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Agent Skill · 研究检索

airflow-plugins(气流插件)

airflow-plugins 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

airflow-plugins 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 20,356。

总安装 5,242周安装 210GitHub Stars 349下载 1,697核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:airflow-plugins(气流插件)
来源仓库:https://github.com/astronomer/agents
仓库路径:skills/airflow-plugins
安装命令:
npx skills add https://github.com/astronomer/agents --skill airflow-plugins
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/astronomer/agents --skill airflow-plugins

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

airflow-plugins 支持在 Airflow 3+ 中嵌入 FastAPI 应用和 React UI 组件。适用于需要在调度界面内嵌 Web 服务或自定义操作按钮的场景。提供插件注册、路由保护和外部视图集成等完整解决方案。要求 Airflow 3.1+ 版本,不支持 Flask 等传统框架模式。

建议将插件组件限制在可信代码范围内,防止安全风险扩散。

来源仓库内路径:skills/airflow-plugins

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/astronomer/agents --skill airflow-plugins;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

airflow-plugins 怎么安装?

在终端执行 npx skills add https://github.com/astronomer/agents --skill airflow-plugins。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

airflow-plugins 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

airflow-plugins 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

airflow-plugins 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

airflow-plugins 用的人多吗?

公开数据是累计安装 5,242 次,近一周安装 210 次,下载 1,697 次,GitHub 349 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

airflow-plugins 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
airflow-plugins

气流插件 · 本页

5,242349接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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. 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. 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. 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?

Step 1: Choose plugin components

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

ComponentWhat it doesField
Custom API endpointsFastAPI app mounted in Airflow processfastapi_apps
Nav / page linkEmbeds a URL as an iframe or links outexternal_views
React componentCustom React app embedded in Airflow UIreact_apps
API middlewareIntercepts all Airflow API requests/responsesfastapi_root_middlewares
Jinja macrosReusable Python functions in DAG templatesmacros
Task instance buttonExtra link button in task Detail viewoperator_extra_links / global_operator_extra_links
Custom timetableCustom scheduling logictimetables
Event hooksListener callbacks for Airflow eventslisteners

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

destinationWhere it appears
"nav"Left navigation bar (also set category)
"dag"Extra tab on every Dag page
"dag_run"Extra tab on every Dag run page
"task"Extra tab on every task page
"task_instance"Extra tab on every task instance page

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.


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

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:

File foundAction
requirements.txtAppend apache-airflow-client
pyproject.toml (uv / poetry)uv add apache-airflow-client or poetry add apache-airflow-client
None of the aboveTell the user: "Add apache-airflow-client to your dependencies before running the plugin."

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: MYPLUGIN_USERNAME and MYPLUGIN_PASSWORD are not needed on Astro.

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>

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)

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.


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.

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

Common pitfalls

ProblemCauseFix
Nav link goes to 404Leading / in href"my-plugin/ui" not "/my-plugin/ui"
Nav icon not showingMissing / in iconicon takes an absolute path: "/my-plugin/static/icon.svg"
Event loop freezes under loadSync SDK called directly in async defWrap with asyncio.to_thread()
401 errors after 1 hourJWT expires with no refreshUse the 5-minute pre-expiry refresh pattern
StaticFiles raises on startupDirectory missingCreate assets/ and static/ before starting
Plugin not showing upPython file changed without restartastro dev restart
Endpoints accessible without loginFastAPI apps are not auto-authenticatedAdd FastAPI security (e.g. OAuth2, API key) if endpoints must be private
Middleware affecting wrong routesMiddleware applies to all API trafficFilter by request.url.path inside dispatch()
JS fetch() breaks on AstroAbsolute path in fetch()Always use relative paths: fetch('api/dags')

References

平台分布

Codex

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Gemini CLI

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安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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