wordfreq/tests/test_general.py

import pytest
from wordfreq import (
    available_languages,
    cB_to_freq,
    lossy_tokenize,
    random_ascii_words,
    random_words,
    tokenize,
    top_n_list,
    word_frequency,
)


def test_freq_examples():
    # Stopwords are most common in the correct language
    assert word_frequency("the", "en") > word_frequency("de", "en")
    assert word_frequency("de", "es") > word_frequency("the", "es")
    # We get word frequencies from the 'large' list when available
    assert word_frequency("infrequency", "en") > 0.0


def test_languages():
    # Make sure we get all the languages when looking for the default
    # 'best' wordlist
    avail = available_languages()
    assert len(avail) >= 34

    # 'small' covers the same languages, but with some different lists
    avail_small = available_languages("small")
    assert len(avail_small) == len(avail)
    assert avail_small != avail

    # 'combined' is the same as 'small'
    avail_old_name = available_languages("combined")
    assert avail_old_name == avail_small

    # 'large' covers fewer languages
    avail_large = available_languages("large")
    assert len(avail_large) >= 14
    assert len(avail) > len(avail_large)

    # Look up the digit '2' in the main word list for each language
    for lang in avail:
        assert word_frequency("2", lang) > 0

        # Make up a weirdly verbose language code and make sure
        # we still get it
        new_lang_code = "%s-001-x-fake-ext" % lang.upper()
        assert word_frequency("2", new_lang_code) > 0


def test_minimums():
    assert word_frequency("esquivalience", "en") == 0
    assert word_frequency("esquivalience", "en", minimum=1e-6) == 1e-6
    assert word_frequency("the", "en", minimum=1) == 1


def test_most_common_words():
    # If something causes the most common words in well-supported languages to
    # change, we should know.

    def get_most_common(lang):
        """
        Return the single most common word in the language.
        """
        return top_n_list(lang, 1)[0]

    assert get_most_common("ar") == "في"
    assert get_most_common("bg") == "на"
    assert get_most_common("bn") == "না"
    assert get_most_common("ca") == "de"
    assert get_most_common("cs") == "a"
    assert get_most_common("da") == "i"
    assert get_most_common("el") == "και"
    assert get_most_common("de") == "die"
    assert get_most_common("en") == "the"
    assert get_most_common("es") == "de"
    assert get_most_common("fi") == "ja"
    assert get_most_common("fil") == "sa"
    assert get_most_common("fr") == "de"
    assert get_most_common("he") == "את"
    assert get_most_common("hi") == "के"
    assert get_most_common("hu") == "a"
    assert get_most_common("id") == "yang"
    assert get_most_common("is") == "og"
    assert get_most_common("it") == "di"
    assert get_most_common("ja") == "の"
    assert get_most_common("ko") == "이"
    assert get_most_common("lt") == "ir"
    assert get_most_common("lv") == "un"
    assert get_most_common("mk") == "на"
    assert get_most_common("ms") == "yang"
    assert get_most_common("nb") == "i"
    assert get_most_common("nl") == "de"
    assert get_most_common("pl") == "w"
    assert get_most_common("pt") == "de"
    assert get_most_common("ro") == "de"
    assert get_most_common("ru") == "в"
    assert get_most_common("sh") == "je"
    assert get_most_common("sk") == "a"
    assert get_most_common("sl") == "je"
    assert get_most_common("sv") == "är"
    assert get_most_common("ta") == "ஒரு"
    assert get_most_common("tr") == "ve"
    assert get_most_common("uk") == "в"
    assert get_most_common("ur") == "کے"
    assert get_most_common("vi") == "là"
    assert get_most_common("zh") == "的"


def test_language_matching():
    freq = word_frequency("的", "zh")
    assert word_frequency("的", "zh-TW") == freq
    assert word_frequency("的", "zh-CN") == freq
    assert word_frequency("的", "zh-Hant") == freq
    assert word_frequency("的", "zh-Hans") == freq
    assert word_frequency("的", "yue-CN") == freq
    assert word_frequency("的", "cmn") == freq


def test_cB_conversion():
    assert cB_to_freq(0) == 1.0
    assert cB_to_freq(-100) == pytest.approx(0.1)
    assert cB_to_freq(-600) == pytest.approx(1e-6)


def test_failed_cB_conversion():
    with pytest.raises(ValueError):
        cB_to_freq(1)


def test_tokenization():
    # We preserve apostrophes within words, so "can't" is a single word in the
    # data
    assert tokenize("I don't split at apostrophes, you see.", "en") == [
        "i",
        "don't",
        "split",
        "at",
        "apostrophes",
        "you",
        "see",
    ]

    assert tokenize("I don't split at apostrophes, you see.", "en", include_punctuation=True) == [
        "i",
        "don't",
        "split",
        "at",
        "apostrophes",
        ",",
        "you",
        "see",
        ".",
    ]

    # Certain punctuation does not inherently split a word.
    assert tokenize("Anything is possible at zombo.com", "en") == [
        "anything",
        "is",
        "possible",
        "at",
        "zombo.com",
    ]

