[英]Recursion in Python, creating several new instances from each loop
I have a problem where I have a dictionary that contains class objects, that references one or more items.我有一个问题,我有一个包含类对象的字典,它引用了一个或多个项目。 The key of the dictionary is the id of each item.
字典的键是每个项目的 id。 I am trying to set up a recursive function for finding the chain of adjacent item IDs, for x steps.
我正在尝试为 x 步设置一个递归函数来查找相邻项目 ID 链。
It works, but only if there is only one item in each "adjacent_items"-variable.它有效,但前提是每个“adjacent_items”变量中只有一个项目。 If there are more, it still only catches the first and moves on.
如果还有更多,它仍然只捕获第一个并继续前进。 In the example the "7" is never handled.
在示例中,从未处理过“7”。
I am very new to recursive functions, but I feel like there should be an efficient way so solve this with recursion.我对递归函数很陌生,但我觉得应该有一种有效的方法,所以用递归来解决这个问题。 Any input would be appreciated.
任何输入将不胜感激。
class Item:
def __init__(self, id_num: str, adjacent: list):
self.id = id_num
self.adjacent_items = adjacent
def get_adjacent_x_steps(start: str, item_dict: dict, x: int, wip_set=None):
"""Get adjacent items for x steps"""
if wip_set is None:
wip_set = set()
if x != 0:
x -= 1
for item in item_dict[start].adjacent_items:
wip_set.add(item)
# Todo, only takes first hit, return exits this instance..
return get_adjacent_x_steps(item, item_dict, x, wip_set)
else:
return wip_set
def example():
"""Example items"""
item1 = Item("1", ["4", "7"])
item2 = Item("4", ["5"])
item3 = Item("7", ["5"])
item4 = Item("5", ["8", "17"])
item_dict = {}
for item in (item1, item2, item3, item4):
item_dict[item.id] = item
chained_items = get_adjacent_x_steps("1", item_dict, 2)
print(chained_items)
if __name__ == '__main__':
example()
I am not sure whether you want to get the paths along with x
steps, or only the destinations.我不确定您是要获取路径和
x
步,还是只获取目的地。 If the latter is the case, try the following:如果是后者,请尝试以下操作:
class Item:
def __init__(self, id_num: str, adjacent: list):
self.id = id_num
self.adjacent_items = adjacent
def get_adjacent_x_steps(start, item_dict, x):
if x == 0 or start not in item_dict:
return [[]]
return [[adj, *lst]
for adj in item_dict[start].adjacent_items
for lst in get_adjacent_x_steps(adj, item_dict, x - 1)]
item1 = Item("1", ["4", "7"])
item2 = Item("4", ["5"])
item3 = Item("7", ["5"])
item4 = Item("5", ["8", "17"])
item_dict = {i.id: i for i in (item1, item2, item3, item4)}
print(get_adjacent_x_steps('1', item_dict, 1))
print(get_adjacent_x_steps('1', item_dict, 2))
print(get_adjacent_x_steps('1', item_dict, 3))
Recursion happens at the list comprehension;递归发生在列表理解中; at
start
, get all adjacent items ( for adj in item_dict[start].adjacent_items
), and apply the function to those items with one step less ( get_adjacent_x_steps(adj, item_dict, x - 1)
).在
start
,获取所有相邻项目( for adj in item_dict[start].adjacent_items
),并将该函数应用于那些少一步的项目( get_adjacent_x_steps(adj, item_dict, x - 1)
)。 Then return the resulting list lst
along with adj
.然后返回结果列表
lst
和adj
。
Output:输出:
[['4'], ['7']]
[['4', '5'], ['7', '5']]
[['4', '5', '8'], ['4', '5', '17'], ['7', '5', '8'], ['7', '5', '17']]
If you want to get the set of destinations, then you can apply set comprehension afterwards:如果你想得到一组目的地,那么你可以在之后应用集合理解:
print({x[-1] for x in get_adjacent_x_steps('1', item_dict, 3)})
# {'17', '8'}
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