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62 lines
2.1 KiB
Python
62 lines
2.1 KiB
Python
from wordfreq import tokenize
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from wordfreq.preprocess import preprocess_text
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def test_transliteration():
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# "Well, there's a lot of things you do not understand."
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# (from somewhere in OpenSubtitles
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assert tokenize("Па, има ту много ствари које не схваташ.", "sr") == [
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"pa",
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"ima",
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"tu",
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"mnogo",
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"stvari",
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"koje",
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"ne",
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"shvataš",
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]
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assert tokenize("Pa, ima tu mnogo stvari koje ne shvataš.", "sr") == [
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"pa",
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"ima",
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"tu",
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"mnogo",
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"stvari",
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"koje",
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"ne",
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"shvataš",
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]
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# I don't have examples of complete sentences in Azerbaijani that are
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# naturally in Cyrillic, because it turns out everyone writes Azerbaijani
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# in Latin letters on the Internet, _except_ sometimes for Wiktionary.
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# So here are some individual words.
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# 'library' in Azerbaijani Cyrillic
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assert preprocess_text("китабхана", "az") == "kitabxana"
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assert preprocess_text("КИТАБХАНА", "az") == "kitabxana"
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assert preprocess_text("KİTABXANA", "az") == "kitabxana"
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# 'scream' in Azerbaijani Cyrillic
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assert preprocess_text("бағырты", "az") == "bağırtı"
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assert preprocess_text("БАҒЫРТЫ", "az") == "bağırtı"
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assert preprocess_text("BAĞIRTI", "az") == "bağırtı"
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def test_actually_russian():
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# This looks mostly like Serbian, but was probably actually Russian.
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# In Russian, Google Translate says it means:
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# "a hundred out of a hundred, boys!"
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#
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# We make sure to handle this case so we don't end up with a mixed-script
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# word like "pacanы".
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assert tokenize("сто из ста, пацаны!", "sr") == ["sto", "iz", "sta", "pacany"]
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assert tokenize("культуры", "sr") == ["kul'tury"]
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def test_alternate_codes():
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# Try language codes for Serbo-Croatian that have been split, and now
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# are canonically mapped to Serbian
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assert tokenize("культуры", "sh") == ["kul'tury"]
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assert tokenize("культуры", "hbs") == ["kul'tury"]
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