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airflow-adapter

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Aktualisiert2. März 2026 um 20:32

Airflow adapter pattern for v2/v3 API compatibility. Use when working with adapters, version detection, or adding new API methods that need to work across Airflow 2.x and 3.x.

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astronomer

astronomer/agents

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SoftwareentwicklerInformatik- und Mathematikberufe·SOC 15-1252

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SKILL.md

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name	airflow-adapter
description	Airflow adapter pattern for v2/v3 API compatibility. Use when working with adapters, version detection, or adding new API methods that need to work across Airflow 2.x and 3.x.

Airflow Adapter Pattern

Enables compatibility with both Airflow 2.x (/api/v1) and 3.x (/api/v2).

Architecture

MCP Tool → _get_adapter() → AirflowV2Adapter or AirflowV3Adapter → Airflow API

Version is auto-detected at startup.

Key Files

adapters/base.py - Abstract interface
adapters/airflow_v2.py - Airflow 2.x (/api/v1)
adapters/airflow_v3.py - Airflow 3.x (/api/v2)

Related Files

@api-differences.md - V2 vs V3 field/endpoint differences
@patterns.md - Implementation patterns

Quick Reference

adapter = _get_adapter()
dags = adapter.list_dags(limit=100)
run = adapter.trigger_dag_run("my_dag", conf={"key": "value"})

Mehr aus diesem Repository

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authoring-java-sdk-tasks

astronomer/agents

Writes Airflow task logic in Java, Kotlin, or any JVM language using the Airflow Java SDK. Use when the user wants to implement Airflow tasks in Java/JVM, asks about `@Builder.Dag`/`@Builder.Task`/`@Builder.XCom`, the `Task`/`BundleBuilder` interfaces, reading connections/variables/XComs from Java, the JSON-to-Java type mapping, or logging from Java tasks. This skill covers the Java-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building/shipping the bundle see deploying-java-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.

2026-07-16411

authoring-language-sdk-tasks

astronomer/agents

The language-neutral foundation for Airflow language SDKs — implement task logic in a non-Python language while the DAG stays in Python. Use when the user wants to run an Airflow task in another language (Java, Kotlin, Go, or other JVM/native languages), asks how the Python `@task.stub` pairs with native task code, how task/DAG IDs must match across the two sides, how data passes via XCom as JSON, or which language SDKs exist. This skill owns the shared Python-stub pattern and conceptual model; for a specific language's native API, build, and runtime, use that language's skill (e.g. authoring-java-sdk-tasks, authoring-go-sdk-tasks).

2026-07-16411

configuring-airflow-language-sdks

astronomer/agents

Configures Airflow to run language SDK tasks (Java, Go, and future native SDKs) — register a coordinator, map a queue to it, ensure the runtime/artifact on workers, and tune coordinator options. Use when the user wants Airflow to route a queue to a native-language coordinator, asks about the `[sdk]` `coordinators`/`queue_to_coordinator` settings, `AIRFLOW__SDK__COORDINATORS`, `jars_root`, `executables_root` or other coordinator `kwargs`, `task_startup_timeout`, or why their native tasks aren't being picked up. Covers the shared routing mechanism plus per-coordinator options (e.g. JavaCoordinator, ExecutableCoordinator).

2026-07-16411

deploying-java-sdk-bundles

astronomer/agents

Builds and deploys compiled Airflow Java SDK bundles so workers can run them. Use when the user wants to package a JVM task bundle into a JAR, asks about the `org.apache.airflow.sdk` Gradle plugin, `./gradlew bundle`, the Maven shade/BOM setup, fat vs thin JARs, the logging integration artifacts (JPL, SLF4J, Log4j 2, JUL), preview/snapshot builds, or getting the JAR onto an Airflow worker (Docker, Kubernetes, or Astro). For the task code see authoring-java-sdk-tasks; for the Airflow coordinator settings see configuring-airflow-language-sdks.

2026-07-16411

migrating-dagster-to-airflow

astronomer/agents

Guide for migrating Dagster projects to Apache Airflow 3 on Astro. Use when the user mentions migrating, converting, or porting Dagster (or Dagster+) code to Airflow or Astro, wants to plan or assess such a migration, or asks what a Dagster construct maps to in Airflow. Covers assets, partitions, schedules, sensors, declarative automation, resources, IO managers, ops/jobs, dbt, Pipes, Components, and Dagster+ platform config. Always load this skill as the first step for any Dagster-to-Airflow request.

2026-07-13411

authoring-go-sdk-tasks

astronomer/agents

Writes Airflow task logic in Go using the Airflow Go SDK. Use when the user wants to implement Airflow tasks in Go, asks about `BundleProvider`/`RegisterDags`, the `bundlev1` Registry/Dag interfaces, registering Go tasks (`AddTask`/`AddTaskWithName`), dependency injection by parameter type (`context.Context`, `sdk.TIRunContext`, `*slog.Logger`, `sdk.Client`), or reading connections/variables/XComs from Go. This skill covers the Go-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building/packing/shipping the bundle see deploying-go-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.

2026-07-10411

name	airflow-adapter
description	Airflow adapter pattern for v2/v3 API compatibility. Use when working with adapters, version detection, or adding new API methods that need to work across Airflow 2.x and 3.x.

Airflow Adapter Pattern

Enables compatibility with both Airflow 2.x (/api/v1) and 3.x (/api/v2).

Architecture

MCP Tool → _get_adapter() → AirflowV2Adapter or AirflowV3Adapter → Airflow API

Version is auto-detected at startup.

Key Files

adapters/base.py - Abstract interface
adapters/airflow_v2.py - Airflow 2.x (/api/v1)
adapters/airflow_v3.py - Airflow 3.x (/api/v2)

Related Files

@api-differences.md - V2 vs V3 field/endpoint differences
@patterns.md - Implementation patterns

Quick Reference

adapter = _get_adapter()
dags = adapter.list_dags(limit=100)
run = adapter.trigger_dag_run("my_dag", conf={"key": "value"})