Refactor to PEP8 standards and clarify doc_strings

Author: smlindauer

src/sasctl/pzmm/modelParameters.py

@@ -7,55 +7,70 @@
 # TODO: Convert STRINGIO calls to string or dict format
 
 
-def find_file(model, fileName):
+def _find_file(model, file_name):
     """
-    Retrieves first file from specified model that contains fileName as a substring.
+    Retrieves the first file from a registered model on SAS Model Manager that contains the provided
+    file_name as an exact match or substring.
+
     Parameters
     ----------
-    model : str
-        ID of the model the desired file is located in
-    fileName : str
-        The name of the desired file, or a substring that is contained within the file name
+    model : str or dict
+        The name or id of the model, or a dictionary representation of the model.
+    file_name : str
+        The name of the desired file, or a substring that is contained within the file name.
+
     Returns
     -------
     RestObj
-        The first file with a name containing fileName
-
+        The first file with a name containing file_name.
     """
     from ..core import current_session
 
     sess = current_session()
-    fileList = mr.get_model_contents(model)
-    for file in fileList:
+    file_list = mr.get_model_contents(model)
+    for file in file_list:
         print(file.name)
-        if fileName.lower() in file.name.lower():
-            correctFile = sess.get(
-                "modelRepository/models/{}/contents/{}/content".format(model, file.id)
-            )
-            break
-    return correctFile
+        if file_name.lower() in file.name.lower():
+            correct_file = sess.get(f"modelRepository/models/{model}/contents/{file.id}/content")
+            return correct_file
 
 
 class ModelParameters:
     @classmethod
-    def generate_hyperparameters(cls, model, modelPrefix, pPath):
+    def generate_hyperparameters(cls, model, model_prefix, pickle_path):
         """
-        Generates hyperparameters for a given model
+        Generates hyperparameters for a given model and creates a JSON file representation.
+
+        Currently only supports generation of scikit-learn model hyperparameters.
+
         Parameters
         ----------
-        model : str, list, dict
-            Name, id, or dictionary representation of the model
-        modelPrefix : str
-            Name used to create model files
-            e.g. (modelPrefix) + "Hyperparameters.json")
-        pPath : str, Path
-            Directory location of model files
+        model : Python object
+            Python object representing the model.
+        model_prefix : str
+            Name used to create model files. (e.g. (modelPrefix) + "Hyperparameters.json")
+        pickle_path : str, Path
+            Directory location of model files.
+
+        Yields
+        ------
+        JSON file
+            Named {model_prefix}Hyperparameters.json.
         """
+        def sklearn_params():
+            """
+            Generates hyperparameters for the models generated by scikit-learn.
+            """
+            hyperparameters = model.get_params()
+            model_json = {"hyperparameters": hyperparameters}
+            with open(Path(pickle_path) / f"{model_prefix}Hyperparameters.json", "w") as f:
+                f.write(json.dumps(model_json, indent=4))
+
         if all(hasattr(model, attr) for attr in ["_estimator_type", "get_params"]):
-            cls.sklearn_params(model, modelPrefix, pPath)
+            sklearn_params(model, model_prefix, pickle_path)
         else:
             raise ValueError(
-                "Other model types not currently supported for hyperparameter generation."
+                "This model type is not currently supported for hyperparameter generation."
             )
 
     @classmethod
@@ -68,10 +83,11 @@ def update_kpis(
         """
         Updates hyperparameter file to include KPIs generated by performance definitions, as well
         as any custom KPIs imported by user to the SAS KPI data table.
+
         Parameters
         ----------
-        project : dict, str, list
-            Name, id, or dictionary representation of the project
+        project : str or dict
+            The name or id of the project, or a dictionary representation of the project.
         server : str, optional
             Server on which the KPI data table is stored. Defaults to "cas-shared-default".
         caslib : str, optional
@@ -81,36 +97,38 @@ def update_kpis(
         from io import StringIO
 
