24 lines
864 B
Python
24 lines
864 B
Python
import os
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import pandas as pd
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import numpy as np
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from scraper.top100_extractor import programming_crime_list
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from typing import Optional
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DF_HIST_PATH: str = os.path.join(os.path.dirname(__file__), '..', '..', 'Elaborated_Data', 'price_history_data.csv')
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DF_HIST: Optional[pd.DataFrame] = None
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def lazy_load_history():
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global DF_HIST
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if DF_HIST is None:
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DF_HIST = pd.read_csv(DF_HIST_PATH, index_col=0)
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def get_closing_price_hist(tickers: list[str]) -> list[dict]:
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lazy_load_history()
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ticker_series = pd.Series(tickers)
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df = DF_HIST.loc[DF_HIST.symbol.isin(ticker_series), :] \
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.rename(columns={"Closing Price": "price", "symbol": "ticker"}) \
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.reset_index(drop=True)
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df = df.pivot(index='date', columns='ticker', values='price').reset_index(drop=False)
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return df.replace({ np.nan: None }).to_dict('records') |