__copyright__ = "Copyright (C) 2023 Ali Mustapha"
__license__ = "GPL-3.0-or-later"

from unidecode import unidecode
import pandas as od
import regex
import unicodedata
import re
def is_most_common_char(s):
    max_count = len(s) * 0.90  # calculate the maximum count of a single character
    char_count = {}  # create an empty dictionary to store character counts
    for c in s:
        if not unicodedata.name(c, "") or not unicodedata.name(c).startswith('LATIN'):
            return False  # return False if the character is not a Latin character
        char_count[c] = char_count.get(c, 0) + 1  # increment the count of the character
        if char_count[c] > max_count:  # if the count exceeds the maximum count
            return True  # return True
    return False  # return False if no Latin character appears more than MAX_COUNT% of the time

def find_common_item(list_array):
    result_array = [pair[0] for pair in list_array]
    
    m_count = len(list(filter(lambda g: g==0, result_array)))
    f_count = len(list(filter(lambda g: g==1, result_array)))
    u_count = len(list(filter(lambda g: g==2, result_array)))
    if u_count > max(m_count,f_count):
        return 2
    else:
        if m_count > f_count:
            return 0
        elif f_count > m_count:
            return 1
        
        else:
            return 2
        
def is_roman_language(text):
    roman_pattern = r'^\p{Latin}+$'
    match = regex.match(roman_pattern, text, flags=regex.UNICODE)
    return match is not None

def text_to_romanize(text):
    if not is_roman_language(text):
        return unidecode(text)
    else:
        return text
    
def is_alpha(s:str, min_alpha=0.60)->bool:
    if len(s)==0:
        return False
    else:
        alpha_chars=sum(
            map(lambda c: 1 if unicodedata.category(c).startswith("L") or unicodedata.category(c)=="Zs"  else 0,s)
        )
        return alpha_chars/len(s) >=min_alpha
    
def remove_spaces_from_ends(input_string):
    return re.sub(r'^\s+|\s+$', '', input_string)