# Natural Language Toolkit: Tokenizer Utilities
#
# Copyright (C) 2001-2021 NLTK Project
# Author: Steven Bird <stevenbird1@gmail.com>
# URL: <http://nltk.sourceforge.net>
# For license information, see LICENSE.TXT

from re import finditer
from xml.sax.saxutils import escape, unescape


def string_span_tokenize(s, sep):
    r"""
    Return the offsets of the tokens in *s*, as a sequence of ``(start, end)``
    tuples, by splitting the string at each occurrence of *sep*.

        >>> from nltk.tokenize.util import string_span_tokenize
        >>> s = '''Good muffins cost $3.88\nin New York.  Please buy me
        ... two of them.\n\nThanks.'''
        >>> list(string_span_tokenize(s, " "))
        [(0, 4), (5, 12), (13, 17), (18, 26), (27, 30), (31, 36), (37, 37),
        (38, 44), (45, 48), (49, 55), (56, 58), (59, 73)]

    :param s: the string to be tokenized
    :type s: str
    :param sep: the token separator
    :type sep: str
    :rtype: iter(tuple(int, int))
    """
    if len(sep) == 0:
        raise ValueError("Token delimiter must not be empty")
    left = 0
    while True:
        try:
            right = s.index(sep, left)
            if right != 0:
                yield left, right
        except ValueError:
            if left != len(s):
                yield left, len(s)
            break

        left = right + len(sep)


def regexp_span_tokenize(s, regexp):
    r"""
    Return the offsets of the tokens in *s*, as a sequence of ``(start, end)``
    tuples, by splitting the string at each successive match of *regexp*.

        >>> from nltk.tokenize.util import regexp_span_tokenize
        >>> s = '''Good muffins cost $3.88\nin New York.  Please buy me
        ... two of them.\n\nThanks.'''
        >>> list(regexp_span_tokenize(s, r'\s'))
        [(0, 4), (5, 12), (13, 17), (18, 23), (24, 26), (27, 30), (31, 36),
        (38, 44), (45, 48), (49, 51), (52, 55), (56, 58), (59, 64), (66, 73)]

    :param s: the string to be tokenized
    :type s: str
    :param regexp: regular expression that matches token separators (must not be empty)
    :type regexp: str
    :rtype: iter(tuple(int, int))
    """
    left = 0
    for m in finditer(regexp, s):
        right, next = m.span()
        if right != left:
            yield left, right
        left = next
    yield left, len(s)


def spans_to_relative(spans):
    r"""
    Return a sequence of relative spans, given a sequence of spans.

        >>> from nltk.tokenize import WhitespaceTokenizer
        >>> from nltk.tokenize.util import spans_to_relative
        >>> s = '''Good muffins cost $3.88\nin New York.  Please buy me
        ... two of them.\n\nThanks.'''
        >>> list(spans_to_relative(WhitespaceTokenizer().span_tokenize(s)))
        [(0, 4), (1, 7), (1, 4), (1, 5), (1, 2), (1, 3), (1, 5), (2, 6),
        (1, 3), (1, 2), (1, 3), (1, 2), (1, 5), (2, 7)]

    :param spans: a sequence of (start, end) offsets of the tokens
    :type spans: iter(tuple(int, int))
    :rtype: iter(tuple(int, int))
    """
    prev = 0
    for left, right in spans:
        yield left - prev, right - left
        prev = right


class CJKChars:
    """
    An object that enumerates the code points of the CJK characters as listed on
    http://en.wikipedia.org/wiki/Basic_Multilingual_Plane#Basic_Multilingual_Plane

    This is a Python port of the CJK code point enumerations of Moses tokenizer:
    https://github.com/moses-smt/mosesdecoder/blob/master/scripts/tokenizer/detokenizer.perl#L309
    """

    # Hangul Jamo (1100–11FF)
    Hangul_Jamo = (4352, 4607)  # (ord(u"\u1100"), ord(u"\u11ff"))

    # CJK Radicals Supplement (2E80–2EFF)
    # Kangxi Radicals (2F00–2FDF)
    # Ideographic Description Characters (2FF0–2FFF)
    # CJK Symbols and Punctuation (3000–303F)
    # Hiragana (3040–309F)
    # Katakana (30A0–30FF)
    # Bopomofo (3100–312F)
    # Hangul Compatibility Jamo (3130–318F)
    # Kanbun (3190–319F)
    # Bopomofo Extended (31A0–31BF)
    # CJK Strokes (31C0–31EF)
    # Katakana Phonetic Extensions (31F0–31FF)
    # Enclosed CJK Letters and Months (3200–32FF)
    # CJK Compatibility (3300–33FF)
    # CJK Unified Ideographs Extension A (3400–4DBF)
    # Yijing Hexagram Symbols (4DC0–4DFF)
    # CJK Unified Ideographs (4E00–9FFF)
    # Yi Syllables (A000–A48F)
    # Yi Radicals (A490–A4CF)
    CJK_Radicals = (11904, 42191)  # (ord(u"\u2e80"), ord(u"\ua4cf"))

    # Phags-pa (A840–A87F)
    Phags_Pa = (43072, 43135)  # (ord(u"\ua840"), ord(u"\ua87f"))

    # Hangul Syllables (AC00–D7AF)
    Hangul_Syllables = (44032, 55215)  # (ord(u"\uAC00"), ord(u"\uD7AF"))

    # CJK Compatibility Ideographs (F900–FAFF)
    CJK_Compatibility_Ideographs = (63744, 64255)  # (ord(u"\uF900"), ord(u"\uFAFF"))

