managing-astro-local-env
# ClaudeWave: managing-astro-local-env This skill provides commands for managing local Airflow environments using Astro CLI in Docker and Standalone modes. Use it to start, stop, restart, or troubleshoot local Airflow instances, view logs, access the webserver, and manage containers or virtual environments. It covers both Docker-based development and Docker-free Standalone mode with venv configuration.
git clone --depth 1 https://github.com/astronomer/agents /tmp/managing-astro-local-env && cp -r /tmp/managing-astro-local-env/skills/managing-astro-local-env ~/.claude/skills/managing-astro-local-envSKILL.md
# Astro Local Environment This skill helps you manage your local Airflow environment using the Astro CLI. Two modes: **Docker** (default, uses containers) and **Standalone** (Docker-free, uses a local venv — requires Airflow 3 + `uv`). > **To set up a new project**, see the **setting-up-astro-project** skill. > **When Airflow is running**, use MCP tools from **authoring-dags** and **testing-dags** skills. --- ## Start / Stop / Restart (Docker) ```bash # Start local Airflow (webserver at http://localhost:8080) astro dev start # Stop containers (preserves data) astro dev stop # Kill and remove volumes (clean slate) astro dev kill # Restart all containers astro dev restart # Restart specific component astro dev restart --scheduler astro dev restart --webserver ``` **Default credentials:** admin / admin **Restart after modifying:** `requirements.txt`, `packages.txt`, `Dockerfile` > **Standalone mode?** See the next section. --- ## Standalone Mode Docker-free local development. Runs Airflow directly on your machine in a `.venv/` managed by `uv`. **Requirements:** Airflow 3 (runtime 3.x), `uv` on PATH. Not supported on Windows. > Plain `astro dev init` already pins a runtime 3.x image, so no version flag is needed. See **setting-up-astro-project** for project initialization. ### Start ```bash # One-time: set standalone as default mode astro config set dev.mode standalone # Or use the flag per invocation astro dev start --standalone ``` | Flag | Description | |------|-------------| | `--foreground` / `-f` | Stream output in foreground | | `--port` / `-p` | Override webserver port (default: 8080) | | `--no-proxy` | Disable reverse proxy | ### Stop / Kill / Restart ```bash # Stop (preserves .venv) astro dev stop # Kill (removes .venv and .astro/standalone/ — clean slate) astro dev kill # Restart (preserves .venv for fast restart, use -k to kill first) astro dev restart ``` > If you used `--standalone` on start instead of setting the config, pass `--standalone` on every subsequent command too (stop, kill, restart, bash, run, logs, etc.). **State locations:** venv in `.venv/`, database and logs in `.astro/standalone/`, DAGs from `dags/`. --- ## Reverse Proxy Run multiple Airflow projects locally without port conflicts. Works in both Docker and standalone modes. Each project gets a hostname like `<project-name>.localhost:6563`. Visit `http://localhost:6563` to see all active projects. ```bash # Check proxy status and active routes astro dev proxy status # Force-stop proxy (auto-restarts on next astro dev start) astro dev proxy stop ``` | Config | Command | |--------|---------| | Change proxy port | `astro config set proxy.port <port>` | | Disable per-start | `astro dev start --no-proxy` | Default proxy port: **6563** --- ## Check Status ```bash astro dev ps ``` --- ## View Logs ```bash # All logs astro dev logs # Specific component astro dev logs --scheduler astro dev logs --webserver # Follow in real-time astro dev logs -f ``` **Standalone:** `astro dev logs` works the same but shows a unified log (no per-component filtering). --- ## Run Airflow CLI Commands ```bash # Open a shell with Airflow environment astro dev bash # Run Airflow CLI commands astro dev run airflow info astro dev run airflow dags list ``` **Standalone:** Same commands work — `bash` opens a venv-activated shell, `run` executes in the venv. --- ## Querying the Airflow API Use `astro api airflow` to query a running local Airflow instance. Prefer operation IDs over URL paths. **Defaults:** localhost:8080, admin/admin (auto-detected). Override with `--api-url`, `--username`, `--password`. ### Discovery ```bash # List all endpoints astro api airflow ls # Filter by keyword astro api airflow ls dags astro api airflow ls task # Show params