def GetFitSolutionResults(self, request, context):
"""grpc GetFitSolutionResults call"""
msgd(self.GetFitSolutionResults.__doc__)
total_loops = 3
for loop_num in range(total_loops):
# pause 1, 3 seconds...
pause_secs = random.randint(1, 3)
print('(loop %d/%d) pausing %d seconds' % \
((loop_num + 1), total_loops, pause_secs))
time.sleep(pause_secs)
step_progress = core_pb2.StepProgress(\
progress=get_progress(no_errors=True),
steps=[core_pb2.StepProgress(\
progress=get_progress(no_errors=True))])
resp = core_pb2.GetFitSolutionResultsResponse(\
progress=get_progress(no_errors=True),
steps=[step_progress],
exposed_outputs=dict(\
key1=value_pb2.Value(csv_uri='file://uri/to-a/csv'),
key2=value_pb2.Value(dataset_uri='file://uri/to-a/dataset')),
fitted_solution_id=get_solution_id_str())
yield resp
def GetSearchSolutionsResults(self, request, context):
"""grpc GetSearchSolutionsResults call"""
msgd(self.GetSearchSolutionsResults.__doc__)
total_loops = 3
for loop_num in range(total_loops):
# pause 1, 3 seconds...
pause_secs = random.randint(1, 3)
print('(loop %d/%d) pausing %d seconds' % \
((loop_num + 1), total_loops, pause_secs))
time.sleep(pause_secs)
score_list = []
for _loop in range(0, random.randint(0, 3)):
score_list.append(get_solution_search_score())
resp = core_pb2.GetSearchSolutionsResultsResponse(\
progress=get_progress(),
done_ticks=random.randint(1, 9),
all_ticks=10,
solution_id=get_solution_id_str(),
internal_score=0,
scores=score_list)
self.print_resp(resp)
yield resp
def test_SolutionExport():
req = core_pb2.SolutionExportRequest(\
fitted_solution_id=get_solution_id_str(),
rank=round(random.random(), 3))
print(MessageToJson(req, including_default_value_fields=True))
def test_ScoreSolution():
"""work out the req/resp"""
perf_metrics = [\
problem_pb2.ProblemPerformanceMetric(metric=\
get_rand_enum_val(problem_pb2.PerformanceMetric)),
problem_pb2.ProblemPerformanceMetric(metric=\
get_rand_enum_val(problem_pb2.PerformanceMetric))]
req = core_pb2.ScoreSolutionRequest(\
solution_id=get_solution_id_str(),
inputs=[value_pb2.Value(csv_uri='file://uri/to-a/csv'),
value_pb2.Value(dataset_uri='file://uri/to-a/dataset')],
performance_metrics=perf_metrics,
users=[core_pb2.SolutionRunUser(\
id='uuid of user',
choosen=True,
reason='best solution'),
core_pb2.SolutionRunUser(\
id='uuid of user',
choosen=False)],
configuration=get_scoring_configuration())
"""
message ScoreSolutionRequest {
string solution_id = 1;
repeated Value inputs = 2;
repeated ProblemPerformanceMetric performance_metrics = 3;
// Any users associated with this call itself. Optional.
repeated SolutionRunUser users = 4;
ScoringConfiguration configuration = 5;
}
"""
print(MessageToJson(req, including_default_value_fields=True))
def test_ProduceSolution():
req = core_pb2.ProduceSolutionRequest(\
fitted_solution_id=get_solution_id_str(),
inputs=[value_pb2.Value(csv_uri='file://uri/to-a/csv'),
value_pb2.Value(dataset_uri='file://uri/to-a/dataset')],
expose_outputs=['steps.1.steps.4.produce'],
expose_value_types=[get_rand_enum_val(value_pb2.ValueType),
get_rand_enum_val(value_pb2.ValueType)],
users=[core_pb2.SolutionRunUser(\
id='uuid of user',
choosen=True,
reason='best solution'),
core_pb2.SolutionRunUser(\
id='uuid of user',
choosen=False)])
print(MessageToJson(req, including_default_value_fields=True))
def test_GetSearchSolutionsResults():
"""work out the req/resp"""
req = core_pb2.GetSearchSolutionsResultsRequest(\
search_id=get_search_id_str())
print(MessageToJson(req))
score_list = []
for _loop in range(0, random.randint(1, 3)):
score_list.append(get_solution_search_score())
resp = core_pb2.GetSearchSolutionsResultsResponse(\
progress=get_progress(),
done_ticks=random.randint(1, 9),
all_ticks=10,
solution_id=get_solution_id_str(),
internal_score=0,
scores=score_list)
print(MessageToJson(resp, including_default_value_fields=True))
def test_GetFitSolutionResults():
req = core_pb2.GetFitSolutionResultsRequest(
request_id=get_request_id_str())
print(MessageToJson(req, including_default_value_fields=True))
step_progress = core_pb2.StepProgress(\
progress=get_progress(no_errors=True),
steps=[core_pb2.StepProgress(\
progress=get_progress(no_errors=True))])
resp = core_pb2.GetFitSolutionResultsResponse(\
progress=get_progress(no_errors=True),
steps=[step_progress],
exposed_outputs=dict(\
key1=value_pb2.Value(csv_uri='file://uri/to-a/csv'),
key2=value_pb2.Value(dataset_uri='file://uri/to-a/dataset')),
fitted_solution_id=get_solution_id_str())
print(MessageToJson(resp, including_default_value_fields=True))