import sys
from typing import Union
# Define types for mean function, trying to analyze input possibilities
Number = Union[int, float] # Number can be either int or float type
Numbers = list[Number] # Numbers is a list of Number types
Scores = Union[Number, Numbers] # Scores can be single or multiple
def mean(scores: Scores, method: int = 1) -> float:
"""
Calculate the mean of a list of scores.
Average and Average2 are hidden functions performing mean algorithm
If a single score is provided in scores, it is returned as the mean.
If a list of scores is provided, the average is calculated and returned.
"""
def average(scores):
"""Calculate the average of a list of scores using a Python for loop with rounding."""
sum = 0
len = 0
for score in scores:
if isinstance(score, Number):
sum += score
len += 1
else:
print("Bad data: " + str(score) + " in " + str(scores))
sys.exit()
return sum / len
def average2(scores):
"""Calculate the average of a list of scores using the built-in sum() function with rounding."""
return sum(scores) / len(scores)
# test to see if scores is a list of numbers
if isinstance(scores, list):
if method == 1:
# long method
result = average(scores)
else:
# built in method
result = average2(scores)
return round(result + 0.005, 2)
return scores # case where scores is a single valu
# try with one number
singleScore = 100
print("Print test data: " + str(singleScore)) # concat data for single line
print("Mean of single number: " + str(mean(singleScore)))
print()
# define a list of numbers
testScores = [90.5, 100, 85.4, 88]
print("Print test data: " + str(testScores))
print("Average score, loop method: " + str(mean(testScores)))
print("Average score, function method: " + str(mean(testScores, 2)))
print()
badData = [100, "NaN", 90]
print("Print test data: " + str(badData))
print("Mean with bad data: " + str(mean(badData)))
Print test data: 100 Mean of single number: 100
Print test data: [90.5, 100, 85.4, 88] Average score, loop method: 90.98 Average score, function method: 90.98
Print test data: [100, ‘NaN’, 90] Bad data: NaN in [100, ‘NaN’, 90]