import os
import pandas as pd
import numpy as np
from scraper.top100_extractor import programming_crime_list
from typing import Optional
from dateutil.parser import isoparse

DF_EPS_PATH: str = os.path.join(os.path.dirname(__file__), '..', '..', 'Elaborated_Data', 'eps_quarterly_bar_chart.csv')

def ticker_quarter_list(df_ticker: pd.Series) -> list[int]:
    dfu = df_ticker.unique()
    months = set([isoparse(date).month for date in dfu])
    return list(sorted(months))


def get_eps(tickers: list[str]) -> list[dict]:
    df = pd.read_csv(DF_EPS_PATH)
    ticker_series = pd.Series(tickers)
    qmap = dict([ \
        [ticker, ticker_quarter_list(df.loc[df.symbol == ticker, 'quarter'])] \
        for ticker in tickers \
    ])

    df = df.loc[df.symbol.isin(ticker_series), :] \
        .rename(columns={"epsActual": "quarterlyEps", "symbol": "ticker"}) \
        .reset_index(drop=True)

    def get_quart(x):
        date = isoparse(x.quarter)
        quarter = qmap[x.ticker].index(date.month) + 1
        return f"{date.year}-Q{quarter}"

    df['quarter'] = df.apply(get_quart, axis=1)
    df = df.pivot(index='quarter', columns='ticker', values='quarterlyEps').reset_index(drop=False)
    return df.replace({ np.nan: None }).to_dict('records')


def get_eps_old(tickers: list[str]) -> list[dict]:
    eps_df = pd.read_csv('Elaborated_Data/eps_quarterly_bar_chart.csv', index_col=[0])

    s_tickers = pd.Series(tickers)
    eps_df = eps_df.loc[eps_df['symbol'].isin(s_tickers), :]

    dates = eps_df['quarter'].to_list()

    for i, date in enumerate(dates):
        eps_df[date] = eps_df['epsActual'].copy().apply(lambda x: int(eval(str(x))[i]))

    eps_df = pd.melt(eps_df, id_vars=['symbol'], value_vars=['quarter'], var_name='quarter').reset_index(drop=True)
    print(eps_df)
    eps_df = eps_df.pivot(index='value', columns='symbol', values='value').reset_index(drop=False)
    exit(1)
    for ticker in tickers:
        filepath = f'Companies_Data/{ticker}_Data/{ticker}earnings.csv'
        eps_quarterly = pd.read_csv(filepath)
        ticker_df = eps_quarterly.loc[eps_quarterly['symbol'] == ticker]
        ticker_df['ticker'] = ticker
        combined_df = combined_df._append(ticker_df)