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@ -1,753 +0,0 @@
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# Original Source Code: https://github.com/teamclairvoyant/airflow-rest-api-plugin
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# Date when airflow-rest-api-plugin source codes were downloaded: 2017-06-27
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# Kept majority of the codes and removed those that are not needed for our purpose
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from airflow.models import DagBag, DagModel
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from airflow.plugins_manager import AirflowPlugin
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from airflow import configuration
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from airflow.www.app import csrf
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from flask import Blueprint, request, jsonify
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from flask_admin import BaseView, expose
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from datetime import datetime
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import airflow
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import logging
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import subprocess
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import os
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import socket
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"""
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CLIs this REST API exposes are Defined here: http://airflow.incubator.apache.org/cli.html
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"""
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# Location of the REST Endpoint
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# Note: Changing this will only effect where the messages are posted to on the web interface and will not change where the endpoint actually resides
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rest_api_endpoint = "/admin/rest_api/api"
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# Getting Versions and Global variables
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hostname = socket.gethostname()
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airflow_version = airflow.__version__
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# Getting configurations from airflow.cfg file
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airflow_webserver_base_url = configuration.get('webserver', 'BASE_URL')
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airflow_base_log_folder = configuration.get('core', 'BASE_LOG_FOLDER')
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airflow_dags_folder = configuration.get('core', 'DAGS_FOLDER')
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log_loading = configuration.getboolean("rest_api_plugin", "LOG_LOADING") if configuration.has_option("rest_api_plugin", "LOG_LOADING") else False
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filter_loading_messages_in_cli_response = configuration.getboolean("rest_api_plugin", "FILTER_LOADING_MESSAGES_IN_CLI_RESPONSE") if configuration.has_option("rest_api_plugin", "FILTER_LOADING_MESSAGES_IN_CLI_RESPONSE") else True
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# Using UTF-8 Encoding so that response messages don't have any characters in them that can't be handled
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os.environ['PYTHONIOENCODING'] = 'utf-8'
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"""
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Metadata that defines a single API:
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{
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"name": "{string}", # Name of the API (cli command to be executed)
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"description": "{string}", # Description of the API
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"airflow_version": "{string}", # Version the API was available in to allow people to better determine if the API is available. (to be displayed on the Admin page)
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"http_method": "{string}", # HTTP method to use when calling the function. (Default: GET) (Optional)
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# removed "background_mode": {boolean}
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"arguments": [ # List of arguments that can be provided to the API
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{
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"name": "{string}", # Name of the argument
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"description": "{string}", # Description of the argument
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"form_input_type": "{string}", # Type of input to use on the Admin page for the argument
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"required": {boolean}, # Whether the argument is required upon submission
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"cli_end_position": {int} # In the case with a CLI command that the arguments value should be appended on to the end (for example: airflow trigger_dag some_dag_id), this is the position that the argument should be provided in the CLI command. (Optional)
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}
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],
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"fixed_arguments": [ # List of arguments that will always be used by the API endpoint and can't be changed
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{
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"name": "{string}", # Name of the argument
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"description": "{string}", # Description of the argument
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"fixed_value": "{string}" # Fixed value that will always be used
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}
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],
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"post_arguments": [ # List of arguments that can be provided in the POST body to the API
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{
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"name": "{string}", # Name of the argument
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"description": "{string}", # Description of the argument
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"form_input_type": "{string}", # Type of input to use on the Admin page for the argument
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"required": {boolean}, # Whether the argument is required upon submission
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}
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]
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},
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"""
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# Metadata about the APIs and how to call them. Representing them like this allows us to dynamically generate the APIs
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# in the admin page and dynamically execute them. This also allows us to easily add new ones.
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# API Object definition is described in the comment block above.
