def test_root(self):
model_app = ModelApp([])
app = model_app.app.test_client()
resp = app.get('/')
self.assertEqual(resp.status_code, 200)
model_app = ModelApp([], expose_docs=True)
app = model_app.app.test_client()
resp = app.get('/')
self.assertEqual(resp.status_code, 302)
def setUpClass(cls):
# DO NOT set app.testing = True here
# doing so *disables* error handling in the application and instead
# passes errors on to the test client (in our case, instances of
# unittest.TestCase).
# In this class we actually want to test the applications error handling
# and thus do not set this attribute.
# See, http://flask.pocoo.org/docs/0.12/api/#flask.Flask.test_client
prediction_service = PredictionService(name='failing-model',
api_version='B',
model=None,
meta={
'1': 'one',
'two': 2
})
cls.model_app = ModelApp([prediction_service])
flask_app = cls.model_app.app
@flask_app.route('/test-error-handling/', methods=['POST'])
def test_error():
flask.request.get_json(force=True)
raise Exception('exceptional testing of exceptions')
cls.app_test_client = flask_app.test_client()
def test_readiness_not_ready1(self):
model_app = ModelApp([])
app = model_app.app.test_client()
resp_alive = app.get('/-/alive')
resp_ready = app.get('/-/ready')
expected_data = {
'request_id': '123',
'porter_version': __version__,
'deployed_on': cn.HEALTH_CHECK_VALUES.DEPLOYED_ON,
'services': {},
'app_meta': {
'description': '<div></div><div><p>(porter v0.15.3)</p></div>',
'expose_docs': False,
'name': None,
'version': None
},
}
self.assertEqual(resp_alive.status_code, 200)
self.assertEqual(resp_ready.status_code, 503)
alive_response = json.loads(resp_alive.data)
ready_respnose = json.loads(resp_ready.data)
self.assertEqual(alive_response, expected_data)
self.assertEqual(ready_respnose, expected_data)
# make sure the defined schema matches reality
sc.health_check.validate(alive_response) # should not raise exception
sc.health_check.validate(ready_respnose) # should not raise exception
def test_custom2(self, mock_app, mock_make_openapi_spec):
model_app = ModelApp([], docs_prefix='/docs', docs_url='/d/', docs_json_url='/d.json', expose_docs=True)
expected_calls = [
mock.call('/docs/d/'),
mock.call('/docs/assets/swagger-ui/<path:filename>'),
mock.call('/docs/d.json'),
]
model_app.app.route.assert_has_calls(expected_calls, any_order=True)
def test_defaults(self, mock_app, mock_make_openapi_spec):
model_app = ModelApp([], expose_docs=True)
expected_calls = [
mock.call('/docs/'),
mock.call('/assets/swagger-ui/<path:filename>'),
mock.call('/_docs.json'),
]
model_app.app.route.assert_has_calls(expected_calls, any_order=True)
def test_readiness_not_ready2(self, mock_init):
mock_init.return_value = None
class C(PredictionService):
status = 'NOTREADY'
request_schemas = {}
response_schemas = {}
svc = C()
svc.name = 'foo'
svc.api_version = 'bar'
svc.meta = {'k': 1}
svc.id = 'foo:bar'
svc.endpoint = '/foo/bar/'
svc.route_kwargs = {}
model_app = ModelApp([svc])
app = model_app.app.test_client()
resp_alive = app.get('/-/alive')
resp_ready = app.get('/-/ready')
expected_data = {
'request_id': '123',
'porter_version': __version__,
'deployed_on': cn.HEALTH_CHECK_VALUES.DEPLOYED_ON,
'services': {
'foo:bar': {
'status': 'NOTREADY',
'endpoint': '/foo/bar/',
'model_context': {
'model_name': 'foo',
'api_version': 'bar',
'model_meta': {
'k': 1
}
}
}
},
'app_meta': {
'description': '<div></div><div><p>(porter v0.15.3)</p></div>',
'expose_docs': False,
'name': None,
'version': None
},
}
self.assertEqual(resp_alive.status_code, 200)
self.assertEqual(resp_ready.status_code, 503)
