一波神奇的Python语句、函数与方法的使用技巧总结
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显示有限的接口到外部 #!/usr/bin/env python # -*- coding: utf-8 -*- from base import APIBase from client import Client from decorator import interface,export,stream from server import Server from storage import Storage from util import (LogFormatter,disable_logging_to_stderr,enable_logging_to_kids,info) __all__ = ['APIBase','Client','LogFormatter','Server','Storage','disable_logging_to_stderr','enable_logging_to_kids','export','info','interface','stream'] with的魔力 其中上下文表达式是跟在with之后的表达式， 该表达式返回一个上下文管理对象。
# 常见with使用场景
with open("test.txt","r") as my_file: # 注意,是__enter__()方法的返回值赋值给了my_file,for line in my_file:
print line
知道具体原理，我们可以自定义支持上下文管理协议的类，类中实现__enter__和__exit__方法。
#!/usr/bin/env python
# -*- coding: utf-8 -*-
class MyWith(object):
def __init__(self):
print "__init__ method"
def __enter__(self):
print "__enter__ method"
return self # 返回对象给as后的变量
def __exit__(self,exc_type,exc_value,exc_traceback):
print "__exit__ method"
if exc_traceback is None:
print "Exited without Exception"
return True
else:
print "Exited with Exception"
return False
def test_with():
with MyWith() as my_with:
print "running my_with"
print "------分割线-----"
with MyWith() as my_with:
print "running before Exception"
raise Exception
print "running after Exception"
if __name__ == '__main__':
test_with()
执行结果如下： __init__ method __enter__ method running my_with __exit__ method Exited without Exception ------分割线----- __init__ method __enter__ method running before Exception __exit__ method Exited with Exception Traceback (most recent call last): File "bin/python",line 34,in <module> exec(compile(__file__f.read(),__file__,"exec")) File "test_with.py",line 33,in <module> test_with() File "test_with.py",line 28,in test_with raise Exception Exception 证明了会先执行__enter__方法,然后调用with内的逻辑,最后执行__exit__做退出处理,并且,即使出现异常也能正常退出 filter的用法 #!/usr/bin/env python # -*- coding: utf-8 -*- lst = [1,2,3,4,5,6] # 所有奇数都会返回True,偶数会返回False被过滤掉 print filter(lambda x: x % 2 != 0,lst) #输出结果 [1,5] 一行作判断 lst = [1,3] new_lst = lst[0] if lst is not None else None print new_lst # 打印结果 1 装饰器之单例
# 单例装饰器
def singleton(cls):
instances = dict() # 初始为空
def _singleton(*args,**kwargs):
if cls not in instances: #如果不存在,则创建并放入字典
instances[cls] = cls(*args,**kwargs)
return instances[cls]
return _singleton
@singleton
class Test(object):
pass
if __name__ == '__main__':
t1 = Test()
t2 = Test()
# 两者具有相同的地址
print t1,t2
staticmethod装饰器 普通成员函数,其中第一个隐式参数为对象
#!/usr/bin/env python
# -*- coding: utf-8 -*-
class A(object):
# 普通成员函数
def foo(self,x):
print "executing foo(%s,%s)" % (self,x)
@classmethod # 使用classmethod进行装饰
def class_foo(cls,x):
print "executing class_foo(%s,%s)" % (cls,x)
@staticmethod # 使用staticmethod进行装饰
def static_foo(x):
print "executing static_foo(%s)" % x
def test_three_method():
obj = A()
# 直接调用噗通的成员方法
obj.foo("para") # 此处obj对象作为成员函数的隐式参数,就是self
obj.class_foo("para") # 此处类作为隐式参数被传入,就是cls
A.class_foo("para") #更直接的类方法调用
obj.static_foo("para") # 静态方法并没有任何隐式参数,但是要通过对象或者类进行调用
A.static_foo("para")
if __name__ == '__main__':
test_three_method()
# 函数输出
executing foo(<__main__.A object at 0x100ba4e10>,para)
executing class_foo(<class '__main__.A'>,para)
executing static_foo(para)
executing static_foo(para)
property装饰器 #python内建函数 property(fget=None,fset=None,fdel=None,doc=None) fget是获取属性的值的函数，fset是设置属性值的函数，fdel是删除属性的函数，doc是一个字符串(像注释一样)。从实现来看，这些参数都是可选的。 property有三个方法getter()， setter()和delete() 来指定fget， fset和fdel。 这表示以下这行：
class Student(object):
@property #相当于property.getter(score) 或者property(score)
def score(self):
return self._score
@score.setter #相当于score = property.setter(score)
def score(self,value):
if not isinstance(value,int):
raise ValueError('score must be an integer!')
if value < 0 or value > 100:
raise ValueError('score must between 0 ~ 100!')
self._score = value
iter魔法
#!/usr/bin/env python
# -*- coding: utf-8 -*-
class TestIter(object):
def __init__(self):
self.lst = [1,5]
def read(self):
for ele in xrange(len(self.lst)):
yield ele
def __iter__(self):
return self.read()
def __str__(self):
return ','.join(map(str,self.lst))
__repr__ = __str__
def test_iter():
obj = TestIter()
for num in obj:
print num
print obj
if __name__ == '__main__':
test_iter()
神奇partial 在stackoverflow给出了类似与partial的运行方式：
def partial(func,*part_args):
def wrapper(*extra_args):
args = list(part_args)
args.extend(extra_args)
return func(*args)
return wrapper
利用用闭包的特性绑定预先绑定一些函数参数，返回一个可调用的变量， 直到真正的调用执行： #!/usr/bin/env python # -*- coding: utf-8 -*- from functools import partial def sum(a,b): return a + b def test_partial(): fun = partial(sum,2) # 事先绑定一个参数,fun成为一个只需要一个参数的可调用变量 print fun(3) # 实现执行的即是sum(2,3) if __name__ == '__main__': test_partial() # 执行结果 5 神秘eval 看一下下面这个例子：
#!/usr/bin/env python
# -*- coding: utf-8 -*-
def test_first():
return 3
def test_second(num):
return num
action = { # 可以看做是一个sandbox
"para": 5,"test_first" : test_first,"test_second": test_second
}
def test_eavl():
condition = "para == 5 and test_second(test_first) > 5"
res = eval(condition,action) # 解释condition并根据action对应的动作执行
print res
if __name__ == '_
exec
#!/usr/bin/env python
# -*- coding: utf-8 -*-
def test_first():
print "hello"
def test_second():
test_first()
print "second"
def test_third():
print "third"
action = {
"test_second": test_second,"test_third": test_third
}
def test_exec():
exec "test_second" in action
if __name__ == '__main__':
test_exec() # 无法看到执行结果
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