def test_get_flow_run_info_raises_informative_error(patch_post):
post = patch_post(dict(data={"flow_run_by_pk": None}))
with set_temporary_config(
{"cloud.api": "http://my-cloud.foo", "cloud.auth_token": "secret_token"}
):
client = Client()
with pytest.raises(ClientError, match="not found"):
client.get_flow_run_info(flow_run_id="74-salt")
def test_get_flow_run_info_with_nontrivial_payloads(monkeypatch):
response = """
{
"flow_run_by_pk": {
"version": 0,
"parameters": {"x": {"deep": {"nested": 5}}},
"context": {"my_val": "test"},
"scheduled_start_time": "2019-01-25T19:15:58.632412+00:00",
"serialized_state": {
"type": "Pending",
"_result": {"type": "SafeResult", "value": "42", "result_handler": {"type": "JSONResultHandler"}},
"message": null,
"__version__": "0.3.3+309.gf1db024",
"cached_inputs": null
},
"task_runs":[
{
"id": "da344768-5f5d-4eaf-9bca-83815617f713",
"task": {
"id": "da344768-5f5d-4eaf-9bca-83815617f713",
"slug": "da344768-5f5d-4eaf-9bca-83815617f713"
},
"version": 0,
"serialized_state": {
"type": "Pending",
"result": null,
"message": null,
"__version__": "0.3.3+309.gf1db024",
"cached_inputs": null
}
}
]
}
}
"""
post = MagicMock(return_value=MagicMock(json=MagicMock(return_value=dict(
data=json.loads(response)))))
session = MagicMock()
session.return_value.post = post
monkeypatch.setattr("requests.Session", session)
with set_temporary_config({
"cloud.graphql": "http://my-cloud.foo",
"cloud.auth_token": "secret_token"
}):
client = Client()
result = client.get_flow_run_info(flow_run_id="74-salt")
assert isinstance(result, FlowRunInfoResult)
assert isinstance(result.scheduled_start_time, datetime.datetime)
assert result.scheduled_start_time.minute == 15
assert result.scheduled_start_time.year == 2019
assert isinstance(result.state, Pending)
assert result.state.result == "42"
assert result.state.message is None
assert result.version == 0
assert isinstance(result.parameters, dict)
assert result.parameters["x"]["deep"]["nested"] == 5
# ensures all sub-dictionaries are actually dictionaries
assert json.loads(json.dumps(result.parameters)) == result.parameters
assert isinstance(result.context, dict)
assert result.context["my_val"] == "test"
def test_get_flow_run_info_raises_informative_error(monkeypatch):
response = """
{
"flow_run_by_pk": null
}
"""
post = MagicMock(return_value=MagicMock(json=MagicMock(return_value=dict(
data=json.loads(response)))))
session = MagicMock()
session.return_value.post = post
monkeypatch.setattr("requests.Session", session)
with set_temporary_config({
"cloud.graphql": "http://my-cloud.foo",
"cloud.auth_token": "secret_token"
}):
client = Client()
with pytest.raises(ClientError, match="not found"):
client.get_flow_run_info(flow_run_id="74-salt")
def test_get_flow_run_info(patch_post):
response = {
"flow_run_by_pk": {
"id": "da344768-5f5d-4eaf-9bca-83815617f713",
"flow_id": "da344768-5f5d-4eaf-9bca-83815617f713",
"name": "flow-run-name",
"version": 0,
"parameters": {},
"context": None,
"scheduled_start_time": "2019-01-25T19:15:58.632412+00:00",
"serialized_state": {
"type": "Pending",
"_result": {
"type": "SafeResult",
"value": "42",
"result_handler": {"type": "JSONResultHandler"},
},
"message": None,
"__version__": "0.3.3+309.gf1db024",
"cached_inputs": None,
},
"task_runs": [
{
"id": "da344768-5f5d-4eaf-9bca-83815617f713",
"task": {
"id": "da344768-5f5d-4eaf-9bca-83815617f713",
"slug": "da344768-5f5d-4eaf-9bca-83815617f713",
},
"version": 0,
"serialized_state": {
"type": "Pending",
"result": None,
"message": None,
"__version__": "0.3.3+309.gf1db024",
"cached_inputs": None,
},
}
],
}
}
post = patch_post(dict(data=response))
with set_temporary_config(
{"cloud.api": "http://my-cloud.foo", "cloud.auth_token": "secret_token"}
):
client = Client()
result = client.get_flow_run_info(flow_run_id="74-salt")
assert isinstance(result, FlowRunInfoResult)
assert isinstance(result.scheduled_start_time, datetime.datetime)
assert result.scheduled_start_time.minute == 15
assert result.scheduled_start_time.year == 2019
assert isinstance(result.state, Pending)
assert result.state.result == "42"
assert result.state.message is None
assert result.version == 0
assert isinstance(result.parameters, dict)
assert result.context is None
def test_get_flow_run_info(monkeypatch):
response = """
{
"flow_run_by_pk": {
"version": 0,
"parameters": {},
"context": null,
"scheduled_start_time": "2019-01-25T19:15:58.632412+00:00",
"serialized_state": {
"type": "Pending",
"_result": {"type": "SafeResult", "value": "42", "result_handler": {"type": "JSONResultHandler"}},
"message": null,
"__version__": "0.3.3+309.gf1db024",
"cached_inputs": null
},
"task_runs":[
{
"id": "da344768-5f5d-4eaf-9bca-83815617f713",
"task_id": "da344768-5f5d-4eaf-9bca-83815617f713",
"version": 0,
"serialized_state": {
"type": "Pending",
"result": null,
"message": null,
"__version__": "0.3.3+309.gf1db024",
"cached_inputs": null
}
}
]
}
}
"""
post = MagicMock(
return_value=MagicMock(
json=MagicMock(return_value=dict(data=json.loads(response)))
)
)
monkeypatch.setattr("requests.post", post)
with set_temporary_config(
{"cloud.graphql": "http://my-cloud.foo", "cloud.auth_token": "secret_token"}
):
client = Client()
result = client.get_flow_run_info(flow_run_id="74-salt")
assert isinstance(result, FlowRunInfoResult)
assert isinstance(result.scheduled_start_time, datetime.datetime)
assert result.scheduled_start_time.minute == 15
assert result.scheduled_start_time.year == 2019
assert isinstance(result.state, Pending)
assert result.state.result == "42"
assert result.state.message is None
assert result.version == 0
assert result.parameters == dict()
def create_prefect_flow_run(flow_name: str, project_name: str, task_refs: List,
params: Mapping) -> str:
"""Creates new prefect flow run for given flow id, parameters, task references
and API server URL to send GraphQL requests to.
Returns results value and state from a Prefect flow run.
"""
try:
flow_run = StartFlowRun(flow_name=flow_name,
project_name=project_name,
parameters=params)
flow_run_id = flow_run.run()
client = Client()
while True:
time.sleep(10)
flow_run_info = client.get_flow_run_info(flow_run_id)
flow_state = flow_run_info.state
task_runs_info = flow_run_info.task_runs
if flow_state.is_finished():
task_res_locs = {}
for task_run in task_runs_info:
# Return ref if ref string is a substring of any task slug
ref = next((ref_str for ref_str in task_refs
if ref_str in task_run.task_slug), None)
if ref:
task_id = task_run.id
task_state = client.get_task_run_state(task_id)
task_res_locs[ref] = task_state._result.location
task_results = {}
for ref, loc in task_res_locs.items():
local_res = LocalResult()
result = local_res.read(loc)
task_results[ref] = result.value
return task_results, flow_state, task_res_locs
except ValueError as err:
raise err
