OpenBB/openbb_terminal/stocks/behavioural_analysis/finnhub_view.py

""" Finnhub View """
__docformat__ = "numpy"

import logging

import os
from typing import Optional, List
import numpy as np
import pandas as pd
import yfinance as yf
from matplotlib import pyplot as plt
from openbb_terminal.stocks.behavioural_analysis import finnhub_model
from openbb_terminal.decorators import log_start_end
from openbb_terminal.config_terminal import theme
from openbb_terminal.config_plot import PLOT_DPI
from openbb_terminal.helper_funcs import (
    export_data,
    plot_autoscale,
    is_valid_axes_count,
)
from openbb_terminal.decorators import check_api_key

logger = logging.getLogger(__name__)


@log_start_end(log=logger)
@check_api_key(["API_FINNHUB_KEY"])
def display_stock_price_headlines_sentiment(
    symbol: str,
    export: str = "",
    external_axes: Optional[List[plt.Axes]] = None,
):
    """Display stock price and headlines sentiment using VADER model over time. [Source: Finnhub]

    Parameters
    ----------
    symbol : str
        Ticker of company
    export: str
        Format to export data
    external_axes : Optional[List[plt.Axes]], optional
        External axes (2 axes are expected in the list), by default None
    """
    sentiment = finnhub_model.get_headlines_sentiment(symbol)

    if not sentiment.empty:
        sentiment_data = [item for sublist in sentiment.values for item in sublist]

        df_stock = yf.download(
            symbol,
            start=min(sentiment.index).to_pydatetime().date(),
            interval="15m",
            prepost=True,
            progress=False,
        )

        if not df_stock.empty:

            # This plot has 2 axes
            if external_axes is None:
                _, axes = plt.subplots(
                    figsize=plot_autoscale(),
                    dpi=PLOT_DPI,
                    nrows=2,
                    ncols=1,
                    sharex=True,
                    gridspec_kw={"height_ratios": [2, 1]},
                )
                (ax1, ax2) = axes
            elif is_valid_axes_count(external_axes, 2):
                (ax1, ax2) = external_axes
            else:
                return

            ax1.set_title(f"Headlines sentiment and {symbol} price")
            for uniquedate in np.unique(df_stock.index.date):
                ax1.plot(
                    df_stock[df_stock.index.date == uniquedate].index,
                    df_stock[df_stock.index.date == uniquedate]["Adj Close"].values,
                    c="#FCED00",
                )

            ax1.set_ylabel("Stock Price")
            theme.style_primary_axis(ax1)
            theme.style_primary_axis(ax2)

            ax2.plot(
                sentiment.index,
                pd.Series(sentiment_data)
                .rolling(window=5, min_periods=1)
                .mean()
                .values,
                c="#FCED00",
            )
            ax2.bar(
                sentiment[sentiment.values >= 0].index,
                [
                    item
                    for sublist in sentiment[sentiment.values >= 0].values
                    for item in sublist
                ],
                color=theme.up_color,
                width=0.01,
            )
            ax2.bar(
                sentiment[sentiment.values < 0].index,
                [
                    item
                    for sublist in sentiment[sentiment.values < 0].values
                    for item in sublist
                ],
                color=theme.down_color,
                width=0.01,
            )
            ax2.yaxis.set_label_position("right")
            ax2.set_ylabel("Headline Sentiment")

            if external_axes is None:
                theme.visualize_output()

            export_data(
                export, os.path.dirname(os.path.abspath(__file__)), "snews", sentiment
            )