Stardag

Declarative and composable DAGs for Python.

Stardag provides a clean Python API for representing persistently stored assets, the code that produces them, and their dependencies as a declarative Directed Acyclic Graph (DAG). It is a spiritual—but highly modernized—descendant of Luigi, designed for iterative data and ML workflows.

Built on Pydantic, Stardag uses expressive type annotations to reduce boilerplate and make task I/O contracts explicit—enabling composable tasks and pipelines while maintaining a fully declarative specification of every produced asset.

Quick Example

import stardag as sd

@sd.task
def get_range(limit: int) -> list[int]:
    return list(range(limit))

@sd.task
def get_sum(integers: sd.Depends[list[int]]) -> int:
    return sum(integers)

# Declarative DAG specification - no computation yet
sum_task = get_sum(integers=get_range(limit=4))

# Materialize all tasks' targets
sd.build(sum_task)

# Load results
assert sum_task.load() == 6
assert sum_task.integers.load() == [0, 1, 2, 3]

Installation

pip install stardag

Or with uv:

uv add stardag

Optional extras:

pip install stardag[s3]      # S3 storage support
pip install stardag[prefect] # Prefect integration
pip install stardag[modal]   # Modal integration

Documentation

Read the docs for tutorials, guides, and API reference.

Getting Started — Installation and first steps
Core Concepts — Tasks, targets, dependencies
How-To Guides — Integrations with Prefect, Modal
Configuration — Profiles, CLI reference

Stardag Cloud

Stardag Cloud provides optional services for team collaboration and monitoring:

Web UI — Dashboard for build monitoring and task inspection
API Service — Task tracking and coordination across distributed builds

The SDK works fully standalone—the platform adds value for teams needing shared visibility and coordination.

Why Stardag?

Composability — Task instances as first-class parameters enable loose coupling and reusability
Declarative — Full DAG specification before execution; inspect, serialize, and reason about pipelines
Deterministic — Parameter hashing gives each task a unique, reproducible ID and output path
Pydantic-native — Tasks are Pydantic models with full validation and serialization support
Framework-agnostic — Integrate with Prefect, Modal, or run standalone

Release files for stardag 0.27.0rc1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for stardag 0.27.0rc1
File	Size	Uploaded
stardag-0.27.0rc1.tar.gz	849.2 kB	Sep 25, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for stardag 0.27.0rc1
File	Interpreter	ABI	Platform	Reset
stardag-0.27.0rc1-py3-none-any.whl 464.2 kB Sep 25, 2026	Python 3	none	any	Details

Total release size: 1.3 MB

Release files / stardag-0.27.0rc1.tar.gz

Download URL	stardag-0.27.0rc1.tar.gz
Size	849.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`4a1a9a72f0a630289f74403bccc9c8b5865637e78219a0e94f3c90040b5407aa`
BLAKE2b-256 checksum How to use checksums	`0c0aee6aadf6d8a11f317e2bd4c802361b5d5c660b54f52e8480e3cb9d20933a`
Upload date	Sep 25, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/stardag-dev/stardag
Publishing commit: github.com/stardag-dev/stardag/tree/13891dd159be081c12d7992b2c29b92ed7d150b9

Workflow

Publishing configuration: github.com/stardag-dev/stardag/blob/13891dd159be081c12d7992b2c29b92ed7d150b9/.github/workflows/publish.yml
Publishing logs: github.com/stardag-dev/stardag/actions/runs/36117603687/attempts/1

Artifact

Subject: stardag-0.27.0rc1.tar.gz
SHA-256 checksum: 4a1a9a72f0a630289f74403bccc9c8b5865637e78219a0e94f3c90040b5407aa Verifying attestations

Release files / stardag-0.27.0rc1-py3-none-any.whl

Download URL	stardag-0.27.0rc1-py3-none-any.whl
Size	464.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`d3743f96a77fb78901a035b0f763475cc5fde9eec37b11017fe2fe0853841f47`
BLAKE2b-256 checksum How to use checksums	`22217b53bff44b9a7763851e609bf1f1b2f4d84f52a11402ca3176db6714bbad`
Upload date	Sep 25, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/stardag-dev/stardag
Publishing commit: github.com/stardag-dev/stardag/tree/13891dd159be081c12d7992b2c29b92ed7d150b9

Workflow

Publishing configuration: github.com/stardag-dev/stardag/blob/13891dd159be081c12d7992b2c29b92ed7d150b9/.github/workflows/publish.yml
Publishing logs: github.com/stardag-dev/stardag/actions/runs/36117603687/attempts/1

Artifact

Subject: stardag-0.27.0rc1-py3-none-any.whl
SHA-256 checksum: d3743f96a77fb78901a035b0f763475cc5fde9eec37b11017fe2fe0853841f47 Verifying attestations