    # CJK Compatibility Forms (FE30–FE4F)
    CJK_Compatibility_Forms = (65072, 65103)  # (ord(u"\uFE30"), ord(u"\uFE4F"))

    # Range U+FF65–FFDC encodes halfwidth forms, of Katakana and Hangul characters
    Katakana_Hangul_Halfwidth = (65381, 65500)  # (ord(u"\uFF65"), ord(u"\uFFDC"))

    # Supplementary Ideographic Plane 20000–2FFFF
    Supplementary_Ideographic_Plane = (
        131072,
        196607,
    )  # (ord(u"\U00020000"), ord(u"\U0002FFFF"))

    ranges = [
        Hangul_Jamo,
        CJK_Radicals,
        Phags_Pa,
        Hangul_Syllables,
        CJK_Compatibility_Ideographs,
        CJK_Compatibility_Forms,
        Katakana_Hangul_Halfwidth,
        Supplementary_Ideographic_Plane,
    ]


def is_cjk(character):
    """
    Python port of Moses' code to check for CJK character.

    >>> CJKChars().ranges
    [(4352, 4607), (11904, 42191), (43072, 43135), (44032, 55215), (63744, 64255), (65072, 65103), (65381, 65500), (131072, 196607)]
    >>> is_cjk(u'\u33fe')
    True
    >>> is_cjk(u'\uFE5F')
    False

    :param character: The character that needs to be checked.
    :type character: char
    :return: bool
    """
    return any(
        [
            start <= ord(character) <= end
            for start, end in [
                (4352, 4607),
                (11904, 42191),
                (43072, 43135),
                (44032, 55215),
                (63744, 64255),
                (65072, 65103),
                (65381, 65500),
                (131072, 196607),
            ]
        ]
    )


def xml_escape(text):
    """
    This function transforms the input text into an "escaped" version suitable
    for well-formed XML formatting.

    Note that the default xml.sax.saxutils.escape() function don't escape
    some characters that Moses does so we have to manually add them to the
    entities dictionary.

        >>> input_str = ''')| & < > ' " ] ['''
        >>> expected_output =  ''')| &amp; &lt; &gt; ' " ] ['''
        >>> escape(input_str) == expected_output
        True
        >>> xml_escape(input_str)
        ')&#124; &amp; &lt; &gt; &apos; &quot; &#93; &#91;'

    :param text: The text that needs to be escaped.
    :type text: str
    :rtype: str
    """
    return escape(
        text,
        entities={
            r"'": r"&apos;",
            r'"': r"&quot;",
            r"|": r"&#124;",
            r"[": r"&#91;",
            r"]": r"&#93;",
        },
    )


def xml_unescape(text):
    """
    This function transforms the "escaped" version suitable
    for well-formed XML formatting into humanly-readable string.

    Note that the default xml.sax.saxutils.unescape() function don't unescape
    some characters that Moses does so we have to manually add them to the
    entities dictionary.

        >>> from xml.sax.saxutils import unescape
        >>> s = ')&#124; &amp; &lt; &gt; &apos; &quot; &#93; &#91;'
        >>> expected = ''')| & < > \' " ] ['''
        >>> xml_unescape(s) == expected
        True

    :param text: The text that needs to be unescaped.
    :type text: str
    :rtype: str
    """
    return unescape(
        text,
        entities={
            r"&apos;": r"'",
            r"&quot;": r'"',
            r"&#124;": r"|",
            r"&#91;": r"[",
            r"&#93;": r"]",
        },
    )


def align_tokens(tokens, sentence):
    """
    This module attempt to find the offsets of the tokens in *s*, as a sequence
    of ``(start, end)`` tuples, given the tokens and also the source string.

        >>> from nltk.tokenize import TreebankWordTokenizer
        >>> from nltk.tokenize.util import align_tokens
        >>> s = str("The plane, bound for St Petersburg, crashed in Egypt's "
        ... "Sinai desert just 23 minutes after take-off from Sharm el-Sheikh "
        ... "on Saturday.")
        >>> tokens = TreebankWordTokenizer().tokenize(s)
        >>> expected = [(0, 3), (4, 9), (9, 10), (11, 16), (17, 20), (21, 23),
        ... (24, 34), (34, 35), (36, 43), (44, 46), (47, 52), (52, 54),
        ... (55, 60), (61, 67), (68, 72), (73, 75), (76, 83), (84, 89),
        ... (90, 98), (99, 103), (104, 109), (110, 119), (120, 122),
        ... (123, 131), (131, 132)]
        >>> output = list(align_tokens(tokens, s))
        >>> len(tokens) == len(expected) == len(output)  # Check that length of tokens and tuples are the same.
        True
        >>> expected == list(align_tokens(tokens, s))  # Check that the output is as expected.
        True
        >>> tokens == [s[start:end] for start, end in output]  # Check that the slices of the string corresponds to the tokens.
        True

    :param tokens: The list of strings that are the result of tokenization
    :type tokens: list(str)
    :param sentence: The original string
    :type sentence: str
    :rtype: list(tuple(int,int))
    """
    point = 0
    offsets = []
    for token in tokens:
        try:
            start = sentence.index(token, point)
        except ValueError as e:
            raise ValueError(f'substring "{token}" not found in "{sentence}"') from e
        point = start + len(token)
        offsets.append((start, point))
    return offsets
