MorningPy

A modern Python library for financial data — Stocks, ETFs, Funds, Indices, Financial Statements, Timeseries, and News.

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Overview

MorningPy provides a Pythonic and intuitive interface to access financial and market data from Morningstar.com.
It is designed for students, practitioners, and researchers who need fast, consistent, and transparent access to high-quality market information.

MorningPy enables professional-grade data handling and covers a wide range of financial instruments, including:

• Stocks, ETFs, Funds, Indices
• Financial Statements and Holdings
• Historical and Intraday Timeseries
• News and Market Updates
• Ticker conversion

News

• First version of MorningPy released — excited to start the journey! 🎉

Installation

Install from PyPI:

pip install morningpy

Install from source:

git clone https://github.com/ThomasPiton/morningpy.git
pip install -e morningpy

Usage

Importing Modules

# All modules
from morningpy import(
    get_market_us_calendar_info,
    get_market_commodities,
    get_market_currencies,
    get_market_movers,
    get_market_indexes,
    get_market_fair_value,
    get_intraday_timeseries,
    get_historical_timeseries,
    get_financial_statement,
    get_holding,
    get_holding_info,
    get_intraday_timeseries,
    get_historical_timeseries,
)

# Market data
from morningpy.api.market import (
    get_market_us_calendar_info,
    get_market_commodities,
    get_market_currencies,
    get_market_movers,
    get_market_indexes,
    get_market_fair_value,
)

# Timeseries data
from morningpy.api.timeseries import (
    get_intraday_timeseries,
    get_historical_timeseries
)

# Security data
from morningpy.api.security import (
    get_financial_statement,
    get_holding,
    get_holding_info
)

# Ticker info
from morningpy.api.ticker import (
    search_tickers,
    convert,
    batch_convert,
)

# News
from morningpy.api.news import get_headline_news

Examples

Market Information

from morningpy.api.market import (
    get_market_us_calendar_info,
    get_market_commodities,
    get_market_currencies,
    get_market_movers,
    get_market_indexes,
    get_market_fair_value,
    get_market_info
)

# US earnings calendar
calendar_info = get_market_us_calendar_info(date=["2025-11-12"], info_type="earnings")
print(calendar_info.head())

# Commodities and currencies
commodities = get_market_commodities()
currencies = get_market_currencies()

# Market movers
movers = get_market_movers(mover_type=["gainers", "losers", "actives"])

# Indexes and fair value
indexes = get_market_indexes(index_type=["americas", "us"])
fair_value = get_market_fair_value(value_type=["overvaluated", "undervaluated"])

# General market info
market_info = get_market_info(info_type=["global_barometer", "commodities"])

Timeseries

from morningpy.api.timeseries import (
    get_intraday_timeseries,
    get_historical_timeseries
)

# Intraday data
intraday = get_intraday_timeseries(
    security_id=["0P00009WL3"],
    start_date="2024-11-08",
    end_date="2025-11-07",
    frequency="1min",
    pre_after=False
)

# Historical daily data
historical = get_historical_timeseries(
    security_id=["0P0000OQN8", "0P0001RWKZ"],
    start_date="2010-11-05",
    end_date="2025-11-05",
    frequency="daily",
    pre_after=False
)

Security

from morningpy.api.security import (
    get_financial_statement,
    get_holding,
    get_holding_info
)

# Financial statement
income_statement = get_financial_statement(
    statement_type="Income Statement",
    report_frequency="Quarterly",
    security_id=["0P000115U4"]
)

# Holdings
holding_info = get_holding_info(
    performance_id=["0P0001PU03", "0P0001BG3E"]
)
holding = get_holding(
    performance_id=["0P0001PU03", "0P00013Z57"]
)

Ticker

from morningpy.api.ticker import (
    search_tickers,
    convert,
    batch_convert,
)

# Retrieve US stock tickers
us_stock_tickers = search_tickers(security_type="stock", country_id="USA", exact_match=True)

# Search for specific tickers
tech_tickers = search_tickers(ticker=["AAPL", "MSFT", "GOOGL"])

# Search for active ETFs in technology sector
tech_etf = search_tickers(
    security_type="etf",
    sector="Technology",
    is_active=True
)

# Search by security label
tech_label_security = search_tickers(
    security_label="Technology",  # Finds all securities with "Technology" in name
    exact_match=False
)

# Batch conversion
sec_batch = batch_convert(
    ["AAPL", "MSFT", "GOOGL", "AMZN"], 
    from_field="ticker", 
    to_field="isin"
)

# Single conversion
isin = convert(performance_id="0P0001PU03", convert_to="isin")
security_id = convert(isin="US0378331005", convert_to="security_id")

News

from morningpy.api.news import get_headline_news

# Get headline news
news = get_headline_news(
    market="Spain",
    news="economy",
    edition="Central Europe"
)
print(news.head())

Documentation

Advanced documentation is available at Documentation

Legal

MorningPy is distributed under the MIT License. See the LICENSE file for details.

MorningPy is not affiliated with, endorsed by, or vetted by Morningstar, Inc. It's an open-source tool that uses Morningstar's publicly available APIs, and is intended for research and educational purposes. Users should refer to Morningstar's terms of use for details on their rights to use the actual data downloaded.

Contributing

Contributions are always welcome! Please see our Code of Conduct and contributing guidelines for details on how to participate in this project.

Support

• Documentation
• Issue Tracker