pandas_market_calendars
Market and exchange trading calendars for pandas
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, low install friction, and solves a concrete problem for quantitative finance workflows. It is production-stable (Development Status 5), widely used (top 5000 PyPI), and permissively licensed. Install it if you need to work with market hours, holidays, or trading schedules in pandas.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; minimum version changed in v5.0 from 3.9.
- Low install friction with only two runtime dependencies (pandas and exchange-calendars).
- Active maintenance with a release 79 days ago and continuous repository activity; supports current Python versions (3.10–3.14).
License · maintenance · safety
MIT (permissive) — MIT license is permissive, allowing commercial and private use with minimal restrictions.
last release 2026-05-27 (79 days) · last repo commit 2026-07-12 · 990 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,099,085 downloads/mo, #3,297 on PyPI
Alternatives
Verify before relying
pip install pandas_market_calendars
import pandas_market_calendars as mcal
nyse = mcal.get_calendar('NYSE')
schedule = nyse.schedule(start_date='2012-07-01', end_date='2012-07-10')
dates = mcal.date_range(schedule, frequency='1D')- Accuracy and timeliness of calendar data for all 50+ exchanges—whether updates keep pace with real-world market changes
- Performance characteristics when working with large date ranges or many calendars simultaneously
What it is and what it does
pandas_market_calendars fills a gap in pandas by providing pre-built holiday, trading hours, and market break calendars for specific exchanges and OTC markets. Rather than fetching live data at runtime, calendars are shipped as package code and updated via new releases. The package wraps exchange-calendars to mirror its calendar definitions and adds utility functions to work with market schedules—most notably a date_range function that generates pandas DatetimeIndex objects containing only times when markets are open, accounting for holidays, early closes, and intraday breaks (such as lunch breaks in Asian markets or processing breaks in 24-hour futures markets).
Typical usage involves loading a calendar by exchange name (e.g., NYSE), querying its schedule for a date range to see market_open and market_close times, and then generating aligned datetime sequences for backtesting, data alignment, or trading logic. The package is designed for quantitative finance workflows where precise market hours and holiday handling are essential.
Use it for
- Backtest trading strategies by generating datetime sequences aligned only to market hours for a specific exchange
- Align time series data to market open/close times when building multi-asset portfolios across different exchanges
- Identify market holidays and early closes programmatically to avoid scheduling trades or data pulls on non-trading days
- Handle intraday breaks in Asian and futures markets when calculating trading durations or generating periodic resampling
- Build global trading calendars by combining schedules from multiple exchanges to coordinate cross-market strategies
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, low install friction, and solves a concrete problem for quantitative finance workflows. It is production-stable (Development Status 5), widely used (top 5000 PyPI), and permissively licensed. Install it if you need to work with market hours, holidays, or trading schedules in pandas.
Install
pandas-market-calendars on PyPI
Before you install
Low install friction with only two runtime dependencies (pandas and exchange-calendars). Active maintenance with a release 79 days ago and continuous repository activity; supports current Python versions (3.10–3.14).
Requires Python 3.10 or later; minimum version changed in v5.0 from 3.9.
License in practice
MIT license is permissive, allowing commercial and private use with minimal restrictions.
Quickstart
pip install pandas_market_calendars
import pandas_market_calendars as mcal
nyse = mcal.get_calendar('NYSE')
schedule = nyse.schedule(start_date='2012-07-01', end_date='2012-07-10')
dates = mcal.date_range(schedule, frequency='1D')Verify before relying
- Accuracy and timeliness of calendar data for all 50+ exchanges—whether updates keep pace with real-world market changes
- Performance characteristics when working with large date ranges or many calendars simultaneously
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesexchange-calendarspandas |
| Maintenance | Actively maintained 79 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,099,085 / month, #3,297 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Software Development |
Evidence: pandas_market_calendars-5.4.0-py3-none-any.whl
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