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apis_metadata = [
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{
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"name": "version",
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"description": "Displays the version of Airflow you're using",
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"airflow_version": "1.0.0 or greater",
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"http_method": "GET",
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"arguments": []
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},
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{
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"name": "render",
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"description": "Render a task instance's template(s)",
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"airflow_version": "1.7.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "task_id", "description": "The id of the task", "form_input_type": "text", "required": True, "cli_end_position": 2},
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{"name": "execution_date", "description": "The execution date of the DAG (Example: 2017-01-02T03:04:05)", "form_input_type": "text", "required": True, "cli_end_position": 3},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "variables",
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"description": "CRUD operations on variables",
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"airflow_version": "1.7.1 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "set", "description": "Set a variable. Expected input in the form: KEY VALUE.", "form_input_type": "text", "required": False},
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{"name": "get", "description": "Get value of a variable", "form_input_type": "text", "required": False},
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{"name": "json", "description": "Deserialize JSON variable", "form_input_type": "checkbox", "required": False},
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{"name": "default", "description": "Default value returned if variable does not exist", "form_input_type": "text", "required": False},
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{"name": "import", "description": "Import variables from JSON file", "form_input_type": "text", "required": False},
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{"name": "export", "description": "Export variables to JSON file", "form_input_type": "text", "required": False},
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{"name": "delete", "description": "Delete a variable", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "connections",
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"description": "List/Add/Delete connections",
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"airflow_version": "1.8.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "list", "description": "List all connections", "form_input_type": "checkbox", "required": False},
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{"name": "add", "description": "Add a connection", "form_input_type": "checkbox", "required": False},
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{"name": "delete", "description": "Delete a connection", "form_input_type": "checkbox", "required": False},
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{"name": "conn_id", "description": "Connection id, required to add/delete a connection", "form_input_type": "text", "required": False},
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{"name": "conn_uri", "description": "Connection URI, required to add a connection", "form_input_type": "text", "required": False},
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{"name": "conn_extra", "description": "Connection 'Extra' field, optional when adding a connection", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "pause",
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"description": "Pauses a DAG",
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"airflow_version": "1.7.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "unpause",
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"description": "Unpauses a DAG",
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"airflow_version": "1.7.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "task_failed_deps",
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"description": "Returns the unmet dependencies for a task instance from the perspective of the scheduler. In other words, why a task instance doesn't get scheduled and then queued by the scheduler, and then run by an executor).",
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"airflow_version": "1.8.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "task_id", "description": "The id of the task", "form_input_type": "text", "required": True, "cli_end_position": 2},
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{"name": "execution_date", "description": "The execution date of the DAG (Example: 2017-01-02T03:04:05)", "form_input_type": "text", "required": True, "cli_end_position": 3},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "trigger_dag",
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"description": "Trigger a DAG run",
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"airflow_version": "1.6.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False},
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{"name": "run_id", "description": "Helps to identify this run", "form_input_type": "text", "required": False},
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{"name": "conf", "description": "JSON string that gets pickled into the DagRun's conf attribute", "form_input_type": "text", "required": False},
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{"name": "exec_date", "description": "The execution date of the DAG", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "test",
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"description": "Test a task instance. This will run a task without checking for dependencies or recording it's state in the database.",
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"airflow_version": "0.1 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "task_id", "description": "The id of the task", "form_input_type": "text", "required": True, "cli_end_position": 2},
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{"name": "execution_date", "description": "The execution date of the DAG (Example: 2017-01-02T03:04:05)", "form_input_type": "text", "required": True, "cli_end_position": 3},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False},
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{"name": "dry_run", "description": "Perform a dry run", "form_input_type": "checkbox", "required": False},
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{"name": "task_params", "description": "Sends a JSON params dict to the task", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "dag_state",
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"description": "Get the status of a dag run",
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"airflow_version": "1.8.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "execution_date", "description": "The execution date of the DAG (Example: 2017-01-02T03:04:05)", "form_input_type": "text", "required": True, "cli_end_position": 2},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "run",
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"description": "Run a single task instance",
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"airflow_version": "1.0.0 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "task_id", "description": "The id of the task", "form_input_type": "text", "required": True, "cli_end_position": 2},
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{"name": "execution_date", "description": "The execution date of the DAG (Example: 2017-01-02T03:04:05)", "form_input_type": "text", "required": True, "cli_end_position": 3},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False},
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{"name": "mark_success", "description": "Mark jobs as succeeded without running them", "form_input_type": "checkbox", "required": False},
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{"name": "force", "description": "Ignore previous task instance state, rerun regardless if task already succeede", "form_input_type": "checkbox", "required": False},
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{"name": "pool", "description": "Resource pool to use", "form_input_type": "text", "required": False},
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{"name": "cfg_path", "description": "Path to config file to use instead of airflow.cfg", "form_input_type": "text", "required": False},
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{"name": "local", "description": "Run the task using the LocalExecutor", "form_input_type": "checkbox", "required": False},
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{"name": "ignore_all_dependencies", "description": "Ignores all non-critical dependencies, including ignore_ti_state and ignore_task_depsstore_true", "form_input_type": "checkbox", "required": False},
