我有一些文字：

 s="Imageclassificationmethodscan beroughlydividedinto two broad families of approaches:"

我想将其解析为单独的单词。我很快地研究了附魔和nltk，但没有看到任何看起来立即有用的东西。如果我有时间在这方面投入，我会考虑编写一个动态程序，用 enchant 来检查单词是否是英语。我本以为可以在网上做一些事情，我错了吗？

使用 trie 的贪心方法

尝试使用这个生物蟒蛇 https://github.com/biopython/biopython (pip install biopython):

from Bio import trie
import string


def get_trie(dictfile='/usr/share/dict/american-english'):
    tr = trie.trie()
    with open(dictfile) as f:
        for line in f:
            word = line.rstrip()
            try:
                word = word.encode(encoding='ascii', errors='ignore')
                tr[word] = len(word)
                assert tr.has_key(word), "Missing %s" % word
            except UnicodeDecodeError:
                pass
    return tr


def get_trie_word(tr, s):
    for end in reversed(range(len(s))):
        word = s[:end + 1]
        if tr.has_key(word): 
            return word, s[end + 1: ]
    return None, s

def main(s):
    tr = get_trie()
    while s:
        word, s = get_trie_word(tr, s)
        print word

if __name__ == '__main__':
    s = "Imageclassificationmethodscan beroughlydividedinto two broad families of approaches:"
    s = s.strip(string.punctuation)
    s = s.replace(" ", '')
    s = s.lower()
    main(s)

Results

>>> if __name__ == '__main__':
...     s = "Imageclassificationmethodscan beroughlydividedinto two broad families of approaches:"
...     s = s.strip(string.punctuation)
...     s = s.replace(" ", '')
...     s = s.lower()
...     main(s)
... 
image
classification
methods
can
be
roughly
divided
into
two
broad
families
of
approaches

Caveats

英语中有一些退化的情况，这不起作用。您需要使用回溯来处理这些问题，但这应该可以帮助您开始。

强制性测试

>>> main("expertsexchange")
experts
exchange