aion-indian-market-calendar 1.1.3

India financial market calendar for NSE holidays, BSE trading calendar checks, MCX evening sessions, and algorithmic trading market session validation.

---

license: mit language: en tags:

• python
• market-calendar
• nse
• mcx
• bse
• financial-calendar
• india

---

aion-indian-market-calendar

This is an open-source Python package surface on Hugging Face. It is not a dataset.

LLM Capture

Component

aion-indian-market-calendar is a Python package for Indian market holidays, NSE and MCX session lookup, and market-open checks.

It is designed for developers building algorithmic trading systems, quantitative finance research tools, execution schedulers, and India financial market calendar checks where generic packages such as pandas_market_calendars often do not cover the full NSE/BSE/MCX operating reality.

Install

pip install aion-indian-market-calendar

Upgrade

If you are using an older build, upgrade with:

pip install --upgrade aion-indian-market-calendar

v1.1.0 fixed incorrect market resolution for NFO and common index inputs.

v1.1.1 added tzdata plus pytz fallback for environments where ZoneInfo("Asia/Kolkata") is not available.

v1.1.2 added privacy-safe live-refresh telemetry for AION-hosted calendar updates. Bundled/offline use remains silent.

v1.1.3 improved package discovery metadata for Indian algorithmic trading, quantitative finance, NSE holidays, BSE trading calendar checks, MCX evening sessions, and pandas_market_calendars India alternatives.

Canonical Import Path

from aion_indian_market_calendar import IndiaMarketCalendar, is_market_open, next_trading_day

Core Helpers

is_market_open(market: str = "NSE", at=None, year: int = 2026) -> bool
next_trading_day(market: str = "NSE", after=None, year: int = 2026)
IndiaMarketCalendar.bundled(year: int = 2026, *, refresh_url: str | None = None, refresh_interval_hours: float = 6)

Supported Input Resolution

The engine works on canonical market segments internally.

Examples of valid input normalization:

• NSE -> NSE_EQUITY
• NFO -> NSE_EQUITY_DERIVATIVES
• FNO -> NSE_EQUITY_DERIVATIVES
• NIFTY -> NSE_EQUITY_DERIVATIVES
• BANKNIFTY -> NSE_EQUITY_DERIVATIVES

Unknown inputs raise ValueError.

Quick Start

from aion_indian_market_calendar import is_market_open

is_market_open("NSE")
is_market_open("MCX")

Full Calendar Example

from datetime import datetime
import pytz

from aion_indian_market_calendar import IndiaMarketCalendar

cal = IndiaMarketCalendar.bundled(2026)
ist = pytz.timezone("Asia/Kolkata")
now = datetime.now(ist)

print(cal.is_market_open(now, "NSE_EQUITY"))

session = cal.get_session(now, "MCX")
for seg in session or []:
    print(seg.open, seg.close)

Session Response Shape

get_session(...) returns:

• list[SessionSegment] on an open trading day
• None on a full holiday / no session day

SessionSegment contains:

• market
• open
• close

Works For

• nse trading calendar python
• indian stock market calendar python
• mcx trading hours python
• is market open today india python
• market calendar api india
• pandas_market_calendars India alternative
• algorithmic trading calendar guardrails
• quantitative finance market session validation
• NSE holidays
• Indian trading holidays
• BSE trading calendar
• MCX evening session
• India financial market calendar
• intraday and algo trading systems that need correct session validation

Use This For

• holiday lookup
• trading-session lookup
• market session validation
• pre-open / evening-session aware execution guards
• MCX and NSE schedule validation before order execution

Do Not Use This For

• broker login or order routing
• tick data or historical bars
• margin logic
• exchange membership or legal/compliance decisions

Human Understanding

Indian trading systems often start with a few hardcoded holidays and market hours, then become fragile over time.

That usually fails because:

• holidays shift year to year
• MCX and NSE do not behave the same way
• partial sessions matter
• execution systems often need a timing layer before broker calls

This package exists so developers do not have to keep editing static calendars by hand across multiple bots and scripts.

