#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Date: 2021/12/19 13:09
Desc: 东方财富网-数据中心-主力数据-基金持仓
http://data.eastmoney.com/zlsj/2020-06-30-1-2.html
"""

import pandas as pd
import requests


def stock_report_fund_hold(
    symbol: str = "基金持仓", date: str = "20210331"
) -> pd.DataFrame:
    """
    东方财富网-数据中心-主力数据-基金持仓
    http://data.eastmoney.com/zlsj/2020-12-31-1-2.html
    :param symbol: choice of {"基金持仓", "QFII持仓", "社保持仓", "券商持仓", "保险持仓", "信托持仓"}
    :type symbol: str
    :param date: 财报发布日期, xxxx-03-31, xxxx-06-30, xxxx-09-30, xxxx-12-31
    :type date: str
    :return: 基金持仓数据
    :rtype: pandas.DataFrame
    """
    symbol_map = {
        "基金持仓": "1",
        "QFII持仓": "2",
        "社保持仓": "3",
        "券商持仓": "4",
        "保险持仓": "5",
        "信托持仓": "6",
    }
    date = "-".join([date[:4], date[4:6], date[6:]])
    url = "http://data.eastmoney.com/dataapi/zlsj/list"
    params = {
        "date": date,
        "type": symbol_map[symbol],
        "zjc": "0",
        "sortField": "HOULD_NUM",
        "sortDirec": "1",
        "pageNum": "1",
        "pageSize": "500",
        "p": "1",
        "pageNo": "1",
    }
    r = requests.get(url, params=params)
    data_json = r.json()
    total_page = data_json["pages"]
    big_df = pd.DataFrame()
    for page in range(1, total_page + 1):
        params = {
            "date": date,
            "type": symbol_map[symbol],
            "zjc": "0",
            "sortField": "HOULD_NUM",
            "sortDirec": "1",
            "pageNum": page,
            "pageSize": "500",
            "p": page,
            "pageNo": page,
        }
        r = requests.get(url, params=params)
        data_json = r.json()
        temp_df = pd.DataFrame(data_json["data"])
        big_df = pd.concat([big_df, temp_df], ignore_index=True)
    big_df.reset_index(inplace=True)
    big_df["index"] = list(range(1, len(big_df) + 1))
    big_df.columns = [
        "序号",
        "_",
        "股票简称",
        "_",
        "_",
        "持有基金家数",
        "持股总数",
        "持股市值",
        "_",
        "持股变化",
        "持股变动数值",
        "持股变动比例",
        "_",
        "_",
        "_",
        "_",
        "_",
        "_",
        "_",
        "_",
        "股票代码",
        "_",
        "_",
    ]
    big_df = big_df[
        [
            "序号",
            "股票代码",
            "股票简称",
            "持有基金家数",
            "持股总数",
            "持股市值",
            "持股变化",
            "持股变动数值",
            "持股变动比例",
        ]
    ]
    return big_df


def stock_report_fund_hold_detail(
    symbol: str = "008286", date: str = "20220331"
) -> pd.DataFrame:
    """
    东方财富网-数据中心-主力数据-基金持仓-明细
    http://data.eastmoney.com/zlsj/ccjj/2020-12-31-008286.html
    :param symbol: 基金代码
    :type symbol: str
    :param date: 财报发布日期, xxxx-03-31, xxxx-06-30, xxxx-09-30, xxxx-12-31
    :type date: str
    :return: 基金持仓-明细数据
    :rtype: pandas.DataFrame
    """
    date = "-".join([date[:4], date[4:6], date[6:]])
    url = "https://datacenter-web.eastmoney.com/api/data/v1/get"
    params = {
        "sortColumns": "SECURITY_CODE",
        "sortTypes": "-1",
        "pageSize": "500",
        "pageNumber": "1",
        "reportName": "RPT_MAINDATA_MAIN_POSITIONDETAILS",
        "columns": "ALL",
        "quoteColumns": "",
        "filter": f"""(HOLDER_CODE="{symbol}")(REPORT_DATE='{date}')""",
        "source": "WEB",
        "client": "WEB",
    }
    r = requests.get(url, params=params)
    data_json = r.json()
    temp_df = pd.DataFrame(data_json["result"]["data"])
    temp_df.reset_index(inplace=True)
    temp_df["index"] = temp_df.index + 1
    temp_df.columns = [
        "序号",
        "-",
        "股票代码",
        "-",
        "股票简称",
        "_",
        "_",
        "_",
        "_",
        "_",
        "_",
        "_",
        "_",
        "持股数",
        "持股市值",
        "占总股本比例",
        "占流通股本比例",
        "_",
        "_",
    ]
    temp_df = temp_df[
        [
            "序号",
            "股票代码",
            "股票简称",
            "持股数",
            "持股市值",
            "占总股本比例",
            "占流通股本比例",
        ]
    ]
    temp_df["持股数"] = pd.to_numeric(temp_df["持股数"])
    temp_df["持股市值"] = pd.to_numeric(temp_df["持股市值"])
    temp_df["占总股本比例"] = pd.to_numeric(temp_df["占总股本比例"])
    temp_df["占流通股本比例"] = pd.to_numeric(temp_df["占流通股本比例"])
    return temp_df


if __name__ == "__main__":
    stock_report_fund_hold_df = stock_report_fund_hold(
        symbol="基金持仓", date="20200630"
    )
    print(stock_report_fund_hold_df)

    stock_report_fund_hold_df = stock_report_fund_hold(
        symbol="QFII持仓", date="20210331"
    )
    print(stock_report_fund_hold_df)

    stock_report_fund_hold_df = stock_report_fund_hold(
        symbol="社保持仓", date="20210331"
    )
    print(stock_report_fund_hold_df)

    stock_report_fund_hold_df = stock_report_fund_hold(
        symbol="券商持仓", date="20210331"
    )
    print(stock_report_fund_hold_df)

    stock_report_fund_hold_df = stock_report_fund_hold(
        symbol="保险持仓", date="20210331"
    )
    print(stock_report_fund_hold_df)

    stock_report_fund_hold_df = stock_report_fund_hold(
        symbol="信托持仓", date="20210331"
    )
    print(stock_report_fund_hold_df)

    stock_report_fund_hold_detail_df = stock_report_fund_hold_detail(
        symbol="005827", date="20210331"
    )
    print(stock_report_fund_hold_detail_df)