mcxlib 0.4

python library to get MCX India data

mcxlib

mcxlib is a Python library for fetching publicly available market data from the MCX India website and returning it as pandas DataFrames.

It provides a lightweight wrapper around common MCX endpoints so you can pull market snapshots, derivatives data, and historical reports directly into your Python workflows.

What It Provides

• Live market data such as market watch, available contracts, heat map, top gainers, and top losers
• Derivatives data such as option chain, put-call ratio, and most active contracts
• Historical reports such as bhav copy, date-wise historical data, and trading statistics
• MCX index and participant-level datasets such as iCOMDEX indices and PRO/CLI details

Installation

Install from PyPI:

pip install mcxlib

Upgrade an existing installation:

pip install --upgrade mcxlib

If you are working from source:

pip install -r requirements.txt
pip install -e .

Dependencies

The project relies mainly on:

• pandas
• requests
• xlrd

Some MCX datasets are published as Excel files, so spreadsheet-reading support is required for part of the API.

Quick Start

import mcxlib

market_watch = mcxlib.get_market_watch()
print(market_watch.head())

bhav_copy = mcxlib.get_bhav_copy(
    trade_date="20231102",
    instrument="ALL",
)

option_chain = mcxlib.get_option_chain(
    commodity="CRUDEOIL",
    expiry="15NOV2023",
)

historical_data = mcxlib.get_historical_data(
    start_date="20230101",
    end_date="20231103",
)

Public API

Most exported functions return a pandas.DataFrame. get_mcx_datetime() returns a timezone-aware Python datetime object in IST.

Live Market Data

• get_mcx_datetime()
• get_market_watch()
• get_available_contracts(commodity="ALL", instrument="ALL")
• get_heat_map()
• get_top_gainers()
• get_top_losers()
• get_most_active_contracts(instrument="ALL")
• get_most_active_puts_calls(option_type="PE", product="ALL", instrument="OPTFUT")

Options and Sentiment Data

• get_recent_expires(commodity="ALL")
• get_option_chain(commodity="CRUDEOIL", expiry="15NOV2023")
• get_put_call_ratio(ratio_type="expiry_wise")

Historical and Report Data

• get_bhav_copy(trade_date="YYYYMMDD", instrument="ALL")
• get_historical_date_wise_data(start_date="YYYYMMDD", end_date="YYYYMMDD")
• get_historical_data(start_date="YYYYMMDD", end_date="YYYYMMDD")
• get_category_wise_turnover(year=2023, month_number=9)
• get_category_wise_oi(year=2023, month_number=9)
• get_trading_statistics(year=2023, month_number=9)
• get_ccl_delivery(year=2023, month_number=9)

Index and Participant Data

• get_mcx_icomdex_indices()
• get_pro_cli_details(trade_month="YYYYMM")

Parameter Notes

• Dates for get_bhav_copy() and get_historical_data() use YYYYMMDD
• get_pro_cli_details() uses month format YYYYMM
• get_option_chain() expiry uses DDMMMYYYY, for example 15NOV2023
• Historical date-wise queries are limited by MCX to a maximum range of 365 days
• Valid parameter values depend on what MCX currently exposes for each endpoint

Example Use Cases

Get the latest market watch data:

import mcxlib

df = mcxlib.get_market_watch()
print(df.columns)
print(df.head())

Fetch live contracts for a commodity and convert them to JSON:

import mcxlib

df = mcxlib.get_available_contracts(
    commodity="LEADMINI",
    instrument="FUTCOM",
)

print(df.to_json(orient="records"))

Fetch historical data for analysis:

import mcxlib

df = mcxlib.get_historical_data(
    start_date="20230101",
    end_date="20230331",
)

print(df.head())

Fetch option chain data for a commodity:

import mcxlib

df = mcxlib.get_option_chain(
    commodity="CRUDEOIL",
    expiry="15NOV2023",
)

print(df.head())

Error Handling

Most functions raise ValueError when:

• Parameters are invalid
• MCX does not return data for the request
• The upstream MCX endpoint format changes

If you receive an error, first verify the parameter format and whether the requested dataset is currently available on the MCX website.

Limitations

• This library depends on public MCX endpoints and report files remaining available
• Changes on the MCX website can break one or more functions without a package release
• Live data availability depends on MCX publishing current values at request time

Contributing

Contributions are welcome. If you want to help:

• Open an issue: https://github.com/RuchiTanmay/mcxlib/issues
• Submit a pull request with a focused fix or enhancement
• Share examples or documentation improvements to help other users get started

License

This project is licensed under the MIT License. See LICENSE for details.