OpenChart - NSE India Market Data

* IMPORTANT LEGAL DISCLAIMER *

OpenChart is not affiliated, endorsed, or vetted by NSE India. It's an open-source tool that uses NSE India's publicly available APIs, and is intended for research and educational purposes.

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Overview

OpenChart is a Python library for downloading intraday and EOD (End of Day) historical data from NSE India's charting platform. It supports indices, equities, futures, and options.

Features

Search for symbols across indices, equities, and F&O segments
Fetch historical OHLCV data
Support for multiple timeframes from 1-minute to monthly
No authentication required

Installation

pip install openchart

Or install from GitHub:

pip install git+https://github.com/marketcalls/openchart.git

Quick Start

from openchart import NSEData
from datetime import datetime, timedelta

nse = NSEData()
end = datetime.now()
start = end - timedelta(days=30)

# Get NIFTY 50 daily data
data = nse.historical('NIFTY 50', 'IDX', start, end, '1d')
print(data)

Market Segments

| Segment | Description | Examples | |---------|-------------|----------| | IDX | Indices | NIFTY 50, NIFTY BANK, NIFTY IT | | EQ | Equities | RELIANCE-EQ, INFY-EQ, TCS-EQ | | FO | Futures & Options | NIFTY26JANFUT, BANKNIFTY26JANFUT |

Supported Timeframes

| Timeframe | Description | |-----------|-------------| | 1m | 1 minute | | 5m | 5 minutes | | 10m | 10 minutes | | 15m | 15 minutes | | 30m | 30 minutes | | 1h | 1 hour | | 1d | 1 day | | 1w | 1 week | | 1M | 1 month |

Usage Examples

Search for Symbols

from openchart import NSEData

nse = NSEData()

# Search indices
indices = nse.search('NIFTY', 'IDX')
print(indices)

Output:

             symbol scripcode       description   type exchange
0          NIFTY 50     26000          NIFTY 50  Index      NSE
1          NIFTY IT     26001          NIFTY IT  Index      NSE
2     NIFTY NEXT 50     26002     NIFTY NEXT 50  Index      NSE
3        NIFTY BANK     26004        NIFTY BANK  Index      NSE
4  NIFTY MIDCAP 100     26005  NIFTY MIDCAP 100  Index      NSE

# Search equities
equities = nse.search('RELIANCE', 'EQ')
print(equities)

Output:

        symbol scripcode                description    type exchange
0      RCOM-BE     13188  RELIANCE COMMUNICATIONS L  Equity      NSE
1  RELCHEMQ-EQ      9652  RELIANCE CHEMOTEX IND LTD  Equity      NSE
2  RELIANCE-EQ      2885    RELIANCE INDUSTRIES LTD  Equity      NSE
3      RHFL-BZ    759204  RELIANCE HOME FINANCE LTD  Equity      NSE
4      RIIL-EQ      2912  RELIANCE INDUSTRIAL INFRA  Equity      NSE
5    RPOWER-EQ     15259        RELIANCE POWER LTD.  Equity      NSE

# Search futures & options
fo = nse.search('NIFTY', 'FO')
print(fo)

Output:

               symbol scripcode             description     type exchange
0       NIFTY26FEBFUT     59182       NIFTY 24 FEB 2026  Futures      NSE
1       NIFTY26JANFUT     49229       NIFTY 27 JAN 2026  Futures      NSE
2       NIFTY26MARFUT     51714       NIFTY 30 MAR 2026  Futures      NSE
3  NIFTYNXT5026FEBFUT     59187  NIFTYNXT50 24 FEB 2026  Futures      NSE
4  NIFTYNXT5026JANFUT     49234  NIFTYNXT50 27 JAN 2026  Futures      NSE
...
6   NIFTY2612020400CE     38639  NIFTY 20 JAN 2026 CE 20400.00  Options      NSE
7   NIFTY2612020400PE     38640  NIFTY 20 JAN 2026 PE 20400.00  Options      NSE

Fetch Historical Data

Index Data (NIFTY 50)

from openchart import NSEData
from datetime import datetime, timedelta

nse = NSEData()
end = datetime.now()
start = end - timedelta(days=30)

# Daily data
data = nse.historical('NIFTY 50', 'IDX', start, end, '1d')
print(data)

Output:

                Open      High       Low     Close     Volume
Timestamp
2025-12-18  25764.70  25902.35  25726.30  25815.55  197553755
2025-12-19  25911.50  25993.35  25880.45  25966.40  382927284
2025-12-22  26055.85  26180.70  26047.80  26172.40  252990050
...

Equity Data (RELIANCE)

# Daily data for RELIANCE
data = nse.historical('RELIANCE-EQ', 'EQ', start, end, '1d')
print(data)

Output:

              Open    High     Low   Close    Volume
Timestamp
2026-01-09  1465.0  1479.9  1465.0  1475.3   8335311
2026-01-12  1475.3  1485.3  1451.0  1484.0   8877273
2026-01-13  1485.0  1485.8  1444.7  1456.9  13498784
2026-01-14  1444.0  1467.0  1440.2  1458.8   8320926
2026-01-16  1458.8  1480.0  1455.3  1455.8  10959650

Equity Data (INFY)

# Daily data for INFOSYS
data = nse.historical('INFY-EQ', 'EQ', start, end, '1d')
print(data)

Output:

              Open    High     Low   Close    Volume
Timestamp
2026-01-09  1610.0  1631.3  1607.0  1616.9   6816214
2026-01-12  1610.1  1613.3  1592.6  1597.6   6984534
2026-01-13  1618.0  1618.0  1586.4  1600.0   8080368
2026-01-14  1588.0  1617.0  1583.1  1599.8   7554679
2026-01-16  1663.7  1693.0  1653.4  1686.3  14395786

