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Writing a tokenizer in Python

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I want to design a custom tokenizer module in Python that lets users specify what tokenizer(s) to use for the input. For instance, consider the following input:

Q: What is a good way to achieve this? A: I am not so sure. I think I
will use Python.

I want to be able to provide NLTK’s sentence tokenization, sent_tokenize() as an option because it works well in many situations and I don’t want to re-invent the wheel. In addition to this, I also want to provide a finer-grained tokenization builder (something along the lines of a rule-engine). Let me explain:

Assume that I provider a couple of tokenizers:

SENTENCE # Tokenizes the given input by using sent_tokenize()
WORD # Tokenizes the given input by using word_tokenize()
QA # Tokenizes using a custom regular expression. E.g., Q: (.*?) A: (.*?)

I want to support rules as follows:

  1. QA -> SENTENCE: Apply the QA tokenizer first, followed by the sentence tokenizer
  2. QA: Apply just the QA tokenizer

Therefore, the expected output is as follows:

1. QA -> SENTENCE

[
  ('QUESTION', 
             ('SENTENCE', 'What is a good way to achieve this?'), 
  ),
  ('ANSWER', 
             ('SENTENCE', 'I am not so sure', 'I think I will use Python')
  )
]

2. QA

[
  ('QUESTION', 'What is a good way to achieve this?'),
  ('ANSWER', 'I am not so sure. I think I will use Python')
]

What is a good design to achieve this efficiently?

As tokenizing is easy in Python, I’m wondering what your module is planned to provide.
I mean when starting a piece of software a good design rather comes from thinking about the usage scenarios than considering data structures first.

Your examples for expected output are a bit confusing.
I assume you want the tokenizers return name on left side and a list of tokens on right side.
I played a bit to achieve similar results, but using lists for easier handling:

import re

# some tokenizers
def tokzr_WORD(txt): return ('WORD', re.findall(r'(?ms)W*(w+)', txt))  # split words
def tokzr_SENT(txt): return ('SENTENCE', re.findall(r'(?ms)s*(.*?(?:.|?|!))', txt))  # split sentences
def tokzr_QA(txt):
    l_qa = []
    for m in re.finditer(r'(?ms)^[s#-*]*(?:Q|Question)s*:s*(?P<QUESTION>S.*??)[s#-*]+(?:A|Answer)s*:s*(?P<ANSWER>S.*?)$', txt):  # split (Q, A) sequences
        for k in ['QUESTION', 'ANSWER']:
            l_qa.append(m.groupdict()[k])
    return ('QA', l_qa)
def tokzr_QA_non_canonical(txt):  # Note: not supported by tokenize_recursively() as not canonical.
    l_qa = []
    for m in re.finditer(r'(?ms)^[s#-*]*(?:Q|Question)s*:s*(?P<QUESTION>S.*??)[s#-*]+(?:A|Answer)s*:s*(?P<ANSWER>S.*?)$', txt):  # split (Q, A) sequences
        for k in ['QUESTION', 'ANSWER']:
            l_qa.append((k, m.groupdict()[k]))
    return l_qa

dict_tokzr = {  # control string: tokenizer function
    'WORD'    : tokzr_WORD,
    'SENTENCE': tokzr_SENT,
    'QA'      : tokzr_QA,
}

# the core function
def tokenize_recursively(l_tokzr, work_on, lev=0):
    if isinstance(work_on, basestring):
        ctrl, work_on = dict_tokzr[l_tokzr[0]](work_on)  # tokenize
    else:
        ctrl, work_on = work_on[0], work_on[1:]  # get right part
    ret = [ctrl]
    if len(l_tokzr) == 1:
        ret.append(work_on)  # add right part
    else:
        for wo in work_on:  # dive into tree
            t = tokenize_recursively(l_tokzr[1:], wo, lev + 1)
            ret.append(t)
    return ret

# just for printing
def nestedListLines(aList, ind='    ', d=0):
    """ Returns multi-line string representation of param aList.  Use param ind to indent per level. """
    sRet = 'n' + d * ind + '['
    nested = 0
    for i, e in enumerate(aList):
        if i:
            sRet += ', '
        if type(e) == type(aList):
            sRet += nestedListLines(e, ind, d + 1)
            nested = 1
        else:
            sRet += 'n' + (d + 1) * ind + repr(e) if nested else repr(e)
    sRet += 'n' + d * ind + ']' if nested else ']'
    return sRet

# main()
inp1 = """
    * Question: I want try something.  Should I?
    * Answer  : I'd assume so.  Give it a try.
"""
inp2 = inp1 + 'Q: What is a good way to achieve this?  A: I am not so sure. I think I will use Python.'
print repr(tokzr_WORD(inp1))
print repr(tokzr_SENT(inp1))
print repr(tokzr_QA(inp1))
print repr(tokzr_QA_non_canonical(inp1))  # Really this way?
print

for ctrl, inp in [  # example control sequences
    ('SENTENCE-WORD', inp1),
    ('QA-SENTENCE', inp2)
]:
    res = tokenize_recursively(ctrl.split('-'), inp)
    print nestedListLines(res)

Btw. Python/Lib/tokenize.py (for Python code itself) might be worth a look how to handle things.

thoku

Writing a tokenizer in Python
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