Airflow Plugins

Airflow 3 Plugins

Airflow 3 plugins let you embed FastAPI apps, React UIs, middleware, macros, operator buttons, and custom timetables directly into the Airflow process. No sidecar, no extra server.

CRITICAL: Plugin components (fastapi_apps, react_apps, external_views) require Airflow 3.1+. NEVER import `flask`, `flask_appbuilder`, or use `appbuilder_views` / `flask_blueprints` — these are Airflow 2 patterns and will not work in Airflow 3. If existing code uses them, rewrite the entire registration block using FastAPI.

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Security: FastAPI plugin endpoints are not automatically protected by Airflow auth. If your endpoints need to be private, implement authentication explicitly using FastAPI's security utilities.

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Restart required: Changes to Python plugin files require restarting the API server. Static file changes (HTML, JS, CSS) are picked up immediately. Set AIRFLOW__CORE__LAZY_LOAD_PLUGINS=False during development to load plugins at startup rather than lazily.

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Relative paths always: In external_views, href must have no leading slash. In HTML and JavaScript, use relative paths for all assets and fetch() calls. Absolute paths break behind reverse proxies.

Before writing any code, verify

1. Am I using fastapi_apps / FastAPI — not appbuilder_views / Flask? 2. Are all HTML/JS asset paths and fetch() calls relative (no leading slash)? 3. Are all synchronous SDK or SQLAlchemy calls wrapped in asyncio.to_thread()? 4. Do the static/ and assets/ directories exist before the FastAPI app mounts them? 5. If the endpoint must be private, did I add explicit FastAPI authentication?

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Step 1: Choose plugin components

A single plugin class can register multiple component types at once.

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Step 2: Plugin registration skeleton

Project file structure

Give each plugin its own subdirectory under plugins/ — this keeps the Python file, static assets, and templates together and makes multi-plugin projects manageable:

plugins/
  my-plugin/
    plugin.py       # AirflowPlugin subclass — auto-discovered by Airflow
    static/
      index.html
      app.js
    assets/
      icon.svg

BASE_DIR = Path(__file__).parent in plugin.py resolves to plugins/my-plugin/ — static and asset paths will be correct relative to that. Create the subdirectory and any static/assets folders before starting Airflow, or StaticFiles will raise on import.

from pathlib import Path
from airflow.plugins_manager import AirflowPlugin
from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse

BASE_DIR = Path(__file__).parent

app = FastAPI(title="My Plugin")

# Both directories must exist before Airflow starts or FastAPI raises on import
app.mount("/static", StaticFiles(directory=BASE_DIR / "static"), name="static")
app.mount("/assets", StaticFiles(directory=BASE_DIR / "assets"), name="assets")


class MyPlugin(AirflowPlugin):
    name = "my_plugin"

    fastapi_apps = [
        {
            "app": app,
            "url_prefix": "/my-plugin",   # plugin available at {AIRFLOW_HOST}/my-plugin/
            "name": "My Plugin",
        }
    ]

    external_views = [
        {
            "name": "My Plugin",
            "href": "my-plugin/ui",              # NO leading slash — breaks on Astro and reverse proxies
            "destination": "nav",                # see locations table below
            "category": "browse",                # nav bar category (nav destination only)
            "url_route": "my-plugin",            # unique route name (required for React apps)
            "icon": "/my-plugin/static/icon.svg" # DOES use a leading slash — served by FastAPI
        }
    ]

External view locations

Nav bar categories (destination: "nav")

Set "category" to place the link under a specific nav group: "browse", "admin", or omit for top-level.

External URLs and minimal plugins

href can be a relative path to an internal endpoint ("my-plugin/ui") or a full external URL. A plugin with only external_views and no fastapi_apps is valid — no backend needed for a simple link or tab:

from airflow.plugins_manager import AirflowPlugin

class LearnViewPlugin(AirflowPlugin):
    name = "learn_view_plugin"

    external_views = [
        {
            "name": "Learn Airflow 3",
            "href": "https://www.astronomer.io/docs/learn",
            "destination": "dag",   # adds a tab to every Dag page
            "url_route": "learn"
        }
    ]

The no-leading-slash rule applies to internal paths only — full https:// URLs are fine.

