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

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


def get_eps_comp(tickers: list[str]) -> list[dict]:
    df = pd.read_csv(DF_EPS_PATH)
    ticker_series = pd.Series(tickers)
    df = df.loc[df['Ticker'].isin(ticker_series), :] \
        .rename(columns={"epsDifferential": "quarterlyDifferential", "Ticker": "ticker"}) \
        .reset_index(drop=True)
    df = df.pivot(index='quarter', columns='ticker', values='quarterlyDifferential').reset_index(drop=False)
    return df.replace({ np.nan: None }).to_dict('records')