---
id: databricks-dlt
version: "0.3.0"
license: Databricks Proprietary License
license_treatment: unclear
maintenance: dormant
---

# databricks-dlt — Databricks DLT Library

License: unclear · Maintenance: dormant · Downloads: 2.1M/mo

## What it is and what it does

databricks-dlt is a Python stub library that provides type hints, API specifications, and docstring references for the Databricks Delta Live Tables (DLT) Python API. It is designed to improve the local development experience by enabling IDE autocomplete and type checking in your code editor when writing DLT pipeline code, without providing any functional runtime implementation.

The package depends on databricks-connect and is intended as a development aid only. It does not allow you to create or run DLT pipelines locally; actual pipeline execution requires deployment to Databricks Services. The library's sole purpose is to make writing pipeline code in your local environment more productive by offering the same API surface and type information you would see when running on Databricks.

Use it for:

- Enable IDE autocomplete and type hints when writing DLT pipeline code in your local development environment before deployment.
- Perform static type checking on DLT pipeline code using tools like mypy or pyright without needing a live Databricks connection.
- Reference DLT Python API docstrings and method signatures locally during development to reduce context switching to external documentation.
- Catch API usage errors early in development by leveraging Python type annotations before pushing code to Databricks.
- Support team development workflows where developers write and review pipeline code locally with full IDE support.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides type hints, API specs, and IDE autocomplete support for developing Databricks Delta Live Tables pipelines locally without functional runtime implementation.

Yes, if you are actively developing Databricks DLT pipelines and want IDE autocomplete and type checking in your local environment. The low install friction and lack of known vulnerabilities make it a safe addition to your development setup. However, maintenance is dormant, so type hints may lag behind the current DLT API. The proprietary license restricts use to Databricks Services; verify compliance with your organization's licensing terms before adopting.

## Install

pip install databricks-dlt
uv add databricks-dlt
poetry add databricks-dlt

## Installing databricks-dlt

Before you install: Low install friction with a single runtime dependency on databricks-connect. Maintenance status is dormant; the package has not been updated since its latest release on 2024-11-27.

License in practice: Licensed under Databricks Proprietary License (not SPDX-standardized). Use is restricted to connection with Databricks Services under their Master Cloud Services Agreement; redistribution is permitted only under the same terms and with proper attribution.

Quickstart:

pip install databricks-dlt

import dlt
# Access DLT module for type hints and autocomplete in your local IDE

Requires Python 3.9 or later. This package provides only type stubs and API specs—it cannot run or execute DLT pipelines locally; actual pipeline execution requires Databricks Services.

Verify before relying:

- Whether dormant maintenance status reflects intentional stability or active abandonment.
- Compatibility with recent versions of databricks-connect and whether breaking changes have occurred.
- Whether type hints cover the full current DLT Python API or only a subset as of the last release.

## Package facts

- License: Databricks Proprietary License (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: dormant
- Downloads: 2.1M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

delta live tables python stubs, dlt local development ide support, databricks dlt type hints, delta live tables autocomplete, dlt pipeline development tools, databricks pipeline type checking, dlt python api reference, databricks, type-stubs, local-development

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