import pandas as pd

from api import Navs, Datum
from basic.dao import robo_exrate as re, robo_fund_navs as rfn
from framework import get_config, component, autowired


@component
class DefaultNavs(Navs):

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

    def get_fund_navs(self, fund_ids=None, min_date=None, max_date=None):
        navs = rfn.get_navs(fund_id=fund_ids, min_date=min_date, max_date=max_date)
        if 'exrate' in self._config:
            navs = pd.DataFrame(navs)
            navs = navs.pivot_table(index='nav_date', columns='fund_id', values='nav_cal')
            for exrate_config in self._config['exrate']:
                exrate = pd.DataFrame(re.get_exrates(ticker=exrate_config['ticker'], min_date=navs.index.min(),
                                                     max_date=navs.index.max()))
                exrate = exrate[['date', 'close']]
                exrate.set_index('date', inplace=True)
                for fund in self._datum.get_fund_datums(crncy=exrate_config['from']):
                    if fund['id'] in navs.columns:
                        navs[fund['id']] = round(navs[fund['id']] * exrate['close'], 4)
            navs = navs.reset_index().melt(id_vars='nav_date', value_name='nav_cal')
            navs.dropna(inplace=True)
            navs = navs[['fund_id', 'nav_date', 'nav_cal']]
            navs.sort_values(by=['fund_id', 'nav_date'], inplace=True)
            navs = navs.to_dict('records')
        return navs