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{"name": "ignore_dependencies", "description": "Ignore task-specific dependencies, e.g. upstream, depends_on_past, and retry delay dependencies", "form_input_type": "checkbox", "required": False},
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{"name": "ignore_depends_on_past", "description": "Ignore depends_on_past dependencies (but respect upstream dependencies)", "form_input_type": "checkbox", "required": False},
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{"name": "ship_dag", "description": "Pickles (serializes) the DAG and ships it to the worker", "form_input_type": "checkbox", "required": False},
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{"name": "pickle", "description": "Serialized pickle object of the entire dag (used internally)", "form_input_type": "text", "required": False},
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]
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},
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{
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"name": "list_tasks",
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"description": "List the tasks within a DAG",
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"airflow_version": "0.1 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "tree", "description": "Tree view", "form_input_type": "checkbox", "required": False},
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{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False}
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]
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},
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{
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"name": "backfill",
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"description": "Run subsections of a DAG for a specified date range",
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"airflow_version": "0.1 or greater",
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"http_method": "GET",
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"arguments": [
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{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
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{"name": "task_regex", "description": "The regex to filter specific task_ids to backfill (optional)", "form_input_type": "text", "required": False},
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{"name": "start_date", "description": "Override start_date YYYY-MM-DD. Either this or the end_date needs to be provided.", "form_input_type": "text", "required": False},
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{"name": "end_date", "description": "Override end_date YYYY-MM-DD. Either this or the start_date needs to be provided.", "form_input_type": "text", "required": False},
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{"name": "mark_success", "description": "Mark jobs as succeeded without running them", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "local", "description": "Run the task using the LocalExecutor", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "donot_pickle", "description": "Do not attempt to pickle the DAG object to send over to the workers, just tell the workers to run their version of the code.", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "include_adhoc", "description": "Include dags with the adhoc argument.", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "ignore_dependencies", "description": "Ignore task-specific dependencies, e.g. upstream, depends_on_past, and retry delay dependencies", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "ignore_first_depends_on_past", "description": "Ignores depends_on_past dependencies for the first set of tasks only (subsequent executions in the backfill DO respect depends_on_past).", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "pool", "description": "Resource pool to use", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "dry_run", "description": "Perform a dry run", "form_input_type": "checkbox", "required": False}
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "list_dags",
|
|
|
|
|
"description": "List all the DAGs",
|
|
|
|
|
"airflow_version": "0.1 or greater",
|
|
|
|
|
"http_method": "GET",
|
|
|
|
|
"arguments": [
|
|
|
|
|
{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "report", "description": "Show DagBag loading report", "form_input_type": "checkbox", "required": False}
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "task_state",
|
|
|
|
|
"description": "Get the status of a task instance",
|
|
|
|
|
"airflow_version": "1.0.0 or greater",
|
|
|
|
|
"http_method": "GET",
|
|
|
|
|
"arguments": [
|
|
|
|
|
{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
|
|
|
|
|
{"name": "task_id", "description": "The id of the task", "form_input_type": "text", "required": True, "cli_end_position": 2},
|
|
|
|
|
{"name": "execution_date", "description": "The execution date of the DAG (Example: 2017-01-02T03:04:05)", "form_input_type": "text", "required": True, "cli_end_position": 3},
|
|
|
|
|
{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False}
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "pool",
|
|
|
|
|
"description": "CRUD operations on pools",
|
|
|
|
|
"airflow_version": "1.8.0 or greater",
|
|
|
|
|
"http_method": "GET",
|
|
|
|
|
"arguments": [
|
|
|
|
|
{"name": "set", "description": "Set pool slot count and description, respectively. Expected input in the form: NAME SLOT_COUNT POOL_DESCRIPTION.", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "get", "description": "Get pool info", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "delete", "description": "Delete a pool", "form_input_type": "text", "required": False}
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
# removed retrieval of logs from this interface, as it uses a background
|
|
|
|
|
# mode call, we don't use it, and lets us remove a security vulnerability
|
|
|
|
|
{
|
|
|
|
|
"name": "clear",
|
|
|
|
|
"description": "Clear a set of task instance, as if they never ran",
|
|
|
|
|
"airflow_version": "0.1 or greater",
|
|
|
|
|
"http_method": "GET",
|
|
|
|
|
"arguments": [
|
|
|
|
|
{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True, "cli_end_position": 1},
|
|
|
|
|
{"name": "task_regex", "description": "The regex to filter specific task_ids to backfill (optional)", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "start_date", "description": "Override start_date YYYY-MM-DD", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "end_date", "description": "Override end_date YYYY-MM-DD", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "subdir", "description": "File location or directory from which to look for the dag", "form_input_type": "text", "required": False},
|
|
|
|
|
{"name": "upstream", "description": "Include upstream tasks", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "downstream", "description": "Include downstream tasks", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "only_failed", "description": "Only failed jobs", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "only_running", "description": "Only running jobs", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "exclude_subdags", "description": "Exclude subdags", "form_input_type": "checkbox", "required": False}
|
|
|
|
|
],
|
|
|
|
|
"fixed_arguments": [
|
|
|
|
|
{"name": "no_confirm", "description": "Do not request confirmation", "fixed_value": ""}
|
|
|
|
|
],
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "deploy_dag",
|
|
|
|
|
"description": "Deploy a new DAG File to the DAGs directory",
|
|
|
|
|
"airflow_version": "None - Custom API",
|
|
|
|
|
"http_method": "POST",
|
|
|
|
|
"post_body_description": "dag_file - POST Body Element - REQUIRED",
|
|
|
|
|
"form_enctype": "multipart/form-data",
|
|
|
|
|
"arguments": [],
|
|
|
|
|
"post_arguments": [
|
|
|
|
|
{"name": "dag_file", "description": "Python file to upload and deploy", "form_input_type": "file", "required": True},
|
|
|
|
|
{"name": "force", "description": "Whether to forcefully upload the file if the file already exists or not", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "pause", "description": "The DAG will be forced to be paused when created and override the 'dags_are_paused_at_creation' config.", "form_input_type": "checkbox", "required": False},
|
|
|
|
|
{"name": "unpause", "description": "The DAG will be forced to be unpaused when created and override the 'dags_are_paused_at_creation' config.", "form_input_type": "checkbox", "required": False}
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "refresh_dag",
|
|
|
|
|
"description": "Refresh a DAG in the Web Server",
|
|
|
|
|
"airflow_version": "None - Custom API",
|
|
|
|
|
"http_method": "GET",
|
|
|
|
|
"arguments": [
|
|
|
|
|
{"name": "dag_id", "description": "The id of the dag", "form_input_type": "text", "required": True}
|
|
|
|
|
]
|
|
|
|
|
}
|
|
|
|
|
]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Utility for creating the REST Responses
|
|
|
|
|
class REST_API_Response_Util():
|
|
|
|
|
|
|
|
|
|
# Gets the Base Response object with all required response fields included. To be used at the beginning of the REST Call.
