Python编程语言中有哪些鲜为人知但很有用的特性?
尽量将答案限制在Python核心。 每个回答一个特征。 给出一个例子和功能的简短描述，而不仅仅是文档链接。 使用标题作为第一行标记该特性。
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参数解包 牙套 链接比较运算符 修饰符 可变默认参数的陷阱/危险 描述符 字典默认的.get值 所以测试 省略切片语法 枚举 其他/ 函数作为iter()参数 生成器表达式 导入该 就地值交换 步进列表 __missing__物品 多行正则表达式 命名字符串格式化 嵌套的列表/生成器推导 运行时的新类型 .pth文件 ROT13编码 正则表达式调试 发送到发电机 交互式解释器中的制表符补全 三元表达式 试着/ / else除外 拆包+打印()函数 与声明
当前回答
对迭代器的多个引用
你可以使用列表乘法创建对同一个迭代器的多个引用:
>>> i = (1,2,3,4,5,6,7,8,9,10) # or any iterable object
>>> iterators = [iter(i)] * 2
>>> iterators[0].next()
1
>>> iterators[1].next()
2
>>> iterators[0].next()
3
这可以用来将一个可迭代对象分组成块，例如，就像这个来自itertools文档的例子
def grouper(n, iterable, fillvalue=None):
"grouper(3, 'ABCDEFG', 'x') --> ABC DEF Gxx"
args = [iter(iterable)] * n
return izip_longest(fillvalue=fillvalue, *args)
其他回答
Python的禅宗
>>> import this
The Zen of Python, by Tim Peters
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
>>> float('infinity')
inf
>>> float('NaN')
nan
更多信息:
http://docs.python.org/library/functions.html#float http://www.python.org/dev/peps/pep-0754/ Python nan和inf值
只需少量的工作，线程模块就变得非常容易使用。此装饰器更改函数，使其在自己的线程中运行，返回占位符类实例，而不是常规结果。你可以通过检查placeolder来探测答案。结果或通过调用placeholder.awaitResult()来等待它。
def threadify(function):
"""
exceptionally simple threading decorator. Just:
>>> @threadify
... def longOperation(result):
... time.sleep(3)
... return result
>>> A= longOperation("A has finished")
>>> B= longOperation("B has finished")
A doesn't have a result yet:
>>> print A.result
None
until we wait for it:
>>> print A.awaitResult()
A has finished
we could also wait manually - half a second more should be enough for B:
>>> time.sleep(0.5); print B.result
B has finished
"""
class thr (threading.Thread,object):
def __init__(self, *args, **kwargs):
threading.Thread.__init__ ( self )
self.args, self.kwargs = args, kwargs
self.result = None
self.start()
def awaitResult(self):
self.join()
return self.result
def run(self):
self.result=function(*self.args, **self.kwargs)
return thr
Re可以调用函数!
事实上，您可以在每次匹配正则表达式时调用函数，这非常方便。 这里我有一个例子，把每个“Hello”替换为“Hi”，把“there”替换为“Fred”，等等。
import re
def Main(haystack):
# List of from replacements, can be a regex
finds = ('Hello', 'there', 'Bob')
replaces = ('Hi,', 'Fred,', 'how are you?')
def ReplaceFunction(matchobj):
for found, rep in zip(matchobj.groups(), replaces):
if found != None:
return rep
# log error
return matchobj.group(0)
named_groups = [ '(%s)' % find for find in finds ]
ret = re.sub('|'.join(named_groups), ReplaceFunction, haystack)
print ret
if __name__ == '__main__':
str = 'Hello there Bob'
Main(str)
# Prints 'Hi, Fred, how are you?'
Pow()也可以有效地计算(x ** y) % z。
内置pow()函数有一个鲜为人知的第三个参数，它允许你比简单地(x ** y) % z更有效地计算xy对z的模量:
>>> x, y, z = 1234567890, 2345678901, 17
>>> pow(x, y, z) # almost instantaneous
6
相比之下，对于相同的值，(x ** y) % z在我的机器上一分钟内没有给出结果。