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Step 3: Serve the UI entry point

@app.get("/ui", response_class=FileResponse)
async def serve_ui():
    return FileResponse(BASE_DIR / "static" / "index.html")

In HTML, always use relative paths. Absolute paths break when Airflow is mounted at a sub-path:

<!-- correct -->
<link rel="stylesheet" href="static/app.css" />
<script src="static/app.js?v=20240315"></script>

<!-- breaks behind a reverse proxy -->
<script src="/my-plugin/static/app.js"></script>

Same rule in JavaScript:

fetch('api/dags')           // correct — relative to current page
fetch('/my-plugin/api/dags') // breaks on Astro and sub-path deploys

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Step 4: Call the Airflow API from your plugin

Only needed if your plugin calls the Airflow REST API. Plugins that only serve static files, register external_views, or use direct DB access do not need this step — skip to Step 5 or Step 6.

Add the dependency

Only if REST API communication is being implemented: add apache-airflow-client to the project's dependencies. Check which file exists and act accordingly:

Use apache-airflow-client to talk to Airflow's own REST API. The SDK is synchronous but FastAPI routes are async — never call blocking SDK methods directly inside async def or you will stall the event loop and freeze all concurrent requests.

JWT token management

Cache one token per process. Refresh 5 minutes before the 1-hour expiry. Use double-checked locking so multiple concurrent requests don't all race to refresh simultaneously:

Replace MYPLUGIN_ with a short uppercase prefix derived from the plugin name (e.g. if the plugin is called "Trip Analyzer", use TRIP_ANALYZER_). If no plugin name has been given yet, ask the user before writing env var names.

import asyncio
import os
import threading
import time
import airflow_client.client as airflow_sdk
import requests

AIRFLOW_HOST  = os.environ.get("MYPLUGIN_HOST",     "http://localhost:8080")
AIRFLOW_USER  = os.environ.get("MYPLUGIN_USERNAME", "admin")
AIRFLOW_PASS  = os.environ.get("MYPLUGIN_PASSWORD", "admin")
AIRFLOW_TOKEN = os.environ.get("MYPLUGIN_TOKEN")    # Astronomer Astro: Deployment API token

_cached_token: str | None = None
_token_expires_at: float  = 0.0
_token_lock = threading.Lock()


def _fetch_fresh_token() -> str:
    """Exchange username/password for a JWT via Airflow's auth endpoint."""
    response = requests.post(
        f"{AIRFLOW_HOST}/auth/token",
        json={"username": AIRFLOW_USER, "password": AIRFLOW_PASS},
        timeout=10,
    )
    response.raise_for_status()
    return response.json()["access_token"]


def _get_token() -> str:
    # Astronomer Astro production: use static Deployment API token directly
    if AIRFLOW_TOKEN:
        return AIRFLOW_TOKEN
    global _cached_token, _token_expires_at
    now = time.monotonic()
    # Fast path — no lock if still valid
    if _cached_token and now < _token_expires_at:
        return _cached_token
    # Slow path — one thread refreshes, others wait
    with _token_lock:
        if _cached_token and now < _token_expires_at:
            return _cached_token
        _cached_token = _fetch_fresh_token()
        _token_expires_at = now + 55 * 60  # refresh 5 min before 1-hour expiry
    return _cached_token


def _make_config() -> airflow_sdk.Configuration:
    config = airflow_sdk.Configuration(host=AIRFLOW_HOST)
    config.access_token = _get_token()
    return config

After implementing auth, tell the user:

• Local development: set MYPLUGIN_USERNAME and MYPLUGIN_PASSWORD in .env — JWT exchange happens automatically.
• Astronomer Astro (production): create a Deployment API token and set it as MYPLUGIN_TOKEN — the JWT exchange is skipped entirely:

1. Astro UI → open the Deployment → Access → API Tokens → + Deployment API Token 2. Copy the token value (shown only once) 3. astro deployment variable create MYPLUGIN_TOKEN=<token>

MYPLUGIN_USERNAME and MYPLUGIN_PASSWORD are not needed on Astro.