alive_response = json.loads(resp_alive.data)
ready_respnose = json.loads(resp_ready.data)
self.assertEqual(alive_response, expected_data)
self.assertEqual(ready_respnose, expected_data)
# make sure the defined schema matches reality
sc.health_check.validate(alive_response) # should not raise exception
sc.health_check.validate(ready_respnose) # should not raise exception
def test_constructor_fail_on_duplicate_services(self, mock_app):
class service1:
id = 'service1'
endpoint = '/an/endpoint'
route_kwargs = {}
request_schemas = {}
response_schemas = {}
name = 'service1'
class service2:
id = 'service1'
endpoint = '/foobar'
route_kwargs = {}
request_schemas = {}
response_schemas = {}
name = 'service2'
with self.assertRaisesRegex(ValueError, 'service has already been added'):
model_app = ModelApp([service1, service2])
def test_docs_paths(self):
class SC(BaseService):
def serve(self):
pass
def status(self):
pass
action = 'endpoint'
service = SC(name='the', api_version='v1')
model_app = ModelApp([service], expose_docs=True)
docs_json = model_app.docs_json
expected_keys = ['openapi', 'info', 'paths', 'components']
self.assertEqual(set(docs_json.keys()), set(expected_keys))
expected_paths = ['/the/v1/endpoint', '/-/alive', '/-/ready']
self.assertEqual(set(docs_json['paths'].keys()), set(expected_paths))
def test_constructor_schema_handling(self, mock_make_openapi_spec, mock_app):
class service1:
id = 'service1'
endpoint = '/an/endpoint'
route_kwargs = {'foo': 1, 'bar': 'baz'}
request_schemas = {'GET': object()}
response_schemas = {'POST': object()}
name = 'service1'
class service2:
id = 'service2'
endpoint = '/foobar'
route_kwargs = {'methods': ['GET']}
request_schemas = {'GET': object()}
response_schemas = None
name = 'service2'
class service3:
id = 'service3'
endpoint = '/supa/dupa'
route_kwargs = {'methods': ['GET'], 'strict_slashes': True}
request_schemas = {'GET': object(), 'POST': object()}
response_schemas = {'GET': object()}
name = 'service3'
# add the services and validate they were routed with the correct
# parameters.
model_app = ModelApp([service1, service2, service3],
expose_docs=True, docs_url='/custom/docs/url/')
# verify that the schemas were correctly registered
expected_request_schemas = {
service1.endpoint: service1.request_schemas,
service2.endpoint: service2.request_schemas,
service3.endpoint: service3.request_schemas
}
self.assertEqual(model_app._request_schemas, expected_request_schemas)
health_check_responses = [schemas.ResponseSchema(schemas.health_check, 200)]
expected_response_schemas = {
service1.endpoint: service1.response_schemas,
# service 2 did not have a response schema
service3.endpoint: service3.response_schemas,
'/-/alive': ModelApp._health_check_response_schemas,
'/-/ready': ModelApp._health_check_response_schemas
}
self.assertEqual(model_app._response_schemas, expected_response_schemas)
def test_constructor_routing(self, mock__route_endpoint, mock_make_openapi_spec):
class service1:
id = 'service1'
endpoint = '/an/endpoint'
route_kwargs = {'foo': 1, 'bar': 'baz'}
request_schemas = {'GET': object()}
response_schemas = {'POST': object()}
name = 'service1'
class service2:
id = 'service2'
endpoint = '/foobar'
route_kwargs = {'methods': ['GET']}
request_schemas = {'GET': object()}
response_schemas = None
name = 'service2'
class service3:
id = 'service3'
endpoint = '/supa/dupa'
route_kwargs = {'methods': ['GET'], 'strict_slashes': True}
request_schemas = {'GET': object(), 'POST': object()}
response_schemas = {'GET': object()}
name = 'service3'
