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Python SDK

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

The code for the Python SDk is available on Github. Please feel free to file PRs, issues, etc. there.

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.worker.worker_interface import WorkerInterface
    class SimplePythonWorker(WorkerInterface):
        def execute(self, task):
            task_result = self.get_task_result_from_task(task)
            task_result.add_output_data('key', 'value')
            task_result.status = '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_example_task'
        workers = [
        with TaskHandler(workers, configuration) as task_handler:
    if __name__ == '__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
      $ 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: * Conductor API: * http://localhost:8080/swagger-ui/index.html * Conductor UI: * http://localhost:5000

  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": ""
  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": "",
        "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


Run with code coverage

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


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

Visual coverage results:

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