and schema for an operation astro api airflow describe get_dag ``` ### Key Flags | Flag | Purpose | |------|---------| | `-p key=value` | Path parameters | | `-F key=value` | Body/query fields (auto-converts booleans/numbers) | | `-q` / `--jq` | jq filter on response | | `--paginate` | Fetch all pages | | `-X` / `--method` | Override HTTP method | | `--generate` | Output curl command instead of executing | ### DAGs ```bash # List all DAGs astro api airflow get_dags # Filter by pattern (SQL LIKE — use % wildcards) astro api airflow get_dags -F dag_id_pattern=%etl% # Get a specific DAG astro api airflow get_dag -p dag_id=my_dag # Get full details (schedule, params, etc.) astro api airflow get_dag_details -p dag_id=my_dag # Pause / unpause astro api airflow patch_dag -p dag_id=my_dag -F is_paused=true astro api airflow patch_dag -p dag_id=my_dag -F is_paused=false # View DAG source code astro api airflow get_dag_source -p dag_id=my_dag # Check import errors astro api airflow get_import_errors ``` ### DAG Runs ```bash # List runs for a DAG astro api airflow get_dag_runs -p dag_id=my_dag # Trigger a run astro api airflow trigger_dag_run -p dag_id=my_dag # Trigger with config astro api airflow trigger_dag_run -p dag_id=my_dag -F conf[key]=value # Get a specific run astro api airflow get_dag_run -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 # Clear (re-run) a DAG run astro api airflow clear_dag_run -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 -F dry_run=false ``` ### Task Instances ```bash # List task instances for a run astro api airflow get_task_instances -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 # Use ~ as wildcard (all DAGs or all runs) astro api airflow get_task_instances -p dag_id=my_dag -p dag_run_id=~ # Get a specific task instance astro api airflow get_task_instance -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 -p task_id=extract # Clear/retry failed tasks astro api airflow post_clear_task_instances -p dag_id=my_dag \ -F dag_run_id=manual__2026-04-07 -F only_failed=true -F dry_run=false # Get task logs astro api airflow get_log -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 \ -p task_id=extrac
Add a new method to both Airflow adapters
Add a new MCP tool to server.py
Verify code works with both Airflow 2.x and 3.x
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.
Use when the user needs human-in-the-loop workflows in Airflow (approval/reject, form input, or human-driven branching). Covers ApprovalOperator, HITLOperator, HITLBranchOperator, HITLEntryOperator, HITLTrigger. Requires Airflow 3.1+. Does not cover AI/LLM calls (see airflow-ai).
Build Airflow 3.1+ plugins that embed FastAPI apps, custom UI pages, React components, middleware, macros, and operator links directly into the Airflow UI. Use this skill whenever the user wants to create an Airflow plugin, add a custom UI page or nav entry to Airflow, build FastAPI-backed endpoints inside Airflow, serve static assets from a plugin, embed a React app in the Airflow UI, add middleware to the Airflow API server, create custom operator extra links, or call the Airflow REST API from inside a plugin. Also trigger when the user mentions AirflowPlugin, fastapi_apps, external_views, react_apps, plugin registration, or embedding a web app in Airflow 3.1+. If someone is building anything custom inside Airflow 3.1+ that involves Python and a browser-facing interface, this skill almost certainly applies.
Queries, manages, and troubleshoots Apache Airflow using the af CLI. Covers listing DAGs, triggering runs, reading task logs, diagnosing failures, debugging DAG import errors, checking connections, variables, pools, and monitoring health. Also routes to sub-skills for writing DAGs, debugging, deploying, and migrating Airflow 2 to 3. Use when user mentions "Airflow", "DAG", "DAG run", "task log", "import error", "parse error", "broken DAG", or asks to "trigger a pipeline", "debug import errors", "check Airflow health", "list connections", "retry a run", or any Airflow operation. Do NOT use for warehouse/SQL analytics on Airflow metadata tables — use analyzing-data instead.
Queries data warehouse and answers business questions about data. Handles questions requiring database/warehouse queries including "who uses X", "how many Y", "show me Z", "find customers", "what is the count", data lookups, metrics, trends, or SQL analysis.