# add the services and validate they were routed with the correct
# parameters.
model_app = ModelApp([service1, service2, service3],
expose_docs=True, docs_url='/custom/docs/url/')
expected_calls = [
mock.call(service1.endpoint, service1, service1.route_kwargs,
request_schemas=service1.request_schemas,
response_schemas=service1.response_schemas,
additional_params={'GET': {'tags': [service1.name]},
'POST': {'tags': [service1.name]}}),
mock.call(service2.endpoint, service2, service2.route_kwargs,
request_schemas=service2.request_schemas,
response_schemas=service2.response_schemas,
additional_params={'GET': {'tags': [service2.name]}}),
mock.call(service3.endpoint, service3, service3.route_kwargs,
request_schemas=service3.request_schemas,
response_schemas=service3.response_schemas,
additional_params={'GET': {'tags': [service3.name]},
'POST': {'tags': [service3.name]}})
]
mock__route_endpoint.assert_has_calls(expected_calls, any_order=True)
def test_can_serve_swagger_files(self):
model_app = ModelApp([], expose_docs=True)
app = model_app.app.test_client()
files = [
'favicon-16x16.png',
'favicon-32x32.png',
'index.html',
'oauth2-redirect.html',
'swagger-ui-bundle.js',
'swagger-ui-bundle.js.map',
'swagger-ui-standalone-preset.js',
'swagger-ui-standalone-preset.js.map',
'swagger-ui.css',
'swagger-ui.css.map',
'swagger-ui.js',
'swagger-ui.js.map',
'swagger_template.html',
]
for filename in files:
resp = app.get(f'/assets/swagger-ui/{filename}')
self.assertEqual(resp.status_code, 200)
from porter.datascience import BaseModel
from porter.services import ModelApp, PredictionService
from porter.utils import JSONLogFormatter
class Model(BaseModel):
def predict(self, X):
return (X['foo'] % 3) * X['bar']
prediction_svc = PredictionService(model=Model(),
name='my-model',
api_version='v1',
batch_prediction=True,
log_api_calls=True)
app = ModelApp([prediction_svc])
if __name__ == '__main__':
import logging
stream_handler = logging.StreamHandler()
formatter = JSONLogFormatter('asctime', 'levelname', 'module', 'name',
'message', 'request_id', 'request_data',
'response_data', 'service_class', 'event')
stream_handler.setFormatter(formatter)
logger = logging.getLogger('porter')
logger.setLevel('INFO')
logger.addHandler(stream_handler)
app.run()
api_version='v1', # The version of the model. Returned
# to client in the prediction response.
# Required.
#
preprocessor=preprocessor, # preprocessor.process() is
# called on the POST request data
# before predicting. Optional.
#
postprocessor=Postprocessor(), # postprocessor.process() is
# called on the model's predictions before
# returning to user. Optional.
#
feature_schema=feature_schema, # The input schema is used to validate
# the payload of the POST request.
# Optional.
validate_request_data=True, # Whether to validate the request data.
#
batch_prediction=True # Whether the API will accept an array of
# JSON objects to predict on or a single
# JSON object only.
)
