# coding: utf-8
import re
from difflib import SequenceMatcher

import yaml
from profanityfilter import ProfanityFilter

YAML_FILE = "story/story_data.yaml"


with open("story/censored_words.txt", "r") as f:
    censored_words = [l.replace("\n", "") for l in f.readlines()]

pf = ProfanityFilter(custom_censor_list=censored_words)


def console_print(text, width=75):
    last_newline = 0
    i = 0
    while i < len(text):
        if text[i] == "\n":
            last_newline = 0
        elif last_newline > width and text[i] == " ":
            text = text[:i] + "\n" + text[i:]
            last_newline = 0
        else:
            last_newline += 1
        i += 1
    print(text)


def get_similarity(a, b):
    return SequenceMatcher(None, a, b).ratio()


def get_num_options(num):

    while True:
        choice = input("Enter the number of your choice: ")
        try:
            result = int(choice)
            if result >= 0 and result < num:
                return result
            else:
                print("Error invalid choice. ")
        except ValueError:
            print("Error invalid choice. ")


def player_died(text):
    """
    TODO: Add in more sophisticated NLP, maybe a custom classifier
    trained on hand-labelled data that classifies second-person
    statements as resulting in death or not.
    """
    lower_text = text.lower()
    you_dead_regexps = [
        "you('re| are) (dead|killed|slain|no more|nonexistent)",
        "you (die|pass away|perish|suffocate|drown|bleed out)",
        "you('ve| have) (died|perished|suffocated|drowned|been (killed|slain))",
        "you (\w* )?(yourself )?to death",
        "you (\w* )*(collapse|bleed out|chok(e|ed|ing)|drown|dissolve) (\w* )*and (die(|d)|pass away|cease to exist|(\w* )+killed)",
    ]
    return any(re.search(regexp, lower_text) for regexp in you_dead_regexps)


def player_won(text):
    lower_text = text.lower()
    won_phrases = [
        "you ((\w* )*and |)live happily ever after",
        "you ((\w* )*and |)live (forever|eternally|for eternity)",
        "you ((\w* )*and |)(are|become|turn into) ((a|now) )?(deity|god|immortal)",
        "you ((\w* )*and |)((go|get) (in)?to|arrive (at|in)) (heaven|paradise)",
        "you ((\w* )*and |)celebrate your (victory|triumph)",
        "you ((\w* )*and |)retire",
        "The rest is history...",
    ]
    return any(re.search(regexp, lower_text) for regexp in won_phrases)


def remove_profanity(text):
    return pf.censor(text)


def cut_trailing_quotes(text):
    num_quotes = text.count('"')
    if num_quotes % 2 is 0:
        return text
    else:
        final_ind = text.rfind('"')
        return text[:final_ind]


def split_first_sentence(text):
    first_period = text.find(".")
    first_exclamation = text.find("!")

    if first_exclamation < first_period and first_exclamation > 0:
        split_point = first_exclamation + 1
    elif first_period > 0:
        split_point = first_period + 1
    else:
        split_point = text[0:20]

    return text[0:split_point], text[split_point:]


def cut_trailing_action(text):
    lines = text.split("\n")
    last_line = lines[-1]
    if (
        "you ask" in last_line
        or "You ask" in last_line
        or "you say" in last_line
        or "You say" in last_line
    ) and len(lines) > 1:
        text = "\n".join(lines[0:-1])
    return text


def cut_trailing_sentence(text):
    text = standardize_punctuation(text)
    last_punc = max(text.rfind("."), text.rfind("!"), text.rfind("?"))
    if last_punc <= 0:
        last_punc = len(text) - 1

    et_token = text.find("<")
    if et_token > 0:
        last_punc = min(last_punc, et_token - 1)

    act_token = text.find(">")
    if act_token > 0:
        last_punc = min(last_punc, act_token - 1)

    text = text[:last_punc+1]

    text = cut_trailing_quotes(text)
    text = cut_trailing_action(text)
    return text


def replace_outside_quotes(text, current_word, repl_word):
    text = standardize_punctuation(text)

    reg_expr = re.compile(current_word + '(?=([^"]*"[^"]*")*[^"]*$)')

