我希望能够获得用户输入的测试分数并写入外部文本文件。然后让应用程序从中读取值并计算平均值。但是,我不确定如何在循环和函数中实现python语法。我试图利用我的资源来更好地了解如何执行此操作,但是在理解python如何处理外部文件时遇到了一些麻烦。另外,在这种情况下,使用append比编写更好? 当前语法:
def testAvgCalculation():
#Variables
total = 0
total_quiz = 0
while True:
#User Input and Variable to stop loop
inpt = input("Enter score: ")
if inpt.lower()== 'stop':
break
#Data Validation
try:
if int(inpt) in range(1,101):
total += int(inpt)
total_quiz += 1
else:
print("Score too small or Big")
except ValueError:
print("Not a Number")
return total, total_quiz
def displayAverage(total, total_quiz):
average = total / total_quiz
print('The Average score is: ', format(average, '.2f'))
print('You have entered', total_quiz, 'scores')
#Main Function
def main():
total, total_quiz = testAvgCalculation()
displayAverage(total, total_quiz)
#Run Main Function
main()
答案 0 :(得分:0)
这很骇人,但我尝试使用已经存在的东西。我将原始函数的数据验证部分拆分为一个单独的函数。在main()
中,其值counter
返回到calculate_average()
,该值跟踪输入了多少个值,然后counter
逐行读取文件,直到def write_file():
#Variables
counter = 0
file = open("Scores.txt", "w")
while True:
#User Input and Variable to stop loop
inpt = input("Enter score: ")
file.write(inpt + "\n")
if inpt.lower()== 'stop':
file.close()
break
counter += 1
return counter
def calculate_average(counter):
total = 0
total_quiz = counter
scores = open("Scores.txt", "r")
s = ""
try:
while counter > 0 and s != 'stop':
s = int(scores.readline())
if int(s) in range(1,101):
total += int(s)
counter -= 1
else:
print("Invalid data in file.")
except ValueError:
print("Invalid data found")
return total, total_quiz
def displayAverage(total, total_quiz):
average = total / total_quiz
print('The Average score is: ', format(average, '.2f'))
print('You have entered', total_quiz, 'scores')
#Main Function
def main():
total, total_quiz = calculate_average(write_file())
displayAverage(total, total_quiz)
#Run Main Function
main()
变为0,这意味着它将要读取单词“ stop”(允许通过if语句中的“ and”识别EOF),执行计算并返回其值。
models/official/transformer/v2/transformer.py:143 call *
encoder_outputs = self.encode(inputs, attention_bias, training)
models/official/transformer/v2/transformer.py:166 encode
embedded_inputs = self.embedding_softmax_layer(inputs)
TypeError: Cannot convert provided value to EagerTensor. Provided value: 0.0 Requested dtype: int64
注意:该文件最初是在写入模式下创建的,该模式每次都会覆盖该文件,因此您永远不需要一个新文件。如果您想保留一条记录,则可能需要更改它以追加,尽管您需要管理从旧输入中提取正确的行。
一点都不漂亮,但是应该让您了解如何实现自己的目标。