代码报错求助
本帖最后由 蔬菜好吃 于 2021-6-16 16:36 编辑<div class="blockcode"><blockquote># 输入模块
def input_interest():
# 初始化数组
i = 1
abnormal = 0
name1 = []
name2 = []
client = []
Fscreen = []
logo = []
qualification = []
intercommunication = []
loading = []
payment = []
time1 = []
while i==1:
#输入游戏的名称
abnormal = input("请输入游戏全名：")
name1.append(abnormal)
abnormal = input("请输入游戏显示名称：")
name2.append(abnormal)
# 输入测试包体的客户端
while i==1:
abnormal = input("请输入客户端类别：")
if abnormal == "ios" or abnormal == "安卓" or abnormal == "H5" or abnormal == "iOs":
client.append(abnormal)
break
elif i == 1:
print("请输入正确参数！")
# 判断闪屏有无问题有问题
while i==1:
abnormal = input("闪屏有无问题有问题？")
if abnormal=="有"or abnormal=="无" :
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
Fscreen.append("异常（"+abnormal+")")
elif i == 1:
Fscreen.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断logo有无问题有问题
while i == 1:
abnormal = input("logo有无问题有问题？")
if abnormal == "有" or abnormal == "无":
if abnormal== "有":
abnormal = input("异常现象表现有什么？")
logo.append("异常（" + abnormal + ")")
elif i == 1:
logo.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断资质有无问题有问题
while i == 1:
abnormal = input("资质有无问题有问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
qualification.append("异常（" + abnormal + ")")
elif i == 1:
qualification.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断登录初始化有无问题有问题
while i == 1:
abnormal = input("登录初始化有无问题有问题？")
if abnormal== "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
loading.append("异常（" + abnormal + ")")
elif i == 1:
loading.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断双端互通有无问题有问题
while i == 1:
abnormal = input("双端互通有无问题有问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
intercommunication.append("异常（" + abnormal + ")")
elif i==1:
intercommunication.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断充值档位有无问题有问题
while i == 1:
gear=[]
abnormal = input("充值档位有无问题有问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
gear.append("异常（" + abnormal + ")")
elif i==1:
gear.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断支付有无问题有问题
while i == 1:
abnormal = input("支付有无问题有问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
payment.append("异常（" + abnormal + ")")
elif i == 1:
payment.append(abnormal)
break
else:
print("请输入有或者无！")
# # 记录登记时间
import time
t=time.localtime()
abnormal=time.strftime(" %Y-%m-%d %H:%M:%S", t)
time1.append(abnormal)
result=[]
Break=input("如要结束请输入是")
if Break == "是":
break
length=len(time1)
print(length)
for b in range(length):
result.append(, name2, client, Fscreen, logo, qualification, loading, intercommunication,gear, payment, time1])#这里报错
return result
#建表模块
def save_to_excel(result):
import openpyxl
wb = openpyxl.Workbook()
ws = wb.active
ws['A1'] = "游戏名称"
ws['B1'] = "icon名称"
ws['C1'] = "客户端"
ws['D1'] = "闪屏"
ws['E1'] = "logo"
ws['F1'] = "资质"
ws['G1'] = "登录初始化"
ws['H1'] = "双端互通"
ws['I1'] = "充值档位"
ws['J1'] = "支付"
ws['K1'] = "时间"
for each in result:
ws.append(each)
wb.save("测试记录.xlsx")
def main():
# result=["1","2","3","4"]
result=[]
result.extend(input_interest())
print(result)
# with open("test.txt", "w", encoding="utf-8") as f:
# for each in result:
# f.write(each)
save_to_excel(result)
if __name__ == "__main__":
main()
static/image/hrline/line7.png
求助这里报列表超出索引：data:image/jpeg;base64,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{:10_257:}看不到图片，不过测试了好像没有什么问题啊，生成了xlsx文件，文件中也有输出得内容 ...
length=len(time1)
print(length)
for b in range(length):
result.append(, name2, client, Fscreen, logo, qualification, loading, intercommunication,gear, payment, time1])
# 这里这么多个不同的列表，它们的长度都一样？—— 不一样，那你都用 b 来取值，那自然会可能超过最大索引。 fish_nian 发表于 2021-6-16 17:02
看不到图片，不过测试了好像没有什么问题啊，生成了xlsx文件，文件中也有输出得内容
输入多组数据会报超出最大索引 阿奇_o 发表于 2021-6-16 17:10
...
