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<h1>Source code for nltk.classify.textcat</h1><div class="highlight"><pre>
<span></span><span class="c1"># Natural Language Toolkit: Language ID module using TextCat algorithm</span>
<span class="c1">#</span>
<span class="c1"># Copyright (C) 2001-2021 NLTK Project</span>
<span class="c1"># Author: Avital Pekker <avital.pekker@utoronto.ca></span>
<span class="c1">#</span>
<span class="c1"># URL: <http://nltk.org/></span>
<span class="c1"># For license information, see LICENSE.TXT</span>
<span class="sd">"""</span>
<span class="sd">A module for language identification using the TextCat algorithm.</span>
<span class="sd">An implementation of the text categorization algorithm</span>
<span class="sd">presented in Cavnar, W. B. and J. M. Trenkle,</span>
<span class="sd">"N-Gram-Based Text Categorization".</span>
<span class="sd">The algorithm takes advantage of Zipf's law and uses</span>
<span class="sd">n-gram frequencies to profile languages and text-yet to</span>
<span class="sd">be identified-then compares using a distance measure.</span>
<span class="sd">Language n-grams are provided by the "An Crubadan"</span>
<span class="sd">project. A corpus reader was created separately to read</span>
<span class="sd">those files.</span>
<span class="sd">For details regarding the algorithm, see:</span>
<span class="sd">http://www.let.rug.nl/~vannoord/TextCat/textcat.pdf</span>
<span class="sd">For details about An Crubadan, see:</span>
<span class="sd">http://borel.slu.edu/crubadan/index.html</span>
<span class="sd">"""</span>
<span class="kn">from</span> <span class="nn">sys</span> <span class="kn">import</span> <span class="n">maxsize</span>
<span class="kn">from</span> <span class="nn">nltk.util</span> <span class="kn">import</span> <span class="n">trigrams</span>
<span class="c1"># Note: this is NOT "re" you're likely used to. The regex module</span>
<span class="c1"># is an alternative to the standard re module that supports</span>
<span class="c1"># Unicode codepoint properties with the \p{} syntax.</span>
<span class="c1"># You may have to "pip install regx"</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">regex</span> <span class="k">as</span> <span class="nn">re</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="n">re</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1">######################################################################</span>
<span class="c1">## Language identification using TextCat</span>
<span class="c1">######################################################################</span>
<div class="viewcode-block" id="TextCat"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.TextCat">[docs]</a><span class="k">class</span> <span class="nc">TextCat</span><span class="p">:</span>
<span class="n">_corpus</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">fingerprints</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">_START_CHAR</span> <span class="o">=</span> <span class="s2">"<"</span>
<span class="n">_END_CHAR</span> <span class="o">=</span> <span class="s2">">"</span>
<span class="n">last_distances</span> <span class="o">=</span> <span class="p">{}</span>
<div class="viewcode-block" id="TextCat.__init__"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.TextCat.__init__">[docs]</a> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">re</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">OSError</span><span class="p">(</span>
<span class="s2">"classify.textcat requires the regex module that "</span>
<span class="s2">"supports unicode. Try '$ pip install regex' and "</span>
<span class="s2">"see https://pypi.python.org/pypi/regex for "</span>
<span class="s2">"further details."</span>
<span class="p">)</span>
<span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">crubadan</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_corpus</span> <span class="o">=</span> <span class="n">crubadan</span>
<span class="c1"># Load all language ngrams into cache</span>
<span class="k">for</span> <span class="n">lang</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_corpus</span><span class="o">.</span><span class="n">langs</span><span class="p">():</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_corpus</span><span class="o">.</span><span class="n">lang_freq</span><span class="p">(</span><span class="n">lang</span><span class="p">)</span></div>
<div class="viewcode-block" id="TextCat.remove_punctuation"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.TextCat.remove_punctuation">[docs]</a> <span class="k">def</span> <span class="nf">remove_punctuation</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">text</span><span class="p">):</span>
<span class="sd">"""Get rid of punctuation except apostrophes"""</span>
<span class="k">return</span> <span class="n">re</span><span class="o">.</span><span class="n">sub</span><span class="p">(</span><span class="sa">r</span><span class="s2">"[^\P</span><span class="si">{P}</span><span class="s2">\']+"</span><span class="p">,</span> <span class="s2">""</span><span class="p">,</span> <span class="n">text</span><span class="p">)</span></div>
<div class="viewcode-block" id="TextCat.profile"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.TextCat.profile">[docs]</a> <span class="k">def</span> <span class="nf">profile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">text</span><span class="p">):</span>
<span class="sd">"""Create FreqDist of trigrams within text"""</span>
<span class="kn">from</span> <span class="nn">nltk</span> <span class="kn">import</span> <span class="n">FreqDist</span><span class="p">,</span> <span class="n">word_tokenize</span>
