How to use the yfinance.Ticker function in yfinance

webbrowser.get().open(url)
        speak(f'Here is what I found for {search_term} on youtube')

    # 7: get stock price
    if there_exists(["price of"]):
        search_term = voice_data.lower().split(" of ")[-1].strip() #strip removes whitespace after/before a term in string
        stocks = {
            "apple":"AAPL",
            "microsoft":"MSFT",
            "facebook":"FB",
            "tesla":"TSLA",
            "bitcoin":"BTC-USD"
        }
        try:
            stock = stocks[search_term]
            stock = yf.Ticker(stock)
            price = stock.info["regularMarketPrice"]

            speak(f'price of {search_term} is {price} {stock.info["currency"]} {person_obj.name}')
        except:
            speak('oops, something went wrong')
    if there_exists(["exit", "quit", "goodbye"]):
        speak("going offline")
        exit()

def get_prices(
        self, market: Market, interval: Interval, data_range: int
    ) -> MarketHistory:
        self._wait_before_call(self._config.get_yfinance_api_timeout())

        ticker = yf.Ticker(self._format_market_id(market.id))
        # TODO check data_range and fetch only necessary data
        data = ticker.history(
            period="max", interval=self._to_yf_interval(interval).value
        )
        # Reverse dataframe to have most recent data at the top
        data = data.iloc[::-1]
        history = MarketHistory(
            market,
            data.index,
            data["High"].values,
            data["Low"].values,
            data["Close"].values,
            data["Volume"].values,
        )
        return history

continue

            predicted_value = predictor.get_prediction(diff)
            ticker = fc.getTickerFromCik(cik)

            # print('cik: ', cik)
            # print('ticker: ', ticker)
            # print('current_date.hour: ', current_date.hour)
            # print('days_since_last_filing: ', days_since_last_filing)
            # print(diff[:100])
            # print('predicted_value: ', predicted_value)

            if predicted_value == 0:

                try:
                    price = yf.Ticker(ticker).info['regularMarketPreviousClose']
                except Exception as e:
                    print(e)
                    continue

                quantity_to_buy = int(1000 / price)
                print(ticker, quantity_to_buy)
                if api.get_asset(ticker).tradable:
                    submitShort(api, ticker, quantity_to_buy)
            print('length: ', len(diff))
        except Exception as e:
            print(e)
            continue

def load(ticker_str):
    ticker_str = ticker_str.upper()
    ticker = yf.Ticker(ticker_str)

    try:
        data = ticker.info
    except ValueError:
        return None

    history = ticker.history(period="1d")
    current_price = history["Close"][0]

    change = current_price - data["previousClose"]
    change_percent = (change / data["previousClose"]) * 100

    pile = urwid.Pile(
        [
            urwid.Text("STOCKI: The CLI Interface for fetching stock market data\n", align="center"),
            urwid.Text(("title", "{} OVERVIEW".format(ticker_str))),

def download_returns(ticker, period="max"):
    if isinstance(period, _pd.DatetimeIndex):
        p = {"start": period[0]}
    else:
        p = {"period": period}
    return _yf.Ticker(ticker).history(**p)['Close'].pct_change()