_data("NIFTY 50", "15-08-2024", "31-12-2024")

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⚠️ Known Limitations & Notes

• Index historical data: get_index_historical_data(...) is currently not working (NSE endpoints may have changed / rate‑limited). Use alternate data sources or your own cached series.
• 52‑week high/low: get_52_week_high_low() currently errors; pending fix.
• Daily row caps: NSE may cap history responses (e.g., ~70 rows). Prefer rolling downloads with local caching.
• Stability: NSE’s public endpoints can change without notice. Handle HTTP 301/403/429, add retry with backoff, and include a realistic User‑Agent header.
• Compliance: Respect NSE terms of use. This library is for educational/research purposes; not endorsed by or affiliated with NSE.

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🛠️ Troubleshooting

• Empty/blocked responses → rotate/retry with polite backoff; verify cookies and headers.
• Schema changes → use df.columns introspection and normalize keys defensively.
• Timezones → NSE trading hours are IST; align your schedulers & timestamps accordingly.
• Option Greeks → Ensure required columns (spot, strike, rate, expiry, iv) are present/derived before calling compute_greek.

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🗺️ Roadmap

• Stable index history with fallbacks
• Robust 52‑week high/low endpoint
• Built‑in caching & sqlite/duckdb persistence helpers
• Async client implementation
• Expanded Greeks/IV calculators + RND utilities

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🤝 Contributing

PRs and issues welcome! Please:

1. Open an issue describing the bug/feature with sample payloads.
2. Add tests where possible.
3. Follow standard formatting (black, ruff) and type hints.

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📄 License

MIT (or your preferred license). Update LICENSE accordingly.

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🙏 Acknowledgements

• NSE India public website and documentation.
• Community packages & references that inspired certain endpoints and data normalizations.

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