import json
import os

import pandas as pd
from py_jftech import component, parse_date, get_config, to_tuple, get_project_path, transaction

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


@component(bean_name='datum')
class DefaultDatum(Datum):

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

    @property
    def excludes(self):
        excludes = self._config['excludes'] if 'excludes' in self._config else []
        if isinstance(excludes, dict):
            excludes = excludes[RoboExecutor.use_name()] if RoboExecutor.use_name() in excludes else []
        return excludes

    @property
    def change_date(self):
        change = self._config['change'] if 'change' in self._config else {}
        return pd.to_datetime(change['date']) if 'date' in change else None

    @property
    def change_file(self):
        change = self._config['change'] if 'change' in self._config else {}
        if 'file' not in change or change['file'] is None:
            return None
        file_path: str = change['file']
        if file_path.startswith('.'):
            return os.path.abspath(os.path.join(os.path.dirname(__file__), file_path))
        elif file_path.startswith('/'):
            return os.path.abspath(file_path)
        return os.path.abspath(os.path.join(get_project_path(), file_path))

    def format_datum(self, datum):
        if DatumType(datum['type']) is DatumType.FUND:
            return {
                **datum,
                'inceptDate': parse_date(datum.get('inceptDate')) if datum.get('inceptDate') else None
            }
        return datum

    def get_datums(self, type: DatumType = None, crncy=None, risk=None, datum_ids=None, ticker=None, exclude=True):
        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
                not exclude or x['id'] in (datum_ids or []) 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

    @transaction
    def update_change(self, date):
        if self.change_date is not None and self.change_date == pd.to_datetime(date):
            if self.change_file is not None:
                for fund in pd.read_excel(self.change_file).to_dict('records'):
                    db_data = rbd.get_base_datums(ticker=fund['bloombergTicker'])
                    rbd.update_datum(db_data['id'], json.dumps({
                        **json.loads(db_data['datas']),
                        **fund
                    }))
            return True
        return False


@component(bean_name='datum')
class HkDatum(DefaultDatum):
    def get_datums(self, type: DatumType = None, crncy=None, risk=None, datum_ids=None, ticker=None, exclude=True):
        datas = super().get_datums(type, crncy, None, datum_ids, ticker, exclude)
        # 香港基金risk与现有risk有差异，全查出来再筛选
        datas = [d for d in datas if d.get('hk')]
        # 进行值的覆盖操作
        datas = [d.update(d['hk']) or d for d in datas]
        # 进行筛选操作
        datas = [d for d in datas if not risk or d['risk'] == risk]
        return datas