handler

handler.py

@@ -0,0 +1,27 @@
+from typing import Dict, List, Union
+import os
+import joblib
+import numpy as np
+
+features = ["fixed_acidity", "volatile_acidity", "citric_acid", "residual_sugar", "chlorides", "free_sulfur_dioxide", "total_sulfur_dioxide", "density", "pH", "sulphates", "alcohol"]
+
+class EndpointHandler():
+    def __init__(self, path=""):
+        self.model = joblib.load("sklearn_model.joblib")
+
+    def __call__(
+        self, inputs: Dict[str, Dict[str, List[Union[str, float]]]]
+    ) -> List[Union[str, float]]:
+        """
+        Args:
+            inputs (:obj:`dict`):
+                a dictionary containing a key 'data' mapping to a dict in which
+                the values represent each column.
+        Return:
+            A :obj:`list` of floats or strings: The classification output for each row.
+        """
+        data = inputs["data"]
+        X = np.array([data[i] for i in features])
+        X = np.transpose(X, (1, 0))
+        return self.model.predict(X)
+