import pytest
import pandas as pd
from src.data import data_preprocessing

def test_preprocess_data():
    # create a mock data
    raw_data = pd.DataFrame({
        'Open': [1.0, 2.0, 3.0, 4.0, 5.0],
        'High': [1.1, 2.1, 3.1, 4.1, 5.1],
        'Low': [0.9, 1.9, 2.9, 3.9, 4.9],
        'Close': [1.0, 2.0, 3.0, 4.0, 5.0],
        'Volume': [1000, 2000, 3000, 4000, 5000]
    })

    # perform preprocessing
    processed_data = data_preprocessing.preprocess_data(raw_data)

    # check that the data has the expected columns
    expected_columns = ['Open', 'High', 'Low', 'Close', 'Volume']
    assert all(column in processed_data.columns for column in expected_columns)

    # check the shape of the data
    assert processed_data.shape == raw_data.shape

    # check that values are normalized (within a certain range, e.g. -1.0 to 1.0)
    assert all(-1.0 <= value <= 1.0 for value in processed_data.values.flatten())