# The model app is simply a wrapper around the `flask.Flask` object.
model_app = ModelApp([prediction_service])
if __name__ == '__main__':
# you can run this with `gunicorn app:model_app`, or
# simply execute this script with Python and send POST requests
# to localhost:8000/supa-dupa-model/prediction/
model_app.run(port=8000)
def setUpClass(cls):
# define objects for model 1
class Preprocessor1(BasePreProcessor):
def process(self, X):
X = X.copy() # silence SettingWithCopyWarning
X['feature2'] = X.feature2.astype(str)
return X
class Model1(BaseModel):
feature2_map = {str(x + 1): x for x in range(5)}
def predict(self, X):
return X['feature1'] * X.feature2.map(self.feature2_map)
class Postprocessor1(BasePostProcessor):
def process(self, X_input, X_preprocessed, predictions):
return predictions * -1
feature_schema1 = sc.Object(properties={
'feature1': sc.Number(),
'feature2': sc.Number(),
})
# define objects for model 2
class Preprocessor2(BasePreProcessor):
def process(self, X):
X['feature3'] = range(len(X))
return X
class Model2(BaseModel):
def predict(self, X):
return X['feature1'] + X['feature3']
feature_schema2 = sc.Object(properties={'feature1': sc.Number()})
def user_check(X):
if (X.feature1 == 0).any():
raise exc.UnprocessableEntity
# define objects for model 3
class Model3(BaseModel):
def predict(self, X):
return X['feature1'] * -1
feature_schema3 = sc.Object(properties={'feature1': sc.Number()})
wrong_prediction_schema3 = sc.Number(additional_params=dict(minimum=0))
cls.prediction_service_error = E = Exception(
'this mock service failed during prediction')
class ModelFailing(BaseModel):
def predict(self, X):
raise E
# define configs and add services to app
prediction_service1 = PredictionService(model=Model1(),
name='a-model',
api_version='v0',
action='predict',
preprocessor=Preprocessor1(),
postprocessor=Postprocessor1(),
feature_schema=feature_schema1,
validate_request_data=True,
batch_prediction=True)
prediction_service2 = PredictionService(model=Model2(),
name='anotherModel',
api_version='v1',
namespace='n/s/',
preprocessor=Preprocessor2(),
postprocessor=None,
feature_schema=feature_schema2,
validate_request_data=True,
batch_prediction=True,
additional_checks=user_check)
with warnings.catch_warnings():
warnings.simplefilter('ignore')
prediction_service3 = PredictionService(
model=Model3(),
name='model-3',
api_version='v0.0-alpha',
preprocessor=None,
postprocessor=None,
feature_schema=feature_schema3,
validate_request_data=True,
validate_response_data=True,
batch_prediction=False,
meta={
'algorithm': 'randomforest',
'lasttrained': 1
})
prediction_service4 = PredictionService(
model=Model3(),
name='model-4',
api_version='v0.0-alpha',
preprocessor=None,
postprocessor=None,
feature_schema=feature_schema3,
validate_request_data=True,
validate_response_data=True,
batch_prediction=False,
meta={
'algorithm': 'randomforest',
'lasttrained': 1
})
prediction_service5 = PredictionService(
model=Model3(),
name='model-5',
api_version='v0.0-alpha',
preprocessor=None,
postprocessor=None,
feature_schema=feature_schema3,
prediction_schema=wrong_prediction_schema3,
validate_request_data=True,
validate_response_data=True,
batch_prediction=False,
meta={
'algorithm': 'randomforest',
'lasttrained': 1
})
prediction_service_failing = PredictionService(
model=ModelFailing(),
name='failing-model',
api_version='v1',
action='fail',
)
cls.model_app = ModelApp([
prediction_service1,
prediction_service2,
prediction_service3,
prediction_service4,
prediction_service5,
prediction_service_failing,
])
cls.app = cls.model_app.app.test_client()
def test_readiness_ready_ready2(self, mock_init):
mock_init.return_value = None
svc1 = PredictionService()
svc1.name = 'model1'
svc1.api_version = '1.0.0'
svc1.id = 'model1:1.0.0'
svc1.endpoint = '/model1/1.0.0/prediction'
svc1.meta = {'foo': 1, 'bar': 2}
svc1.response_schemas = {}
svc1.request_schemas = {}
svc2 = PredictionService()
svc2.name = 'model2'
svc2.api_version = 'v0'
svc2.id = 'model2:v0'
svc2.endpoint = '/model2/v0/prediction'
svc2.meta = {'foo': 1}
svc2.response_schemas = {}
svc2.request_schemas = {}
model_app = ModelApp([svc1, svc2])