Wrapping SDK calls with asyncio.to_thread

from fastapi import HTTPException
from airflow_client.client.api import DAGApi

@app.get("/api/dags")
async def list_dags():
    try:
        def _fetch():
            with airflow_sdk.ApiClient(_make_config()) as client:
                return DAGApi(client).get_dags(limit=100).dags
        dags = await asyncio.to_thread(_fetch)
        return [{"dag_id": d.dag_id, "is_paused": d.is_paused, "timetable_summary": d.timetable_summary} for d in dags]
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

API field names: Never guess response field names — verify against the REST API reference. Key DAGResponse fields: dag_id, dag_display_name, description, is_paused, timetable_summary, timetable_description, fileloc, owners, tags.

The pattern is always: define a plain inner def _fetch() with all SDK logic, then await asyncio.to_thread(_fetch).

Alternative: Direct database access

Warning — use with caution and tell the user. The Airflow metadb is not a public interface. Direct writes or poorly-formed queries can corrupt scheduler state. Whenever you use this pattern, explicitly tell the user: "This accesses Airflow's internal database directly. The internal models are not part of the public API, can change between Airflow versions, and incorrect queries can cause issues in the metadb. Prefer apache-airflow-client unless the operation is not exposed via the REST API."

Since FastAPI plugin endpoints run inside the API server process (not in a task worker), they have direct access to Airflow's internal SQLAlchemy models — no HTTP round-trip or JWT needed. Use only for read operations not exposed via the REST API, or when the extra HTTP overhead genuinely matters. Always wrap DB calls in asyncio.to_thread() — SQLAlchemy queries are blocking.

from airflow.models import DagBag, DagModel
from airflow.utils.db import provide_session

@app.get("/api/dags/status")
async def dag_status():
    def _fetch():
        @provide_session
        def _query(session=None):
            dagbag = DagBag()
            paused = sum(
                1 for dag_id in dagbag.dags
                if (m := session.query(DagModel).filter(DagModel.dag_id == dag_id).first())
                and m.is_paused
            )
            return {"total": len(dagbag.dags), "paused": paused}
        return _query()
    return await asyncio.to_thread(_fetch)

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Step 5: Common API endpoint patterns

If you need an SDK method or field not shown in the examples below, verify it before generating code — do not guess. Either run python3 -c "from airflow_client.client.api import <Class>; print([m for m in dir(<Class>) if not m.startswith('_')])" in any environment where the SDK is installed, or search the `apache/airflow-client-python` repo for the class definition.

from airflow_client.client.api import DAGApi, DagRunApi
from airflow_client.client.models import TriggerDAGRunPostBody, DAGPatchBody


@app.post("/api/dags/{dag_id}/trigger")
async def trigger_dag(dag_id: str):
    def _run():
        with airflow_sdk.ApiClient(_make_config()) as client:
            return DagRunApi(client).trigger_dag_run(dag_id, TriggerDAGRunPostBody())
    result = await asyncio.to_thread(_run)
    return {"run_id": result.dag_run_id, "state": normalize_state(result.state)}


@app.patch("/api/dags/{dag_id}/pause")
async def toggle_pause(dag_id: str, is_paused: bool):
    def _run():
        with airflow_sdk.ApiClient(_make_config()) as client:
            DAGApi(client).patch_dag(dag_id, DAGPatchBody(is_paused=is_paused))
    await asyncio.to_thread(_run)
    return {"dag_id": dag_id, "is_paused": is_paused}


