浅谈Python中数据解析

本文给大家介绍的是Python中的数据解析的集中方式,包括列表解析、字典解析、集合解析,并附上相关示例,有需要的小伙伴可以参考下。

Import os; -- Python自带
print(os.getcwd()) -- 获得当前工作目录
os.chdir('/Users/longlong/Documents') -- 转换到/Users/longlong/Documents目录
os.path.join(parm1, parm2,...) -- 从一个或多个路径片段中构造一个路径名。
os.path.expanduser() -- 用来将包含~符号的路径扩展为完整的路径

复制代码 代码如下:

>>> pathname = '/Users/pilgrim/diveintopython3/examples/humansize.py'
>>> os.path.split(pathname)  --('/Users/pilgrim/diveintopython3/examples', 'humansize.py')罗列目录内容构造绝对路径

复制代码 代码如下:

>>> import os
>>> print(os.getcwd())
/Users/longlong/Documents
>>> os.chdir("./python/")
>>> os.getcwd()
'/Users/longlong/Documents/python'
>>> print(os.path.realpath('whileloop.py')
      )
/Users/longlong/Documents/python/whileloop.py
>>> print(os.path.realpath("whileloop.py"))
/Users/longlong/Documents/python/whileloop.py
>>>

列表解析

复制代码 代码如下:

>>> [os.path.realpath(f) for f in glob.glob("*.py")]
['/Users/longlong/Documents/python/indices_over_two_objects.py', '/Users/longlong/Documents/python/loops_over_indices.py', '/Users/longlong/Documents/python/while_loops.py']

>>> [f for f in glob.glob("*.py") if os.stat(f).st_size > 700]
['indices_over_two_objects.py', 'while_loops.py']
1
 
 

字典解析

 >>> metadat_dict = { f:os.stat(f) for f in glob.glob('*.py')} >>> type(metadat_dict)  >>> list(metadat_dict.keys()) ['indices_over_two_objects.py', 'while_loops.py', 'loops_over_indices.py'] >>> metadat_dict['indices_over_two_objects.py'].st_size 871 
 >>> list(metadat_dict.keys()) ['indices_over_two_objects.py', 'while_loops.py', 'loops_over_indices.py'] >>> a_dict = {'a':1, 'b':2,'c':3} >>> {value:key for key,value in a_dict.items()} {1: 'a', 2: 'b', 3: 'c'} 

集合解析

 >>> a_set = set(range(10)) >>> a_set {0, 1, 2, 3, 4, 5, 6, 7, 8, 9} >>> {x**2 for x in a_set} {0, 1, 64, 4, 36, 9, 16, 49, 81, 25} >>> {x for x in a_set if x%2 == 0 } {0, 8, 2, 4, 6} >>> {2**x for x in range(10)} {32, 1, 2, 64, 4, 128, 256, 512, 8, 16} 

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