|
|
|
|
|
@staticmethod
|
|
|
|
|
def get_base_response(status="OK", http_response_code=200, call_time=datetime.now(), include_arguments=True):
|
|
|
|
|
base_response = {"status": status, "http_response_code": http_response_code, "call_time": call_time}
|
|
|
|
|
if include_arguments:
|
|
|
|
|
base_response["arguments"] = request.args
|
|
|
|
|
base_response["post_arguments"] = request.form
|
|
|
|
|
return base_response
|
|
|
|
|
|
|
|
|
|
# Finalize the Base Response with additional data
|
|
|
|
|
@staticmethod
|
|
|
|
|
def _get_final_response(base_response, output=None, airflow_cmd=None, http_response_code=None, warning=None):
|
|
|
|
|
final_response = base_response
|
|
|
|
|
final_response["response_time"] = datetime.now()
|
|
|
|
|
if output:
|
|
|
|
|
final_response["output"] = output
|
|
|
|
|
if airflow_cmd:
|
|
|
|
|
final_response["airflow_cmd"] = airflow_cmd
|
|
|
|
|
if http_response_code:
|
|
|
|
|
final_response["http_response_code"] = http_response_code
|
|
|
|
|
if warning:
|
|
|
|
|
final_response["warning"] = warning
|
|
|
|
|
return jsonify(final_response)
|
|
|
|
|
|
|
|
|
|
# Set the Base Response as a 200 HTTP Response object
|
|
|
|
|
@staticmethod
|
|
|
|
|
def get_200_response(base_response, output=None, airflow_cmd=None, warning=None):
|
|
|
|
|
logging.info("Returning a 200 Response Code with response '" + str(output) + "'")
|
|
|
|
|
return REST_API_Response_Util._get_final_response(base_response=base_response, output=output, airflow_cmd=airflow_cmd, warning=warning)
|
|
|
|
|
|
|
|
|
|
# Set the Base Response and an Error
|
|
|
|
|
@staticmethod
|
|
|
|
|
def _get_error_response(base_response, error_code, output=None):
|
|
|
|
|
base_response["status"] = "ERROR"
|
|
|
|
|
return REST_API_Response_Util._get_final_response(base_response=base_response, output=output, http_response_code=error_code), error_code
|
|
|
|
|
|
|
|
|
|
# Set the Base Response as a 400 HTTP Response object
|
|
|
|
|
@staticmethod
|
|
|
|
|
def get_400_error_response(base_response, output=None):
|
|
|
|
|
logging.warning("Returning a 400 Response Code with response '" + str(output) + "'")
|
|
|
|
|
return REST_API_Response_Util._get_error_response(base_response, 400, output)
|
|
|
|
|
|
|
|
|
|
# Set the Base Response as a 403 HTTP Response object
|
|
|
|
|
@staticmethod
|
|
|
|
|
def get_403_error_response(base_response, output=None):
|
|
|
|
|
logging.warning("Returning a 403 Response Code with response '" + str(output) + "'")
|
|
|
|
|
return REST_API_Response_Util._get_error_response(base_response, 403, output)
|
|
|
|
|
|
|
|
|
|
# Set the Base Response as a 500 HTTP Response object
|
|
|
|
|
@staticmethod
|
|
|
|
|
def get_500_error_response(base_response, output=None):
|
|
|
|
|
logging.warning("Returning a 500 Response Code with response '" + str(output) + "'")
|
|
|
|
|
return REST_API_Response_Util._get_error_response(base_response, 500, output)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# REST_API View which extends the flask_admin BaseView
|
|
|
|
|
class REST_API(BaseView):
|
|
|
|
|
|
|
|
|
|
# Checks a string object to see if it is none or empty so we can determine if an argument (passed to the rest api) is provided
|
|
|
|
|
@staticmethod
|
|
|
|
|
def is_arg_not_provided(arg):
|
|
|
|
|
return arg is None or arg == ""
|
|
|
|
|
|
|
|
|
|
# Get the DagBag which has a list of all the current Dags
|
|
|
|
|
@staticmethod
|
|
|
|
|
def get_dagbag():
|
|
|
|
|
return DagBag()
|
|
|
|
|
|
|
|
|
|
# '/' Endpoint where the Admin page is which allows you to view the APIs available and trigger them
|
