dagster-pipes
Toolkit for Dagster integrations with transform logic outside of Dagster
Decision gist · record as of 2026-08-14
Yes, if you are already using Dagster and need to execute transforms or integrations outside the main process. The active maintenance, zero external dependencies, and permissive license make it a low-friction addition to a Dagster deployment. Not relevant for non-Dagster workflows.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; designed to work as part of a Dagster orchestration setup, not as a standalone tool.
- Active maintenance with a release 7 days ago.
- No runtime dependencies, making installation straightforward.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 licensed under a permissive regime, allowing commercial use, modification, and distribution with minimal restrictions.
last release 2026-08-07 (7 days) · last repo commit 2026-08-13 · 15,996 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 9,387,238 downloads/mo, #1,538 on PyPI
Alternatives
Verify before relying
pip install dagster-pipes
import dagster_pipes
# Use within a Dagster asset or op to execute external transform logic
result = dagster_pipes.execute_external_transform()- Specific external execution patterns and supported deployment targets beyond the toolkit description.
- Performance characteristics and scalability limits for remote execution workloads.
- Integration requirements with specific data platforms or cloud providers.
What it is and what it does
Dagster-pipes is a specialized toolkit within the Dagster ecosystem that enables you to run transform logic and integrations outside the main Dagster process. It sits between Dagster's orchestration engine and external compute environments, allowing you to execute data transformations remotely while maintaining lineage and observability through Dagster's central control plane.
The package is designed for scenarios where your data processing needs to run in a separate environment—such as a different container, machine, or cloud service—but you still want Dagster to coordinate, monitor, and track the results. It abstracts away the complexity of subprocess communication and result serialization, letting you focus on defining what work happens where rather than managing the plumbing.
Use it for
- Execute dbt models or SQL transforms in a remote database while orchestrating them through Dagster.
- Run Python transforms in isolated containers or Kubernetes pods with Dagster managing the workflow.
- Integrate third-party tools or legacy systems that cannot run directly in the Dagster process.
- Scale compute-heavy transformations to specialized infrastructure while keeping Dagster as the control plane.
- Build multi-environment pipelines where different stages run on different systems or cloud providers.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using Dagster and need to execute transforms or integrations outside the main process.
The active maintenance, zero external dependencies, and permissive license make it a low-friction addition to a Dagster deployment. Not relevant for non-Dagster workflows.
Install
dagster-pipes on PyPI
Before you install
Active maintenance with a release 7 days ago. No runtime dependencies, making installation straightforward. Supports Python 3.10 through 3.14.
Requires Python 3.10 or later; designed to work as part of a Dagster orchestration setup, not as a standalone tool.
License in practice
Apache-2.0 licensed under a permissive regime, allowing commercial use, modification, and distribution with minimal restrictions.
Quickstart
pip install dagster-pipes
import dagster_pipes
# Use within a Dagster asset or op to execute external transform logic
result = dagster_pipes.execute_external_transform()Verify before relying
- Specific external execution patterns and supported deployment targets beyond the toolkit description.
- Performance characteristics and scalability limits for remote execution workloads.
- Integration requirements with specific data platforms or cloud providers.
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 | None |
| Maintenance | Actively maintained 7 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 9,387,238 / month, #1,538 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: dagster_pipes-1.13.17-py3-none-any.whl
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See also dagster · dagster-cloud-cli · piper · dagster-webserver · dagster-aws · dagster-shell · dagster-dg-core · dagster-docker · dagster-dbt · kestra