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
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!
其他回答
threading.enumerate()提供了对系统中所有Thread对象的访问，sys._current_frames()返回系统中所有线程的当前堆栈帧，因此将这两者结合起来，你会得到Java风格的堆栈转储:
def dumpstacks(signal, frame):
id2name = dict([(th.ident, th.name) for th in threading.enumerate()])
code = []
for threadId, stack in sys._current_frames().items():
code.append("\n# Thread: %s(%d)" % (id2name[threadId], threadId))
for filename, lineno, name, line in traceback.extract_stack(stack):
code.append('File: "%s", line %d, in %s' % (filename, lineno, name))
if line:
code.append(" %s" % (line.strip()))
print "\n".join(code)
import signal
signal.signal(signal.SIGQUIT, dumpstacks)
在多线程python程序开始时执行此操作，您可以通过发送SIGQUIT随时访问线程的当前状态。你也可以选择信号。SIGUSR1或signal。sigusr2。
See
如果你不喜欢使用空格来表示作用域，你可以通过发出以下命令来使用c风格{}:
from __future__ import braces
切片运算符中的step参数。例如:
a = [1,2,3,4,5]
>>> a[::2] # iterate over the whole list in 2-increments
[1,3,5]
特殊情况x[::-1]是“x反转”的有用习语。
>>> a[::-1]
[5,4,3,2,1]
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)
使用关键字参数作为赋值
有时需要根据一个或多个参数构建一系列函数。然而，这很容易导致闭包都引用相同的对象和值:
funcs = []
for k in range(10):
funcs.append( lambda: k)
>>> funcs[0]()
9
>>> funcs[7]()
9
可以通过将lambda表达式转换为仅依赖其参数的函数来避免这种行为。关键字参数存储绑定到它的当前值。函数调用不需要改变:
funcs = []
for k in range(10):
funcs.append( lambda k = k: k)
>>> funcs[0]()
0
>>> funcs[7]()
7