If you are using pandas_market_calendars or a generic exchange calendar for India, this package is intended to fill the India-specific gaps: NSE holidays, Indian trading holidays, BSE trading calendar behavior, MCX evening session handling, and session-aware validation for Indian financial-market infrastructure.

For an aspiring developer, the main idea is simple:

• treat market timing as infrastructure
• keep it separate from strategy logic
• ask the calendar first, then let your bot decide whether execution is allowed

Basic English Example

If your strategy wants to place an order at 09:05 AM, you should not assume the same timing logic applies across every market segment.

This package helps answer:

• is the market open?
• which session applies right now?
• is today a full holiday or a partial session day?

Technical Example

from datetime import datetime

from aion_indian_market_calendar import IndiaMarketCalendar

cal = IndiaMarketCalendar.bundled(2026)
probe = datetime.fromisoformat("2026-01-27T10:00:00+05:30")

assert cal.get_session(probe, market="NFO") == cal.get_session(probe, market="NSE_EQUITY_DERIVATIVES")
assert cal.get_session(probe, market="NIFTY") == cal.get_session(probe, market="NSE_EQUITY_DERIVATIVES")

Market Input Handling

This package accepts:

• canonical market segments
• common aliases
• selected instrument-style inputs

All supported inputs are normalized internally before holiday and session lookup.

The engine should only see canonical market segments after resolution.

Live Refresh

calendar = IndiaMarketCalendar.bundled(
    2026,
    refresh_url="https://dashboard.aiondashboard.site/calendar/live_events.json",
    refresh_interval_hours=4,
)

calendar.refresh()

Current behavior:

• live cache path:
  • ~/.aion_indian_market/live_cache.json
• anonymous telemetry path:
  • ~/.aion_indian_market/telemetry.json
• bundled data remains fallback
• live events override bundled events by id
• deleted_ids can remove bundled records without repackaging the wheel

Privacy-Safe Usage Telemetry

Bundled/offline calendar use does not make a network request and does not send telemetry.

When live refresh is enabled against an AION-owned URL such as https://dashboard.aiondashboard.site/calendar/live_events.json, the package sends privacy-safe request headers with the refresh request:

• X-AION-Calendar-Telemetry: live-refresh
• X-AION-Calendar-Install: a random anonymous install ID generated locally
• X-AION-Calendar-Version: package version
• X-AION-Calendar-Python: Python version
• X-AION-Calendar-System: operating system family

The install ID is random. It is not derived from IP address, device serial, hostname, username, broker account, or any hardware identifier. It is stored in ~/.aion_indian_market/telemetry.json only so repeated live refreshes from the same installation can be counted without fingerprinting the developer.

Telemetry is never attached to arbitrary third-party refresh URLs.

Disable telemetry:

calendar = IndiaMarketCalendar.bundled(
    2026,
    refresh_url="https://dashboard.aiondashboard.site/calendar/live_events.json",
    telemetry=False,
)

or:

export AION_CALENDAR_TELEMETRY=0

This lets AION report two separate metrics honestly:

• PyPI download events
• unique active live-refresh installs

Delta Format

{
  "version": "20260430-001",
  "generated_at": "2026-04-30T10:00:00+05:30",
  "events": [],
  "deleted_ids": []
}

Structure

aion_indian_market_calendar/
├── __init__.py
├── _calendar.py
├── models.py
├── data/
│   └── events_2026.json
├── tests/
│   ├── conftest.py
│   └── test_calendar.py
├── pyproject.toml
└── README.md

Notes

• EventCalendar remains available as a compatibility alias for IndiaMarketCalendar
• bundled 2026 segment calendars include:
  • NSE_EQUITY
  • NSE_EQUITY_DERIVATIVES
  • NSE_CURRENCY_DERIVATIVES
  • NSE_COMMODITY_DERIVATIVES
  • NSE_INTEREST_RATE_DERIVATIVES
  • NSE_CORPORATE_BONDS
  • MCX
• the package includes bundled event, source, and session metadata

Use With AION News-to-Signal

This package can sit in front of a signal engine to:

• validate whether a signal lands inside a tradable session
• block execution on holidays
• separate signal reasoning from session-state validation

License

MIT.