Missing "not applicable" positional arguments for job task settings about databricks-sdk-py

[nfx]

yep, it revealed another usability bug :D

[PaulCornellDB]

OK, for completeness, noting here that I changed the title. Also, with your guidance, I now have something that is more syntactically correct:

import os
from databricks.sdk import WorkspaceClient
from databricks.sdk.service.jobs import JobTaskSettings, NotebookTask, NotebookTaskSource

host  = os.getenv('DATABRICKS_HOST')
token = os.getenv('DATABRICKS_TOKEN')

w = WorkspaceClient(host  = host, token = token, auth_type = "pat")

w.jobs.create(
  job_name = 'my-job',
  tasks = [
    JobTaskSettings(
      description = "My job.",
      existing_cluster_id = "1128-232547-p64vrmx2",
      notebook_task = NotebookTask(
        base_parameters = {""},
        notebook_path = "/Users/[email protected]/go-fakedata",
        source = NotebookTaskSource("WORKSPACE")
      ),
      task_key = "my-key"
    )
  ]
)

However, I now get this type error:

TypeError: __init__() missing 16 required positional arguments: 'dbt_task', 'depends_on', 'email_notifications', 'job_cluster_key', 'libraries', 'max_retries', 'min_retry_interval_millis', 'new_cluster', 'pipeline_task', 'python_wheel_task', 'retry_on_timeout', 'spark_jar_task', 'spark_python_task', 'spark_submit_task', 'sql_task', and 'timeout_seconds'

None of these apply to my use case here.

[nfx]

@PaulCornellDB yes, i have to default to None all non-required fields in dataclasses and regenerate

[nfx]

one more thing: you don't have to read env vars, because it supports the same Unified Auth semantics as Go SDK. still need to add unit tests to ensure it's not breaking and compliant

host  = os.getenv('DATABRICKS_HOST')
token = os.getenv('DATABRICKS_TOKEN')

[nfx]

fixed in v0.0.2