import csv
import re
import sys

from collections import (
    Counter,
    defaultdict,
)


LANGUAGE_REGEXP = re.compile(r'\((.+)\)')
COUNTRY_REGEXP = re.compile(r'(\w{2,})/')


def get_country(text):
    found = COUNTRY_REGEXP.search(text)
    return found.group(1) if found else found


def get_email(text):
    return text.rsplit('/', 1)[0]


def get_income(text):
    if text:
        return float(text.rsplit('/', 1)[-1])
    return 0


def get_language(text):
    found = LANGUAGE_REGEXP.search(text)
    return found.group(1) if found else found


def question_1(rows):
    return Counter(map(get_language, rows[0].keys())).most_common(1)


def question_2(rows):
    persons = set()
    for row in rows:
        persons.update(
            {
                get_email(person) for key, person in row.items()
                if person and get_language(key).lower() == 'python'
            }
        )
    return len(persons)


def question_3(rows):
    income_per_language = defaultdict(int)
    for row in rows:
        for key, data in row.items():
            if data:
                income_per_language[get_language(key)] += get_income(data)
    return max(
        (income, language) for language, income in income_per_language.items()
    )[-1]


def question_4(rows):
    cost_per_country = defaultdict(int)
    for row in rows:
        for key, data in row.items():
            if data:
                cost_per_country[get_country(data)] += get_income(data)
    return max(
        (cost, country) for country, cost in cost_per_country.items()
    )[-1]


if __name__ == '__main__':
    with open(sys.argv[1], 'r') as f:
        csv_dict = csv.DictReader(f, delimiter=';')
        rows = list(csv_dict)
    print(f'1) {question_1(rows)}')
    print(f'2) {question_2(rows)}')
    print(f'3) {question_3(rows)}')
    print(f'4) {question_4(rows)}')