嵌套for-loop元素列表比较 [英] Nested for-loop element-wise list comparison

问题描述

作为一种解决我的挑战的新方法，此处，我已经整理了以下内容：

As a novel approach to solving my challenge described here, I have put together the following:

from difflib import SequenceMatcher

def similar(a, b):
    return SequenceMatcher(None, a, b).ratio()

diffs =[
"""- It contains a Title II provision that changes the age at which workers
compensation/public disability offset ends for disability beneficiaries from age 65 to full retirement age (FRA).""",
"""+ It contains a Title II provision that changes the age at which workers 
compensation/public disability offset ends for disability beneficiaries from age 68 to full retirement age (FRA).""",
"""+ Here's a new paragraph I added for testing."""]

for s in diffs:
    others = [i for i in diffs if i != s]
    for j in others:
        if similar(s, j) > 0.7:
            print '"{}" and "{}" refer to the same sentence'.format(s, j)
            print
            diffs.remove(j)
        else:
            print '"{}" is a new sentence'.format(s)

我们的想法是循环遍历字符串，并将每个字符串与其他字符串进行比较。如果给定的字符串被认为与另一个字符串相似，则删除另一个字符串，否则给定的字符串被认为是列表中的唯一字符串。

The idea is to loop over the strings, and compare each with the others. If a given string is deemed to be similar to another, remove the other, otherwise the given string is deemed to be a unique string in the list.

这是输出：

"- It contains a Title II provision that changes the age at which workers
compensation/public disability offset ends for disability beneficiaries from age 65 to full retirement age (FRA)." and "+ It contains a Title II provision that changes the age at which workers 
compensation/public disability offset ends for disability beneficiaries from age 68 to full retirement age (FRA)." refer to the same sentence


"- It contains a Title II provision that changes the age at which workers
compensation/public disability offset ends for disability beneficiaries from age 65 to full retirement age (FRA)." is a new sentence
"+ Here's a new paragraph I added for testing." is a new sentence

所以它正确地检测到前两个句子是相似的，而最后一个是独特。问题是它然后回过头来判断第一个句子是唯一的（它不是，它不应该回到这个句子）。

So it's correctly detecting that the first two sentences are similar, and that the last is unique. The problem is it's then going back and deeming the first sentence to be unique (which it isn't, and it should not be returning to this sentence anyway).

循环逻辑中的缺陷在哪里？这可以在没有嵌套的和删除元素的情况下实现吗？

Where's the flaw in my looping logic? Can this be achieved without nested fors and removal of elements?

推荐答案

from difflib import SequenceMatcher
from collections import defaultdict

def similar(a, b):
    return SequenceMatcher(None, a, b).ratio()

diffs =[
"""- It contains a Title II provision that changes the age at which workers
compensation/public disability offset ends for disability beneficiaries from age 65 to full retirement age (FRA).""",
"""+ It contains a Title II provision that changes the age at which workers 
compensation/public disability offset ends for disability beneficiaries from age 68 to full retirement age (FRA).""",
"""+ Here's a new paragraph I added for testing."""]


sims = set()
simdict = defaultdict(list)
for i in range(len(diffs)):
    if i in sims:
        continue
    s = diffs[i]

    for j in range(i+1, len(diffs)):
        r = diffs[j]
        if similar(s, r) > 0.7:
            sims.add(j)
            simdict[i].append(j)


for k, v in simdict.iteritems():
    print diffs[k] + " is similar to:"
    print '\n'.join(diffs[e] for e in v)

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