Daft User Guide#
Welcome to Daft!
This user guide aims to help Daft users master the usage of the Daft for all your data needs.
Note
Looking to get started with Daft ASAP?
The Daft User Guide is a useful resource to take deeper dives into specific Daft concepts, but if you are ready to jump into code you may wish to take a look at these resources:
10 minutes Quickstart: Itching to run some Daft code? Hit the ground running with our 10 minute quickstart notebook.
API Documentation: Searchable documentation and reference material to Daft’s public API.
Table of Contents#
The Daft User Guide is laid out as follows:
Basic Concepts#
High-level overview of Daft interfaces and usage to give you a better understanding of how Daft will fit into your day-to-day workflow.
Daft in Depth#
Core Daft concepts all Daft users will find useful to understand deeply.
Structured Query Language (SQL)#
A look into Daft’s SQL interface and how it complements Daft’s Pythonic DataFrame APIs.
The Daft Poweruser#
Become a true Daft Poweruser! This section explores advanced topics to help you configure Daft for specific application environments, improve reliability and optimize for performance.
Integrations#
Learn how to use Daft’s integrations with other technologies such as Ray Datasets or Apache Iceberg.
Tutorials#
Applications built using Daft to serve as inspiration for your own projects