         kpis = get_project_kpis(project, server, caslib)
-        modelsToUpdate = kpis["ModelUUID"].unique().tolist()
-        for model in modelsToUpdate:
-            currentParams = find_file(model, "hyperparameters")
-            currentJSON = currentParams.json()
-            modelRows = kpis.loc[kpis["ModelUUID"] == model]
-            modelRows.set_index("TimeLabel", inplace=True)
-            kpiJSON = modelRows.to_json(orient="index")
-            parsedJSON = json.loads(kpiJSON)
-            currentJSON["kpis"] = parsedJSON
-            fileName = "{}Hyperparameters.json".format(
-                currentJSON["kpis"][list(currentJSON["kpis"].keys())[0]]["ModelName"]
+        models_to_update = kpis["ModelUUID"].unique().tolist()
+        for model in models_to_update:
+            current_params = _find_file(model, "hyperparameters")
+            current_json = current_params.json()
+            model_rows = kpis.loc[kpis["ModelUUID"] == model]
+            model_rows.set_index("TimeLabel", inplace=True)
+            kpi_json = model_rows.to_json(orient="index")
+            parsed_json = json.loads(kpi_json)
+            current_json["kpis"] = parsed_json
+            file_name = "{}Hyperparameters.json".format(
+                current_json["kpis"][list(current_json["kpis"].keys())[0]]["ModelName"]
             )
             mr.add_model_content(
                 model,
-                StringIO((json.dumps(currentJSON, indent=4))),
-                fileName,
+                StringIO(json.dumps(current_json, indent=4)),
+                file_name,
             )
 
     @classmethod
     def get_hyperparameters(cls, model):
         """
-        Gets hyperparameter json file from specified model.
+        Retrieves the hyperparameter json file from specified model on SAS Model Manager.
+
         Parameters
         ----------
-        model : str, dict, list
-            Name, id, or dictionary representation of the model
+        model : str or dict
+            The name or id of the model, or a dictionary representation of the model.
+
         Returns
         -------
         dict
-            dictionary containing the contents of the hyperparameter file
+            Dictionary containing the contents of the hyperparameter file.
         """
         if mr.is_uuid(model):
             id_ = model
@@ -119,19 +137,20 @@ def get_hyperparameters(cls, model):
         else:
             model = mr.get_model(model)
             id_ = model["id"]
-        file = find_file(id_, "hyperparameters")
+        file = _find_file(id_, "hyperparameters")
         return file.json()
 
     @classmethod
     def add_hyperparameters(cls, model, **kwargs):
         """
-        Adds custom hyperparameters to the hyperparameter file contained within the model in Model Manager.
+        Adds custom hyperparameters to the hyperparameter file contained within the model in SAS Model Manager.
+
         Parameters
         ----------
-        model : str, dict
-            name, id, or dictionary representation of the model
+        model : str or dict
+            The name or id of the model, or a dictionary representation of the model.
         kwargs
-            named variables representing hyperparameters to be added to the hyperparameter file
+            Named variables pairs representing hyperparameters to be added to the hyperparameter file.
         """
         from io import StringIO
 
@@ -142,23 +161,6 @@ def add_hyperparameters(cls, model, **kwargs):
             hyperparameters["hyperparameters"][key] = value
         mr.add_model_content(
             model,
-            StringIO((json.dumps(hyperparameters, indent=4))),
-            "{}Hyperparameters.json".format(model.name),
+            StringIO(json.dumps(hyperparameters, indent=4)),
+            f"{model.name}Hyperparameters.json"
         )
-
-    def sklearn_params(model, modelPrefix, pPath):
-        """
-        Generates hyperparameters for the models genereated by SciKit Learn.
-        Parameters
-        ----------
-        modelPrefix : str
-            Name used to create model files
-        pPath : str, Path
-            Directory location of model files
-        """
-        hyperparameters = model.get_params()
-        modelJson = {"hyperparameters": hyperparameters}
-        with open(
-            Path(pPath) / ("{}Hyperparameters.json".format(modelPrefix)), "w"
-        ) as f:
-            f.write(json.dumps(modelJson, indent=4))