Removing Python dependencies

from unicodedata import category


def find_words(full_text: str) -> list[str]:
    words_list = []
    current_word = ""

    for char in full_text:

        is_unicode_letter: bool = char == "_" or category(char).startswith("L")
        if is_unicode_letter:
            current_word += char
            continue

        word_is_empty: bool = not current_word
        if word_is_empty:
            continue

        words_list.append(current_word)
        current_word = ""

    word_left = bool(current_word)
    if word_left:
        words_list.append(current_word)

    return words_list


def find_autocompletions(
    expected_keywords: list[str], full_text: str, original_word: str
) -> list[str]:
    """Returns a list of autocompletions based on the word"""

    words_in_text: list[str] = find_words(full_text)

    words_after_original_removal = [
        word for word in words_in_text if word != original_word
    ]

    no_usable_words_in_text: bool = not words_after_original_removal
    if no_usable_words_in_text:
        words_after_original_removal = expected_keywords

    relevant_words = [
        word for word in words_after_original_removal if word.startswith(original_word)
    ]

    autocomplete_matches = sorted(
        set(relevant_words), key=(lambda s: (-relevant_words.count(s), -len(s), s))
    )

    return autocomplete_matches


assert find_words("Hello this is a variable_name 用户数量") == [
    "Hello",
    "this",
    "is",
    "a",
    "variable_name",
    "用户数量",
]
assert find_autocompletions([], "Long text!", "te") == ["text"]

from unicodedata import category


def find_words(full_text: str) -> list[str]:
    words_list = []
    current_word = ""

    for char in full_text:

        is_unicode_letter: bool = char == "_" or category(char).startswith("L")
        if is_unicode_letter:
            current_word += char
            continue

        word_is_empty: bool = not current_word
        if word_is_empty:
            continue

        words_list.append(current_word)
        current_word = ""

    word_left = bool(current_word)
    if word_left:
        words_list.append(current_word)

    return words_list


def find_autocompletions(
    expected_keywords: list[str], full_text: str, original_word: str
) -> list[str]:
    """Returns a list of autocompletions based on the word"""

    words_in_text: list[str] = find_words(full_text)

    words_after_original_removal = [
        word for word in words_in_text if word != original_word
    ]

    no_usable_words_in_text: bool = not words_after_original_removal
    if no_usable_words_in_text:
        words_after_original_removal = expected_keywords

    relevant_words = [
        word for word in words_after_original_removal if word.startswith(original_word)
    ]

    autocomplete_matches = sorted(
        set(relevant_words), key=(lambda s: (-relevant_words.count(s), -len(s), s))
    )

    return autocomplete_matches


assert find_words("Hello this is a variable_name 用户数量") == [
    "Hello",
    "this",
    "is",
    "a",
    "variable_name",
    "用户数量",
]
assert find_autocompletions([], "Long text!", "te") == ["text"]