blob: 1d45f31261e82447edbfc0a8cae30aaa170339af [file]
# coding: utf-8
"""
Airflow API
Airflow API. All endpoints located under ``/api/v2`` can be used safely, are stable and backward compatible. Endpoints located under ``/ui`` are dedicated to the UI and are subject to breaking change depending on the need of the frontend. Users should not rely on those but use the public ones instead. **Filtering with pattern parameters.** Many list endpoints accept ``*_pattern`` and ``*_prefix_pattern`` query parameters. Unless a parameter's own description says otherwise, ``*_pattern`` is a case-insensitive substring match (SQL ``ILIKE '%term%'``) where ``%`` matches any sequence and ``_`` matches any single character (e.g. ``%customer_%``) — convenient, but it cannot use B-tree indexes, so it is slow on large tables. ``*_prefix_pattern`` matches the start of the value, is case-sensitive and index-friendly (prefer it at scale); there ``%`` and ``_`` are literal and trailing non-alphanumeric characters are stripped so the range scan stays index-compatible under locale-aware collations (e.g. ``test_`` matches values starting with ``test``, and ``s3://`` matches ``s3``). In both, ``|`` means OR (e.g. ``dag1|dag2``) and ``~`` matches everything. Regular expressions are not supported by these parameters; regex-capable endpoints expose a separate parameter.
The version of the OpenAPI document: 2
Generated by OpenAPI Generator (https://openapi-generator.tech)
Do not edit the class manually.
""" # noqa: E501
import unittest
from airflow_client.client.models.dag_details_response import DAGDetailsResponse
class TestDAGDetailsResponse(unittest.TestCase):
"""DAGDetailsResponse unit test stubs"""
def setUp(self):
pass
def tearDown(self):
pass
def make_instance(self, include_optional) -> DAGDetailsResponse:
"""Test DAGDetailsResponse
include_optional is a boolean, when False only required
params are included, when True both required and
optional params are included """
# uncomment below to create an instance of `DAGDetailsResponse`
"""
model = DAGDetailsResponse()
if include_optional:
return DAGDetailsResponse(
active_runs_count = 56,
allowed_run_types = [
'backfill'
],
asset_expression = { },
bundle_name = '',
bundle_version = '',
catchup = True,
concurrency = 56,
dag_display_name = '',
dag_id = '',
dag_run_timeout = '',
default_args = { },
description = '',
doc_md = '',
end_date = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
file_token = '',
fileloc = '',
has_import_errors = True,
has_task_concurrency_limits = True,
is_backfillable = True,
is_favorite = True,
is_paused = True,
is_paused_upon_creation = True,
is_stale = True,
last_expired = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
last_parse_duration = 1.337,
last_parsed = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
last_parsed_time = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
latest_dag_version = airflow_client.client.models.dag_version_response.DagVersionResponse(
bundle_name = '',
bundle_url = '',
bundle_version = '',
created_at = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
dag_display_name = '',
dag_id = '',
id = '',
version_number = 56, ),
max_active_runs = 56,
max_active_tasks = 56,
max_consecutive_failed_dag_runs = 56,
next_dagrun_data_interval_end = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
next_dagrun_data_interval_start = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
next_dagrun_logical_date = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
next_dagrun_run_after = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
owner_links = {
'key' : ''
},
owners = [
''
],
params = { },
relative_fileloc = '',
render_template_as_native_obj = True,
rerun_with_latest_version = True,
start_date = datetime.datetime.strptime('2013-10-20 19:20:30.00', '%Y-%m-%d %H:%M:%S.%f'),
tags = [
airflow_client.client.models.dag_tag_response.DagTagResponse(
dag_display_name = '',
dag_id = '',
name = '', )
],
template_search_path = [
''
],
timetable_description = '',
timetable_partitioned = True,
timetable_periodic = True,
timetable_summary = '',
timezone = ''
)
else:
return DAGDetailsResponse(
catchup = True,
concurrency = 56,
dag_display_name = '',
dag_id = '',
file_token = '',
fileloc = '',
has_import_errors = True,
has_task_concurrency_limits = True,
is_backfillable = True,
is_paused = True,
is_stale = True,
max_active_tasks = 56,
max_consecutive_failed_dag_runs = 56,
owners = [
''
],
render_template_as_native_obj = True,
tags = [
airflow_client.client.models.dag_tag_response.DagTagResponse(
dag_display_name = '',
dag_id = '',
name = '', )
],
timetable_partitioned = True,
timetable_periodic = True,
)
"""
def testDAGDetailsResponse(self):
"""Test DAGDetailsResponse"""
# inst_req_only = self.make_instance(include_optional=False)
# inst_req_and_optional = self.make_instance(include_optional=True)
if __name__ == '__main__':
unittest.main()