DLT developer reference

This section contains reference and instructions for DLT developers.

Data loading and transformations are implemented in a DLT pipeline by queries that define streaming tables and materialized views. To implement these queries, DLT supports SQL and Python interfaces. Because these interfaces provide equivalent functionality for most data processing use cases, pipeline developers can choose the interface that they are most comfortable with.

The following pages provide an overview of and references for developing DLT code:

Topic	Description
Develop pipeline code with Python	An overview of developing DLT pipelines in Python.
DLT Python language reference	Python reference documentation for the dlt module.
Develop pipeline code with SQL	An overview of developing DLT pipelines in SQL.
DLT SQL language reference	Reference documentation for SQL syntax for DLT.
Manage Python dependencies for DLT pipelines	Instructions for managing Python libraries with DLT.
Convert a DLT pipeline into a Databricks Asset Bundle project	Instructions for working with Databricks Asset Bundles with DLT.
Develop DLT pipeline code in your local development environment	An overview of options for developing DLT code locally.