如何比較列表中的每個元素與另一個列表中的每個元素？

Question

我想比較提取的促銷代碼列表與正確的促銷代碼列表。

如果正在與correct_promo_code列表中的促銷代碼進行比較的extracted_list中的促銷代碼沒有找到完全匹配，那麼這意味着促銷代碼有錯誤。爲了從correct_promo_codes列表中找到正確的促銷代碼，我需要找到與正在比較的（來自extracted_list）的編輯距離（levenshtein距離）最小的促銷代碼。

代碼至今： -

import csv 

with open("all_correct_promo.csv","rb") as file1: 
    reader1 = csv.reader(file1) 
    correctPromoList = list(reader1) 
    #print correctPromoList 

with open("all_extracted_promo.csv","rb") as file2: 
    reader2 = csv.reader(file2) 
    extractedPromoList = list(reader2) 
    #print extractedPromoList 

incorrectPromo = [] 
count = 0 
for extracted in extractedPromoList: 
    if(extracted not in correctPromoList): 
     incorrectPromo.append(extracted) 
    else: 
     count = count + 1 
#print incorrectPromo 

for promos in incorrectPromo: 
    print promos 

Answer 1

根據nltk docs

nltk.metrics.distance.edit_distance(s1, s2, transpositions=False) 

計算兩個字符串之間的萊文斯坦編輯距離。編輯距離是將s1轉換爲s2所需要替換，插入或刪除的字符數。例如，將「雨」轉換爲「閃耀」需要三個步驟，包括兩個替換和一個插入：「雨」 - >「sain」 - >「shin」 - >「閃耀」。這些操作可能是以其他的順序完成的，但至少需要三個步驟。

來到你代碼，我覺得在下半區的一些變化將捕捉到的編輯距離 -

from nltk.metrics import distance # slow to load 

extractedPromoList = ['abc','acd','abd'] # csv of extracted promo codes dummy 
correctPromoList = ['abc','aba','xbz','abz','abx'] # csv to real promo codes dummy 

def find_min_edit(str_,list_): 
    nearest_correct_promos = [] 
    distances = {} 
    min_dist = 100 # arbitrary large assignment 
    for correct_promo in list_: 
     dist = distance.edit_distance(extracted,correct_promo,True) # compute Levenshtein distance 
     distances[correct_promo] = dist # store each score for real promo codes 
     if dist<min_dist: 
      min_dist = dist # store min distance 
    # extract all real promo codes with minimum Levenshtein distance 
    nearest_correct_promos.append(','.join([i[0] for i in distances.items() if i[1]==min_dist])) 
    return ','.join(nearest_correct_promos) # return a comma separated string of nearest real promo codes 

incorrectPromo = {} 
count = 0 
for extracted in extractedPromoList: 
    print 'Computing %dth promo code...' % count 
    incorrectPromo[extracted] = find_min_edit(extracted,correctPromoList) # get comma separated str of real promo codes nearest to extracted 
    count+=1 
print incorrectPromo 

輸出

Computing 0th promo code... 
Computing 1th promo code... 
Computing 2th promo code... 
{'abc': 'abc', 'abd': 'abx,aba,abz,abc', 'acd': 'abx,aba,abz,abc'}