对带有子列表的可迭代对象的每个元素应用一个函数
apply a function over each element of an iterable with sublists
我正在尝试将函数应用于包含任意子列表子级别的列表的每个元素。像这样。
a = [1,2,3]
b = [[1,2,3],[4,5,6]]
c = [[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]]
function = lambda x: x+1
def apply(iterable,f):
# do stuff here
print(apply(a,function)) # [2,3,4]
print(apply(b,function)) # [[2,3,4],[5,6,7]]
print(apply(c,function)) # [[[2,3,4],[5,6,7]],[[8,9,10],[11,12,13]]]
基本上我找不到编写apply
函数的方法。我尝试使用 numpy,但这当然不是解决方案,因为列表的内容也可以是字符串、对象 ...
这是一种方法。请注意,字符串也是可迭代的,因此根据您的用例,您可能需要添加更多检查。
def apply(iterable, f):
try:
iterator = iter(iterable)
for i in iterator:
apply(i, f)
except Exception as e:
f(iterable)
c = [[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]]
apply(c, print)
听起来递归应该可以解决这个问题:
a = [1,2,3]
b = [[1,2,3], [4,5,6]]
c = [[[1,2,3], [4,5,6]], [[7,8,9], [10,11,12]]]
f = lambda x : x+1
def apply(iterable, f):
# suggestion by Jérôme:
# from collections.abc import Iterable and use
# isinstance(iterable, collections.abc.Iterable) so it works for tuples etc.
if isinstance(iterable, list):
# apply function to each element
return [apply(w, f) for w in iterable]
else:
return f(iterable)
print(apply(a, f)) # [2,3,4]
print(apply(b, f)) # [[2,3,4],[5,6,7]]
print(apply(c, f)) # [[[2,3,4],[5,6,7]],[[8,9,10],[11,12,13]]]
试试这个递归:
def apply(it, func):
try:
return [apply(e) for e in it]
except TypeError:
return func(it)
请注意,除非您另有指定,否则这将遍历任何可迭代对象,例如,您可以在开头检查它是否是一个字典,然后将其应用到它上面的函数.. add
if isinstance(it,dict):
func(it)
如果你所有的嵌套列表都是相同的形状,你应该可以用 numpy 做到这一点:
import numpy as np
ary = np.array([['a', 'b'], ['c', 'd'], ['e', 'f']])
res = np.vectorize(lambda c: c + ':)')(ary)
print(res)
# [['a:)' 'b:)']
# ['c:)' 'd:)']
# ['e:)' 'f:)']]
我正在尝试将函数应用于包含任意子列表子级别的列表的每个元素。像这样。
a = [1,2,3]
b = [[1,2,3],[4,5,6]]
c = [[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]]
function = lambda x: x+1
def apply(iterable,f):
# do stuff here
print(apply(a,function)) # [2,3,4]
print(apply(b,function)) # [[2,3,4],[5,6,7]]
print(apply(c,function)) # [[[2,3,4],[5,6,7]],[[8,9,10],[11,12,13]]]
基本上我找不到编写apply
函数的方法。我尝试使用 numpy,但这当然不是解决方案,因为列表的内容也可以是字符串、对象 ...
这是一种方法。请注意,字符串也是可迭代的,因此根据您的用例,您可能需要添加更多检查。
def apply(iterable, f):
try:
iterator = iter(iterable)
for i in iterator:
apply(i, f)
except Exception as e:
f(iterable)
c = [[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]]
apply(c, print)
听起来递归应该可以解决这个问题:
a = [1,2,3]
b = [[1,2,3], [4,5,6]]
c = [[[1,2,3], [4,5,6]], [[7,8,9], [10,11,12]]]
f = lambda x : x+1
def apply(iterable, f):
# suggestion by Jérôme:
# from collections.abc import Iterable and use
# isinstance(iterable, collections.abc.Iterable) so it works for tuples etc.
if isinstance(iterable, list):
# apply function to each element
return [apply(w, f) for w in iterable]
else:
return f(iterable)
print(apply(a, f)) # [2,3,4]
print(apply(b, f)) # [[2,3,4],[5,6,7]]
print(apply(c, f)) # [[[2,3,4],[5,6,7]],[[8,9,10],[11,12,13]]]
试试这个递归:
def apply(it, func):
try:
return [apply(e) for e in it]
except TypeError:
return func(it)
请注意,除非您另有指定,否则这将遍历任何可迭代对象,例如,您可以在开头检查它是否是一个字典,然后将其应用到它上面的函数.. add
if isinstance(it,dict):
func(it)
如果你所有的嵌套列表都是相同的形状,你应该可以用 numpy 做到这一点:
import numpy as np
ary = np.array([['a', 'b'], ['c', 'd'], ['e', 'f']])
res = np.vectorize(lambda c: c + ':)')(ary)
print(res)
# [['a:)' 'b:)']
# ['c:)' 'd:)']
# ['e:)' 'f:)']]