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PyKX Documentation


PyKX is a Python first interface to the world's fastest time-series database kdb+ and its underlying vector programming language, q.

For Python developers, PyKX unlocks the speed and power of kdb+ for data processing and storage from within your Python environment. It enables anyone with Python knowledge to apply analytics against vast amounts of data, both in-memory and on-disk, in a fraction of the time, allowing you to focus on getting the best from your data.

For q developers, PyKX brings together Python's data science ecosystem and the power of kdb+'s vector and time-series analytics. This makes them available in both q and Python environments. You can use it to run q code within a Python environment or embed Python analytics within your q session.

To begin your journey with PyKX follow the sections below.

Documentation Breakdown

Getting Started

Documentation for users new to PyKX! Contains installation instructions alongside quickstart guides and sample getting started notebooks.

User Guide

Useful information allowing users to understand the key concepts behind PyKX. Including how the library is intended to be used and examples of this functionality.


Detailed descriptions of the functions, modules and objects managed by PyKX. Using the API reference assumes you have an understanding of how PyKX is intended to be used through the getting started and user guide.

Release Notes

The latest additions and fixes for PyKX alongside historical changes.


What to look out for in the next weeks, months and years from the PyKX team.