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。
快速链接到答案:
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
元组拆包:
>>> (a, (b, c), d) = [(1, 2), (3, 4), (5, 6)]
>>> a
(1, 2)
>>> b
3
>>> c, d
(4, (5, 6))
更模糊的是，你可以在函数参数中做到这一点(在Python 2.x中;Python 3。X将不再允许这样):
>>> def addpoints((x1, y1), (x2, y2)):
... return (x1+x2, y1+y2)
>>> addpoints((5, 0), (3, 5))
(8, 5)
其他回答
描述符
它们是一大堆核心Python特性背后的魔力。
当您使用点访问来查找成员(例如x.y)时，Python首先在实例字典中查找成员。如果没有找到，则在类字典中查找。如果它在类字典中找到它，并且对象实现了描述符协议，而不是仅仅返回它，Python就会执行它。描述符是任何实现__get__、__set__或__delete__方法的类。
下面是如何使用描述符实现自己的(只读)属性版本:
class Property(object):
def __init__(self, fget):
self.fget = fget
def __get__(self, obj, type):
if obj is None:
return self
return self.fget(obj)
你可以像使用内置属性()一样使用它:
class MyClass(object):
@Property
def foo(self):
return "Foo!"
在Python中，描述符用于实现属性、绑定方法、静态方法、类方法和插槽等。理解它们可以很容易地理解为什么以前看起来像Python“怪癖”的很多东西是这样的。
Raymond Hettinger有一个很棒的教程，在描述它们方面比我做得更好。
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!
创建具有相关数据的两个序列的字典
In [15]: t1 = (1, 2, 3)
In [16]: t2 = (4, 5, 6)
In [17]: dict (zip(t1,t2))
Out[17]: {1: 4, 2: 5, 3: 6}
列表中的无限递归
>>> a = [1,2]
>>> a.append(a)
>>> a
[1, 2, [...]]
>>> a[2]
[1, 2, [...]]
>>> a[2][2][2][2][2][2][2][2][2] == a
True
可读正则表达式
在Python中，您可以将正则表达式拆分为多行，命名匹配并插入注释。
示例详细语法(来自Python):
>>> pattern = """
... ^ # beginning of string
... M{0,4} # thousands - 0 to 4 M's
... (CM|CD|D?C{0,3}) # hundreds - 900 (CM), 400 (CD), 0-300 (0 to 3 C's),
... # or 500-800 (D, followed by 0 to 3 C's)
... (XC|XL|L?X{0,3}) # tens - 90 (XC), 40 (XL), 0-30 (0 to 3 X's),
... # or 50-80 (L, followed by 0 to 3 X's)
... (IX|IV|V?I{0,3}) # ones - 9 (IX), 4 (IV), 0-3 (0 to 3 I's),
... # or 5-8 (V, followed by 0 to 3 I's)
... $ # end of string
... """
>>> re.search(pattern, 'M', re.VERBOSE)
命名匹配示例(摘自正则表达式HOWTO)
>>> p = re.compile(r'(?P<word>\b\w+\b)')
>>> m = p.search( '(((( Lots of punctuation )))' )
>>> m.group('word')
'Lots'
由于字符串字面值的串联，你也可以在不使用re.VERBOSE的情况下详细地编写一个正则表达式。
>>> pattern = (
... "^" # beginning of string
... "M{0,4}" # thousands - 0 to 4 M's
... "(CM|CD|D?C{0,3})" # hundreds - 900 (CM), 400 (CD), 0-300 (0 to 3 C's),
... # or 500-800 (D, followed by 0 to 3 C's)
... "(XC|XL|L?X{0,3})" # tens - 90 (XC), 40 (XL), 0-30 (0 to 3 X's),
... # or 50-80 (L, followed by 0 to 3 X's)
... "(IX|IV|V?I{0,3})" # ones - 9 (IX), 4 (IV), 0-3 (0 to 3 I's),
... # or 5-8 (V, followed by 0 to 3 I's)
... "$" # end of string
... )
>>> print pattern
"^M{0,4}(CM|CD|D?C{0,3})(XC|XL|L?X{0,3})(IX|IV|V?I{0,3})$"
