自python2.6开始,新增了一种格式化字符串的函数str.format(),可谓威力十足。那么,他跟之前的%型格式化字符串相比,有什么优越的存在呢?让我们来揭开它羞答答的面纱。
语法
它通过{}和:来代替%。
“映射”示例
通过位置
In [1]: '{0},{1}'.format('kzc',18) Out[1]: 'kzc,18' In [2]: '{},{}'.format('kzc',18) Out[2]: 'kzc,18' In [3]: '{1},{0},{1}'.format('kzc',18) Out[3]: '18,kzc,18'
字符串的format函数可以接受不限个参数,位置可以不按顺序,可以不用或者用多次,不过2.6不能为空{},2.7才可以。
通过关键字参数
In [5]: '{name},{age}'.format(age=18,name='kzc') Out[5]: 'kzc,18'
通过对象属性
class Person: def __init__(self,name,age): self.name,self.age = name,age def __str__(self): return 'This guy is {self.name},is {self.age} old'.format(self=self)
In [2]: str(Person('kzc',18)) Out[2]: 'This guy is kzc,is 18 old'
通过下标
In [7]: p=['kzc',18] In [8]: '{0[0]},{0[1]}'.format(p) Out[8]: 'kzc,18'
有了这些便捷的“映射”方式,我们就有了偷懒利器。基本的python知识告诉我们,list和tuple可以通过“打散”成普通参数给函数,而dict可以打散成关键字参数给函数(通过和*)。所以可以轻松的传个list/tuple/dict给format函数。非常灵活。
格式限定符
它有着丰富的的“格式限定符”(语法是{}中带:号),比如:
填充与对齐
填充常跟对齐一起使用
^、分别是居中、左对齐、右对齐,后面带宽度
:号后面带填充的字符,只能是一个字符,不指定的话默认是用空格填充
比如
In [15]: '{:>8}'.format('189') Out[15]: ' 189' In [16]: '{:0>8}'.format('189') Out[16]: '00000189' In [17]: '{:a>8}'.format('189') Out[17]: 'aaaaa189'
精度与类型f
精度常跟类型f一起使用
In [44]: '{:.2f}'.format(321.33345) Out[44]: '321.33'
其中.2表示长度为2的精度,f表示float类型。
其他类型
主要就是进制了,b、d、o、x分别是二进制、十进制、八进制、十六进制。
In [54]: '{:b}'.format(17) Out[54]: '10001' In [55]: '{:d}'.format(17) Out[55]: '17' In [56]: '{:o}'.format(17) Out[56]: '21' In [57]: '{:x}'.format(17) Out[57]: '11'
用,号还能用来做金额的千位分隔符。
In [47]: '{:,}'.format(1234567890) Out[47]: '1,234,567,890'

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Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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