length=len(time1)
print(length)
查了下长度，有段长度不对{:10_266:} # 输入模块
def input_interest():
# 初始化数组
i = 1
abnormal = 0
name1 = []
name2 = []
client = []
Fscreen = []
logo = []
qualification = []
intercommunication = []
loading = []
gear = []
payment = []
time1 = []
while i==1:
#输入游戏的名称
abnormal = input("请输入游戏全名：")
name1.append(abnormal)
abnormal = input("请输入游戏显示名称：")
name2.append(abnormal)
# 输入测试包体的客户端
while i==1:
abnormal = input("请输入客户端类别：")
if abnormal == "ios" or abnormal == "安卓" or abnormal == "H5" or abnormal == "iOs":
client.append(abnormal)
break
else:
print("请输入正确参数！")
# 判断闪屏有无问题
while i==1:
abnormal = input("闪屏有无问题？")
if abnormal=="有"or abnormal=="无" :
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
Fscreen.append("异常（"+abnormal+")")
else:
Fscreen.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断logo有无问题
while i == 1:
abnormal = input("logo有无问题？")
if abnormal == "有" or abnormal == "无":
if abnormal== "有":
abnormal = input("异常现象表现有什么？")
logo.append("异常（" + abnormal + ")")
else:
logo.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断资质有无问题
while i == 1:
abnormal = input("资质有无问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
qualification.append("异常（" + abnormal + ")")
else:
qualification.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断登录初始化有无问题
while i == 1:
abnormal = input("登录初始化有无问题？")
if abnormal== "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
loading.append("异常（" + abnormal + ")")
else:
loading.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断双端互通有无问题
while i == 1:
abnormal = input("双端互通有无问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
intercommunication.append("异常（" + abnormal + ")")
else:
intercommunication.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断充值档位有无问题
while i == 1:
abnormal = input("充值档位有无问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
gear.append("异常（" + abnormal + ")")
else:
gear.append(abnormal)
break
else:
print("请输入有或者无！")
# 判断支付有无问题
while i == 1:
abnormal = input("支付有无问题？")
if abnormal == "有" or abnormal == "无":
if abnormal == "有":
abnormal = input("异常现象表现有什么？")
payment.append("异常（" + abnormal + ")")
else:
payment.append(abnormal)
break
else:
print("请输入有或者无！")
# # 记录登记时间
import time
t=time.localtime()
abnormal=time.strftime(" %Y-%m-%d %H:%M:%S", t)
time1.append(abnormal)
result=[]
Break=input("如要结束请输入是")
if Break == "是":
break
length=len(time1)
# print(len(name1),len(name2),len(client),len(Fscreen),len(logo),len(qualification),len(loading),len(intercommunication),len(gear),len(payment),len(time1),)
for b in range(length):
x=, name2, client, Fscreen, logo, qualification, loading, intercommunication,gear, payment, time1]
result.append(x)
# result.append(, name2, client, Fscreen, logo, qualification, loading, intercommunication,gear, payment, time1])#这里报错
return result
#建表模块
def save_to_excel(result):
import openpyxl
wb = openpyxl.Workbook()
ws = wb.active
ws['A1'] = "游戏名称"
ws['B1'] = "icon名称"
ws['C1'] = "客户端"
ws['D1'] = "闪屏"
ws['E1'] = "logo"
ws['F1'] = "资质"
ws['G1'] = "登录初始化"
ws['H1'] = "双端互通"
ws['I1'] = "充值档位"
ws['J1'] = "支付"
ws['K1'] = "时间"
for each in result:
ws.append(each)
wb.save("测试记录.xlsx")
def main():
# result=["1","2","3","4"]
result=[]
result.extend(input_interest())
print(result)
# with open("test.txt", "w", encoding="utf-8") as f:
# for each in result:
# f.write(each)
save_to_excel(result)
if __name__ == "__main__":
main()
修好了开心{:5_109:}
蔬菜好吃 发表于 2021-6-16 17:37
修好了开心
这种长代码就得自己慢慢调试 蔬菜好吃 发表于 2021-6-16 17:37
修好了开心
这都是靠多次的经验{:10_275:} 好厉害
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