import random
import time
import datetime
import pandas as pd
import smtplib
from email.mime.text import MIMEText
from email.utils import formataddr

from core.config import Email


def get_uid():
    return hex(int(time.time() * 10 ** 7) + random.randint(0, 10000))[2:]


# 获取筛选条件的包含关系
def get_bijiao(bijiao):
    if bijiao == '==' or bijiao == 'in' or bijiao == 'like' or bijiao == 'is not null':
        return "IN"
    elif bijiao == '!=' or bijiao == 'not like' or bijiao == 'is null':
        return 'NOT LIKE'


# 判断传入的数据类型
def estimate_data(data_type):
    if data_type == 'int':
        return "Nullable(Int64)"
    elif data_type == 'ip':
        return "Nullable(DateTime('UTC'))"
    else:
        return "Nullable(String)"


# 将字典变成字符串
def dict_to_str(dic):
    c = str()
    b = 0
    for k, v in dic.items():
        b += 1
        if b == 1:
            c += "{\"%s\":\"%s\"," % (k, v)
        elif b != len(dic):
            c += "\"%s\":\"%s\"," % (k, v)
        else:
            c += "\"%s\":\"%s\"}" % (k, v)
    return c


def getEveryDay(begin_date, end_date):
    # 前闭后闭
    date_list = []
    begin_date = datetime.datetime.strptime(begin_date, "%Y-%m-%d")
    end_date = datetime.datetime.strptime(end_date, "%Y-%m-%d")
    while begin_date <= end_date:
        date_str = begin_date.strftime("%Y-%m-%d")
        date_list.append(date_str)
        begin_date += datetime.timedelta(days=1)
    return date_list


# print(getEveryDay('2016-01-01','2017-05-11'))
def Download_xlsx(df, name):
    """
    下载功能
    name为文件名
    """
    from urllib.parse import quote
    import mimetypes
    from utils import DfToStream
    from fastapi.responses import StreamingResponse
    file_name = quote(f'{name}.xlsx')
    mime = mimetypes.guess_type(file_name)[0]
    df_to_stream = DfToStream((df, name))
    with df_to_stream as d:
        export = d.to_stream()
    Download = StreamingResponse(export, media_type=mime, headers={'Content-Disposition': f'filename="{file_name}"'})
    return Download


def jiange_insert(list_date):
    """
    间隔1条插入一条数据插入数据
    :param day: list数据
    :return: list
    """
    i = 1
    while i <= len(list_date):
        list_date.insert(i, '-')
        i += 2
    return list_date


def create_df(resp):
    """
    分布分析外部下载功能的df数据
    """
    columns = resp['label']
    day = list(resp['list'].keys())
    jiange_insert(day)
    date = []
    day_nu = 0
    for i in day:
        if i == '-':
            av = day[day_nu - 1]
            day_date = resp['list'][av]['总体']
        else:
            day_date = resp['list'][i]['总体']
        date_dict = {}
        n = 0
        p = 0
        if i == '-':
            date_dict['事件发生时间'] = '-'
            date_dict['总人数'] = '-'
            for nu in range(len(columns)):
                date_dict[columns[nu]] = day_date['p'][p]
                p += 1
            date.append(date_dict)
        else:
            date_dict['事件发生时间'] = i
            date_dict['总人数'] = day_date['total']
            for nu in range(len(columns)):
                date_dict[columns[nu]] = day_date['n'][n]
                n += 1
            date.append(date_dict)
        day_nu += 1
    columns.insert(0, '总人数')
    columns.insert(0, '事件发生时间')
    df = pd.DataFrame(data=date, columns=columns)
    return df


def create_neidf(resp, columnName):
    """
    分布分析内部下载功能的df数据
    """
    columns = resp['label']
    day = list(resp['list'].keys())
    jiange_insert(day)
    date = []
    day_nu = 0
    for i in day:
        if i == '-':
            av = day[day_nu - 1]
            day_date = resp['list'][av]
        else:
            day_date = resp['list'][i]
        date_dict = {}
        n = 0
        p = 0
        if i == '-':
            date_dict[columnName] = '-'
            date_dict['全部用户数'] = '-'
            for nu in range(len(columns)):
                date_dict[columns[nu]] = day_date['p'][p]
                p += 1
            date.append(date_dict)
        else:
            date_dict[columnName] = i
            date_dict['全部用户数'] = day_date['total']
            for nu in range(len(columns)):
                date_dict[columns[nu]] = day_date['n'][n]
                n += 1
            date.append(date_dict)
        day_nu += 1
    columns.insert(0, '全部用户数')
    columns.insert(0, columnName)
    df = pd.DataFrame(data=date, columns=columns)
    return df


def random_hex():
    """
    生成16位随机数
    :return: 随机数
    """
    result = hex(random.randint(0, 16 ** 16)).replace('0x', '').upper()
    if (len(result) < 16):
        result = '0' * (16 - len(result)) + result
    return result


def get_time(fmt: str = '%Y-%m-%d') -> str:
    '''
    获取当前时间
    '''
    ts = time.time()
    ta = time.localtime(ts)
    t = time.strftime(fmt, ta)
    return t


def import_excel(data, columns, name):
    """
    导出数据到xlsx表里面
    :param data: 需要导出的数据
    :param columns: df的表名  例：['a','b','c']
    :param name: 文件名。例：'随机数'
    :return:
    """
    zh = pd.DataFrame(data, columns=columns)
    zh.to_excel(f'{name}.xlsx', index=False, header=True)


def qujian_time(start_time, end_time):
    """
    把两个时间变成区间
    :param start_time: '2022-07-01 10:00:00'
    :param end_time: '2022-07-01 10:30:00'
    :return: '2022-07-01 10:00:00~10:30:00'
    """
    timess = str(end_time).split(' ')[-1]
    return str(start_time) + '~' + timess


# 发送的文本邮件
def send_str_mail(str_msg, my_user):
    """
    发送的文本邮件
    :param str_msg: 发送的邮件内容
    :param my_user: 接收者的邮箱
    :return: bool
    """
    msg = MIMEText(str_msg, 'plain', 'utf-8')
    msg['From'] = formataddr(["乐谷游戏人事", Email.my_sender])  # 括号里的对应发件人邮箱昵称、发件人邮箱账号
    msg['To'] = formataddr(["FK", my_user])  # 括号里的对应收件人邮箱昵称、收件人邮箱账号
    msg['Subject'] = Email.subject  # 邮件的主题，也可以说是标题

    server = smtplib.SMTP_SSL("smtp.qq.com", 465)  # 发件人邮箱中的SMTP服务器，端口是25
    server.login(Email.my_sender, Email.my_pass)  # 括号中对应的是发件人邮箱账号、邮箱密码
    # server.sendmail(my_sender, [my_user, ], msg.as_string())  # 括号中对应的是发件人邮箱账号、收件人邮箱账号、发送邮件
    server.sendmail(Email.my_sender, [my_user, ], msg.as_string())  # 括号中对应的是发件人邮箱账号、收件人邮箱账号、发送邮件
    server.quit()  # 关闭连接