Python

1.4解释器(运行文件)

1.5注释:#单行,ctrl+/

多行注释       ”””

”””

2.1变量

assert,except;lambda; nonlocal;

2.2数据类型(type()函数可返回数据类型)

数值(int,float)

布尔(Ture,False)

字符串(str)

列表(list)

元组(tuple)

集合(set)

字(dict)

输入输出

# ---格式化输出--- #%s:

字符串   %d:(%u:无符号)

有符号的十进制整数   %f

浮点数%00d:不足以零补全,

print("%02d%f" % (age, c))   按顺序

# f ‘{表达式}’   print( f '今年是{age}' )

print("输出内容", end="\n"# python 中默认为"\n"
print('he', end='\t')

input("提示信息”),接受input有变量,接受的数据类型是字符串


数据类型转换


Int()  Float()  Str(),tuple()

应用:a = int(input('a = '))

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" 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