Prerequisites What's changed in v2 Supported CLI commands Sample code

Apache Airflow CLI command reference

This page describes the supported and unsupported Apache Airflow CLI commands on Amazon Managed Workflows for Apache Airflow.

Prerequisites

The following section describes the preliminary steps required to use the commands and scripts on this page.

Access

AWS account access in AWS Identity and Access Management (IAM) to the Amazon MWAA permissions policy in Apache Airflow UI access policy: AmazonMWAAWebServerAccess.
AWS account access in AWS Identity and Access Management (IAM) to the Amazon MWAA permissions policy Full API and console access policy: AmazonMWAAFullApiAccess.

AWS CLI

The AWS Command Line Interface (AWS CLI) is an open source tool that enables you to interact with AWS services using commands in your command-line shell. To complete the steps on this page, you need the following:

What's changed in v2

New: Airflow CLI command structure. The Apache Airflow v2 CLI is organized so that related commands are grouped together as subcommands, which means you need to update Apache Airflow v1 scripts if you want to upgrade to Apache Airflow v2. For example, unpause in Apache Airflow v1 is now dags unpause in Apache Airflow v2. To learn more, see Airflow CLI changes in 2 in the Apache Airflow reference guide.

Supported CLI commands

The following section lists the Apache Airflow CLI commands available on Amazon MWAA.

Supported commands

Minor versions	Command
v2.0+	cheat-sheet
v2.0+	connections add
v2.0+	connections delete
v2.2+ (note)	dags backfill
v2.0+	dags delete
v2.2+ (note)	dags list
v2.0+	dags list-jobs
v2.6+	dags list-import-errors
v2.2+ (note)	dags list-runs
v2.2+ (note)	dags next-execution
v2.0+	dags pause
v2.0+	dags report
v2.4+	dags reserialize
v2.0+	dags show
v2.0+	dags state
v2.0+	dags test
v2.0+	dags trigger
v2.0+	dags unpause
v2.4+	db clean
v2.0+	providers behaviours
v2.0+	providers get
v2.0+	providers hooks
v2.0+	providers links
v2.0+	providers list
v2.8+	providers notifications
v2.6+	providers secrets
v2.7+	providers triggerer
v2.0+	providers widgets
v2.6+	roles add-perms
v2.6+	roles del-perms
v2.6+	roles add-perms
v2.0+	roles list
v2.0+	tasks clear
v2.0+	tasks failed-deps
v2.0+	tasks list
v2.0+	tasks render
v2.0+	tasks state
v2.0+	tasks states-for-dag-run
v2.0+	tasks test
v2.0+	variables delete
v2.0+	variables get
v2.0+	variables set
v2.0+	variables list
v2.0+	version

Using commands that parse DAGs

If your environment is are running Apache Airflow v1.10.12 or v2.0.2, CLI commands that parse DAGs will fail if the DAG uses plugins that depend on packages installed through a requirements.txt:

Apache Airflow v2.0.2

dags backfill
dags list
dags list-runs
dags next-execution

You can use these CLI commands if your DAGs do not use plugins that depend on packages installed through a requirements.txt.

Sample code

The following section contains examples of different ways to use the Apache Airflow CLI.

Set, get or delete an Apache Airflow v2 variable

You can use the following sample code to set, get or delete a variable in the format of <script> <mwaa env name> get | set | delete <variable> <variable value> </variable> </variable>.


[ $# -eq 0 ] && echo "Usage: $0 MWAA environment name " && exit

if [[ $2 == "" ]]; then
    dag="variables list"

elif  [ $2 == "get" ] ||  [ $2 == "delete" ] ||  [ $2 == "set" ]; then
    dag="variables $2 $3 $4 $5"

else
    echo "Not a valid command"
    exit 1
fi

CLI_JSON=$(aws mwaa --region $AWS_REGION create-cli-token --name $1) \
    && CLI_TOKEN=$(echo $CLI_JSON | jq -r '.CliToken') \
    && WEB_SERVER_HOSTNAME=$(echo $CLI_JSON | jq -r '.WebServerHostname') \
    && CLI_RESULTS=$(curl --request POST "https://$WEB_SERVER_HOSTNAME/aws_mwaa/cli" \
    --header "Authorization: Bearer $CLI_TOKEN" \
    --header "Content-Type: text/plain" \
    --data-raw "$dag" ) \
    && echo "Output:" \
    && echo $CLI_RESULTS | jq -r '.stdout' | base64 --decode \
    && echo "Errors:" \
    && echo $CLI_RESULTS | jq -r '.stderr' | base64 --decode

Add a configuration when triggering a DAG

You can use the following sample code with Apache Airflow v1 and Apache Airflow v2 to add a configuration when triggering a DAG, such as airflow trigger_dag 'dag_name' —conf '{"key":"value"}'.


import boto3
import json
import requests 
import base64

mwaa_env_name = 'YOUR_ENVIRONMENT_NAME'
dag_name = 'YOUR_DAG_NAME'
key = "YOUR_KEY"
value = "YOUR_VALUE"
conf = "{\"" + key + "\":\"" + value + "\"}"

client = boto3.client('mwaa')

mwaa_cli_token = client.create_cli_token(
  Name=mwaa_env_name
)

mwaa_auth_token = 'Bearer ' + mwaa_cli_token['CliToken']
mwaa_webserver_hostname = 'https://{0}/aws_mwaa/cli'.format(mwaa_cli_token['WebServerHostname'])
raw_data = "trigger_dag {0} -c '{1}'".format(dag_name, conf)

mwaa_response = requests.post(
      mwaa_webserver_hostname,
      headers={
          'Authorization': mwaa_auth_token,
          'Content-Type': 'text/plain'
          },
      data=raw_data
      )
      
mwaa_std_err_message = base64.b64decode(mwaa_response.json()['stderr']).decode('utf8')
mwaa_std_out_message = base64.b64decode(mwaa_response.json()['stdout']).decode('utf8')

print(mwaa_response.status_code)
print(mwaa_std_err_message)
print(mwaa_std_out_message)

Run CLI commands on an SSH tunnel to a bastion host

The following example shows how to run Airflow CLI commands using an SSH tunnel proxy to a Linux Bastion Host.

Using curl


ssh -D 8080 -f -C -q -N YOUR_USER@YOUR_BASTION_HOST


curl -x socks5h://0:8080 --request POST https://YOUR_HOST_NAME/aws_mwaa/cli --header YOUR_HEADERS --data-raw YOUR_CLI_COMMAND

Samples in GitHub and AWS tutorials

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Document Conventions

Apache Airflow CLI token

Managing connections