---
id: dagster-sling
version: "0.29.18"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# dagster-sling — Package for performing ETL/ELT tasks with Sling in Dagster.

License: permissive · Maintenance: active · Downloads: 83.1K/mo

## What it is and what it does

dagster-sling is a Dagster integration library that brings Sling's ETL/ELT capabilities into Dagster's declarative asset orchestration framework. It allows you to define data pipelines using Sling as the execution engine while leveraging Dagster's asset lineage, observability, and orchestration features. The package wraps Sling tasks as Dagster assets, enabling you to compose them with other assets and run them through Dagster's unified control plane.

The integration is designed for teams already using Dagster for data orchestration who want to incorporate Sling's data integration capabilities. It requires Sling and dagster as runtime dependencies, with platform-specific Sling binaries (like sling-mac-arm64) available for different architectures. The package is actively maintained and supports Python 3.10 through 3.14.

Use it for:

- Build data pipelines combining Sling data ingestion with Dagster asset orchestration and lineage tracking.
- Automate ETL/ELT workflows where Sling handles data movement and Dagster manages scheduling and observability.
- Integrate Sling tasks into existing Dagster projects without rewriting orchestration logic.
- Monitor and troubleshoot Sling data jobs through Dagster's unified web UI and observability layer.
- Deploy multi-stage data pipelines where Sling ingests and transforms data, feeding downstream Dagster assets.

## Worth the install?

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

Integrates Sling ETL/ELT tasks into Dagster data pipelines, enabling declarative data asset orchestration with Sling as the execution engine.

Yes. The package is actively maintained, has no known vulnerabilities, uses a permissive Apache-2.0 license, and installs with low friction. It is worth installing if you are already using Dagster and need to incorporate Sling for data integration tasks. If you are not using Dagster, this package alone will not be useful—you would need the Dagster ecosystem first.

## Install

pip install dagster-sling
uv add dagster-sling
poetry add dagster-sling

## Installing dagster-sling

Before you install: Active maintenance with a recent release (0 days since last update). Low install friction with a pure-Python wheel and three runtime dependencies: dagster, sling, and sling-mac-arm64. Suitable for immediate adoption.

License in practice: Apache-2.0 permissive license allows use in commercial and proprietary projects with minimal restrictions; attribution required.

Quickstart:

pip install dagster-sling

import dagster as dg
from dagster_sling import sling_asset

@sling_asset
def my_data_asset():
    pass

Requires Python 3.10 or later (up to 3.14); Sling runtime must be available in the environment.

Verify before relying:

- Specific Sling version compatibility and feature support beyond the runtime dependency declaration.
- Whether sling-mac-arm64 is automatically selected or requires manual configuration on ARM macOS systems.
- Integration patterns and examples beyond the basic asset decorator usage.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 83.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

dagster sling integration, etl orchestration with dagster, data pipeline sling, dagster asset orchestration, elt task automation, data asset pipeline, sling data integration, data-orchestration, etl-elt, integration

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