2.3

import csv
import math
import re
from collections import Counter
import numpy


csv_file = input()


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


def print_cities_by_salaries(input_list: list):
    list_vacancies = []
    for vac in input_list:
        if vac['salary_currency'] == 'RUR':
            list_vacancies.append(vac)
    list_vacancies = sorted(list_vacancies, key=lambda x: x["area_name"])
    temp_list = []
    counter = 0
    dict_cicties = {}

    for i in range(len(list_vacancies) + 1):
        if i == 0:
            continue
        if i != len(list_vacancies):
            if i == len(list_vacancies) - 1:
                if counter > 0:
                    dict_cicties[list_vacancies[i - 1]["area_name"]] = (math.floor(numpy.average(temp_list)), counter)
                else:
                    dict_cicties[list_vacancies[i - 1]["area_name"]] = (list_vacancies[i - 1]["avg_salary"], counter)
                temp_list = []
                counter = 0
            if list_vacancies[i - 1]["area_name"] == list_vacancies[i]["area_name"]:
                temp_list.append(float(list_vacancies[i - 1]["avg_salary"]))
                counter += 1
            else:
                temp_list.append(float(list_vacancies[i - 1]["avg_salary"]))
                counter += 1
                if counter > 0:
                    dict_cicties[list_vacancies[i - 1]["area_name"]] = (math.floor(numpy.average(temp_list)), counter)
                else:
                    dict_cicties[list_vacancies[i - 1]["area_name"]] = (list_vacancies[i - 1]["avg_salary"], counter)
                temp_list = []
                counter = 0
        else:
            temp_list.append(float(list_vacancies[i - 1]["avg_salary"]))
            counter += 1
            if counter > 0:
                dict_cicties[list_vacancies[i - 1]["area_name"]] = (math.floor(numpy.average(temp_list)), counter)
            else:
                dict_cicties[list_vacancies[i - 1]["area_name"]] = (list_vacancies[i - 1]["avg_salary"], counter)
            temp_list = []
            counter = 0

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

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

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

    print(f'Из {len(dict_cicties)} 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_dictionary(titles, list_vac):
    dictionary = {}
    for index, title in enumerate(titles):
        dictionary[title] = list_vac[index]
    dictionary['avg_salary'] = math.floor((float(dictionary['salary_to']) + float(dictionary['salary_from'])) / 2)
    return dictionary


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

        if len(vacancy) == len(title):
            vacancies_list.append(make_dictionary(title, vacancy))


print_vacancies_by_salaries(vacancies_list, True)
print_vacancies_by_salaries(vacancies_list, False)
print_top_skills(vacancies_list)
print_cities_by_salaries(vacancies_list)