added some formatting changes

Author: GoJo-Rika

network_security/components/data_transformation.py

@@ -1,4 +1,3 @@
-import os
 import sys
 
 import numpy as np
@@ -37,13 +36,13 @@ def __init__(
             raise NetworkSecurityException(e, sys)
 
     @staticmethod
-    def read_data(file_path) -> pd.DataFrame:
+    def read_data(file_path: str) -> pd.DataFrame:
         try:
             return pd.read_csv(file_path)
         except Exception as e:
             raise NetworkSecurityException(e, sys)
 
-    def get_data_transformer_object(cls) -> Pipeline:
+    def get_data_transformer_object(self) -> Pipeline:
         """
         It initialises a KNNImputer object with the parameters specified in the training_pipeline.py file
         and returns a Pipeline object with the KNNImputer object as the first step.
@@ -53,14 +52,15 @@ def get_data_transformer_object(cls) -> Pipeline:
 
         Returns:
           A Pipeline object
+
         """
         logging.info(
-            "Entered get_data_trnasformer_object method of Trnasformation class"
+            "Entered get_data_trnasformer_object method of Trnasformation class",
         )
         try:
             imputer: KNNImputer = KNNImputer(**DATA_TRANSFORMATION_IMPUTER_PARAMS)
             logging.info(
-                f"Initialise KNNImputer with {DATA_TRANSFORMATION_IMPUTER_PARAMS}"
+                f"Initialise KNNImputer with {DATA_TRANSFORMATION_IMPUTER_PARAMS}",
             )
             processor: Pipeline = Pipeline([("imputer", imputer)])
             return processor
@@ -69,15 +69,15 @@ def get_data_transformer_object(cls) -> Pipeline:
 
     def initiate_data_transformation(self) -> DataTransformationArtifact:
         logging.info(
-            "Entered initiate_data_transformation method of DataTransformation class"
+            "Entered initiate_data_transformation method of DataTransformation class",
         )
         try:
             logging.info("Starting data transformation")
             train_df = DataTransformation.read_data(
-                self.data_validation_artifact.valid_train_file_path
+                self.data_validation_artifact.valid_train_file_path,
             )
             test_df = DataTransformation.read_data(
-                self.data_validation_artifact.valid_test_file_path
+                self.data_validation_artifact.valid_test_file_path,
             )
 
             ## training dataframe
@@ -94,17 +94,19 @@ def initiate_data_transformation(self) -> DataTransformationArtifact:
 
             preprocessor_object = preprocessor.fit(input_feature_train_df)
             transformed_input_train_feature = preprocessor_object.transform(
-                input_feature_train_df
+                input_feature_train_df,
             )
             transformed_input_test_feature = preprocessor_object.transform(
-                input_feature_test_df
+                input_feature_test_df,
             )
 
             train_arr = np.c_[
-                transformed_input_train_feature, np.array(target_feature_train_df)
+                transformed_input_train_feature,
+                np.array(target_feature_train_df),
             ]
             test_arr = np.c_[
-                transformed_input_test_feature, np.array(target_feature_test_df)
+                transformed_input_test_feature,
+                np.array(target_feature_test_df),
             ]
 
             # save numpy array data

network_security/constant/training_pipeline/__init__.py

@@ -1,9 +1,6 @@
-import os
-import sys
 from pathlib import Path
 
 import numpy as np
-import pandas as pd
 
 """
 defining common constant variable for training pipeline