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import pandas as pd |
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import pickle |
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from typing import Dict, List, Any |
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import numpy as np |
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import os |
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class EndpointHandler(): |
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def __init__(self, path=""): |
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pathb = os.path.join(path,"./churn.pkl") |
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self.pipe = pd.read_pickle(pathb) |
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def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: |
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""" |
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Args: |
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data (:obj:): |
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includes the input data and the parameters for the inference. |
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Return: |
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A :obj:`list`:. A string representing what the label/class is |
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""" |
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inputs = data.pop("inputs", data) |
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parameters = data.pop("parameters", None) |
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df = pd.DataFrame(inputs) |
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df["TotalCharges"] = df["TotalCharges"].replace(" ", np.nan, regex=False).astype(float) |
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df = df.drop(columns=["customerID"]) |
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df = df.drop(columns=["Churn"]) |
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pred = self.pipe.predict(df) |
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return {"pred": pred} |
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