Does it handle Daylight Saving Time (DST)?

Yes, it utilizes IANA timezone data through the exchange_calendars library to automatically handle DST transitions across all supported global jurisdictions.

Which exchanges are supported out of the box?

It includes 10 major exchanges: NYSE, LSE, SIX, FWB, TSX, NZX, JPX (Tokyo), ASX, HKEX, and SGX, with a standard pattern to add more via MIC codes.

Can I use this with SQL databases like ClickHouse?

Yes, the skill includes specific ClickHouse SQL patterns for DST-aware hour extraction and advice on integrating holiday calendars with database workflows.

Why use this instead of simple hour checks?

Simple checks miss holidays, early closes, and complex lunch breaks (like Tokyo or Hong Kong), which can lead to significant inaccuracies in financial data analysis.

Is this skill optimized for large datasets?

Absolutely. It uses a vectorized .isin() lookup pattern with pre-computed trading minutes, making it over 2x faster than standard row-by-row iteration methods.

Exchange Session Detector

Name: Exchange Session Detector
Author: terrylica

byterrylica

•

Data Science & ML

Implements production-grade, DST-aware trading session detection and holiday tracking for global financial markets.

This skill provides a standardized pattern for detecting trading sessions across 10 major global exchanges using the exchange_calendars library. It moves beyond simple hour-range checks to handle complex market realities like lunch breaks in Asian markets, early closes, and public holidays. By utilizing vectorized lookups and a central ExchangeConfig registry, it offers a high-performance solution for adding market context to time-series DataFrames and managing financial data preprocessing pipelines efficiently.

Key Features

01Ready-to-use ClickHouse SQL patterns for server-side market session classification

02High-performance vectorized session lookups optimized for millions of data points

03Automated handling of Asian market lunch breaks for Tokyo, Hong Kong, and Singapore

04Support for 10 global exchanges including NYSE, LSE, and JPX via ISO 10383 MIC codes

0540 GitHub stars

06Full DST and holiday awareness using IANA timezone data and official calendars

Use Cases

01Feature engineering for quantitative models that require precise holiday and trading hour context

02Preprocessing financial tick data to flag sessions and filter out-of-hours market noise

03Generating materialized columns in databases for high-speed market-hour analytics

Key Features

01Ready-to-use ClickHouse SQL patterns for server-side market session classification

02High-performance vectorized session lookups optimized for millions of data points

03Automated handling of Asian market lunch breaks for Tokyo, Hong Kong, and Singapore

04Support for 10 global exchanges including NYSE, LSE, and JPX via ISO 10383 MIC codes

0540 GitHub stars

06Full DST and holiday awareness using IANA timezone data and official calendars

Use Cases

01Feature engineering for quantitative models that require precise holiday and trading hour context

02Preprocessing financial tick data to flag sessions and filter out-of-hours market noise

03Generating materialized columns in databases for high-speed market-hour analytics