apache-airflow-task-sdk
Python Task SDK for Apache Airflow DAG Authors
Decision gist · record as of 2026-08-14
Yes, if you are building or maintaining Apache Airflow DAGs in Python. The SDK is actively maintained, carries no known vulnerabilities, has low install friction, and is backed by the Apache Foundation. The substantial dependency footprint is expected for an orchestration framework integration layer. Not relevant if you are not using Airflow.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10–3.14 (not 3.15); apache-airflow-core must be installed as a runtime dependency.
- Low install friction with a pure-wheel distribution.
- Active maintenance with a release 2 days old and a recent commit history.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—standard for Apache Foundation projects.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 46,489 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 7,712,210 downloads/mo, #1,705 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-task-sdk
from apache_airflow_task_sdk import ...
# Import and use task interfaces for DAG authoring- Specific task interface classes and their usage patterns are not detailed in the excerpt.
- Whether the SDK is intended for local task development, remote execution, or both.
- Integration points with existing Airflow deployments and version compatibility constraints.
What it is and what it does
Apache Airflow Task SDK is a Python library that provides the interfaces and execution logic needed to author and run tasks within Apache Airflow DAGs. It sits between DAG authors and the Airflow core runtime, offering a structured way to define task behavior and integrate with Airflow's orchestration engine.
The package brings together a substantial dependency graph including apache-airflow-core, pydantic for validation, structlog for logging, httpx for HTTP operations, and utilities like tenacity for retries and pendulum for date handling. It supports modern Python versions (3.10 through 3.14) and is actively maintained by the Apache Foundation, with recent releases and ongoing commits. The library is positioned for developers and system administrators building data pipelines and workflow automation on top of Airflow.
Use it for
- Write custom task logic in Python for Airflow DAGs without directly modifying core Airflow code.
- Develop and test task interfaces locally before deploying to a production Airflow cluster.
- Build reusable task components and patterns for data pipeline orchestration.
- Integrate Python business logic with Airflow's scheduling, monitoring, and retry mechanisms.
- Automate data workflows, ETL pipelines, and scheduled jobs using Airflow's DAG framework.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or maintaining Apache Airflow DAGs in Python.
The SDK is actively maintained, carries no known vulnerabilities, has low install friction, and is backed by the Apache Foundation. The substantial dependency footprint is expected for an orchestration framework integration layer. Not relevant if you are not using Airflow.
Install
apache-airflow-task-sdk on PyPI
Before you install
Low install friction with a pure-wheel distribution. Active maintenance with a release 2 days old and a recent commit history. Depends on apache-airflow-core and multiple runtime packages including structured logging, validation, and async utilities.
Requires Python 3.10–3.14 (not 3.15); apache-airflow-core must be installed as a runtime dependency.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—standard for Apache Foundation projects.
Quickstart
pip install apache-airflow-task-sdk
from apache_airflow_task_sdk import ...
# Import and use task interfaces for DAG authoringVerify before relying
- Specific task interface classes and their usage patterns are not detailed in the excerpt.
- Whether the SDK is intended for local task development, remote execution, or both.
- Integration points with existing Airflow deployments and version compatibility constraints.
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 | 26 packagesapache-airflow-coreasgirefattrsbabelcolorlogfsspecgreenbackhttpximportlib-metadataisodurationjinja2jsonschemamethodtoolsmsgspecopentelemetry-apipackagingpathspecpendulumpluggypsutilpydanticpygtriepython-dateutilstructlogtenacitytyping-extensions |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 7,712,210 / month, #1,705 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_task_sdk-1.3.1-py3-none-any.whl
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See also apache-airflow · apache-airflow-client · apache-airflow-core · apache-airflow-providers-docker · apache-airflow-providers-celery · apache-airflow-providers-git · apache-superset-core · gremlinpython · dag-factory · apache-hamilton