|
|
|
|
@expose('/')
|
|
|
|
|
def index(self):
|
|
|
|
|
logging.info("REST_API.index() called")
|
|
|
|
|
|
|
|
|
|
# get the information that we want to display on the page regarding the dags that are available
|
|
|
|
|
dagbag = self.get_dagbag()
|
|
|
|
|
dags = []
|
|
|
|
|
for dag_id in dagbag.dags:
|
|
|
|
|
orm_dag = DagModel.get_current(dag_id)
|
|
|
|
|
dags.append({
|
|
|
|
|
"dag_id": dag_id,
|
|
|
|
|
"is_active": (not orm_dag.is_paused) if orm_dag is not None else False
|
|
|
|
|
})
|
|
|
|
|
|
|
|
|
|
return self.render("rest_api_plugin/index.html",
|
|
|
|
|
dags=dags,
|
|
|
|
|
airflow_webserver_base_url=airflow_webserver_base_url,
|
|
|
|
|
rest_api_endpoint=rest_api_endpoint,
|
|
|
|
|
apis_metadata=apis_metadata,
|
|
|
|
|
airflow_version=airflow_version,
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
# '/api' REST Endpoint where API requests should all come in
|
|
|
|
|
@csrf.exempt # Exempt the CSRF token
|
|
|
|
|
@expose('/api', methods=["GET", "POST"])
|
|
|
|
|
def api(self):
|
|
|
|
|
base_response = REST_API_Response_Util.get_base_response()
|
|
|
|
|
|
|
|
|
|
# Get the api that you want to execute
|
|
|
|
|
api = request.args.get('api')
|
|
|
|
|
if api is not None:
|
|
|
|
|
api = api.strip().lower()
|
|
|
|
|
logging.info("REST_API.api() called (api: " + str(api) + ")")
|
|
|
|
|
|
|
|
|
|
# Validate that the API is provided
|
|
|
|
|
if self.is_arg_not_provided(api):
|
|
|
|
|
logging.warning("api argument not provided")
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "API should be provided")
|
|
|
|
|
|
|
|
|
|
# Get the api_metadata from the api object list that correcsponds to the api we want to run to get the metadata.
|
|
|
|
|
api_metadata = None
|
|
|
|
|
for test_api_metadata in apis_metadata:
|
|
|
|
|
if test_api_metadata["name"] == api:
|
|
|
|
|
api_metadata = test_api_metadata
|
|
|
|
|
if api_metadata is None:
|
|
|
|
|
logging.info("api '" + str(api) + "' was not found in the apis list in the REST API Plugin")
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "API '" + str(api) + "' was not found")
|
|
|
|
|
|
|
|
|
|
# check if all the required arguments are provided
|
|
|
|
|
missing_required_arguments = []
|
|
|
|
|
dag_id = None
|
|
|
|
|
for argument in api_metadata["arguments"]:
|
|
|
|
|
argument_name = argument["name"]
|
|
|
|
|
argument_value = request.args.get(argument_name)
|
|
|
|
|
if argument["required"]:
|
|
|
|
|
if self.is_arg_not_provided(argument_value):
|
|
|
|
|
missing_required_arguments.append(argument_name)
|
|
|
|
|
if argument_name == "dag_id" and argument_value is not None:
|
|
|
|
|
dag_id = argument_value.strip()
|
|
|
|
|
if len(missing_required_arguments) > 0:
|
|
|
|
|
logging.warning("Missing required arguments: " + str(missing_required_arguments))
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "The argument(s) " + str(missing_required_arguments) + " are required")
|
|
|
|
|
|
|
|
|
|
# Check to make sure that the DAG you're referring to, already exists.
|
|
|
|
|
dag_bag = self.get_dagbag()
|
|
|
|
|
if dag_id is not None and dag_id not in dag_bag.dags:
|
|
|
|
|
logging.info("DAG_ID '" + str(dag_id) + "' was not found in the DagBag list '" + str(dag_bag.dags) + "'")
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "The DAG ID '" + str(dag_id) + "' does not exist")
|
|
|
|
|
|
|
|
|
|
# Deciding which function to use based off the API object that was requested. Some functions are custom and need to be manually routed to.
