import pandas as pd
from deepchecks.tabular import Dataset
from deepchecks.tabular.suites import data_integrity, train_test_validation

def validate_data(train_df: pd.DataFrame, test_df: pd.DataFrame, output_dir: str = "reports"):
    """
    Runs DeepChecks on training and testing data.
    """
    # Create DeepChecks Datasets
    # Assuming 'target_price' is the label for regression
    train_ds = Dataset(train_df, label='target_price', cat_features=[])
    test_ds = Dataset(test_df, label='target_price', cat_features=[])

    import os
    os.makedirs(output_dir, exist_ok=True)

    # 1. Data Integrity Check
    print("Running Data Integrity Check...")
    integrity_suite = data_integrity()
    integrity_result = integrity_suite.run(train_ds)
    integrity_result.save_as_html(f"{output_dir}/data_integrity.html")
    print(f"Data Integrity report saved to {output_dir}/data_integrity.html")

    # 2. Train-Test Validation (Drift)
    print("Running Train-Test Validation (Drift Check)...")
    validation_suite = train_test_validation()
    validation_result = validation_suite.run(train_ds, test_ds)
    validation_result.save_as_html(f"{output_dir}/train_test_validation.html")
    print(f"Train-Test Validation report saved to {output_dir}/train_test_validation.html")

    return integrity_result, validation_result

if __name__ == "__main__":
    # Example usage
    # df = pd.read_csv("data/processed/AAPL_processed.csv")
    # train_df = df.iloc[:-30]
    # test_df = df.iloc[-30:]
    # validate_data(train_df, test_df)
    pass