#!/usr/bin/python
# -*- coding: utf-8 -*-

# импортируем библиотеки
import sys
import getopt
from datetime import datetime
import pandas as pd
from sqlalchemy import create_engine

if __name__ == "__main__":

    #Задаём входные параметры
    unixOptions = "sdt:edt"
    gnuOptions = ["start_dt=", "end_dt="]

    fullCmdArguments = sys.argv
    argumentList = fullCmdArguments[1:] #excluding script name

    try:
        arguments, values = getopt.getopt(argumentList, unixOptions, gnuOptions)
    except getopt.error as err:
        print (str(err))
        sys.exit(2)

    start_dt = ''
    end_dt = ''
    for currentArgument, currentValue in arguments:
        if currentArgument in ("-sdt", "--start_dt"):
            start_dt = currentValue
        elif currentArgument in ("-edt", "--end_dt"):
            end_dt = currentValue

    # Задаём параметры подключения к БД,
    # их можно узнать у администратора БД.
    db_config = {'user': 'my_user',
                 'pwd': '123456',
                 'host': 'localhost',
                 'port': 5432,
                 'db': 'zen'}

    # Формируем строку соединения с БД.
    connection_string = 'postgresql://{}:{}@{}:{}/{}'.format(db_config['user'],
                                    db_config['pwd'],
                                    db_config['host'],
                                    db_config['port'],
                                 db_config['db'])
    # Подключаемся к БД.
    engine = create_engine(connection_string)

    # Формируем sql-запрос.
    query = ''' SELECT event_id, age_segment, event, item_id, item_topic, item_type, source_id, source_topic, source_type,
        TO_TIMESTAMP(ts / 1000) AT TIME ZONE 'Etc/UTC' as dt, user_id
        FROM log_raw
        WHERE TO_TIMESTAMP(ts / 1000) AT TIME ZONE 'Etc/UTC' BETWEEN '{}'::TIMESTAMP AND '{}'::TIMESTAMP
        '''.format(start_dt, end_dt)

    # записываем данные в датафрейм
    raw = pd.io.sql.read_sql(query, con = engine, index_col = 'event_id')

    # округляем до минут
    raw['dt'] = pd.to_datetime(raw['dt']).dt.round('min')

    # создаем агрегирующие таблицы
    dash_engagement = (raw
                        .groupby(['dt','item_topic', 'event', 'age_segment'])
                        .agg({'user_id':'nunique'})
                      )

    dash_visits = (raw
                    .groupby(['item_topic', 'source_topic', 'age_segment', 'dt'])
                    .agg({'user_id':'count'})
                )

    #переименовка колонок для БД
    dash_engagement = dash_engagement.rename(columns = {'user_id': 'unique_users'})
    dash_visits = dash_visits.rename(columns = {'user_id': 'visits'})

    #заполнение пропусков и сброс индекса
    dash_engagement = dash_engagement.fillna(0).reset_index()
    dash_visits = dash_visits.fillna(0).reset_index()

    # удаление ранее записанных данных
    tables = {'dash_engagement':dash_engagement,
              'dash_visits':dash_visits}

    for table_name, table_data in tables.items():
        query = '''
               DELETE FROM {} WHERE dt BETWEEN '{}'::TIMESTAMP
               AND '{}'::TIMESTAMP
               '''.format(table_name, start_dt, end_dt)
        engine.execute(query)

    table_data.to_sql(name=table_name, con=engine, if_exists='append', index=False)
    print('Good!')