Make requests to the Airflow REST API

You can use the Airflow REST API to automate Airflow workflows in your Deployments on Astro. For example, you can externally trigger a DAG run without accessing your Deployment directly by making an HTTP request in Python or cURL to the dagRuns endpoint in the Airflow REST API.

To test Airflow API calls in a local Airflow environment running with the Astro CLI, see Troubleshoot your local Airflow environment.

info

Updates to the Airflow REST API are released in new Airflow versions and new releases don’t have a separate release cycle or versioning scheme. To take advantage of specific Airflow REST API functionality, you might need to upgrade Astro Runtime. See Upgrade Runtime and the Airflow release notes.

Prerequisites

• A Deployment on Astro.
• A Deployment API token, Workspace API token, or an Organization API token.
• cURL or, if using Python, the Requests library.
• The Astro CLI.

Step 1: Retrieve your access token

Workspace token

Follow the steps in Create a Workspace API token to create your token. Make sure to save the token on creation in order to use it later in this setup.

Organization token

Follow the steps in Create a Orgaization API token to create your token. Make sure to save the token on creation in order to use it later in this setup.

Deployment API token

Follow the steps in Create a Deployment API token to create your token. Make sure to save the token on creation in order to use it later in this setup.

Step 2: Retrieve the Deployment URL

Run the following command to retrieve a Deployment URL:

astro deployment inspect -n <deployment-name> -k metadata.webserver_url

The Deployment URL is used to access your Astro Deployment's Airflow UI. It includes the name of your Organization and first 7 letters of your Deployment ID.

For example, the Deployment URL for an Organization named mycompany with the Deployment ID dhbhijp0vt68400dj40tmc8virf is mycompany.astronomer.run/dhbhijp0.

Step 3: Make an Airflow API request

You can execute requests against any endpoint that is listed in the Airflow REST API reference.

To make a request based on Airflow documentation, make sure to:

• Use the Astro access token from Step 1 for authentication.
• Replace airflow.apache.org with your Deployment URL from Step 1.

Example API Requests

The following are common examples of Airflow REST API requests that you can run against a Deployment on Astro.

List DAGs

To retrieve a list of all DAGs in a Deployment, you can run a GET request to the dags endpoint

cURL

curl -X GET https://<your-deployment-url>/api/v1/dags \
   -H 'Cache-Control: no-cache' \
   -H 'Authorization: Bearer <your-access-token>'

Python

import requests
token = "<your-access-token>"
deployment_url = "<your-deployment-url>"
response = requests.get(
   url=f"https://{deployment_url}/api/v1/dags",
   headers={"Authorization": f"Bearer {token}"}
)
print(response.json())
# Prints data about all DAGs in your Deployment

Trigger a DAG run

You can trigger a DAG run by executing a POST request to Airflow's dagRuns endpoint.

This will trigger a DAG run for the DAG you specify with a logical_date value of NOW(), which is equivalent to clicking the Play button in the main DAGs view of the Airflow UI.

cURL

curl -X POST <your-deployment-url>/api/v1/dags/<your-dag-id>/dagRuns \
   -H 'Content-Type: application/json' \
   -H 'Cache-Control: no-cache' \
   -H 'Authorization: Bearer <your-access-token>' \
   -d '{}'

Python

import requests
token = "<your-access-token>"
deployment_url = "<your-deployment-url>"
dag_id = "<your-dag-id>"
response = requests.post(
    url=f"{deployment_url}/api/v1/dags/{dag_id}/dagRuns",
    headers={
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    },
    data='{}'
)
print(response.json())
# Prints metadata of the DAG run that was just triggered

Trigger a DAG run by date

You can also specify a logical_date at the time in which you wish to trigger the DAG run by passing the logical_date with the desired timestamp with the request's data field. The timestamp string is expressed in UTC and must be specified in the format "YYYY-MM-DDTHH:MM:SSZ", where:

• YYYY represents the year.
• MM represents the month.
• DD represents the day.
• HH represents the hour.
• MM represents the minute.
• SS represents the second.
• Z stands for "Zulu" time, which represents UTC.

cURL

curl -v -X POST https://<your-deployment-url>/api/v1/dags/<your-dag-id>/dagRuns \
   -H 'Authorization: Bearer <your-access-token>' \
   -H 'Cache-Control: no-cache' \
   -H 'content-type: application/json' \
   -d '{"logical_date":"2022-11-16T11:34:00Z"}'

Python

Using Python:

import requests
token = "<your-access-token>"
deployment_url = "<your-deployment-url>"
dag_id = "<your-dag-id>"
response = requests.post(
    url=f"https://{deployment_url}/api/v1/dags/{dag_id}/dagRuns",
    headers={
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    },
    data='{"logical_date": "2021-11-16T11:34:01Z"}'
)
print(response.json())
# Prints metadata of the DAG run that was just triggered

Pause a DAG

You can pause a DAG by executing a PATCH command against the dag endpoint.

Replace <your-dag-id> with your own value.

cURL

curl -X PATCH https://<your-deployment-url>/api/v1/dags/<your-dag-id> \
   -H 'Content-Type: application/json' \
   -H 'Cache-Control: no-cache' \
   -H 'Authorization: Bearer <your-access-token>' \
   -d '{"is_paused": true}'

Python

import requests
token = "<your-access-token>"
deployment_url = "<your-deployment-url>"
dag_id = "<your-dag-id>"
response = requests.patch(
    url=f"https://{deployment_url}/api/v1/dags/{dag_id}",
    headers={
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    },
    data='{"is_paused": true}'
)
print(response.json())
# Prints data about the DAG with id <dag-id>

Trigger DAG runs across Deployments

You can use the Airflow REST API to make a request in one Deployment that triggers a DAG run in a different Deployment. This is sometimes necessary when you have interdependent workflows across multiple Deployments. On Astro, you can do this for any Deployment in any Workspace or cluster.

This topic has guidelines on how to trigger a DAG run, but you can modify the example DAG provided to trigger any request that's supported in the Airflow REST API.

1. Create a Deployment API token for the Deployment that contains the DAG you want to trigger.

2. In the Deployment that contains the triggering DAG, create an Airflow HTTP connection with the following values:

   • Connection Id: http_conn

   • Connection Type: HTTP

   • Host: <your-deployment-url>

   • Schema: https

   • Extras:

     {
         "Content-Type": "application/json",
         "Authorization": "Bearer <your-deployment-api-token>"
     }

     See Manage connections in Apache Airflow.

   info

   If the HTTP connection type is not available, double check that the HTTP provider is installed in your Airflow environment. If it's not, add apache-airflow-providers-http to the requirements.txt file of our Astro project and redeploy it to Astro.

3. In your triggering DAG, add the following task. It uses the SimpleHttpOperator to make a request to the dagRuns endpoint of the Deployment that contains the DAG to trigger.

   from datetime import datetime
   from airflow import DAG
   from airflow.providers.http.operators.http import SimpleHttpOperator
   
   with DAG(dag_id="triggering_dag", schedule=None, start_date=datetime(2023, 1, 1)):
       SimpleHttpOperator(
           task_id="trigger_external_dag",
           log_response=True,
           method="POST",
               # Change this to the DAG_ID of the DAG you are triggering
           endpoint=f"api/v1/dags/<triggered_dag>/dagRuns",
           http_conn_id="http_conn",
           data={
               "logical_date": "{{ logical_date }}",
               
               # if you want to add parameters:
               # params: '{"foo": "bar"}'
           }
       )