# -*- coding: utf-8 -*-
#
# Copyright 2017 Mycroft AI Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from difflib import SequenceMatcher

from mycroft.util.lang.parse_en import *
from mycroft.util.lang.parse_pt import *
from mycroft.util.lang.parse_es import *
from mycroft.util.lang.parse_it import *
from mycroft.util.lang.parse_common import *


def fuzzy_match(x, against):
    """Perform a 'fuzzy' comparison between two strings.
    Returns:
        float: match percentage -- 1.0 for perfect match,
               down to 0.0 for no match at all.
    """
    return SequenceMatcher(None, x, against).ratio()


def extractnumber(text, lang="en-us"):
    """Takes in a string and extracts a number.
    Args:
        text (str): the string to extract a number from
        lang (str): the code for the language text is in
    Returns:
        (str): The number extracted or the original text.
    """

    lang_lower = str(lang).lower()
    if lang_lower.startswith("en"):
        # return extractnumber_en(text, remove_articles)
        return extractnumber_en(text)
    elif lang_lower.startswith("pt"):
        return extractnumber_pt(text)
    elif lang_lower.startswith("it"):
        return extractnumber_it(text)

    # TODO: Normalization for other languages
    return text


def extract_datetime(text, anchorDate=None, lang="en-us"):
    """
    Parsing function that extracts date and time information
    from sentences. Parses many of the common ways that humans
    express dates and times. Includes relative dates like "5 days from today".

    Vague terminology are given arbitrary values, like:
        - morning = 8 AM
        - afternoon = 3 PM
        - evening = 7 PM

    If a time isn't supplied, the function defaults to 12 AM

    Args:
        str (string): the text to be normalized
        anchortDate (:obj:`datetime`, optional): the date to be used for
            relative dating (for example, what does "tomorrow" mean?).
            Defaults to the current date
            (acquired with datetime.datetime.now())
        lang (string): the language of the sentence(s)

    Returns:
        [:obj:`datetime`, :obj:`str`]: 'datetime' is the extracted date
            as a datetime object. Times are represented in 24 hour notation.
            'leftover_string' is the original phrase with all date and time
            related keywords stripped out. See examples for further
            clarification

            Returns 'None' if no date was extracted.

    Examples:

        >>> extract_datetime(
        ... "What is the weather like the day after tomorrow?",
        ... datetime(2017, 06, 30, 00, 00)
        ... )
        [datetime.datetime(2017, 7, 2, 0, 0), 'what is weather like']

        >>> extract_datetime(
        ... "Set up an appointment 2 weeks from Sunday at 5 pm",
        ... datetime(2016, 02, 19, 00, 00)
        ... )
        [datetime.datetime(2016, 3, 6, 17, 0), 'set up appointment']
    """

    lang_lower = str(lang).lower()

    if lang_lower.startswith("en"):
        return extract_datetime_en(text, anchorDate)
    elif lang_lower.startswith("pt"):
        return extract_datetime_pt(text, anchorDate)

    return text
# ==============================================================


def normalize(text, lang="en-us", remove_articles=True):
    """Prepare a string for parsing

    This function prepares the given text for parsing by making
    numbers consistent, getting rid of contractions, etc.
    Args:
        text (str): the string to normalize
        lang (str): the code for the language text is in
        remove_articles (bool): whether to remove articles (like 'a', or 'the')
    Returns:
        (str): The normalized string.
    """

    lang_lower = str(lang).lower()
    if lang_lower.startswith("en"):
        return normalize_en(text, remove_articles)
    elif lang_lower.startswith("es"):
        return normalize_es(text, remove_articles)
    elif lang_lower.startswith("pt"):
        return normalize_pt(text, remove_articles)
    elif lang_lower.startswith("it"):
        return normalize_it(text, remove_articles)
    # TODO: Normalization for other languages
    return text


def get_gender(word, input_string="", lang="en-us"):
    '''
    guess gender of word, optionally use raw input text for context
    returns "m" if the word is male, "f" if female, False if unknown
    '''
    if "pt" in lang or "es" in lang:
        # spanish follows same rules
        return get_gender_pt(word, input_string)
    elif "it" in lang:
        return get_gender_it(word, input_string)

    return False