bse-index-data 1.1.1

Download BSE India market data as pandas DataFrames — SENSEX, BSE indices, historical OHLC. Works on AWS Lambda.

bse-index-data

BSE India market data as pandas DataFrames.
SENSEX, BSE500, BANKEX and 50+ indices — historical OHLC + live quotes.
Works on AWS Lambda and any cloud environment.

pip install bse-index-data

Part of the indian-market-data monorepo.

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Quick Start

from bsedata import bse

# Historical SENSEX OHLC
df = bse.get_index("SENSEX", "2026-01-01", "2026-05-22")

# Historical BSE500
df = bse.get_index("BSE500", "2026-01-01", "2026-05-22")

# All 120+ indices for one date (single API call)
df = bse.get_all_indices("2026-05-22")

# Live SENSEX quote
df = bse.get_live_sensex()

# Download to S3 (Lambda with IAM role)
bse.download_index("SENSEX", "2026-01-01", "2026-05-22",
                   s3_bucket="my-bucket", s3_prefix="raw/bse/")

# List all 55 supported indices
bse.list_indices()
bse.list_indices(category="Sectoral")

Supported Indices (55)

Category	Indices
Broad Market	SENSEX, SENSEX50, SENSEXNXT50, BSE100, BSE200, BSE500, BSEALLCAP, BSEMIDCAP, BSESMALLCAP, BSE150MIDCAP, BSE250SMALLCAP, BSE400MIDSMALLCAP, BSE250LARGEMIDCAP, BSEMIDCAPSELECT, BSESMALLCAPSELECT, BSELARGECAP
Sectoral	BANKEX, BSEAUTO, BSECG, BSECD, BSECDGS, BSEENERGY, BSEFMCG, BSEFINANCE, BSEHC, BSEIT, BSEINDUSTRIALS, BSEMETAL, BSEOILGAS, BSEPOWER, BSEPRIVATEBANKS, BSEPSU, BSEREALTY, BSESERVICES, BSETECK, BSETELECOM, BSEUTILS
Thematic	BSECPSE, BSEIPO, BSESMEIPO, BSEGREENEX, BSECARBONEX, BSEINFRA, BSEMANUFACTURING, BHARAT22
Strategy	BSEMOMENTUM, BSEQUALITY, BSEVALUE, BSELOWVOL, BSEDIVSTAB, BSE100ESG
Global	DOLLEX30, DOLLEX100, DOLLEX200

CLI

bse-index-data list
bse-index-data list --category Sectoral
bse-index-data index --name SENSEX --from 2026-01-01 --to 2026-05-22
bse-index-data all-indices --date 2026-05-22
bse-index-data live

Polars output (optional)

By default every function returns a pandas DataFrame. To get polars DataFrames instead, install the extra and set one environment variable before importing — no code changes needed:

pip install bse-index-data[polars]

import os
os.environ["IMD_DATAFRAME"] = "polars"   # set before importing bsedata

from bsedata import bse
df = bse.get_index("SENSEX", "2026-01-01", "2026-05-22")
type(df)   # polars.DataFrame

All internal logic stays in pandas; conversion happens only at the final return step. Leave IMD_DATAFRAME unset (or =pandas) for the default pandas output.

License

MIT — data from BSE India.