Documentation
https://marketsetup.in/documentation/jugaad-data/
Introduction
jugaad-data is a python library to download historical/live stock, index as well as economic data from NSE and RBI website using.
Features
- Supports new NSE website, (All libraries based on old NSE website might stop working)
- Powerful CLI (Command line interface), Even non-coders can use it easily
- Built-in caching mechanism to play nice with NSE. Avoid making un-necessary requests to NSE's website and getting blocked
- Optional
pandassupport
Road map
| Website | Segment | Supported? |
|---|---|---|
| NSE | Stocks | Yes |
| NSE | Stocks F&O | Yes |
| NSE | Index | Yes |
| NSE | Index F&O | Yes |
| RBI | Current Rates | Yes |
| AMFI | Mutual Fund NAV | Yes |
Installation
pip install jugaad-data
Getting started
Python inteface
Historical data
from datetime import date
from jugaad_data.nse import bhavcopy_save, bhavcopy_fo_save
# Download bhavcopy
bhavcopy_save(date(2020,1,1), "/path/to/directory")
# Download bhavcopy for futures and options
bhavcopy_fo_save(date(2020,1,1), "/path/to/directory")
# Download stock data to pandas dataframe
from jugaad_data.nse import stock_df
df = stock_df(symbol="SBIN", from_date=date(2020,1,1),
to_date=date(2020,1,30), series="EQ")
Live data
from jugaad_data.nse import NSELive
n = NSELive()
q = n.stock_quote("HDFC")
print(q['priceInfo'])
{'lastPrice': 2635,
'change': -49.05000000000018,
'pChange': -1.8274622305843848,
'previousClose': 2684.05,
'open': 2661,
'close': 2632.75,
'vwap': 2645.57,
'lowerCP': '2415.65',
'upperCP': '2952.45',
'pPriceBand': 'No Band',
'basePrice': 2684.05,
'intraDayHighLow': {'min': 2615.6, 'max': 2688.45, 'value': 2635},
'weekHighLow': {'min': 1473.45,
'minDate': '24-Mar-2020',
'max': 2777.15,
'maxDate': '13-Jan-2021',
'value': 2635}}
Command line interface
$ jdata stock --help
Usage: jdata stock [OPTIONS]
Download historical stock data
$jdata stock --symbol STOCK1 -f yyyy-mm-dd -t yyyy-mm-dd --o file_name.csv
Options:
-s, --symbol TEXT [required]
-f, --from TEXT [required]
-t, --to TEXT [required]
-S, --series TEXT [default: EQ]
-o, --output TEXT
--help Show this message and exit.
$ jdata stock -s SBIN -f 2020-01-01 -t 2020-01-31 -o SBIN-Jan.csv
SBIN [####################################] 100%
Saved file to : SBIN-Jan.csv
Download historical index data (niftyindices.com)
from datetime import date
from jugaad_data.nse import (index_raw, index_pe_raw, index_tri_raw,
index_type_list, index_subtype_list, index_name_list)
# OHLC data for an index
data = index_raw("NIFTY 50", date(2026, 1, 1), date(2026, 7, 31))
# P/E, P/B and Dividend Yield
pe_data = index_pe_raw("NIFTY 50", date(2026, 1, 1), date(2026, 7, 31))
# Total Return Index values
# For standard indices name == index_name; for strategy indices use the short code as name
tri_data = index_tri_raw("NIFTY 50", "NIFTY 50", date(2026, 1, 1), date(2026, 7, 31))
# Discover available indices (3-level hierarchy)
index_type_list() # ['Equity', 'Fixed Income', 'Multi Asset']
index_subtype_list('Equity', 'Historical Index Data') # ['Broad Market Indices', 'Sectoral Indices', ...]
index_name_list('Broad Market Indices', 'Historical Index Data') # ['NIFTY 50', 'NIFTY 100', ...]
# index_group options:
# 'Historical Index Data'
# 'Total returns Index Values '
# 'P/E, P/B & Div.Yield values'
Download mutual fund NAV history (AMFI)
from datetime import date
from jugaad_data.amfi import nav_history_raw, nav_history_df, nav_history_csv
# Raw rows (every scheme / AMC / date)
rows = nav_history_raw(date(2026, 9, 1), date(2026, 10, 6))
# pandas DataFrame (nav as float, date as datetime)
df = nav_history_df(date(2026, 9, 1), date(2026, 10, 6))
df[df["scheme_type"] == "Interval Fund"].head()
# Save to CSV
nav_history_csv(date(2026, 9, 1), date(2026, 10, 6), output="nav.csv")
Every row carries scheme_type (Open Ended / Close Ended / Interval Fund),
category (e.g. Money Market) and amc alongside the scheme NAV fields.
Download historical derivatives (F&O) data
$ jdata deriviatives --help
Usage: cli.py derivatives [OPTIONS]
Sample usage-
Download stock futures-
jdata derivatives -s SBIN -f 2020-01-01 -t 2020-01-30 -e 2020-01-30 -i FUTSTK -o file_name.csv
Download index futures-
jdata derivatives -s NIFTY -f 2020-01-01 -t 2020-01-30 -e 2020-01-30 -i FUTIDX -o file_name.csv
Download stock options-
jdata derivatives -s SBIN -f 2020-01-01 -t 2020-01-30 -e 2020-01-30 -i OPTSTK -p 330 --ce -o file_name.csv
Download index options-
jdata derivatives -s NIFTY -f 2020-01-01 -t 2020-01-30 -e 2020-01-23 -i OPTIDX -p 11000 --pe -o file_name.csv
Options:
-s, --symbol TEXT Stock/Index symbol [required]
-f, --from TEXT From date - yyyy-mm-dd [required]
-t, --to TEXT To date - yyyy-mm-dd [required]
-e, --expiry TEXT Expiry date - yyyy-mm-dd [required]
-i, --instru TEXT FUTSTK - Stock futures, FUTIDX - Index Futures, OPTSTK -
Stock Options, OPTIDX - Index Options [required]
-p, --price TEXT Strike price (Only for OPTSTK and OPTIDX)
--ce / --pe --ce for call and --pe for put (Only for OPTSTK and
OPTIDX)
-o, --output TEXT Full path of output file
--help Show this message and exit.
Buy me a coffee
If my work has helped you in anyway, you can buy me a coffee
1 maintainer
Metadata
1 maintainer
Release files for jugaad-data 0.36.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| jugaad_data-0.36.0.tar.gz | 46.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| jugaad_data-0.36.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 80.5 kB
Release files / jugaad_data-0.36.0.tar.gz
| Download URL | jugaad_data-0.36.0.tar.gz |
|---|---|
| Size | 46.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
1c379bf58d8ea4d2f12756820bb4595bfd6c2e5238b8295fe74865e4ac3fa03e
|
|
BLAKE2b-256 checksum How to use checksums |
7c19c7e96e28e0c3de6a9be2ce8afe7c006c429209c8850936c8c1b754708ca2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Release files / jugaad_data-0.36.0-py3-none-any.whl
| Download URL | jugaad_data-0.36.0-py3-none-any.whl |
|---|---|
| Size | 34.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a42e8f2597c70d907a767223da200e1a8b3b5a898f0e5409d8ce54f530c5218e
|
|
BLAKE2b-256 checksum How to use checksums |
09ceae5cabfa875c1d09ae3ec2a4ccaf990ca331ea55b195f60929416a63a5f8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Security for jugaad-data 0.36.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
