code linted

app.py

@@ -1,11 +1,13 @@
 import streamlit as st
 from fastai.text.all import *
 
+
 @st.cache_resource
 def load_model():
     learn = load_learner('text_classifier_learner.pth')
     return learn
 
+
 learn = load_model()
 
 # Streamlit app

main.py

@@ -28,4 +28,6 @@ def run_pipeline_stage(stage_name, pipeline_class) -> None:
 
 if __name__ == '__main__':
     run_pipeline_stage("DATA INGESTION STAGE", DataIngestionTrainingPipeline)
-    run_pipeline_stage("MODEL TRAINING AND EVALUATION STAGE", ModelTrainingAndEvaluationPipeline)
+    run_pipeline_stage(
+        "MODEL TRAINING AND EVALUATION STAGE",
+        ModelTrainingAndEvaluationPipeline)

src/swahiliNewsClassifier/components/data_ingestion.py

@@ -63,7 +63,8 @@ def extract_zip_file(self):
                 with zipfile.ZipFile(zip_file, "r") as zip_ref:
                     zip_ref.extractall(decompress_path)
 
-                log.info(f"Extracted zip file {zip_file} into: {decompress_path}")
+                log.info(
+                    f"Extracted zip file {zip_file} into: {decompress_path}")
             except Exception as e:
                 log.error(f"Error extracting zip file: {zip_file}")
                 raise e

src/swahiliNewsClassifier/configuration/configuration.py

@@ -6,6 +6,7 @@
 
 load_dotenv()
 
+
 class ConfigurationManager:
     def __init__(self, config_filepath=CONFIG_FILE_PATH,
                  params_filepath=PARAMS_FILE_PATH):
@@ -41,7 +42,8 @@ def get_data_ingestion_config(self) -> DataIngestionConfig:
             decompressed_dir=data_ingestion_config.decompressed_dir
         )
 
-    def get_model_training_and_evaluation_config(self) -> ModelTrainingAndEvaluationConfig:
+    def get_model_training_and_evaluation_config(
+            self) -> ModelTrainingAndEvaluationConfig:
         """
         Get the model training and evaluation configuration.
 

src/swahiliNewsClassifier/entity/entities.py

@@ -32,39 +32,39 @@ class ModelTrainingAndEvaluationConfig:
         test_size (float): Proportion of the dataset to include in the test split. This parameter is used to split the dataset into training and validation sets.
 
         learning_rate_1 (float): Learning rate for training the language model learner. This is used during the fine-tuning of the pre-trained language model.
-        
+
         learning_rate_2 (float): Learning rate for the first phase of classifier training. This is used in the initial phase of training the text classifier.
-        
+
         learning_rate_3 (float): Learning rate for the second phase of classifier training. This is used in the second phase of training the text classifier.
-        
+
         learning_rate_4 (float): Learning rate for the third phase of classifier training. This is used in the third phase of training the text classifier.
-        
+
         learning_rate_5 (float): Learning rate for the fourth phase of classifier training. This is used in the final phase of training the text classifier.
-        
+
         batch_size_1 (int): Batch size for language model training. This parameter defines the number of samples that will be propagated through the network at once during language model training.
-        
+
         batch_size_2 (int): Batch size for text classifier training. This parameter defines the number of samples that will be propagated through the network at once during text classifier training.
-        
+
         epochs_1 (int): Number of epochs for training the language model learner. This defines the number of complete passes through the training dataset.
-        
+
         epochs_2 (int): Number of epochs for the first phase of classifier training. This defines the number of complete passes through the training dataset in the first phase.
-        
+
         epochs_3 (int): Number of epochs for the second phase of classifier training. This defines the number of complete passes through the training dataset in the second phase.
-        
+
         epochs_4 (int): Number of epochs for the third phase of classifier training. This defines the number of complete passes through the training dataset in the third phase.
-        
+
         epochs_5 (int): Number of epochs for the fourth phase of classifier training. This defines the number of complete passes through the training dataset in the final phase.
-        
+
         training_data (Path): Path to the training data CSV file. This file contains the text data and corresponding labels for training and validation.
 
         root_dir (Path): Root directory for storing model artifacts. This directory is used to save trained models, logs, and other artifacts.
-        
+
         mlflow_tracking_uri (str): URI for the MLflow tracking server. This is used to log and track experiments with MLflow.
-        
+
         mlflow_repo_name (str): Repository name for MLflow tracking. This is used to organize and identify different MLflow runs within the repository.
-        
+
         mlflow_repo_owner (str): Owner of the MLflow repository. This is used to identify the owner of the MLflow repository.
-        
+
         all_params (dict): Dictionary containing all parameters used for model training. This includes all hyperparameters and other settings for reproducibility and logging.
     """
     test_size: float

src/swahiliNewsClassifier/pipeline/stage_01_data_ingestion.py

@@ -18,7 +18,8 @@ def main(self):
         """
         try:
             data_ingestion_config = self.config.get_data_ingestion_config()
-            data_ingestion = DataIngestion(data_ingestion_configurations=data_ingestion_config)
+            data_ingestion = DataIngestion(
+                data_ingestion_configurations=data_ingestion_config)
             data_ingestion.download_file()
             data_ingestion.extract_zip_file()
         except Exception as e:

tests/test_data_ingestion.py

@@ -26,7 +26,8 @@ def data_ingestion_configurations():
 
 @pytest.fixture
 def data_ingestion(data_ingestion_configurations):
-    return DataIngestion(data_ingestion_configurations=data_ingestion_configurations)
+    return DataIngestion(
+        data_ingestion_configurations=data_ingestion_configurations)
 
 
 @patch('swahiliNewsClassifier.components.data_ingestion.os.makedirs')