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# -*- coding: utf-8 -*- |
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# Copyright 2018 by Christopher C. Little. |
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# This file is part of Abydos. |
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# |
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# Abydos is free software: you can redistribute it and/or modify |
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# it under the terms of the GNU General Public License as published by |
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# the Free Software Foundation, either version 3 of the License, or |
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# (at your option) any later version. |
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# |
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# Abydos is distributed in the hope that it will be useful, |
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# but WITHOUT ANY WARRANTY; without even the implied warranty of |
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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# GNU General Public License for more details. |
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# |
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# You should have received a copy of the GNU General Public License |
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# along with Abydos. If not, see <http://www.gnu.org/licenses/>. |
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"""abydos.tokenizer._tokenize. |
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_Tokenizer base class |
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""" |
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from __future__ import ( |
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absolute_import, |
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division, |
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print_function, |
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unicode_literals, |
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) |
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from collections import Counter |
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from math import exp, log, log1p |
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__all__ = ['_Tokenizer'] |
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class _Tokenizer(object): |
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"""Abstract _Tokenizer class. |
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.. versionadded:: 0.4.0 |
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""" |
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def __init__(self, scaler=None, *args, **kwargs): |
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"""Initialize Tokenizer. |
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Parameters |
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---------- |
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scaler : None, str, or function |
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A scaling function for the Counter: |
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- None : no scaling |
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- 'set' : All non-zero values are set to 1. |
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- 'length' : Each token has weight equal to its length. |
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- 'length-log' : Each token has weight equal to the log of its |
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length + 1. |
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- 'length-exp' : Each token has weight equal to e raised to its |
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length. |
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- 'entropy' : Weights are scaled to the (log_2) information |
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entropy of each key's frequency. |
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- a callable function : The function is applied to each value |
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in the Counter. Some useful functions include math.exp, |
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math.log1p, math.sqrt, and indexes into interesting integer |
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sequences such as the Fibonacci sequence. |
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.. versionadded:: 0.4.0 |
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""" |
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super(_Tokenizer, self).__init__() |
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self._scaler = scaler |
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self._tokens = Counter() |
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self._string = '' |
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self._ordered_tokens = [] |
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self._ordered_weights = [] |
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def tokenize(self, string=None): |
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"""Tokenize the term and store it. |
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The tokenized term is stored as an ordered list and as a Counter |
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object. |
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Parameters |
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---------- |
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string : str or None |
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The string to tokenize |
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.. versionadded:: 0.4.0 |
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.. versionchanged:: 0.4.1 |
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Added 'length', 'entropy', and related scalers |
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""" |
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if string is not None: |
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self._string = string |
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self._ordered_tokens = [self._string] |
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self._ordered_weights = [1] |
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if self._scaler in {'SSK', 'length', 'length-log', 'length-exp'}: |
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self._tokens = Counter() |
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if self._scaler[:6] == 'length': |
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self._ordered_weights = [len(_) for _ in self._ordered_tokens] |
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if self._scaler == 'length-log': |
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self._ordered_weights = [ |
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log1p(_) for _ in self._ordered_weights |
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] |
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elif self._scaler == 'length-exp': |
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self._ordered_weights = [ |
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exp(_) for _ in self._ordered_weights |
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] |
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for token, weight in zip( |
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self._ordered_tokens, self._ordered_weights |
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): |
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self._tokens[token] += weight |
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elif self._scaler == 'entropy': |
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counts = Counter(self._ordered_tokens) |
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n = len(self._ordered_tokens) |
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self._tokens = { |
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key: -(val / n) * log(val / n, 2) |
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for key, val in counts.items() |
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} |
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self._ordered_weights = [ |
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self._tokens[tok] / counts[tok] for tok in self._ordered_tokens |
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] |
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else: |
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self._tokens = Counter(self._ordered_tokens) |
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return self |
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def count(self): |
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"""Return token count. |
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Returns |
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------- |
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int |
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The total count of tokens |
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Examples |
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-------- |
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>>> tok = _Tokenizer().tokenize('term') |
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>>> tok.count() |
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1 |
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.. versionadded:: 0.4.0 |
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""" |
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return sum(self.get_counter().values()) |
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def count_unique(self): |
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"""Return the number of unique elements. |
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Returns |
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------- |
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int |
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The number of unique tokens |
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Examples |
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-------- |
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>>> tok = _Tokenizer().tokenize('term') |
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>>> tok.count_unique() |
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1 |
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.. versionadded:: 0.4.0 |
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""" |
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return len(self._tokens.values()) |
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def get_counter(self): |
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"""Return the tokens as a Counter object. |
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Returns |
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------- |
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Counter |
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The Counter of tokens |
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Examples |
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-------- |
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>>> tok = _Tokenizer().tokenize('term') |
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>>> tok.get_counter() |
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Counter({'term': 1}) |
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.. versionadded:: 0.4.0 |
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""" |
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if self._scaler == 'set': |
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return Counter({key: 1 for key in self._tokens.keys()}) |
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elif callable(self._scaler): |
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return Counter( |
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{key: self._scaler(val) for key, val in self._tokens.items()} |
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) |
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else: |
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return self._tokens |
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def get_set(self): |
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"""Return the unique tokens as a set. |
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Returns |
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------- |
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Counter |
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The set of tokens |
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Examples |
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-------- |
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>>> tok = _Tokenizer().tokenize('term') |
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>>> tok.get_set() |
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{'term'} |
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.. versionadded:: 0.4.0 |
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""" |
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return set(self._tokens.keys()) |
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def get_list(self): |
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"""Return the tokens as an ordered list. |
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Returns |
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------- |
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Counter |
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The list of q-grams in the order they were added. |
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Examples |
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-------- |
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>>> tok = _Tokenizer().tokenize('term') |
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>>> tok.get_list() |
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['term'] |
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.. versionadded:: 0.4.0 |
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""" |
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return self._ordered_tokens |
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def __repr__(self): |
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"""Return representation of tokens object. |
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.. versionadded:: 0.4.0 |
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""" |
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return self.__class__.__name__ + '{}'.format(str(self._tokens)[7:]) |
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def __and__(self, other): |
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"""Return intersection with other tokens. |
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.. versionadded:: 0.4.0 |
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""" |
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return self.get_counter() & other.get_counter() |
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def __add__(self, other): |
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"""Return union with other tokens. |
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.. versionadded:: 0.4.0 |
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""" |
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return self.get_counter() + other.get_counter() |
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def __sub__(self, other): |
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"""Return difference from other tokens. |
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.. versionadded:: 0.4.0 |
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""" |
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return self.get_counter() - other.get_counter() |
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if __name__ == '__main__': |
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import doctest |
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doctest.testmod() |
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