from itertools import chain
from csv import reader
from glob import glob
from typing import Iterable, Tuple, Any
from datetime import datetime
from dateutil.parser import parse
import matplotlib.pyplot as plt


class CsvItems:
    __slots__ = 'request_type', 'date', 'response_ms', 'code'

    def __init__(self, request_type: str, date: datetime, response_ms: int, code: int):
        self.request_type = request_type
        self.date = date
        self.response_ms = response_ms
        self.code = code


def read_csvs() -> Iterable[str]:
    for csv_name in glob('./*.csv'):
        with open(csv_name) as csv_file:
            csv_reader = reader(csv_file)
            yield from csv_reader


def parse_csv_items(items: Tuple[Any, ...]) -> CsvItems:
    request_type, date, response_ms, code = items
    date = parse(date)
    response_ms, code = map(int, (response_ms, code))
    return CsvItems(request_type, date, response_ms, code)


def main():
    data = [*map(parse_csv_items, read_csvs())]
    gets = [x for x in data if x.request_type == 'GET']
    posts = [x for x in data if x.request_type == 'POST']
    puts = [x for x in data if x.request_type == 'PUT']
    deletes = [x for x in data if x.request_type == 'DELETE']

    for i, label, data in (
            (0, 'GET', gets),
            (1, 'POST', posts),
            (2, 'PUT', puts),
            (3, 'DELETE', deletes)
    ):

        plt.subplot(4, 2, 2*i + 1)
        plt.hist([x.response_ms for x in data], color='blue')
        plt.title(label)
        plt.xlabel('Response time(ms)')
        plt.yscale('log')
        plt.ylabel('Frequency')

        plt.subplot(4, 2, 2*i + 2)
        plt.hist([x.code for x in data], color='orange')
        plt.title(label)
        plt.xlabel('Http code')
        plt.yscale('log')
        plt.ylabel('Frequency')
    plt.tight_layout(1)
    plt.show()


if __name__ == '__main__':
    main()