import time
import statistics
import numpy as np

def mean_normal(list_data):
    """
        Calculate mean of python list normaly
        input: list of int or float
        output: mean value
    """    
    start = time.time()
    avg = sum(list_data)/len(list_data)
    end = time.time()
    print("avg: {} & Time taken by mean_normal: {:.5f} sec".format(avg, end-start))
    return avg

def mean_statistics(list_data):
    """
        Calculate mean of python list using statistics lib
        input: list of int or float
        output: mean value
    """    
    start = time.time()
    avg = statistics.mean(list_data)
    end = time.time()
    print("avg: {} & Time taken by mean_statistics: {:.5f} sec".format(avg, end-start))
    return avg

def mean_numpy_with_list(list_data):
    """
        Calculate mean of python list using numpy lib
        input: list of int or float
        output: mean value
    """    
    start = time.time()
    avg = np.mean(list_data)
    end = time.time()
    print("avg: {} & Time taken by mean_numpy_with_list: {:.5f} sec".format(avg, end-start))
    return avg

def mean_numpy_with_array(array_data):
    """
        Calculate mean of numpy array using numpy lib
        input: 1-d numpy array
        output: mean value
    """    
    start = time.time()
    avg = np.mean(array_data)
    end = time.time()
    print("avg: {} & Time taken by mean_numpy_with_array: {:.5f} sec".format(avg, end-start))
    return avg
  
  
if __name__ == '__main__':
    # Test with int range
    data = list(range(3000000))
    mean_normal(data)
    mean_statistics(data)
    mean_numpy_with_list(data)
    mean_numpy_with_array(np.array(data))
    
    # Test with float range
    data = list(np.linspace(500,1000,3000000))
    mean_normal(data)
    mean_statistics(data)
    mean_numpy_with_list(data)
    mean_numpy_with_array(np.array(data))