Question

按照第一个索引查看排序列表的最优雅方法是什么？输入：

Meni22   xxxx xxxx
Meni32_2 xxxx xxxx
Meni32_2 xxxx xxxx
Meni45_1 xxxx xxxx
Meni45_1 xxxx xxxx
Meni45   xxxx xxxx

是否逐行：

list1 = []
list2 = []
for line in input:
    if line[0] not in list1:
    list.append(line)
else:
    list2.append(line)

示例显然不起作用。它添加了第[0]行的第一个匹配并继续。我宁愿让它通过列表，添加到list1行，它只找到一次，然后休息到list2。

脚本之后：

List1:

Meni22   xxxx xxxx
Meni45   xxxx xxxx

List2: 

Meni45_1 xxxx xxxx
Meni45_1 xxxx xxxx
Meni32_2 xxxx xxxx
Meni32_2 xxxx xxxx

Answer 1

由于文件已排序，您可以使用groupby

from itertools import groupby
list1, list2 = res = [], []
with open('file1.txt', 'rb') as fin:
    for k,g in groupby(fin, key=lambda x:x.partition(' ')[0]):
        g = list(g)
        res[len(g) > 1] += g

或者如果你喜欢这个更长的版本

from itertools import groupby
list1, list2 = [], []
with open('file1.txt', 'rb') as fin:
    for k,g in groupby(fin, key=lambda x:x.partition(' ')[0]):
        g = list(g)
        if len(g) > 1:
            list2 += g
        else:
            list1 += g

Answer 2

您可以使用collections.Counter：

from collections import Counter
lis1 = []
lis2 = []
with open("abc") as f:
    c = Counter(line.split()[0] for line in f)

for key,val in c.items():
    if val == 1:
        lis1.append(key)
    else:
        lis2.extend([key]*val)
print lis1
print lis2

<强>输出：

['Meni45', 'Meni22']
['Meni32_2', 'Meni32_2', 'Meni45_1', 'Meni45_1']

修改

from collections import defaultdict lis1 = [] lis2 = [] with open("abc") as f: dic = defaultdict(list) for line in f: spl =line.split() dic[spl[0]].append(spl[1:]) for key,val in dic.items(): if len(val) == 1: lis1.append(key) else: lis2.append(key) print lis1 print lis2 print dic["Meni32_2"] #access columns related to any key from the the dict

<强>输出：

['Meni45', 'Meni22'] ['Meni32_2', 'Meni45_1'] [['xxxx', 'xxxx'], ['xxxx', 'xxxx']]

Answer 3

考虑使用difflib

import difflib

d = difflib.Differ()
fa = open('a.txt'); fb = open('b.txt')

diff = d.compare("".join(fa.readlines()), "".join(fb.readlines()))
print ''.join(list(diff))

fa.close(); fb.close()

逐行比较文件python

3 个答案: