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[WIP] Dataiku Python API for stratified models when forcing partition #64

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[WIP] Dataiku Python API for stratified models when forcing partition #64

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10 changes: 8 additions & 2 deletions dataikuapi/apinode_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@ def __init__(self, uri, service_id, api_key=None):
"""
DSSBaseClient.__init__(self, "%s/%s" % (uri, "public/api/v1/%s" % service_id), api_key)

def predict_record(self, endpoint_id, features, forced_generation=None, dispatch_key=None, context=None):
def predict_record(self, endpoint_id, features, forced_generation=None, dispatch_key=None, context=None, partition=None):
"""
Predicts a single record on a DSS API node endpoint (standard or custom prediction)

Expand All @@ -25,6 +25,7 @@ def predict_record(self, endpoint_id, features, forced_generation=None, dispatch
:param forced_generation: See documentation about multi-version prediction
:param dispatch_key: See documentation about multi-version prediction
:param context: Optional, Python dictionary of additional context information. The context information is logged, but not directly used.
:param partition: Optional, partition id of partitioned model to use. Guessed otherwise from record if needed.

:return: a Python dict of the API answer. The answer contains a "result" key (itself a dict)
"""
Expand All @@ -37,17 +38,20 @@ def predict_record(self, endpoint_id, features, forced_generation=None, dispatch
obj["dispatch"] = {"forcedGeneration" : forced_generation }
elif dispatch_key is not None:
obj["dispatch"] = {"dispatchKey" : dispatch_key }
if partition is not None:
obj["partition"] = partition

return self._perform_json("POST", "%s/predict" % endpoint_id, body = obj)

def predict_records(self, endpoint_id, records, forced_generation=None, dispatch_key=None):
def predict_records(self, endpoint_id, records, forced_generation=None, dispatch_key=None, partition=None):
"""
Predicts a batch of records on a DSS API node endpoint (standard or custom prediction)

:param str endpoint_id: Identifier of the endpoint to query
:param records: Python list of records. Each record must be a Python dict. Each record must contain a "features" dict (see predict_record) and optionally a "context" dict.
:param forced_generation: See documentation about multi-version prediction
:param dispatch_key: See documentation about multi-version prediction
:param partition: Optional, partition id of partitioned model to use for all records. Guessed otherwise from each record if needed.

:return: a Python dict of the API answer. The answer contains a "results" key (which is an array of result objects)
"""
Expand All @@ -64,6 +68,8 @@ def predict_records(self, endpoint_id, records, forced_generation=None, dispatch
obj["dispatch"] = {"forcedGeneration" : forced_generation }
elif dispatch_key is not None:
obj["dispatch"] = {"dispatchKey" : dispatch_key }
if partition is not None:
obj["partition"] = partition

return self._perform_json("POST", "%s/predict-multi" % endpoint_id, body = obj)

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