Futures Data

# NIFTY Futures
data = nse.historical('NIFTY26JANFUT', 'FO', start, end, '1d')
print(data)

Output:

               Open     High      Low    Close   Volume
Timestamp
2026-01-09  25966.0  26031.6  25725.0  25810.8  5830435
2026-01-12  25770.0  25899.0  25573.2  25876.0   121833
2026-01-13  25911.0  25934.8  25661.1  25790.8    87482
2026-01-14  25750.1  25850.0  25670.0  25719.0    70661
2026-01-16  25784.0  25958.0  25752.0  25787.0  4309695

# BANKNIFTY Futures
data = nse.historical('BANKNIFTY26JANFUT', 'FO', start, end, '1d')
print(data)

Output:

               Open     High      Low    Close  Volume
Timestamp
2026-01-09  59890.0  59930.4  59441.0  59525.0  871110
2026-01-12  59600.0  59812.6  59127.6  59730.4   31441
2026-01-13  59880.0  59930.0  59450.0  59755.2   24419
2026-01-14  59690.0  59950.0  59580.2  59780.6   20723
2026-01-16  59833.0  60280.0  59800.0  60085.2  674130

Intraday Data

# 5-minute data
start_intra = end - timedelta(days=5)
data = nse.historical('NIFTY 50', 'IDX', start_intra, end, '5m')
print(data)

Output:

                         Open      High       Low     Close  Volume
Timestamp
2026-01-14 15:09:59  25686.25  25694.10  25655.05  25673.10       0
2026-01-14 15:14:59  25673.45  25676.40  25650.80  25652.85       0
2026-01-14 15:19:59  25655.25  25662.00  25648.30  25660.15       0
2026-01-14 15:24:59  25660.75  25675.95  25654.85  25675.55       0
2026-01-14 15:29:59  25675.80  25677.40  25662.60  25669.10       0

Direct Historical Access

If you already know the token (scripcode), you can fetch data directly:

# Using historical_direct with known token
data = nse.historical_direct(
    token='26000',
    symbol='NIFTY 50',
    symbol_type='Index',
    start=start,
    end=end,
    interval='1d'
)

Utility Methods

# Get supported timeframes
print(nse.timeframes())
# Output: ['1m', '5m', '10m', '15m', '30m', '1h', '1d', '1w', '1M']

# Get supported segments
print(nse.segments())
# Output: ['IDX', 'EQ', 'FO']

API Reference

`NSEData()`

Initialize the NSE data client.

`search(symbol, segment='EQ')`

Search for symbols in a market segment.

| Parameter | Type | Description | |-----------|------|-------------| | symbol | str | Symbol or partial symbol to search | | segment | str | Market segment: 'IDX', 'EQ', or 'FO' |

Returns: pandas DataFrame with columns: symbol, scripcode, description, type, exchange

`historical(symbol, segment='EQ', start=None, end=None, interval='1d')`

Fetch historical OHLCV data for a symbol.

| Parameter | Type | Description | |-----------|------|-------------| | symbol | str | Symbol to fetch data for | | segment | str | Market segment: 'IDX', 'EQ', or 'FO' | | start | datetime | Start date | | end | datetime | End date | | interval | str | Data interval (see supported timeframes) |

Returns: pandas DataFrame with OHLCV data indexed by timestamp

`historical_direct(token, symbol, symbol_type, start=None, end=None, interval='1d')`

Fetch historical data using known token.

| Parameter | Type | Description | |-----------|------|-------------| | token | str | The scripcode/token for the symbol | | symbol | str | Symbol name | | symbol_type | str | Type: 'Index', 'Equity', 'Futures', 'Options' | | start | datetime | Start date | | end | datetime | End date | | interval | str | Data interval |

`timeframes()`

Returns list of supported timeframes.

`segments()`

Returns list of supported market segments.

Notes

Ensure you have a stable internet connection
Intraday data is filtered to market hours (up to 15:29:59)
Historical data availability depends on NSE's servers

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

Author

Rajandran R

Openchart

Install / Use

README

OpenChart - NSE India Market Data

* IMPORTANT LEGAL DISCLAIMER *

Overview

Features

Installation

Quick Start

Market Segments

Supported Timeframes

Usage Examples

Search for Symbols

Fetch Historical Data

Index Data (NIFTY 50)

Equity Data (RELIANCE)

Equity Data (INFY)

Futures Data

Intraday Data

Direct Historical Access

Utility Methods

API Reference

`NSEData()`

`search(symbol, segment='EQ')`

`historical(symbol, segment='EQ', start=None, end=None, interval='1d')`

`historical_direct(token, symbol, symbol_type, start=None, end=None, interval='1d')`

`timeframes()`

`segments()`

Notes

License

Contributing

Author

Openchart

Install / Use

README

OpenChart - NSE India Market Data

*** IMPORTANT LEGAL DISCLAIMER ***

Overview

Features

Installation

Quick Start

Market Segments

Supported Timeframes

Usage Examples

Search for Symbols

Fetch Historical Data

Index Data (NIFTY 50)

Equity Data (RELIANCE)

Equity Data (INFY)

Futures Data

Intraday Data

Direct Historical Access

Utility Methods

API Reference

NSEData()

search(symbol, segment='EQ')

historical(symbol, segment='EQ', start=None, end=None, interval='1d')

historical_direct(token, symbol, symbol_type, start=None, end=None, interval='1d')

timeframes()

segments()

Notes

License

Contributing

Author

* IMPORTANT LEGAL DISCLAIMER *

`NSEData()`

`search(symbol, segment='EQ')`

`historical(symbol, segment='EQ', start=None, end=None, interval='1d')`

`historical_direct(token, symbol, symbol_type, start=None, end=None, interval='1d')`

`timeframes()`

`segments()`