Update app.py

app.py

@@ -6,25 +6,54 @@ from kaggle.api.kaggle_api_extended import KaggleApi
 
 # Kaggle authentication
 api = KaggleApi()
-api.authenticate()
+try:
+    api.authenticate()
+    print("Kaggle authentication successful.")
+except Exception as e:
+    print(f"Kaggle authentication failed: {e}")
+    exit(1)
 
-# Download dataset from Kaggle (example dataset)
-os.system("kaggle datasets download -d <dataset-path>")  # Replace <dataset-path>
+# Download dataset from Kaggle (replace with your dataset path)
+kaggle_dataset_path = "<dataset-path>"  # Replace with actual dataset path
+try:
+    os.system(f"kaggle datasets download -d {kaggle_dataset_path}")
+    print(f"Dataset {kaggle_dataset_path} downloaded successfully.")
+except Exception as e:
+    print(f"Failed to download Kaggle dataset: {e}")
+    exit(1)
 
-# Extract the dataset (if needed)
-os.system("unzip ./<dataset-name>.zip -d ./data/")  # Replace <dataset-name> with actual dataset name
+# Extract the dataset (replace with actual dataset name)
+dataset_name = "<dataset-name>"  # Replace with actual dataset name
+try:
+    os.system(f"unzip ./{dataset_name}.zip -d ./data/")
+    print(f"Dataset {dataset_name} extracted successfully.")
+except Exception as e:
+    print(f"Failed to extract dataset: {e}")
+    exit(1)
 
-# Load the Hugging Face dataset
-hf_dataset = load_dataset('dataset_name')  # Replace 'dataset_name' with the name of the dataset
-hf_df = pd.DataFrame(hf_dataset['train'])  # Convert to pandas DataFrame
+# Load Hugging Face dataset
+hf_dataset_name = 'dataset_name'  # Replace with actual Hugging Face dataset name
+try:
+    hf_dataset = load_dataset(hf_dataset_name)
+    hf_df = pd.DataFrame(hf_dataset['train'])
+    print(f"Hugging Face dataset {hf_dataset_name} loaded successfully.")
+except Exception as e:
+    print(f"Failed to load Hugging Face dataset: {e}")
+    exit(1)
 
-# Load Kaggle dataset
-kaggle_df = pd.read_csv('./data/kaggle_dataset.csv')  # Replace with the appropriate path
+# Load Kaggle dataset (replace with actual path)
+kaggle_df_path = './data/kaggle_dataset.csv'  # Replace with the actual path to Kaggle dataset
+try:
+    kaggle_df = pd.read_csv(kaggle_df_path)
+    print(f"Kaggle dataset loaded from {kaggle_df_path}.")
+except Exception as e:
+    print(f"Failed to load Kaggle dataset: {e}")
+    exit(1)
 
 # Merge datasets
 merged_df = pd.concat([hf_df, kaggle_df], ignore_index=True)
 
-# Example function to display merged data (this can be modified based on your needs)
+# Function to display merged data
 def display_data():
     return merged_df.head()