nseindiapy 0.1.0

Python client for NSE Indices (niftyindices.com) — historical data, live market data, daily snapshots, reports, and holiday calendar.

nseindiapy

Python client for NSE Indices (niftyindices.com) — historical OHLC, TRI, P/E-P/B, India VIX, live index snapshot, daily snapshots, monthly reports, and the trading holiday calendar. All tabular data returned as Polars DataFrames.

📖 Full documentation

Installation

pip install nseindiapy
# or
uv add nseindiapy

Quick Start

from datetime import date
from nseindiapy import NiftyIndicesClient

client = NiftyIndicesClient()

# Historical OHLC — auto-paginates for ranges > 365 days
df = client.historical.price_history("NIFTY 50", date(2024, 1, 1), date(2024, 12, 31))

# Total Return Index
tri = client.historical.tri_history("NIFTY 50", date(2024, 1, 1), date(2024, 12, 31))

# P/E, P/B, Dividend Yield
pepb = client.historical.pepb_history("NIFTY 50", date(2024, 1, 1), date(2024, 12, 31))

# India VIX (from daily snapshot CSV)
vix = client.historical.vix_history(date(2024, 1, 1), date(2024, 12, 31))

# Live indices (131 indices, CDN, no auth)
live = client.live.live_indices()

# Daily closing snapshot (all indices)
snap = client.reports.daily_snapshot(date.today())

# Holiday calendar
holidays = client.holidays.get_holidays(2026)
trading  = client.holidays.trading_days(date(2026, 1, 1), date(2026, 3, 31))

Features

• Single entry point — NiftyIndicesClient with four sub-modules
• Auto-pagination — 365-day API limit handled transparently
• Session seeding — ASP.NET cookie seeded automatically; no manual setup needed
• Polars DataFrames — typed columns, pl.Date dates, pl.Float64 numerics
• No API key — all endpoints are public

Links

• Documentation
• PyPI
• GitHub