# -*- coding: utf-8 -*-
from __future__ import division, print_function, unicode_literals
from datetime import datetime
from follower import BaseFollower
from log import logger
from misc import parse_cookies_str
import pandas as pd

class XueQiuFollower(BaseFollower):
    LOGIN_PAGE = "https://www.xueqiu.com"
    LOGIN_API = "https://xueqiu.com/snowman/login"
    TRANSACTION_API = "https://xueqiu.com/cubes/rebalancing/history.json"
    PORTFOLIO_URL = "https://xueqiu.com/p/"
    WEB_REFERER = "https://www.xueqiu.com"

    def __init__(self):
        super().__init__()
        self._adjust_sell = None
        self._users = None

    def login(self, user=None, password=None, **kwargs):
        """
        雪球登陆， 需要设置 cookies
        :param cookies: 雪球登陆需要设置 cookies， 具体见
            https://smalltool.github.io/2016/08/02/cookie/
        :return:
        """
        cookies = kwargs.get("cookies")
        
        if cookies is None:
            raise TypeError(
                "雪球登陆需要设置 cookies， 具体见" "https://smalltool.github.io/2016/08/02/cookie/"
            )
        headers = self._generate_headers()
        self.s.headers.update(headers)

        self.s.get(self.LOGIN_PAGE)

        cookie_dict = parse_cookies_str(cookies)
        self.s.cookies.update(cookie_dict)
        #extract_strategy_name(self, 'ZH1332574')
        logger.info("登录成功")



    def extract_strategy_name(self, strategy_url):
        
        base_url = "https://xueqiu.com/cubes/nav_daily/all.json?cube_symbol={}"
        url = base_url.format(strategy_url)
        rep = self.s.get(url)
        
        info_index = 0
        return rep.json()[info_index]["name"]


    def extract_transactions(self, history):
        
        if history["count"] <= 0:
            return []
        rebalancing_index = 0
        raw_transactions = history["list"][rebalancing_index]["rebalancing_histories"]
        transactions = []
        for transaction in raw_transactions:
            if transaction["price"] is None:
                logger.info("该笔交易无法获取价格，疑似未成交，跳过。交易详情: %s", transaction)
                continue
            transactions.append(transaction)
            

        return transactions

    def create_query_transaction_params(self, strategy):
        params = {"cube_symbol": strategy, "page": 1, "count": 1}
        return params

    # noinspection PyMethodOverriding
    def none_to_zero(self, data):
        if data is None:
            return 0
        return data

    # noinspection PyMethodOverriding
    def project_transactions(self, transactions, assets):
        
        pa = pd.DataFrame(index=[],columns=[])
        for transaction in transactions:
            weight_diff = self.none_to_zero(transaction["weight"]) - self.none_to_zero(
                transaction["prev_weight"]
            )
            #print(33333,weight_diff,assets,transaction["price"])
            initial_amount = abs(weight_diff) / 100 * assets / transaction["price"]

            transaction["datetime"] = datetime.fromtimestamp(
                transaction["created_at"] // 1000
            )

            transaction["stock_code"] = transaction["stock_symbol"].lower()

            transaction["action"] = "buy" if weight_diff > 0 else "sell"

            if str(transaction["stock_code"][2:4])=='11' or str(transaction["stock_code"][2:4])=='12':
                shou=1
            else:
                shou=2
            transaction["amount"] = int(round(initial_amount, -shou))
            
            pa.loc[transaction["stock_code"],"price"]=transaction["price"]
            pa.loc[transaction["stock_code"],"amount"]=transaction["amount"]
            pa.loc[transaction["stock_code"],"datetime"]=transaction["datetime"]
            pa.loc[transaction["stock_code"],"action"]=transaction["action"]
        current_time = datetime.now()
        diff = (current_time - transaction["datetime"]).total_seconds()
        if int(diff)<20:
            return pa
        else:
            return []