<span class="n">clean_text</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">remove_punctuation</span><span class="p">(</span><span class="n">text</span><span class="p">)</span>
<span class="n">tokens</span> <span class="o">=</span> <span class="n">word_tokenize</span><span class="p">(</span><span class="n">clean_text</span><span class="p">)</span>
<span class="n">fingerprint</span> <span class="o">=</span> <span class="n">FreqDist</span><span class="p">()</span>
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">tokens</span><span class="p">:</span>
<span class="n">token_trigram_tuples</span> <span class="o">=</span> <span class="n">trigrams</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_START_CHAR</span> <span class="o">+</span> <span class="n">t</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">_END_CHAR</span><span class="p">)</span>
<span class="n">token_trigrams</span> <span class="o">=</span> <span class="p">[</span><span class="s2">""</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">tri</span><span class="p">)</span> <span class="k">for</span> <span class="n">tri</span> <span class="ow">in</span> <span class="n">token_trigram_tuples</span><span class="p">]</span>
<span class="k">for</span> <span class="n">cur_trigram</span> <span class="ow">in</span> <span class="n">token_trigrams</span><span class="p">:</span>
<span class="k">if</span> <span class="n">cur_trigram</span> <span class="ow">in</span> <span class="n">fingerprint</span><span class="p">:</span>
<span class="n">fingerprint</span><span class="p">[</span><span class="n">cur_trigram</span><span class="p">]</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">fingerprint</span><span class="p">[</span><span class="n">cur_trigram</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
<span class="k">return</span> <span class="n">fingerprint</span></div>
<div class="viewcode-block" id="TextCat.calc_dist"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.TextCat.calc_dist">[docs]</a> <span class="k">def</span> <span class="nf">calc_dist</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">lang</span><span class="p">,</span> <span class="n">trigram</span><span class="p">,</span> <span class="n">text_profile</span><span class="p">):</span>
<span class="sd">"""Calculate the "out-of-place" measure between the</span>
<span class="sd"> text and language profile for a single trigram"""</span>
<span class="n">lang_fd</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_corpus</span><span class="o">.</span><span class="n">lang_freq</span><span class="p">(</span><span class="n">lang</span><span class="p">)</span>
<span class="n">dist</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">if</span> <span class="n">trigram</span> <span class="ow">in</span> <span class="n">lang_fd</span><span class="p">:</span>
<span class="n">idx_lang_profile</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">lang_fd</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">trigram</span><span class="p">)</span>
<span class="n">idx_text</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">text_profile</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">trigram</span><span class="p">)</span>
<span class="c1"># print(idx_lang_profile, ", ", idx_text)</span>
<span class="n">dist</span> <span class="o">=</span> <span class="nb">abs</span><span class="p">(</span><span class="n">idx_lang_profile</span> <span class="o">-</span> <span class="n">idx_text</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># Arbitrary but should be larger than</span>
<span class="c1"># any possible trigram file length</span>
<span class="c1"># in terms of total lines</span>
<span class="n">dist</span> <span class="o">=</span> <span class="n">maxsize</span>
<span class="k">return</span> <span class="n">dist</span></div>
<div class="viewcode-block" id="TextCat.lang_dists"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.TextCat.lang_dists">[docs]</a> <span class="k">def</span> <span class="nf">lang_dists</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">text</span><span class="p">):</span>
<span class="sd">"""Calculate the "out-of-place" measure between</span>
<span class="sd"> the text and all languages"""</span>
<span class="n">distances</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">profile</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">profile</span><span class="p">(</span><span class="n">text</span><span class="p">)</span>
<span class="c1"># For all the languages</span>
<span class="k">for</span> <span class="n">lang</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_corpus</span><span class="o">.</span><span class="n">_all_lang_freq</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="c1"># Calculate distance metric for every trigram in</span>
<span class="c1"># input text to be identified</span>
<span class="n">lang_dist</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">trigram</span> <span class="ow">in</span> <span class="n">profile</span><span class="p">:</span>
<span class="n">lang_dist</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_dist</span><span class="p">(</span><span class="n">lang</span><span class="p">,</span> <span class="n">trigram</span><span class="p">,</span> <span class="n">profile</span><span class="p">)</span>
<span class="n">distances</span><span class="p">[</span><span class="n">lang</span><span class="p">]</span> <span class="o">=</span> <span class="n">lang_dist</span>
<span class="k">return</span> <span class="n">distances</span></div>
<div class="viewcode-block" id="TextCat.guess_language"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.TextCat.guess_language">[docs]</a> <span class="k">def</span> <span class="nf">guess_language</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">text</span><span class="p">):</span>
