定義一個函數與變量的定義很是類似,對於有名函數,必須經過變量名訪問ide
def func(x,y,z=1): return x+y+z print(func(1,2,3))
匿名函數定義:使用 lambda 來建立匿名函數函數
匿名函數1. 沒有名字 2:函數體自帶returnspa
匿名函數3d
def func(x,y,z=1): return x+y+z
print(lambda x,y,z=1:x+y+z)
function <lambda> at 0x0000000003469488>
匿名函數也是一個函數對象,匿名函數賦值給一個變量,再利用變量來調用該函數
f=lambda x,y,z=1:x+y+z print(f) print(f(1,2,3))
匿名函數的應用場景:應用於一次性的場景,臨時使用code
max,min,sorted,map,reduce,filter的用法對象
字典的運算:最小值,最大值,排序
salaries={ 'egon':3000, 'alex':100000000, 'wupeiqi':10000, 'yuanhao':2000 } print(max(salaries)) # 默認比較key值大小 print(max(salaries.values())) # 比較values值 print(max(salaries,key=lambda name:salaries[name])) 取values,來比較 print(min(salaries,key=lambda name:salaries[name])) 取values,來比較 print(max(zip(salaries.values(),salaries.keys()))[1]) # 經過zip的方式實現 def get_value(name): return salaries[name] print(max(salaries,key=get_value))
names=['alex','wupeiqi','yuanhao','yanglei','egon'] res=map(lambda x:x if x == 'egon' else x+'二狗子',names) print(res) print(list(res)) names=['alex','wupeiqi','yuanhao','yanglei','egon'] def my_map(func,seq): for item in seq: yield func(item) res1=my_map(lambda x:x+'_二狗',names) print(next(res1)) print(next(res1)) functools中導入reduce模塊 from functools import reduce print(reduce(lambda x,y:x+y,range(101),100)) print(reduce(lambda x,y:x+y,range(101)))
names=['alex_二狗','wupeiqi_二狗','yuanhao_二狗','yanglei_二狗','egon'] print(list(filter(lambda name:name.endswith('二狗'),names)))