本章知识点：
1、模块的创建与使用；
2、内置模块；
3、常用模块；
4、函数的创建和使用；
5、lambda 函数；
6、Generator 函数；
7、函数化程序设计；
5.1 Python 程序的结构
5.2 模块
5.2.1 模块的创建
1 ## 自定义模块
2 def func():
3 print ("MyModule.func()")
4
5 class MyClass:
6 def myFunc(self):
7 print ("MyModule.MyClass.myFunc()")
View Code
1 ## 调用自定义模块的类和函数
2 import myModule
3
4 myModule.func() # 输出：MyModule.func()
5 myClass = myModule.MyClass() # 变量
6 myClass.myFunc() # 输出:MyModule.MyClass.myFunc()
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1 # 模块 myModule
2 count = 1
3 def func():
4 global count
5 count = count + 1
6 return count
7
8
9
10
11 print ("count =",myModule.func())
12 myModule.count = 10
13 print ("count =",myModule.func())
14
15 import myModule
16 print ("count =",myModule.func())
17 # 输出：count = 2
18 # count = 11
19 # count = 12
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5.2.3 模块的属性
1 #myModule.py
2 if __name__ == '__main__':
3 print ('myModule作为主程序运行')
4 else:
5 print ('myModule被另一个模块调用')
6
7 import myModule
8 print (__doc__)
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5.2.4 模块的内置函数
1、apply()
2、filter()
1 def func(x):
2 if x > 0:
3 return x
4 print (filter(func, range(-9, 10)))
5 print (list(filter(func, range(-9, 10))))
6 # 输入：<filter object at 0x000001B9B4D9C080>
7 # [1, 2, 3, 4, 5, 6, 7, 8, 9]
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3、reduce()
1 def sum(x,y):
2 return x + y
3 from functools import reduce
4 print (reduce(sum, range(0, 10)))
5 print (reduce(sum, range(0, 10), 10))
6 print (reduce(sum, range(0, 0), 10))
7 # 输出：45；55；10
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4、map()
1 def power(x):
2 return x ** x
3 print (map(power, range(1, 5)))
4 print (list(map(power, range(1, 5))))
5 def power1(x, y):
6 return x ** y
7 print (map(power1, range(1, 5), range(5, 1, -1)))
8 print (list(map(power1, range(1, 5), range(5, 1, -1))))
9 # 输入：<map object at 0x000001BCEAF2A710>
10 # [1, 4, 27, 256]
11 # <map object at 0x000001BCEB0C8DA0>
12 # [1, 16, 27, 16]
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5.2.5 自定义包
1 if __name__ == "__main__":
2 print ("作为主程序运行")
3 else:
4 print ("pack初始化")
5 # 输出：作为主程序运行
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1 def func():
2 print ("pack.myModule.func()")
3
4 if __name__ == "__main__":
5 print ("myModule作为主程序运行")
6 else:
7 print ("myModule被另一个程序调用")
8 # 输出：myModule作为主程序运行
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5.3 函数
5.3.1 函数的定义
1 ## 函数的定义
2 from __future__ import division
3 def arithmetic(x, y ,operator):
4 result = {
5 "+": x + y,
6 "-": x - y,
7 "*": x * y,
8 "/": x / y
9 }
10
11 ## 函数的调用
12 print (arithmetic(1, 2, "+"))
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1 def arithmetic(x=1, y=2, operator="+"):
2 result = {
3 "+": x + y,
4 "-": x - y,
5 "*": x * y,
6 "/": x / y
7 }
8 return result.get(operator)
9
10 ## 函数的调用
11 print (arithmetic(1, 2))
12 print (arithmetic(1, 2, "-"))
13 print (arithmetic(y=3,operator="-"))
14 print (arithmetic(x=4, operator="-"))
15 print (arithmetic(y=3,x=4, operator="-"))
16 # 输出：3
17 # -1
18 # -2
19 # 2
20 # 1
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1 ## 列表作为参数的传递
