# exchange_calendars Sessions, minutes and holidays for 69 exchanges, keyed by ISO-10383 code. *https://stockmarketstack.com/tools/exchange-calendars · Market Analysis & Portfolio Optimization Libraries* ## Facts ### At a glance | Field | Value | | --- | --- | | Vendor | Gerry Manoim | | Category | Market Analysis & Portfolio Optimization Libraries | | Job | market_calendars | | Website | https://github.com/gerrymanoim/exchange_calendars | | Pricing model | open-source | | Free tier | true | | Open source | true | | Licence | Apache-2.0 | | Self-hosted | true | | Tested hands-on | false | | Last updated | 2026-09-19 | ### Coverage | Field | Value | | --- | --- | | Asset classes | stocks, futures | | Markets | global | | Works outside the US | true | | Data latency | none | | Platforms | library, cli | | AI features | none | ### Interfaces | Field | Value | | --- | --- | | API | false | | Webhooks | false | | Scripting | Python | | Python | true | | Spreadsheet add-in | false | | MCP server | false | | Export | none | ### Capabilities Yes: none No: charting, screening, scanning, backtesting, automation, live_trading, paper_trading, portfolio_tracking, broker_import, tax_reporting, alerts, news, options_analysis *Verified: pricing 2026-09-19; capabilities 2026-09-19; coverage 2026-09-19.* ## What it is `xcals.get_calendar("XNYS")` returns a calendar object, and everything follows from that. The `schedule` property is a DataFrame indexed by session with `open`, `break_start`, `break_end` and `close` columns in UTC, so a Hong Kong lunch break or a US half-day before Independence Day is data rather than a special case you code around. On top of it sit session helpers (`is_session`, `sessions_in_range`, `sessions_window`, `previous_session`, `date_to_session`), minute helpers (`session_minutes`, `is_trading_minute`, `is_break_minute`, `previous_minute`) and `trading_index`, which builds a period index that skips everything the exchange was closed for. Calendars are named by their ISO-10383 market identifier code — XNYS, XLON, XTKS, CMES — and the README table lists 69 of them, from the New York Stock Exchange in version 1.0 to Dubai Financial Market on `master` today. There is also a command-line entry point — `ecal XNYS 2020` prints a unix-cal style year with the holidays in brackets. ## Pricing Free, Apache-2.0, nothing to buy. `pip install exchange_calendars`, with pandas, numpy, toolz, tzdata, pyluach and korean_lunar_calendar behind it — the last two because Israeli and Korean holidays are not solvable with a Gregorian rule. ## Data & coverage 69 exchange calendars covering the Americas, Europe, Asia, the Middle East, Africa and Australasia, mostly equity venues plus a handful of derivative and energy ones — CME, CBOE Futures, ICE US, Eurex and the European Energy Exchange. Sessions, lunch breaks, early closes and one-off interruptions are all modelled; an exchange counts as open only during regular trading, so pre-market, post-market and auction periods read as closed. The calendars are package code, not a feed. Nothing is requested from a server at runtime, which means a corrected holiday reaches you by upgrading the package — and, when the release cadence slows down, by installing from git. ## Integrations [Zipline-reloaded](https://stockmarketstack.com/tools/zipline-reloaded) takes these codes directly through its `--trading-calendar` flag. `pandas_market_calendars` mirrors the whole set and depends on this package; `market_prices`, by the same maintainer who does most of the work here, is built on it. ## Limitations - Every calendar is contributed by users. The README says so plainly — if a holiday is wrong, the fix is a pull request you write. How accurate a given exchange is depends on who last cared about it. - Releases lag the fixes. The last PyPI release is 4.13.2 from 10 March 2026, while `master` has carried the Dubai calendar since 14 August 2026 and Hong Kong weather closures since 15 September 2026. Six months of calendar corrections currently exist only in git. - The default schedule window is twenty years back and one year forward, and future sessions are rule-generated rather than confirmed against an exchange notice. - Versions 4.0 and 4.3 renamed or removed several dozen methods, and the README carries a long deprecation table. Code written against `trading_calendars` or early exchange_calendars will need edits. - PyPI classifies it Development Status :: 4 - Beta. - No intraday auction, settlement or holiday-reason metadata — you get open and closed, not why. ## Alternatives `pandas_market_calendars` wraps the same calendars in a `schedule()` and `date_range()` API and adds futures-product conventions of its own, at the cost of a second layer to keep current. If all you need is US equity sessions, a market data API that already returns bars on an exchange calendar — see [market data APIs](https://stockmarketstack.com/categories/market-data-apis) — removes the question. ## FAQ ### Is exchange_calendars maintained? The code is, the releases less so. Commits land most weeks — the newest on `master` is 15 September 2026 — but the last PyPI release, 4.13.2, went out on 10 March 2026. Gerry Manoim owns the repository and Marcus Read does most of the current work; 21 issues and 7 pull requests are open and nothing is archived. ### Where did it come from? Quantopian's `trading_calendars`, which stopped at version 2.1.1 on 5 January 2021 and saw its last commit on 20 January 2021. exchange_calendars is the continuation and kept the Apache-2.0 licence; the calendar codes are the same, which is why Zipline-reloaded's `--trading-calendar` flag still takes them. ### How far into the future do the calendars go? One year by default, and twenty years back — `GLOBAL_DEFAULT_START` and `GLOBAL_DEFAULT_END` in the source. You can ask for a wider range, but only within the bounds each individual calendar declares, and future holidays are generated from rules rather than from an exchange's published notice. ### Is pandas_market_calendars the same thing? No, it is a separate package by a different author — Ryan Sheftel, MIT-licensed — with its own `schedule()` and `date_range()` API. Since its version 2.0 it mirrors these calendars and lists `exchange-calendars` as a dependency, so choosing it does not mean leaving this project behind; it means adding a layer on top of it. ## Also worth comparing - [pandas-ta](https://stockmarketstack.com/tools/pandas-ta.md) — The DataFrame indicator library whose repo is gone and whose last release is a year old. - [QuantLib](https://stockmarketstack.com/tools/quantlib.md) — The open-source derivatives pricing library banks actually use, reachable from Python. - [TA-Lib](https://stockmarketstack.com/tools/ta-lib.md) — The C indicator library everything else wraps — and pip now ships the C part with it. - [arch](https://stockmarketstack.com/tools/arch.md) — GARCH and the rest of the volatility-model family, plus the tests you need around them. - [empyrical-reloaded](https://stockmarketstack.com/tools/empyrical-reloaded.md) — The maintained fork of Quantopian's empyrical — risk statistics, no plots. - [ffn](https://stockmarketstack.com/tools/ffn.md) — Performance stats, drawdowns and portfolio weights from a DataFrame of prices.