from csv import reader
from math import floor
import re
from collections import Counter
import numpy as np


def print_vacancies_by_salaries(list_vacancies: list, is_high_salary: bool):
    list_vacancies = sorted(list_vacancies,
                            key=lambda x: x['avg_salary'],
                            reverse=is_high_salary)
    print('Самые высокие зарплаты:' if is_high_salary else 'Самые низкие зарплаты:')
    counter = 0
    for index, value in enumerate(list_vacancies):
        if value['salary_currency'] != 'RUR':
            continue
        if counter == 10:
            break
        counter += 1
        print(
            f'    {counter}) {value["name"]} в компании \"{value["employer_name"]}\" - {value["avg_salary"]} '
            f'{get_ruble_suffix(value["avg_salary"])} (г. {value["area_name"]})')
    print()


def get_vacancies_suffix(count: int) -> str:
    if 11 <= count % 100 <= 19:
        return "вакансий"
    elif count % 10 == 0 or 5 <= count % 10 <= 9:
        return "вакансий"
    elif 2 <= count % 10 <= 4:
        return "вакансии"
    else:
        return "вакансия"


def get_times_suffix(count: int) -> str:
    if 11 <= count % 100 <= 19:
        return "раз"
    elif 2 <= count % 10 <= 4:
        return "раза"
    else:
        return "раз"


def get_ruble_suffix(count: int) -> str:
    if count % 10 == 0 or \
            5 <= count % 10 <= 9 or \
            10 <= count % 100 <= 19:
        return 'рублей'
    elif 2 <= count % 10 <= 4:
        return 'рубля'
    else:
        return 'рубль'


def print_top_skills(list_vacancies: list):
    list_with_right_vacancies = list()
    for index, value in enumerate(list_vacancies):
        for second_index, second_value in enumerate(value["key_skills"]):
            list_with_right_vacancies.append(second_value.strip())
    counter = Counter(list_with_right_vacancies).most_common()
    print(f'Из {len(dict(counter))} скиллов, самыми популярными являются:')
    dict_with_right_skills, count = dict(counter), 0
    for key, value in dict(dict_with_right_skills).items():
        if count == 10:
            break
        count += 1
        print(f'    {count}) {key} - упоминается {value} {get_times_suffix(value)}')
    print()


def to_dictionary(titles, vacancies_list):
    dictionary = dict()
    for index, headline in enumerate(titles):
        dictionary[headline] = vacancies_list[index]
    dictionary['avg_salary'] = floor((float(dictionary['salary_to']) + float(dictionary['salary_from'])) / 2)
    return dictionary


def print_cities_by_salaries(input_list: list):
    list_vacancies = sorted([vacancy for vacancy in input_list if vacancy['salary_currency'] == 'RUR'],
                            key=lambda x: x["area_name"])
    temporal_list, cities_dictionary, counter = list(), dict(), 0

    for i in range(len(list_vacancies) + 1):
        if i == 0:
            continue
        if i == len(list_vacancies):
            temporal_list.append(float(list_vacancies[i - 1]["avg_salary"]))
            counter += 1
            if counter <= 0:
                cities_dictionary[list_vacancies[i - 1]["area_name"]] = \
                    (list_vacancies[i - 1]["avg_salary"], counter)
            else:
                cities_dictionary[list_vacancies[i - 1]["area_name"]] = \
                    (floor(np.average(temporal_list)), counter)
            temporal_list, counter = list(), 0
        else:
            if i == len(list_vacancies) - 1:
                if counter <= 0:
                    cities_dictionary[list_vacancies[i - 1]["area_name"]] = \
                        (list_vacancies[i - 1]["avg_salary"], counter)
                else:
                    cities_dictionary[list_vacancies[i - 1]["area_name"]] = \
                        (floor(np.average(temporal_list)), counter)
                temporal_list, counter = list(), 0
            if list_vacancies[i - 1]["area_name"] != list_vacancies[i]["area_name"]:
                temporal_list.append(float(list_vacancies[i - 1]["avg_salary"]))
                counter += 1
                if counter > 0:
                    cities_dictionary[list_vacancies[i - 1]["area_name"]] = \
                        (floor(np.average(temporal_list)), counter)
                else:
                    cities_dictionary[list_vacancies[i - 1]["area_name"]] = \
                        (list_vacancies[i - 1]["avg_salary"], counter)
                temporal_list, counter = list(), 0
            else:
                temporal_list.append(float(list_vacancies[i - 1]["avg_salary"]))
                counter += 1

    big_cities_dictionary = dict()
    for key, value in cities_dictionary.items():
        if value[1] * 100 / len(list_vacancies) >= 0.9:
            big_cities_dictionary[key] = value

    sorted_tuple = sorted(big_cities_dictionary.items(),
                          key=lambda x: (x[1][0], x[0]),
                          reverse=True)

    for index, value in enumerate(sorted_tuple):
        try:
            if sorted_tuple[index - 1][1][0] == sorted_tuple[index][1][0]:
                temp1, temp2 = sorted_tuple[index - 1], sorted_tuple[index]
                sorted_tuple[index - 1] = temp2
                sorted_tuple[index] = temp1
        except:
            pass

    print(f'Из {len(cities_dictionary)} городов, самые высокие средние ЗП:')
    index = 0
    for key, value in sorted_tuple:
        if index >= 10:
            break
        print(f'    {index + 1}) {key} - средняя зарплата {value[0]} {get_ruble_suffix(value[0])} '
              f'({value[1]} {get_vacancies_suffix(value[1])})')
        index += 1
    print()


def make_final_list_with_dictionaries(csv_file):
    with open(csv_file, encoding='utf-8-sig') as f:
        csv_reader = reader(f, delimiter=',')
        all_vacancies_list, headline = list(), next(csv_reader)
        html_tags = re.compile('<.*?>')
        for current_vacancy in csv_reader:
            if current_vacancy[headline.index('salary_currency')] != 'RUR':
                continue
            try:
                current_vacancy.remove('')
            except ValueError:
                pass
            for i in range(len(current_vacancy)):
                if i == headline.index('key_skills'):
                    current_vacancy[i] = current_vacancy[i].strip()
                    current_vacancy[i] = re.split("\n|\n\r", current_vacancy[i])
                else:
                    current_vacancy[i] = re.sub(html_tags, '', current_vacancy[i]).strip()
                    current_vacancy[i] = ' '.join(current_vacancy[i].split())

            if len(current_vacancy) == len(headline):
                all_vacancies_list.append(to_dictionary(headline, current_vacancy))

    print_vacancies_by_salaries(all_vacancies_list, True)
    print_vacancies_by_salaries(all_vacancies_list, False)
    print_top_skills(list_vacancies=all_vacancies_list)
    print_cities_by_salaries(input_list=all_vacancies_list)


make_final_list_with_dictionaries(input())