|
|
|
|
|
if api == "version":
|
|
|
|
|
final_response = self.version(base_response)
|
|
|
|
|
elif api == "rest_api_plugin_version":
|
|
|
|
|
final_response = self.rest_api_plugin_version(base_response)
|
|
|
|
|
elif api == "deploy_dag":
|
|
|
|
|
final_response = self.deploy_dag(base_response)
|
|
|
|
|
elif api == "refresh_dag":
|
|
|
|
|
final_response = self.refresh_dag(base_response)
|
|
|
|
|
else:
|
|
|
|
|
final_response = self.execute_cli(base_response, api_metadata)
|
|
|
|
|
|
|
|
|
|
return final_response
|
|
|
|
|
|
|
|
|
|
# General execution of a CLI command
|
|
|
|
|
# A command will be assembled and then passed to the OS as a commandline function and the results will be returned
|
|
|
|
|
def execute_cli(self, base_response, api_metadata):
|
|
|
|
|
logging.info("Executing cli function")
|
|
|
|
|
|
|
|
|
|
# getting the largest cli_end_position in the api_metadata object so that the cli function can be assembled
|
|
|
|
|
largest_end_argument_value = 0
|
|
|
|
|
for argument in api_metadata.get("arguments", []):
|
|
|
|
|
if argument.get("cli_end_position") is not None and argument["cli_end_position"] > largest_end_argument_value:
|
|
|
|
|
largest_end_argument_value = argument["cli_end_position"]
|
|
|
|
|
|
|
|
|
|
# starting to create the airflow_cmd function
|
|
|
|
|
airflow_cmd_split = ["airflow", api_metadata["name"]]
|
|
|
|
|
|
|
|
|
|
# appending arguments to the airflow_cmd_split array and setting arguments aside in the end_arguments array to be appended onto the end of airflow_cmd_split
|
|
|
|
|
end_arguments = [0] * largest_end_argument_value
|
|
|
|
|
for argument in api_metadata["arguments"]:
|
|
|
|
|
argument_name = argument["name"]
|
|
|
|
|
argument_value = request.args.get(argument_name)
|
|
|
|
|
logging.info("argument_name: " + str(argument_name) + ", argument_value: " + str(argument_value))
|
|
|
|
|
if argument_value is not None:
|
|
|
|
|
# if the argument should be appended onto the end, find the position and add it to the end_arguments array
|
|
|
|
|
if "cli_end_position" in argument:
|
|
|
|
|
logging.info("argument['cli_end_position']: " + str(argument['cli_end_position']))
|
|
|
|
|
end_arguments[argument["cli_end_position"]-1] = argument_value
|
|
|
|
|
else:
|
|
|
|
|
airflow_cmd_split.extend(["--" + argument_name])
|
|
|
|
|
if argument["form_input_type"] is not "checkbox":
|
|
|
|
|
airflow_cmd_split.extend(argument_value.split(" "))
|
|
|
|
|
else:
|
|
|
|
|
logging.warning("argument_value is null")
|
|
|
|
|
|
|
|
|
|
# appending fixed arguments that should always be provided to the APIs
|
|
|
|
|
for fixed_argument in api_metadata.get("fixed_arguments", []):
|
|
|
|
|
fixed_argument_name = fixed_argument["name"]
|
|
|
|
|
fixed_argument_value = fixed_argument.get("fixed_value")
|
|
|
|
|
logging.info("fixed_argument_name: " + str(fixed_argument_name) + ", fixed_argument_value: " + str(fixed_argument_value))
|
|
|
|
|
if fixed_argument_value is not None:
|
|
|
|
|
airflow_cmd_split.extend(["--" + fixed_argument_name])
|
|
|
|
|
if fixed_argument_value:
|
|
|
|
|
airflow_cmd_split.extend(fixed_argument_value.split(" "))
|
|
|
|
|
|
|
|
|
|
# appending the end_arguments to the very end
|
|
|
|
|
airflow_cmd_split.extend(end_arguments)
|
|
|
|
|
|
|
|
|
|
# joining all the individual arguments and components into a single string
|
|
|
|
|
airflow_cmd = " ".join(airflow_cmd_split)
|
|
|
|
|
|
|
|
|
|
logging.info("airflow_cmd array: " + str(airflow_cmd_split))
|
|
|
|
|
logging.info("airflow_cmd: " + str(airflow_cmd))
|
|
|
|
|
|
|
|
|
|
output = self.execute_cli_command(airflow_cmd_split)
|
|
|
|
|
|
|
|
|
|
# if desired, filter out the loading messages to reduce the noise in the output
|
|
|
|
|
if filter_loading_messages_in_cli_response:
|
|
|
|
|
logging.info("Filtering Loading Messages from the CLI Response")
|
|
|
|
|
output = self.filter_loading_messages(output)
|
|
|
|
|
|
|
|
|
|
return REST_API_Response_Util.get_200_response(base_response=base_response, output=output, airflow_cmd=airflow_cmd)
|
|
|
|
|
|
|
|
|
|
# Custom function for the version API
|
|
|
|
|
def version(self, base_response):
|
|
|
|
|
logging.info("Executing custom 'version' function")
|
|
|
|
|
return REST_API_Response_Util.get_200_response(base_response, airflow_version)
|
|
|
|
|
|
|
|
|
|
# Custom Function for the deploy_dag API
|
|
|
|
|
def deploy_dag(self, base_response):
|
|
|
|
|
logging.info("Executing custom 'deploy_dag' function")
|
|
|
|
|
|
|
|
|
|
if 'dag_file' not in request.files or request.files['dag_file'].filename == '': # check if the post request has the file part
|
|
|
|
|
logging.warning("The dag_file argument wasn't provided")
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "dag_file should be provided")
|
|
|
|
|
dag_file = request.files['dag_file']
|
|
|
|
|
|
|
|
|
|
force = True if request.form.get('force') is not None else False
|
|
|
|
|
logging.info("deploy_dag force upload: " + str(force))
|
|
|
|
|
|
|
|
|
|
pause = True if request.form.get('pause') is not None else False
|
|
|
|
|
logging.info("deploy_dag in pause state: " + str(pause))
|
|
|
|
|
|
|
|
|
|
unpause = True if request.form.get('unpause') is not None else False
|
|
|
|
|
logging.info("deploy_dag in unpause state: " + str(unpause))
|
|
|
|
|
|
|
|
|
|
# make sure that the dag_file is a python script
|
|
|
|
|
if dag_file and dag_file.filename.endswith(".py"):
|
|
|
|
|
save_file_path = os.path.join(airflow_dags_folder, dag_file.filename)
|
|
|
|
|
|
|
|
|
|
# Check if the file already exists.
|
|
|
|
|
if os.path.isfile(save_file_path) and not force:
|
|
|
|
|
logging.warning("File to upload already exists")
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "The file '" + save_file_path + "' already exists on host '" + hostname + "'.")
|
|
|
|
|
|
|
|
|
|
logging.info("Saving file to '" + save_file_path + "'")
|
|
|
|
|
dag_file.save(save_file_path)
|
|
|
|
|
|
|
|
|
|
else:
|
|
|
|
|
logging.warning("deploy_dag file is not a python file. It does not end with a .py.")
