我有一個(gè) for 循環(huán)，我需要在其中分配從另一個(gè)字典中獲取的新鍵的值。我試圖避免 for 循環(huán)中的 for 循環(huán)。我的第一本字典如下所示：ids = [{'1020': 'ID-2522'}, {'1030': 'ID-2523'}, {'1040': 'ID-2524'}]我正在循環(huán)的字典列表如下所示：data = [{'sf_id': '1020', TotalPrice': '504'}, {'sf_id': '1030', TotalPrice': '400'}, {'sf_id': '1040', TotalPrice': '500'}]這是我的for循環(huán)：for index, my_dict in enumerate(data): for key, value in my_dict.items(): new_id = my_dict["sf_id"] opportunity = ids[new_id]以便它獲取對(duì)應(yīng)的值。期望的輸出是：print(opportunity)ID-2522ID-2523ID-2524
3 回答
臨摹微笑
TA貢獻(xiàn)1982條經(jīng)驗(yàn) 獲得超2個(gè)贊
假設(shè)整個(gè)集合中沒(méi)有重復(fù)鍵，您可以使用reduce將每個(gè) id 字典合并到一個(gè) id 字典中，因此您只需迭代兩個(gè)集合一次
from functools import reduce
ids = [{'1020': 'ID-2522'}, {'1030': 'ID-2523'}, {'1040': 'ID-2524'}]
data = [{'sf_id': '1020', 'TotalPrice': '504'}, {'sf_id': '1030', 'TotalPrice': '400'}, {'sf_id': '1040', 'TotalPrice': '500'}]
ids_map = reduce(lambda x, y: x.update(y) or x , ids, {})
for my_dict in data:
new_id = my_dict["sf_id"]
opportunity = ids_map[new_id]
print(opportunity)
Cats萌萌
TA貢獻(xiàn)1805條經(jīng)驗(yàn) 獲得超9個(gè)贊
ids是字典列表，而不是字典。這使得查找其中一個(gè)鍵的效率非常低，因?yàn)槟仨毐闅v整個(gè)列表才能找到它。
因此，第一步是將所有這些小字典合并成一個(gè)大字典。
然后，我們可以使用您的預(yù)期輸出有效地構(gòu)建一個(gè)列表：
ids = [{'1020': 'ID-2522'}, {'1030': 'ID-2523'}, {'1040': 'ID-2524'}]
data = [{'sf_id': '1020', 'TotalPrice': '504'},
{'sf_id': '1030', 'TotalPrice': '400'},
{'sf_id': '1040', 'TotalPrice': '500'}]
ids_dict = {k:v for dct in ids for k, v in dct.items()}
opportunity = []
for my_dict in data:
new_id = my_dict["sf_id"]
opportunity.append(ids_dict[new_id])
print(opportunity)
# ['ID-2522', 'ID-2523', 'ID-2524']
（注意enumerate如果不使用索引就不需要）
或者，更短的，使用列表理解：
opportunity = [ids_dict[my_dict["sf_id"]] for my_dict in data]
print(opportunity)
# ['ID-2522', 'ID-2523', 'ID-2524']
慕容3067478
TA貢獻(xiàn)1773條經(jīng)驗(yàn) 獲得超3個(gè)贊
# Create a new variable and save sftoap in it
new_ids = ids
# pop the items from original list of dicts and save it in a new dict
sftoap_dict = {}
for d in new_ids:
key, value = d.popitem()
sftoap_dict[key] = value
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