<span class="sd">"""Find the language with the min distance</span>
<span class="sd"> to the text and return its ISO 639-3 code"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">last_distances</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">lang_dists</span><span class="p">(</span><span class="n">text</span><span class="p">)</span>
<span class="k">return</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">last_distances</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">last_distances</span><span class="o">.</span><span class="n">get</span><span class="p">)</span></div></div>
<span class="c1">#################################################')</span>
<div class="viewcode-block" id="demo"><a class="viewcode-back" href="../../../api/nltk.classify.textcat.html#nltk.classify.textcat.demo">[docs]</a><span class="k">def</span> <span class="nf">demo</span><span class="p">():</span>
<span class="kn">from</span> <span class="nn">nltk.corpus</span> <span class="kn">import</span> <span class="n">udhr</span>
<span class="n">langs</span> <span class="o">=</span> <span class="p">[</span>
<span class="s2">"Kurdish-UTF8"</span><span class="p">,</span>
<span class="s2">"Abkhaz-UTF8"</span><span class="p">,</span>
<span class="s2">"Farsi_Persian-UTF8"</span><span class="p">,</span>
<span class="s2">"Hindi-UTF8"</span><span class="p">,</span>
<span class="s2">"Hawaiian-UTF8"</span><span class="p">,</span>
<span class="s2">"Russian-UTF8"</span><span class="p">,</span>
<span class="s2">"Vietnamese-UTF8"</span><span class="p">,</span>
<span class="s2">"Serbian_Srpski-UTF8"</span><span class="p">,</span>
<span class="s2">"Esperanto-UTF8"</span><span class="p">,</span>
<span class="p">]</span>
<span class="n">friendly</span> <span class="o">=</span> <span class="p">{</span>
<span class="s2">"kmr"</span><span class="p">:</span> <span class="s2">"Northern Kurdish"</span><span class="p">,</span>
<span class="s2">"abk"</span><span class="p">:</span> <span class="s2">"Abkhazian"</span><span class="p">,</span>
<span class="s2">"pes"</span><span class="p">:</span> <span class="s2">"Iranian Persian"</span><span class="p">,</span>
<span class="s2">"hin"</span><span class="p">:</span> <span class="s2">"Hindi"</span><span class="p">,</span>
<span class="s2">"haw"</span><span class="p">:</span> <span class="s2">"Hawaiian"</span><span class="p">,</span>
<span class="s2">"rus"</span><span class="p">:</span> <span class="s2">"Russian"</span><span class="p">,</span>
<span class="s2">"vie"</span><span class="p">:</span> <span class="s2">"Vietnamese"</span><span class="p">,</span>
<span class="s2">"srp"</span><span class="p">:</span> <span class="s2">"Serbian"</span><span class="p">,</span>
<span class="s2">"epo"</span><span class="p">:</span> <span class="s2">"Esperanto"</span><span class="p">,</span>
<span class="p">}</span>
<span class="n">tc</span> <span class="o">=</span> <span class="n">TextCat</span><span class="p">()</span>
<span class="k">for</span> <span class="n">cur_lang</span> <span class="ow">in</span> <span class="n">langs</span><span class="p">:</span>
<span class="c1"># Get raw data from UDHR corpus</span>
<span class="n">raw_sentences</span> <span class="o">=</span> <span class="n">udhr</span><span class="o">.</span><span class="n">sents</span><span class="p">(</span><span class="n">cur_lang</span><span class="p">)</span>
<span class="n">rows</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">raw_sentences</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span>
<span class="n">cols</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">len</span><span class="p">,</span> <span class="n">raw_sentences</span><span class="p">))</span>
<span class="n">sample</span> <span class="o">=</span> <span class="s2">""</span>
<span class="c1"># Generate a sample text of the language</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">rows</span><span class="p">):</span>
<span class="n">cur_sent</span> <span class="o">=</span> <span class="s2">""</span>
<span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">cols</span><span class="p">[</span><span class="n">i</span><span class="p">]):</span>
<span class="n">cur_sent</span> <span class="o">+=</span> <span class="s2">" "</span> <span class="o">+</span> <span class="n">raw_sentences</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">]</span>
<span class="n">sample</span> <span class="o">+=</span> <span class="n">cur_sent</span>
<span class="c1"># Try to detect what it is</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Language snippet: "</span> <span class="o">+</span> <span class="n">sample</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">140</span><span class="p">]</span> <span class="o">+</span> <span class="s2">"..."</span><span class="p">)</span>
<span class="n">guess</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">guess_language</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Language detection: </span><span class="si">{</span><span class="n">guess</span><span class="si">}</span><span class="s2"> (</span><span class="si">{</span><span class="n">friendly</span><span class="p">[</span><span class="n">guess</span><span class="p">]</span><span class="si">}</span><span class="s2">)"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"#"</span> <span class="o">*</span> <span class="mi">140</span><span class="p">)</span></div>
<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s2">"__main__"</span><span class="p">:</span>
<span class="n">demo</span><span class="p">()</span>
</pre></div>
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Oct 11, 2021
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