标签(空格分隔)： 参数 作用域 (个人总结学习)

懒惰即美德

抽象

函数调用

抽象和结构

创建函数

hasattr(func,__call__):判断函数是否可调用

斐波那契数列

def fibs(num):

result = [0, 1]

for i in range(num -2):

result.append(result[-2] + result[-1])

return result

记录函数

字符串文档

>>>square.__doc__

并非真正函数的函数

无返回值的函数返回None

参数

形参和实参

参数可以改变吗？

函数内参数重新绑定，不会影响函数外部的变量，因为参数存储在局部作用域

传入列表

change(name[:])

change(names)

查询联系人

def lookup(data, label, name):

return data[label].get(name)

def store(data, full_name):

names = full_name.split()

if len(names) == 2: names.insert(1,'')

lables = 'first', 'middle', 'last'

for label, name in zip(labels, names)

people = lookup(data, label, name)

if people:

people.append(full_name)

else:

data[label][name] = [full_name]

###关键字参数和默认值

###收集参数

- *params

```python

def print_param(title,*params):

print(title)

print(params)

**keys

def print_params(title,*params, **keys):

print(title)

print(params)

print(keys)

print_params("hello",2,3,4, foo1='23',foo2='34'):

- 实现多个名字存储

```python

def store(data, *full_names):

for full_name in full_names:

names = full_name.split()

if len(names) == 2: names.insert(1,'')

lables = 'first', 'middle', 'last'

for label, name in zip(labels, names)

people = lookup(data, label, name)

if people:

people.append(full_name)

else:

data[label][name] = [full_name]

反转过程

params = {'name': 'Sir Robin', 'greeting': 'wellmet'}

hello(**params)

练习使用参数

def story(**kwds):

return 'Once upon a time, there was a ' \

'%(job)s called %(name)s.' % kwds

def power(x, y, *others):

if others:

print 'Received redundant parameters:', others

return pow(x, y)

def interval(start, stop=None, step=1):

'Imitates range() for step > 0'

if stop is None: # If the stop is not supplied...

start, stop = 0, start # shuffle the parameters

result = []

i = start # We start counting at the start index

while i < stop: # Until the index reaches the stop index...

result.append(i) # ...append the index to out result...

i += step # ...increment the index with the step (> 0)

return result

作用域

命名空间：作用域，不可见字典

Shadowing

globals().['parameter']

vars

locals

nonlocal

递归

最小可能性问题

递归实例

阶乘和幂

另外一个经典：二元查找

def search(sequence, number, lower, upper=None):

if upper is None: upper = len(sequence)-1

if lower == upper:

assert number == sequence[upper]

return upper

else:

middle = (lower + upper) // 2

if number > sequence[middle]:

return search(sequence, number, middle+1, upper)

else:

return search(sequence, number, lower, middle)

本章新函数

map(func, seq[, seq,...])

filter(func,seq)

reduce(func, seq[, initial])

sum(seq)

apply(func[, args[, kwargs]])

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