import json
from datetime import datetime as dt
from typing import List

import pandas as pd
from py_jftech import component, parse_date, get_config, to_tuple, autowired

from api import DatumType, Datum, PortfoliosRisk, RoboReportor
from basic.dao import robo_base_datum as rbd


@component
class DefaultDatum(Datum):

    def __init__(self):
        self._config = get_config(__name__)

    @property
    def excludes(self):
        return self._config['excludes'] if 'excludes' in self._config else []

    def format_datum(self, datum):
        if DatumType(datum['type']) is DatumType.FUND:
            return {
                **datum,
                'inceptDate': parse_date(datum['inceptDate'])
            }
        return datum

    def get_datums(self, type: DatumType = None, crncy=None, risk=None, datum_ids=None, ticker=None):
        datum_ids = to_tuple(datum_ids)
        if ticker:
            datums = rbd.get_base_datums(type=type, ticker=ticker)
            datum_ids = tuple(set(datum_ids or []) | {x['id'] for x in datums})
        result = rbd.get_base_datums(type=type, crncy=crncy, risk=risk, datum_ids=datum_ids)
        result = [{**json.loads(x['datas']), 'id': x['id']} for x in result]
        return [self.format_datum(x) for x in result if DatumType(x['type']) is not DatumType.FUND or x['bloombergTicker'] not in self.excludes]

    def get_high_risk_datums(self, risk: PortfoliosRisk):
        risk3 = self.get_datums(type=DatumType.FUND, risk=3)
        if risk is PortfoliosRisk.FT3:
            return risk3
        risk3 = [x for x in risk3 if x['assetType'] in ['STOCK', 'BALANCED', 'COMMODITY']]
        if risk is PortfoliosRisk.FT6:
            return risk3 + self.get_datums(type=DatumType.FUND, risk=4)
        if risk is PortfoliosRisk.FT9:
            return risk3 + self.get_datums(type=DatumType.FUND, risk=(4, 5))
        return None


@component(bean_name='funds-report')
class FundReportor(RoboReportor):

    @autowired
    def __init__(self, datum: Datum = None):
        self._datum = datum

    @property
    def report_name(self) -> str:
        return '基金资料'

    def load_report(self, max_date=dt.today(), min_date=None) -> List[dict]:
        datums = self._datum.get_datums(type=DatumType.FUND)
        datums = pd.DataFrame(datums)
        datums = datums[['id', 'ftTicker', 'bloombergTicker', 'chineseName', 'englishName', 'lipperKey', 'isin', 'currency', 'risk', 'inceptDate', 'category', 'assetType']]
        return datums.to_dict('records')