Splitting a string into words and punctuation

Question

I'm trying to split a string up into words and punctuation, adding the punctuation to the list produced by the split.

For instance:

>>> c = "help, me"
>>> print c.split()
['help,', 'me']

What I really want the list to look like is:

['help', ',', 'me']

So, I want the string split at whitespace with the punctuation split from the words.

I've tried to parse the string first and then run the split:

>>> for character in c:
...     if character in ".,;!?":
...             outputCharacter = " %s" % character
...     else:
...             outputCharacter = character
...     separatedPunctuation += outputCharacter
>>> print separatedPunctuation
help , me
>>> print separatedPunctuation.split()
['help', ',', 'me']

This produces the result I want, but is painfully slow on large files.

Is there a way to do this more efficiently?

Answer 1

Have you tried using a regex?

http://docs.python.org/library/re.html#re-syntax

---

By the way. Why do you need the "," at the second one? You will know that after each text is written i.e.

[0]

","

[1]

","

So if you want to add the "," you can just do it after each iteration when you use the array..

Answer 2

Thanks Filip, I'll look into the regex library.

On the second point, maybe I should have used a better example.

If I had the string:

d = "Hello, I'm a string!"

I'd want the output:

['Hello', ',', 'I'm', 'a', 'string', "!"]

So, I want to separate all different sorts of punctuation from the alphanumerics, splitting at the whitespace.

Answer 3

In perl-style regular expression syntax, \b matches a word boundary. This should come in handy for doing a regex-based split.

edit: I have been informed by hop that "empty matches" do not work in the split function of Python's re module. I will leave this here as information for anyone else getting stumped by this "feature".

Answer 4

I think you can find all the help you can imagine in the NLTK, especially since you are using python. There's a good comprehensive discussion of this issue in the tutorial.

Answer 5

Here's a minor update to your implementation. If your trying to doing anything more detailed I suggest looking into the NLTK that le dorfier suggested.

This might only be a little faster since ''.join() is used in place of +=, which is known to be faster.

import string

d = "Hello, I'm a string!"

result = []
word = ''

for char in d:
    if char not in string.whitespace:
        if char not in string.ascii_letters + "'":
            if word:
                    result.append(word)
            result.append(char)
            word = ''
        else:
            word = ''.join([word,char])

    else:
        if word:
            result.append(word)
            word = ''
print result
['Hello', ',', "I'm", 'a', 'string', '!']

Answer 6

Here's my entry.

I have my doubts as to how well this will hold up in the sense of efficiency, or if it catches all cases (note the "!!!" grouped together; this may or may not be a good thing).

>>> import re
>>> import string
>>> s = "Helo, my name is Joe! and i live!!! in a button; factory:"
>>> l = [item for item in map(string.strip, re.split("(\W+)", s)) if len(item) > 0]
>>> l
['Helo', ',', 'my', 'name', 'is', 'Joe', '!', 'and', 'i', 'live', '!!!', 'in', 'a', 'button', ';', 'factory', ':']
>>>

One obvious optimization would be to compile the regex before hand (using re.compile) if you're going to be doing this on a line-by-line basis.

Answer 7

This is more or less the way to do it:

>>> import re
>>> re.findall(r"[\w']+|[.,!?;]", "Hello, I'm a string!")
['Hello', ',', "I'm", 'a', 'string', '!']

The trick is, not to think about where to split the string, but what to include in the tokens.

Caveats:

• The underscore (_) is considered an inner-word character. Replace \w, if you don't want that.
• This will not work with (single) quotes in the string.
• Put any additional punctuation marks you want to use in the right half of the regular expression.
• Anything not explicitely mentioned in the re is silently dropped.
• compiling the regular expression beforehand should make this considerably faster