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "dag_file is not a *.py file")
|
|
|
|
|
|
|
|
|
|
warning = None
|
|
|
|
|
# if both the pause and unpause options are provided then skip the pausing and unpausing phase
|
|
|
|
|
if not (pause and unpause):
|
|
|
|
|
if pause or unpause:
|
|
|
|
|
try:
|
|
|
|
|
# import the DAG file that was uploaded so that we can get the DAG_ID to execute the command to pause or unpause it
|
|
|
|
|
import imp
|
|
|
|
|
dag_file = imp.load_source('module.name', save_file_path)
|
|
|
|
|
dag_id = dag_file.dag.dag_id
|
|
|
|
|
|
|
|
|
|
# run the pause or unpause cli command
|
|
|
|
|
airflow_cmd_split = []
|
|
|
|
|
if pause:
|
|
|
|
|
airflow_cmd_split = ["airflow", "pause", dag_id]
|
|
|
|
|
if unpause:
|
|
|
|
|
airflow_cmd_split = ["airflow", "unpause", dag_id]
|
|
|
|
|
cli_output = self.execute_cli_command(airflow_cmd_split)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
warning = "Failed to set the state (pause, unpause) of the DAG: " + str(e)
|
|
|
|
|
logging.warning(warning)
|
|
|
|
|
else:
|
|
|
|
|
warning = "Both options pause and unpause were given. Skipping setting the state (pause, unpause) of the DAG."
|
|
|
|
|
logging.warning(warning)
|
|
|
|
|
|
|
|
|
|
return REST_API_Response_Util.get_200_response(base_response=base_response, output="DAG File [{}] has been uploaded".format(dag_file), warning=warning)
|
|
|
|
|
|
|
|
|
|
# Custom Function for the refresh_dag API
|
|
|
|
|
# This will call the direct function corresponding to the web endpoint '/admin/airflow/refresh' that already exists in Airflow
|
|
|
|
|
def refresh_dag(self, base_response):
|
|
|
|
|
logging.info("Executing custom 'refresh_dag' function")
|
|
|
|
|
dag_id = request.args.get('dag_id')
|
|
|
|
|
logging.info("dag_id to refresh: '" + str(dag_id) + "'")
|
|
|
|
|
if self.is_arg_not_provided(dag_id):
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "dag_id should be provided")
|
|
|
|
|
elif " " in dag_id:
|
|
|
|
|
return REST_API_Response_Util.get_400_error_response(base_response, "dag_id contains spaces and is therefore an illegal argument")
|
|
|
|
|
|
|
|
|
|
try:
|
|
|
|
|
from airflow.www.views import Airflow
|
|
|
|
|
# NOTE: The request argument 'dag_id' is required for the refresh() function to get the dag_id
|
|
|
|
|
refresh_result = Airflow().refresh()
|
|
|
|
|
logging.info("Refresh Result: " + str(refresh_result))
|
|
|
|
|
except Exception as e:
|
|
|
|
|
error_message = "An error occurred while trying to Refresh the DAG '" + str(dag_id) + "': " + str(e)
|
|
|
|
|
logging.error(error_message)
|
|
|
|
|
return REST_API_Response_Util.get_500_error_response(base_response, error_message)
|
|
|
|
|
|
|
|
|
|
return REST_API_Response_Util.get_200_response(base_response=base_response, output="DAG [{}] is now fresh as a daisy".format(dag_id))
|
|
|
|
|
|
|
|
|
|
# General execution of the airflow command passed to it and returns the response
|
|
|
|
|
@staticmethod
|
|
|
|
|
def execute_cli_command(airflow_cmd_split):
|
|
|
|
|
logging.info("Executing CLI Command")
|
|
|
|
|
|
|
|
|
|
# There is a need to handle this case separately as the current implementation
|
|
|
|
|
# breaks the JSON string into multiple parts in a List and this cause the Airflow
|
|
|
|
|
# command to stop working properly
|
|
|
|
|
#
|
|
|
|
|
# The idea here is to handle the JSON string separately and to make use of the
|
|
|
|
|
# fact that the command will take on the following pattern:
|
|
|
|
|
#
|
|
|
|
|
# `airflow trigger_dag --config '{"message": "Hello World"}' test_1`
|
|
|
|
|
#
|
|
|
|
|
# , where test_1 is the name of the Dag
|
|
|
|
|
#
|
|
|
|
|
if airflow_cmd_split[2] == '--conf':
|
|
|
|
|
# Initialize list x and extract the JSON string
|
|
|
|
|
# from the airflow_cmd_split List
|
|
|
|
|
x = []
|
|
|
|
|
for i in range(3, len(airflow_cmd_split) - 1):
|
|
|
|
|
x.append(airflow_cmd_split[i])
|
|
|
|
|
|
|
|
|
|
# Initialize list y
|
|
|
|
|
y = [None] * 5
|
|
|
|
|
|
|
|
|
|
# Assign values to list y
|
|
|
|
|
for j in range(0, 3):
|
|
|
|
|
y[j] = airflow_cmd_split[j]
|
|
|
|
|
|
|
|
|
|
# Create string using list x and assigns to y[3]
|
|
|
|
|
y[3] = " ".join(x)
|
|
|
|
|
|
|
|
|
|
# Dag name will always be airflow_cmd_split[-1]
|
|
|
|
|
y[4] = airflow_cmd_split[-1]
|
|
|
|
|
|
|
|
|
|
# Assigns updated values to airflow_cmd_split
|
|
|
|
|
airflow_cmd_split = y
|
|
|
|
|
|
|
|
|
|
logging.info(airflow_cmd_split)
|
|
|
|
|
|
|
|
|
|
process = subprocess.Popen(airflow_cmd_split, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
|
|
|
|
process.wait()
|
|
|
|
|
return REST_API.collect_process_output(process)
