wordfreq/tests/test_transliteration.py

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