    # Splits occur after symbols, and at splitting punctuation such as hyphens.
    assert tokenize("😂test", "en") == ["😂", "test"]
    assert tokenize("flip-flop", "en") == ["flip", "flop"]
    assert tokenize("this text has... punctuation :)", "en", include_punctuation=True) == [
        "this",
        "text",
        "has",
        "...",
        "punctuation",
        ":)",
    ]

    # Multi-codepoint emoji sequences such as 'medium-skinned woman with headscarf'
    # and 'David Bowie' stay together, because our Unicode segmentation algorithm
    # is up to date
    assert tokenize("emoji test 🧕🏽", "en") == ["emoji", "test", "🧕🏽"]
    assert tokenize("👨‍🎤 Planet Earth is blue, and there's nothing I can do 🌎🚀", "en") == [
        "👨‍🎤",
        "planet",
        "earth",
        "is",
        "blue",
        "and",
        "there's",
        "nothing",
        "i",
        "can",
        "do",
        "🌎",
        "🚀",
    ]

    # Water wave, surfer, flag of California (indicates ridiculously complete support
    # for Unicode 10 and Emoji 5.0)
    assert tokenize("Surf's up 🌊🏄🏴󠁵󠁳󠁣󠁡󠁿'", "en") == ["surf's", "up", "🌊", "🏄", "🏴󠁵󠁳󠁣󠁡󠁿"]


def test_casefolding():
    assert tokenize("WEISS", "de") == ["weiss"]
    assert tokenize("weiß", "de") == ["weiss"]
    assert tokenize("İstanbul", "tr") == ["istanbul"]
    assert tokenize("SIKISINCA", "tr") == ["sıkısınca"]


def test_normalization():
    assert tokenize('"715 - CRΣΣKS" by Bon Iver', "en") == [
        "715",
        "crσσks",
        "by",
        "bon",
        "iver",
    ]
    assert lossy_tokenize('"715 - CRΣΣKS" by Bon Iver', "en") == [
        "715",
        "crσσks",
        "by",
        "bon",
        "iver",
    ]


def test_uncurl_quotes():
    assert lossy_tokenize("let’s", "en") == ["let's"]
    assert word_frequency("let’s", "en") == word_frequency("let's", "en")


def test_phrase_freq():
    ff = word_frequency("flip-flop", "en")
    assert ff > 0
    phrase_freq = 1.0 / word_frequency("flip", "en") + 1.0 / word_frequency("flop", "en")
    assert 1.0 / ff == pytest.approx(phrase_freq, rel=0.01)


def test_not_really_random():
    # If your xkcd-style password comes out like this, maybe you shouldn't
    # use it
    assert random_words(nwords=4, lang="en", bits_per_word=0) == "the the the the"

    # This not only tests random_ascii_words, it makes sure we didn't end
    # up with 'eos' as a very common Japanese word
    assert random_ascii_words(nwords=4, lang="ja", bits_per_word=0) == "1 1 1 1"


def test_not_enough_ascii():
    with pytest.raises(ValueError):
        random_ascii_words(lang="zh", bits_per_word=16)


def test_arabic():
    # Remove tatweels
    assert tokenize("متــــــــعب", "ar") == ["متعب"]

    # Remove combining marks
    assert tokenize("حَرَكَات", "ar") == ["حركات"]

    # An Arabic ligature that is affected by NFKC normalization
    assert tokenize("\ufefb", "ar") == ["\u0644\u0627"]


def test_ideographic_fallback():
    # Try tokenizing Chinese text as English -- it should remain stuck together.
    #
    # More complex examples like this, involving the multiple scripts of Japanese,
    # are in test_japanese.py.
    assert tokenize("中国文字", "en") == ["中国文字"]


def test_other_languages():
    # Test that we leave Thai letters stuck together. If we had better Thai support,
    # we would actually split this into a three-word phrase.
    assert tokenize("การเล่นดนตรี", "th") == ["การเล่นดนตรี"]
    assert tokenize('"การเล่นดนตรี" means "playing music"', "en") == [
        "การเล่นดนตรี",
        "means",
        "playing",
        "music",
    ]

    # Test Khmer, a script similar to Thai
    assert tokenize("សូមស្វាគមន៍", "km") == ["សូមស្វាគមន៍"]

    # Test Hindi -- tokens split where there are spaces, and not where there aren't
    assert tokenize("हिन्दी विक्षनरी", "hi") == ["हिन्दी", "विक्षनरी"]

    # Remove vowel points in Hebrew
    assert tokenize("דֻּגְמָה", "he") == ["דגמה"]

    # Deal with commas, cedillas, and I's in Turkish
    assert tokenize("kișinin", "tr") == ["kişinin"]
    assert tokenize("KİȘİNİN", "tr") == ["kişinin"]

    # Deal with cedillas that should be commas-below in Romanian
    assert tokenize("acelaşi", "ro") == ["același"]
    assert tokenize("ACELAŞI", "ro") == ["același"]