|
|
|
|
|
|
|
|
|
|
# gets and empty object that has all the fields a CLI function would have in it.
|
|
|
|
|
@staticmethod
|
|
|
|
|
def get_empty_process_output():
|
|
|
|
|
return {
|
|
|
|
|
"stderr": "",
|
|
|
|
|
"stdin": "",
|
|
|
|
|
"stdout": ""
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
# Get the output of the CLI process and package it in a dict
|
|
|
|
|
@staticmethod
|
|
|
|
|
def collect_process_output(process):
|
|
|
|
|
output = REST_API.get_empty_process_output()
|
|
|
|
|
if process.stderr is not None:
|
|
|
|
|
output["stderr"] = ""
|
|
|
|
|
for line in process.stderr.readlines():
|
|
|
|
|
output["stderr"] += str(line)
|
|
|
|
|
if process.stdin is not None:
|
|
|
|
|
output["stdin"] = ""
|
|
|
|
|
for line in process.stdin.readlines():
|
|
|
|
|
output["stdin"] += str(line)
|
|
|
|
|
if process.stdout is not None:
|
|
|
|
|
output["stdout"] = ""
|
|
|
|
|
for line in process.stdout.readlines():
|
|
|
|
|
output["stdout"] += str(line)
|
|
|
|
|
logging.info("RestAPI Output: " + str(output))
|
|
|
|
|
return output
|
|
|
|
|
|
|
|
|
|
# Filtering out logging statements from the standard output
|
|
|
|
|
# Content like:
|
|
|
|
|
#
|
|
|
|
|
# [2017-04-19 10:04:34,927] {__init__.py:36} INFO - Using executor CeleryExecutor
|
|
|
|
|
# [2017-04-19 10:04:35,926] {models.py:154} INFO - Filling up the DagBag from /Users/...
|
|
|
|
|
@staticmethod
|
|
|
|
|
def filter_loading_messages(output):
|
|
|
|
|
stdout = output["stdout"]
|
|
|
|
|
new_stdout_array = stdout.split("\n")
|
|
|
|
|
content_to_remove_greatest_index = 0
|
|
|
|
|
for index, content in enumerate(new_stdout_array):
|
|
|
|
|
if content.startswith("["):
|
|
|
|
|
content_to_remove_greatest_index = index
|
|
|
|
|
content_to_remove_greatest_index += 1
|
|
|
|
|
if len(new_stdout_array) > content_to_remove_greatest_index:
|
|
|
|
|
new_stdout_array = new_stdout_array[content_to_remove_greatest_index:]
|
|
|
|
|
output["stdout"] = "\n".join(new_stdout_array)
|
|
|
|
|
return output
|
|
|
|
|
|
|
|
|
|
# Creating View to be used by Plugin
|
|
|
|
|
rest_api_view = REST_API(category="Admin", name="REST API Plugin")
|
|
|
|
|
|
|
|
|
|
# Creating Blueprint
|
|
|
|
|
rest_api_bp = Blueprint(
|
|
|
|
|
"rest_api_bp",
|
|
|
|
|
__name__,
|
|
|
|
|
template_folder='templates',
|
|
|
|
|
static_folder='static',
|
|
|
|
|
static_url_path='/static/'
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Creating the REST_API_Plugin which extends the AirflowPlugin so its imported into Airflow
|
|
|
|
|
class REST_API_Plugin(AirflowPlugin):
|
|
|
|
|
name = "rest_api"
|
|
|
|
|
operators = []
|
|
|
|
|
flask_blueprints = [rest_api_bp]
|
|
|
|
|
hooks = []
|
|
|
|
|
executors = []
|
|
|
|
|
admin_views = [rest_api_view]
|
|
|
|
|
menu_links = []
|
Bryan Strassner