    output = reg_expr.sub(repl_word, text)
    return output


def is_first_person(text):

    count = 0
    for pair in first_to_second_mappings:
        variations = mapping_variation_pairs(pair)
        for variation in variations:
            reg_expr = re.compile(variation[0] + '(?=([^"]*"[^"]*")*[^"]*$)')
            matches = re.findall(reg_expr, text)
            count += len(matches)

    if count > 3:
        return True
    else:
        return False


def is_second_person(text):
    count = 0
    for pair in second_to_first_mappings:
        variations = mapping_variation_pairs(pair)
        for variation in variations:
            reg_expr = re.compile(variation[0] + '(?=([^"]*"[^"]*")*[^"]*$)')
            matches = re.findall(reg_expr, text)
            count += len(matches)

    if count > 3:
        return True
    else:
        return False


def capitalize(word):
    return word[0].upper() + word[1:]


def mapping_variation_pairs(mapping):
    mapping_list = []
    mapping_list.append((" " + mapping[0] + " ", " " + mapping[1] + " "))
    mapping_list.append(
        (" " + capitalize(mapping[0]) + " ", " " + capitalize(mapping[1]) + " ")
    )

    # Change you it's before a punctuation
    if mapping[0] is "you":
        mapping = ("you", "me")
    mapping_list.append((" " + mapping[0] + ",", " " + mapping[1] + ","))
    mapping_list.append((" " + mapping[0] + "\?", " " + mapping[1] + "\?"))
    mapping_list.append((" " + mapping[0] + "\!", " " + mapping[1] + "\!"))
    mapping_list.append((" " + mapping[0] + "\.", " " + mapping[1] + "."))

    return mapping_list


first_to_second_mappings = [
    ("I'm", "you're"),
    ("Im", "you're"),
    ("Ive", "you've"),
    ("I am", "you are"),
    ("was I", "were you"),
    ("am I", "are you"),
    ("wasn't I", "weren't you"),
    ("I", "you"),
    ("I'd", "you'd"),
    ("i", "you"),
    ("I've", "you've"),
    ("was I", "were you"),
    ("am I", "are you"),
    ("wasn't I", "weren't you"),
    ("I", "you"),
    ("I'd", "you'd"),
    ("i", "you"),
    ("I've", "you've"),
    ("I was", "you were"),
    ("my", "your"),
    ("we", "you"),
    ("we're", "you're"),
    ("mine", "yours"),
    ("me", "you"),
    ("us", "you"),
    ("our", "your"),
    ("I'll", "you'll"),
    ("myself", "yourself"),
]

second_to_first_mappings = [
    ("you're", "I'm"),
    ("your", "my"),
    ("you are", "I am"),
    ("you were", "I was"),
    ("are you", "am I"),
    ("you", "I"),
    ("you", "me"),
    ("you'll", "I'll"),
    ("yourself", "myself"),
    ("you've", "I've"),
]


def capitalize_helper(string):
    string_list = list(string)
    string_list[0] = string_list[0].upper()
    return "".join(string_list)


def capitalize_first_letters(text):
    first_letters_regex = re.compile(r"((?<=[\.\?!]\s)(\w+)|(^\w+))")

    def cap(match):
        return capitalize_helper(match.group())

    result = first_letters_regex.sub(cap, text)
    return result


def standardize_punctuation(text):
    text = text.replace("’", "'")
    text = text.replace("`", "'")
    text = text.replace("“", '"')
    text = text.replace("”", '"')
    return text


def first_to_second_person(text):
    text = " " + text
    text = standardize_punctuation(text)
    for pair in first_to_second_mappings:
        variations = mapping_variation_pairs(pair)
        for variation in variations:
            text = replace_outside_quotes(text, variation[0], variation[1])

    return capitalize_first_letters(text[1:])


def second_to_first_person(text):
    text = " " + text
    text = standardize_punctuation(text)
    for pair in second_to_first_mappings:
        variations = mapping_variation_pairs(pair)
        for variation in variations:
            text = replace_outside_quotes(text, variation[0], variation[1])

    return capitalize_first_letters(text[1:])