2 def arithmetic(args=[], operator="+"):
3 x = args[0]
4 y = args[1]
5 result = {
6 "+": x + y,
7 "-": x - y,
8 "*": x * y,
9 "/": x / y
10 }
11 return result.get(operator)
12 print (arithmetic([1, 2]))
13 # 输出：3
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1 def append(args=[]):
2 args.append(0)
3 print (args)
4 append()
5 append([1])
6 append()
7 # 输出：[0]
8 # [1, 0]
9 # [0, 0]
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1 def append(args=[]):
2 if len(args) <= 0:
3 args = []
4 args.append(0)
5 print (args)
6 append()
7 append([1])
8 append()
9 # 输出：[0]
10 # [1, 0]
11 # [0]
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1 ## 传递可变参数
2 def func(*args):
3 print (args)
4 func(1, 2, 3)
5 # 输出：(1, 2, 3)
View Code
1 def search(*t, **d):
2 keys = d.keys()
3 values = d.values()
4 print (keys)
5 print (values)
6 for arg in t:
7 for key in keys:
8 if arg == key:
9 print ("find:",d[key])
10
11 search("one", "three", one="1", two="2", three="3")
12 # 输入：dict_keys(['one', 'two', 'three'])
13 # dict_values(['1', '2', '3'])
14 # find: 1
15 # find: 3
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5.3.3 函数的返回值
## 没有return语句的返回值
def func():
pass
print (func())
# 输出：None
## return返回多个值
def func(x, y, z):
l = [x, y, z]
l.reverse()
numbese = tuple(l)
return numbese
x, y , z = func(0, 1, 2)
print (x, y, z)
# 输出：2 1 0
def func(x, y, z):
l = [x, y, z]
l.reverse()
a, b, c = tuple(l)
return a, b, c
x, y , z = func(0, 1, 2)
print (x, y, z)
# 输出：2 1 0
def func(x):
if x > 0:
return "x > 0"
elif x == 0:
return "x == 0"
else:
return "x < 0"
print (func(-2))
# 输出：x < 0
## 多个return语句的重构
def func(x):
if x > 0:
result = "x > 0"
elif x == 0:
result = "x == 0"
else:
return "x < 0"
return result
print (func(-2))
# 输出：x < 0
5.3.4 函数的嵌套
## 嵌套函数
def sum(a,b):
return a + b
def sub(a, b):
return a - b
def func():
x = 1
y = 2
m = 3
n = 4
return sum(x, y) * sub(m, n)
print (func())
# 输出：-3
## 嵌套函数
def func():
x = 1
y = 2
m = 3
n = 4
def sum(a, b):
return a + b
def sub(a, b):
return a - b
return sum(x, y) * sub(m, n)
print (func())
# 输出：-3
## 嵌套函数，直接使用外层函数的变量
def func():
x = 1
y = 2
m = 3
n = 4
def sum():
return x + y
def sub():
return m - n
return sum() * sub()
print (func())
# 输出：-3
5.3.5 递归函数
## 计算阶乘
def refunc(n):
i = 1
if n > 1:
i = n
n = n * refunc(n-1)
print ("%d! =" %i, n)
return n
refunc(5)
# 输出：1! = 1
# 2! = 2
# 3! = 6
# 4! = 24
# 5! = 120
5.3.6 lambda函数
## lambda函数
def func():
x = 1
y = 2
m = 3
n = 4
sum = lambda x, y : x + y
print (sum)
sub = lambda m, n : m - n
print (sub)
return sum(x, y) * sub(m, n)
print (func())
# 输出：<function func.<locals>.<lambda> at 0x000001652324E158>
# <function func.<locals>.<lambda> at 0x0000016523239C80>
# -3
# ## lambda函数的用法
print ((lambda x:-x)(-2))
#输出：2
5.3.7 Generator函数
## 定义Generator函数
def func(n):
for i in range(n):
yield i
# 在for循环中输出
for i in func(3):
print (i)
# 使用next()输出
r = func(3)
print (r.next())
print (r.next())
print (r.next())
## yield与return区别
def func(n):
for i in range(n):
return i
def func2(n):
for i in range(n):
yield i
print (func(3))
f = func2(3)
print (f)
print (f.next())
print (f.next())
