[HWORKS-798] Add **kwargs to python client libraries (logicalclocks#205)

Author: robzor92

python/__init__.py

@@ -12,4 +12,4 @@
 #   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #   See the License for the specific language governing permissions and
 #   limitations under the License.
-#
+#

python/hsml/deployable_component.py

@@ -33,6 +33,7 @@ def __init__(
         script_file: Optional[str] = None,
         resources: Optional[Resources] = None,
         inference_batcher: Optional[Union[InferenceBatcher, dict]] = None,
+        **kwargs,
     ):
         self._script_file = script_file
         self._resources = resources

python/hsml/deployable_component_logs.py

@@ -29,7 +29,7 @@ class DeployableComponentLogs:
         `DeployableComponentLogs`. Server logs of a deployable component
     """
 
-    def __init__(self, instance_name: str, content: str):
+    def __init__(self, instance_name: str, content: str, **kwargs):
         self._instance_name = instance_name
         self._content = content
         self._created_at = datetime.now()

python/hsml/deployment.py

@@ -34,7 +34,11 @@ class Deployment:
     """Metadata object representing a deployment in Model Serving."""
 
     def __init__(
-        self, predictor, name: Optional[str] = None, description: Optional[str] = None
+        self,
+        predictor,
+        name: Optional[str] = None,
+        description: Optional[str] = None,
+        **kwargs,
     ):
         self._predictor = predictor
         self._description = description

python/hsml/inference_batcher.py

@@ -40,6 +40,7 @@ def __init__(
         max_batch_size: Optional[int] = None,
         max_latency: Optional[int] = None,
         timeout: Optional[int] = None,
+        **kwargs,
     ):
         self._enabled = enabled if enabled is not None else INFERENCE_BATCHER.ENABLED
         self._max_batch_size = max_batch_size if max_batch_size is not None else None

python/hsml/inference_endpoint.py

@@ -30,7 +30,7 @@ class InferenceEndpointPort:
         `InferenceEndpointPort`. Port of an inference endpoint.
     """
 
-    def __init__(self, name: str, number: int):
+    def __init__(self, name: str, number: int, **kwargs):
         self._name = name
         self._number = number
 

python/hsml/inference_logger.py

@@ -37,6 +37,7 @@ def __init__(
         self,
         kafka_topic: Optional[Union[KafkaTopic, dict]] = DEFAULT,
         mode: Optional[str] = INFERENCE_LOGGER.MODE_ALL,
+        **kwargs,
     ):
         self._kafka_topic = util.get_obj_from_json(kafka_topic, KafkaTopic)
         self._mode = self._validate_mode(mode) or (

python/hsml/kafka_topic.py

@@ -29,6 +29,7 @@ def __init__(
         name: str = KAFKA_TOPIC.CREATE,
         num_replicas: Optional[int] = None,
         num_partitions: Optional[int] = None,
+        **kwargs,
     ):
         self._name = name
         self._num_replicas, self._num_partitions = self._validate_topic_config(

python/hsml/model.py

@@ -51,6 +51,7 @@ def __init__(
         input_example=None,
         framework=None,
         model_registry_id=None,
+        **kwargs,
     ):
         self._id = id
         self._name = name

python/hsml/model_registry.py

@@ -34,6 +34,7 @@ def __init__(
         project_id,
         model_registry_id,
         shared_registry_project_name=None,
+        **kwargs,
     ):
         self._project_name = project_name
         self._project_id = project_id

python/hsml/model_schema.py

@@ -35,6 +35,7 @@ def __init__(
         self,
         input_schema: Optional[Schema] = None,
         output_schema: Optional[Schema] = None,
+        **kwargs,
     ):
         if input_schema is not None:
             self.input_schema = input_schema

python/hsml/model_serving.py

@@ -32,7 +32,12 @@
 class ModelServing:
     DEFAULT_VERSION = 1
 
-    def __init__(self, project_name: str, project_id: int):
+    def __init__(
+        self,
+        project_name: str,
+        project_id: int,
+        **kwargs,
+    ):
         self._project_name = project_name
         self._project_id = project_id
 

python/hsml/predictor.py

@@ -52,6 +52,7 @@ def __init__(
         description: Optional[str] = None,
         created_at: Optional[str] = None,
         creator: Optional[str] = None,
+        **kwargs,
     ):
         serving_tool = (
             self._validate_serving_tool(serving_tool)

python/hsml/predictor_state.py

@@ -34,6 +34,7 @@ def __init__(
         deployed: Optional[bool],
         condition: Optional[PredictorStateCondition],
         status: str,
+        **kwargs,
     ):
         self._available_predictor_instances = available_predictor_instances
         self._available_transformer_instances = available_transformer_instances

python/hsml/predictor_state_condition.py

@@ -28,6 +28,7 @@ def __init__(
         type: str,
         status: Optional[bool] = None,
         reason: Optional[str] = None,
+        **kwargs,
     ):
         self._type = type
         self._status = status

python/hsml/python/model.py

@@ -40,6 +40,7 @@ def __init__(
         training_dataset=None,
         input_example=None,
         model_registry_id=None,
+        **kwargs,
     ):
         super().__init__(
             id,

python/hsml/resources.py

@@ -40,6 +40,7 @@ def __init__(
         cores: int,
         memory: int,
         gpus: int,
+        **kwargs,
     ):
         self._cores = cores
         self._memory = memory

python/hsml/schema.py

@@ -44,6 +44,7 @@ def __init__(
                 list,
             ]
         ] = None,
+        **kwargs,
     ):
         # A tensor schema is either ndarray of a list containing name, type and shape dicts
         if isinstance(object, numpy.ndarray) or (

python/hsml/sklearn/model.py

@@ -40,6 +40,7 @@ def __init__(
         training_dataset=None,
         input_example=None,
         model_registry_id=None,
+        **kwargs,
     ):
         super().__init__(
             id,

python/hsml/tag.py

@@ -31,6 +31,7 @@ def __init__(
         items=None,
         count=None,
         type=None,
+        **kwargs,
     ):
         self._name = name
         self._value = value

python/hsml/tensorflow/model.py

@@ -40,6 +40,7 @@ def __init__(
         training_dataset=None,
         input_example=None,
         model_registry_id=None,
+        **kwargs,
     ):
         super().__init__(
             id,

python/hsml/torch/model.py

@@ -40,6 +40,7 @@ def __init__(
         training_dataset=None,
         input_example=None,
         model_registry_id=None,
+        **kwargs,
     ):
         super().__init__(
             id,

python/hsml/transformer.py

@@ -30,6 +30,7 @@ def __init__(
         self,
         script_file: str,
         resources: Optional[Union[TransformerResources, dict]] = None,  # base
+        **kwargs,
     ):
         resources = (
             self._validate_resources(

python/setup.py

@@ -40,13 +40,10 @@ def read(fname):
         "numpy",
         "pyjks",
         "mock",
-        "tqdm"
+        "tqdm",
     ],
     extras_require={
-        "dev": [
-            "pytest",
-            "flake8",
-            "black"],
+        "dev": ["pytest", "flake8", "black"],
         "docs": [
             "mkdocs==1.3.0",
             "mkdocs-material==8.2.8",
@@ -56,7 +53,7 @@ def read(fname):
             "markdown-include",
             "markdown==3.3.7",
             "pymdown-extensions",
-        ]
+        ],
     },
     author="Logical Clocks AB",
     author_email="robin@logicalclocks.com",