app = model_app.app.test_client()
resp_alive = app.get('/-/alive')
resp_ready = app.get('/-/ready')
expected_data = {
'request_id': '123',
'porter_version': __version__,
'deployed_on': cn.HEALTH_CHECK_VALUES.DEPLOYED_ON,
'app_meta': {
'description': '<div></div><div><p>(porter v0.15.3)</p></div>',
'expose_docs': False,
'name': None,
'version': None
},
'services': {
'model1:1.0.0': {
'status': 'READY',
'endpoint': '/model1/1.0.0/prediction',
'model_context': {
'model_name': 'model1',
'api_version': '1.0.0',
'model_meta': {
'foo': 1,
'bar': 2
},
}
},
'model2:v0': {
'status': 'READY',
'endpoint': '/model2/v0/prediction',
'model_context': {
'model_name': 'model2',
'api_version': 'v0',
'model_meta': {
'foo': 1
},
}
}
}
}
self.assertEqual(resp_alive.status_code, 200)
self.assertEqual(resp_ready.status_code, 200)
alive_response = json.loads(resp_alive.data)
ready_respnose = json.loads(resp_ready.data)
self.assertEqual(alive_response, expected_data)
self.assertEqual(ready_respnose, expected_data)
# make sure the defined schema matches reality
sc.health_check.validate(alive_response) # should not raise exception
sc.health_check.validate(ready_respnose) # should not raise exception
raise PorterException('input cannot include zeros', code=422)
input_schema = sc.Array(item_type=sc.Number(), reference_name='InputSchema')
output_schema = sc.Number(reference_name='OutputSchema')
service_kw = dict(input_schema=input_schema,
output_schema=output_schema,
validate_request_data=True)
sum_service = FunctionService('sum',
sum,
name='math',
api_version='v1',
**service_kw)
prod_service = FunctionService('prod',
prod,
name='math',
api_version='v1',
additional_checks=check_for_zeros,
**service_kw)
app = ModelApp(
[sum_service, prod_service],
name='FunctionService Example',
description=
'Expose arbitrary callable functions by subclassing BaseService.',
expose_docs=True)
if __name__ == '__main__':
app.run()
feature_schema = Object(
'Inputs to the ratings model',
properties=dict(
user_id=Integer('The user ID.'),
title_id=Integer('The title ID.'),
is_tv=Boolean('Whether the content is a TV show.'),
genre=String('The genre.',
additional_params={'enum': ['comedy', 'action', 'drama']}),
average_rating=Number('The title\'s average rating.',
additional_params={'minimum': 0, 'maximum': 10}),
),
reference_name='RatingsModelFeatures'
)
# build the prediction service
prediction_service = PredictionService(
model=my_model,
name='my-model',
api_version='v1',
feature_schema=feature_schema,
validate_request_data=True)
app = ModelApp(
[prediction_service],
name='Example Model',
description='Minimal example of a model with input validation and documentation.',
expose_docs=True)
if __name__ == '__main__':
app.run()
def test_liveness_live(self):
model_app = ModelApp([])
app = model_app.app.test_client()
resp = app.get('/-/alive')
self.assertEqual(resp.status_code, 200)
import urllib.request
from porter.services import ModelApp, PredictionService
service1 = PredictionService(model=None, name='a-model', api_version='0.0.0')
service2 = PredictionService(model=None,
name='yet-another-model',
api_version='1.0.0')
service3 = PredictionService(model=None,
name='yet-another-yet-another-model',
api_version='1.0.0-alpha',
meta={'arbitrary details': 'about the model'})
model_app = ModelApp([service1, service2, service3])
def get(url):
with urllib.request.urlopen(url) as f:
return f.read()
def run_app(model_app):
t = threading.Thread(target=model_app.run, daemon=True)
t.start()
class Shhh:
"""Silence flask logging."""
def __init__(self):
By default you can find the OpenAPI documentation at the endpoint `/docs/` but
this too can be customized.
"""
# define the services we want to serve from
services = [
instance_prediction_service,
batch_prediction_service,
probabilistic_service,
spark_interface_service,
custom_service]
model_app = ModelApp(
services,
name='Example Model',
description='An unhelpful description of what this application.',
expose_docs=True)
"""
These are just some convenience functions to test the example.
"""
class Shhh:
"""Silence flask logging."""
def __init__(self):
self.devnull = open(os.devnull, 'w')
self.stdout = sys.stdout
