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Netflix Conductor Python SDK

Project description

Conductor Python

Software Development Kit for Netflix Conductor, written on and providing support for Python.

Quick Guide

  1. Create a virtual environment

    $ virtualenv conductor
    $ source conductor/bin/activate
    $ python3 -m pip list
    Package    Version
    ---------- -------
    pip        22.0.3
    setuptools 60.6.0
    wheel      0.37.1
    
  2. Install latest version of conductor-python from pypi

    $ python3 -m pip install conductor-python
    Collecting conductor-python
    Collecting certifi>=14.05.14
    Collecting urllib3>=1.15.1
    Requirement already satisfied: setuptools>=21.0.0 in ./conductor/lib/python3.8/site-packages (from conductor-python) (60.6.0)
    Collecting six>=1.10
    Installing collected packages: certifi, urllib3, six, conductor-python
    Successfully installed certifi-2021.10.8 conductor-python-1.0.7 six-1.16.0 urllib3-1.26.8
    
  3. Create a worker capable of executing a Task. Example:

    from conductor.client.http.models.task import Task
    from conductor.client.http.models.task_result import TaskResult
    from conductor.client.http.models.task_result_status import TaskResultStatus
    from conductor.client.worker.worker_interface import WorkerInterface
    
    
    class SimplePythonWorker(WorkerInterface):
        def execute(self, task: Task) -> TaskResult:
            task_result = self.get_task_result_from_task(task)
            task_result.add_output_data('key', 'value')
            task_result.status = TaskResultStatus.COMPLETED
            return task_result
    
    • The add_output_data is the most relevant part, since you can store information in a dictionary, which will be sent within TaskResult as your execution response to Conductor
  4. Create a main method to start polling tasks to execute with your worker. Example:

    from conductor.client.automator.task_handler import TaskHandler
    from conductor.client.configuration.configuration import Configuration
    from conductor.client.worker.sample.faulty_execution_worker import FaultyExecutionWorker
    from conductor.client.worker.sample.simple_python_worker import SimplePythonWorker
    
    
    def main():
        configuration = Configuration(debug=True)
        task_definition_name = 'python_task_example'
        workers = [
            FaultyExecutionWorker(task_definition_name),
            SimplePythonWorker(task_definition_name)
        ]
        with TaskHandler(workers, configuration) as task_handler:
            task_handler.start_processes()
            task_handler.join_processes()
    
    
    if __name__ == '__main__':
        main()
    
    • This example contains two workers, each with a different execution method, capable of running the same task_definition_name
  5. Now that you have implemented the example, you can start the Conductor server locally:

    1. Clone Netflix Conductor repository:
      $ git clone https://github.com/Netflix/conductor.git
      $ cd conductor/
      
    2. Start the Conductor server:
      /conductor$ ./gradlew bootRun
      
    3. Start Conductor UI:
      /conductor$ cd ui/
      /conductor/ui$ yarn install
      /conductor/ui$ yarn run start
      

    You should be able to access:

  6. Create a Task within Conductor. Example:

    $ curl -X 'POST' \
        'http://localhost:8080/api/metadata/taskdefs' \
        -H 'accept: */*' \
        -H 'Content-Type: application/json' \
        -d '[
        {
          "name": "python_task_example",
          "description": "Python task example",
          "retryCount": 3,
          "retryLogic": "FIXED",
          "retryDelaySeconds": 10,
          "timeoutSeconds": 300,
          "timeoutPolicy": "TIME_OUT_WF",
          "responseTimeoutSeconds": 180,
          "ownerEmail": "example@example.com"
        }
      ]'
    
  7. Create a Workflow within Conductor. Example:

    $ curl -X 'POST' \
        'http://localhost:8080/api/metadata/workflow' \
        -H 'accept: */*' \
        -H 'Content-Type: application/json' \
        -d '{
        "createTime": 1634021619147,
        "updateTime": 1630694890267,
        "name": "workflow_with_python_task_example",
        "description": "Workflow with Python Task example",
        "version": 1,
        "tasks": [
          {
            "name": "python_task_example",
            "taskReferenceName": "python_task_example_ref_1",
            "inputParameters": {},
            "type": "SIMPLE"
          }
        ],
        "inputParameters": [],
        "outputParameters": {
          "workerOutput": "${python_task_example_ref_1.output}"
        },
        "schemaVersion": 2,
        "restartable": true,
        "ownerEmail": "example@example.com",
        "timeoutPolicy": "ALERT_ONLY",
        "timeoutSeconds": 0
      }'
    
  8. Start a new workflow:

    $ curl -X 'POST' \
        'http://localhost:8080/api/workflow/workflow_with_python_task_example' \
        -H 'accept: text/plain' \
        -H 'Content-Type: application/json' \
        -d '{}'
    

    You should receive a Workflow ID at the Response body

    • Workflow ID example: 8ff0bc06-4413-4c94-b27a-b3210412a914

    Now you must be able to see its execution through the UI.

    • Example: http://localhost:5000/execution/8ff0bc06-4413-4c94-b27a-b3210412a914
  9. Run your Python file with the main method

Unit Tests

Simple validation

/conductor-python/src$ python3 -m unittest -v
test_execute_task (tst.automator.test_task_runner.TestTaskRunner) ... ok
test_execute_task_with_faulty_execution_worker (tst.automator.test_task_runner.TestTaskRunner) ... ok
test_execute_task_with_invalid_task (tst.automator.test_task_runner.TestTaskRunner) ... ok

----------------------------------------------------------------------
Ran 3 tests in 0.001s

OK

Run with code coverage

/conductor-python/src$ python3 -m coverage run --source=conductor/ -m unittest

Report:

/conductor-python/src$ python3 -m coverage report

Visual coverage results:

/conductor-python/src$ python3 -m coverage html

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