dagster-sling
Package for performing ETL/ELT tasks with Sling in Dagster.
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (up to 3.14); Sling runtime must be available in the environment.
- 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.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in commercial and proprietary projects with minimal restrictions; attribution required.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 15,997 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 83,101 downloads/mo, #14,101 on PyPI
Alternatives
Verify before relying
pip install dagster-sling
import dagster as dg
from dagster_sling import sling_asset
@sling_asset
def my_data_asset():
pass- 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.
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 on this page. Verify before relying on it.
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
dagster-sling on PyPI
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.
Requires Python 3.10 or later (up to 3.14); Sling runtime must be available in the environment.
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():
passVerify 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 the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesdagstersling-mac-arm64sling |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 83,101 / month, #14,101 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: dagster_sling-0.29.18-py3-none-any.whl
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See also dagster-embedded-elt · sling · dagster-dlt · dagster · dagster-webserver · dagster-rest-resources · dagster-airbyte · dagster-cloud-cli · meltano · dagster-graphql