@app.delete("/api/dags/{dag_id}")
async def delete_dag(dag_id: str):
    def _run():
        with airflow_sdk.ApiClient(_make_config()) as client:
            DAGApi(client).delete_dag(dag_id)
    await asyncio.to_thread(_run)
    return {"deleted": dag_id}


def normalize_state(raw) -> str:
    """Convert SDK enum objects to plain strings before sending to the frontend."""
    if raw is None:
        return "never_run"
    return str(raw).lower()

DAG runs, task instances, and logs

These are the most common calls beyond basic DAG CRUD. For anything not shown here, consult the REST API reference for available endpoints and the matching Python SDK class/method names.

from airflow_client.client.api import DagRunApi, TaskInstanceApi

# Latest run for a DAG
@app.get("/api/dags/{dag_id}/runs/latest")
async def latest_run(dag_id: str):
    def _fetch():
        with airflow_sdk.ApiClient(_make_config()) as client:
            runs = DagRunApi(client).get_dag_runs(dag_id, limit=1, order_by="-start_date").dag_runs
            return runs[0] if runs else None
    run = await asyncio.to_thread(_fetch)
    if not run:
        return {"state": "never_run"}
    return {"run_id": run.dag_run_id, "state": normalize_state(run.state)}


# Task instances for a specific run
@app.get("/api/dags/{dag_id}/runs/{run_id}/tasks")
async def task_instances(dag_id: str, run_id: str):
    def _fetch():
        with airflow_sdk.ApiClient(_make_config()) as client:
            return TaskInstanceApi(client).get_task_instances(dag_id, run_id).task_instances
    tasks = await asyncio.to_thread(_fetch)
    return [{"task_id": t.task_id, "state": normalize_state(t.state)} for t in tasks]


# Task log (try_number starts at 1)
@app.get("/api/dags/{dag_id}/runs/{run_id}/tasks/{task_id}/logs/{try_number}")
async def task_log(dag_id: str, run_id: str, task_id: str, try_number: int):
    def _fetch():
        with airflow_sdk.ApiClient(_make_config()) as client:
            return TaskInstanceApi(client).get_log(
                dag_id, run_id, task_id, try_number, map_index=-1
            )
    result = await asyncio.to_thread(_fetch)
    return {"log": result.content if hasattr(result, "content") else str(result)}

Streaming proxy

Use StreamingResponse to proxy binary content from an external URL through the plugin — useful when the browser can't fetch the resource directly (CORS, auth, etc.):

import requests
from starlette.responses import StreamingResponse

@app.get("/api/files/{filename}")
async def proxy_file(filename: str):
    def _stream():
        r = requests.get(f"https://files.example.com/{filename}", stream=True)
        r.raise_for_status()
        return r
    response = await asyncio.to_thread(_stream)
    return StreamingResponse(
        response.iter_content(chunk_size=8192),
        media_type="application/octet-stream",
        headers={"Content-Disposition": f'attachment; filename="{filename}"'},
    )

Note that requests.get() is blocking — fetch in asyncio.to_thread so the event loop isn't stalled while waiting for the remote server.

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Step 6: Other plugin component types

Macros

Macros are loaded by the scheduler (and DAG processor), not the API server. Restart the scheduler after changes.

from airflow.plugins_manager import AirflowPlugin

def format_confidence(confidence: float) -> str:
    return f"{confidence * 100:.2f}%"

class MyPlugin(AirflowPlugin):
    name = "my_plugin"
    macros = [format_confidence]

Use in any templated field — including with XCom:

{{ macros.my_plugin.format_confidence(0.95) }}

{{ macros.my_plugin.format_confidence(ti.xcom_pull(task_ids='score_task')['confidence']) }}

The naming pattern is always macros.{plugin_name}.{function_name}.

Middleware

Middleware applies to all Airflow API requests, including the built-in REST API and any FastAPI plugins. Use sparingly and filter requests explicitly if needed:

from starlette.middleware.base import BaseHTTPMiddleware
from fastapi import Request, Response

class AuditMiddleware(BaseHTTPMiddleware):
    async def dispatch(self, request: Request, call_next) -> Response:
        # runs before every request to the Airflow API server
        response = await call_next(request)
        return response

class MyPlugin(AirflowPlugin):
    name = "my_plugin"
    fastapi_root_middlewares = [
        {"middleware": AuditMiddleware, "args": [], "kwargs": {}, "name": "Audit"}
    ]

Operator extra links

from airflow.sdk.bases.operatorlink import BaseOperatorLink

class MyDashboardLink(BaseOperatorLink):
    name = "Open in Dashboard"

    def get_link(self, operator, *, ti_key, **context) -> str:
        return f"https://my-dashboard.example.com/tasks/{ti_key.task_id}"

class MyPlugin(AirflowPlugin):
    name = "my_plugin"
    global_operator_extra_links = [MyDashboardLink()]  # appears on every task
    # operator_extra_links = [MyDashboardLink()]       # attach to specific operator instead

React apps

React apps are embedded as JavaScript bundles served via FastAPI. The bundle must expose itself as a global variable matching the plugin name:

// In your bundle (e.g. my-app.js)
globalThis['My Plugin'] = MyComponent;   // matches plugin name
globalThis.AirflowPlugin = MyComponent;  // fallback Airflow looks for

class MyPlugin(AirflowPlugin):
    name = "my_plugin"
    fastapi_apps = [{"app": app, "url_prefix": "/my-plugin", "name": "My Plugin"}]
    react_apps = [
        {
            "name": "My Plugin",
            "bundle_url": "/my-plugin/my-app.js",
            "destination": "nav",
            "category": "browse",
            "url_route": "my-plugin",
        }
    ]

The same bundle can be registered to multiple destinations by adding multiple entries — each needs a unique url_route:

react_apps = [
    {"name": "My Widget", "bundle_url": "/my-plugin/widget.js", "destination": "nav",  "url_route": "my-widget-nav"},
    {"name": "My Widget", "bundle_url": "/my-plugin/widget.js", "destination": "dag",  "url_route": "my-widget-dag"},
]

React app integration is experimental in Airflow 3.1. Interfaces may change in future releases.

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Step 7: Environment variables and deployment

Never hardcode credentials:

AIRFLOW_HOST = os.environ.get("MYPLUGIN_HOST",     "http://localhost:8080")
AIRFLOW_USER = os.environ.get("MYPLUGIN_USERNAME", "admin")
AIRFLOW_PASS = os.environ.get("MYPLUGIN_PASSWORD", "admin")

Local Astro CLI:

# .env
MYPLUGIN_HOST=http://localhost:8080
MYPLUGIN_USERNAME=admin
MYPLUGIN_PASSWORD=admin

astro dev restart              # required after any Python plugin change

# Check logs by component (Astro CLI):
astro dev logs --api-server    # FastAPI apps, external_views — plugin import errors show here
astro dev logs --scheduler     # macros, timetables, listeners, operator links
astro dev logs --dag-processor # DAG parsing errors

# Non-Astro:
airflow plugins                # CLI — lists all loaded plugins

Production Astronomer:

astro deployment variable create --deployment-id <id> MYPLUGIN_HOST=https://airflow.example.com

Auto-reload during development (skips lazy loading):

AIRFLOW__CORE__LAZY_LOAD_PLUGINS=False

Cache busting for static files after deploy:

<script src="static/app.js?v=20240315-1"></script>

Verify the plugin loaded: open Admin > Plugins in the Airflow UI.

OpenAPI docs are auto-generated for FastAPI plugins:

• Swagger UI: {AIRFLOW_HOST}/{url_prefix}/docs
• OpenAPI JSON: {AIRFLOW_HOST}/{url_prefix}/openapi.json

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Common pitfalls

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References

• Airflow plugins documentation
• Airflow REST API reference — full endpoint list with SDK class/method names
• Astronomer: Using Airflow plugins