How to use the qstrader.price_parser.PriceParser.parse function in qstrader

def setUp(self):
        self.position = Position(
            "SLD", "PG", 100,
            PriceParser.parse(77.69), PriceParser.parse(1.00),
            PriceParser.parse(77.68), PriceParser.parse(77.70)
        )

def run(config, testing, tickers, filename):

    # Benchmark ticker
    benchmark = 'SP500TR'

    # Set up variables needed for backtest
    title = [
        'Moving Average Crossover Example',
        __file__,
        ','.join(tickers) + ': 100x400'
    ]
    events_queue = queue.Queue()
    csv_dir = config.CSV_DATA_DIR
    initial_equity = PriceParser.parse(500000.00)

    # Use Yahoo Daily Price Handler
    price_handler = YahooDailyCsvBarPriceHandler(
        csv_dir, events_queue, tickers
    )

    # Use the MAC Strategy
    strategy = MovingAverageCrossStrategy(tickers, events_queue)

    # Use an example Position Sizer,
    position_sizer = FixedPositionSizer()

    # Use an example Risk Manager,
    risk_manager = ExampleRiskManager()

    # Use the default Portfolio Handler

"SLD", "AMZN", 200,
            PriceParser.parse(565.59), PriceParser.parse(1.00)
        )
        # Multiple transactions bundled into one (in IB)
        # Sell 300 GOOG from the portfolio
        self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.92), PriceParser.parse(1.00)
        )
        self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.90), PriceParser.parse(0.00)
        )
        self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.92), PriceParser.parse(0.50)
        )
        # Finally, sell the remaining GOOG 100 shares
        self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.78), PriceParser.parse(1.00)
        )

        # The figures below are derived from Interactive Brokers
        # demo account using the above trades with prices provided
        # by their demo feed.
        self.assertEqual(len(self.portfolio.positions), 0)
        self.assertEqual(len(self.portfolio.closed_positions), 2)
        self.assertEqual(PriceParser.display(self.portfolio.cur_cash), 499100.50)
        self.assertEqual(PriceParser.display(self.portfolio.equity), 499100.50)
        self.assertEqual(PriceParser.display(self.portfolio.unrealised_pnl), 0.00)
        self.assertEqual(PriceParser.display(self.portfolio.realised_pnl), -899.50)

self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.92), PriceParser.parse(1.00)
        )
        self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.90), PriceParser.parse(0.00)
        )
        self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.92), PriceParser.parse(0.50)
        )
        # Finally, sell the remaining GOOG 100 shares
        self.portfolio.transact_position(
            "SLD", "GOOG", 100,
            PriceParser.parse(704.78), PriceParser.parse(1.00)
        )

        # The figures below are derived from Interactive Brokers
        # demo account using the above trades with prices provided
        # by their demo feed.
        self.assertEqual(len(self.portfolio.positions), 0)
        self.assertEqual(len(self.portfolio.closed_positions), 2)
        self.assertEqual(PriceParser.display(self.portfolio.cur_cash), 499100.50)
        self.assertEqual(PriceParser.display(self.portfolio.equity), 499100.50)
        self.assertEqual(PriceParser.display(self.portfolio.unrealised_pnl), 0.00)
        self.assertEqual(PriceParser.display(self.portfolio.realised_pnl), -899.50)

def test_calculating_statistics(self):
        """
        Purchase/sell multiple lots of AMZN, GOOG
        at various prices/commissions to ensure
        the arithmetic in calculating equity, drawdowns
        and sharpe ratio is correct.
        """
        # Create Statistics object
        price_handler = PriceHandlerMock()
        self.portfolio = Portfolio(price_handler, PriceParser.parse(500000.00))

        portfolio_handler = PortfolioHandlerMock(self.portfolio)
        statistics = SimpleStatistics(self.config, portfolio_handler)

        # Check initialization was correct
        self.assertEqual(PriceParser.display(statistics.equity[0]), 500000.00)
        self.assertEqual(PriceParser.display(statistics.drawdowns[0]), 00)
        self.assertEqual(statistics.equity_returns[0], 0.0)

        # Perform transaction and test statistics at this tick
        self.portfolio.transact_position(
            "BOT", "AMZN", 100,
            PriceParser.parse(566.56), PriceParser.parse(1.00)
        )
        t = "2000-01-01 00:00:00"
        statistics.update(t, portfolio_handler)

def _create_event(self, index, period, ticker, row):
        """
        Obtain all elements of the bar from a row of dataframe
        and return a BarEvent
        """
        open_price = PriceParser.parse(row["Open"])
        high_price = PriceParser.parse(row["High"])
        low_price = PriceParser.parse(row["Low"])
        close_price = PriceParser.parse(row["Close"])
        adj_close_price = PriceParser.parse(row["Adj Close"])
        volume = int(row["Volume"])
        bev = BarEvent(
            ticker, index, period, open_price,
            high_price, low_price, close_price,
            volume, adj_close_price
        )
        return bev

def _create_event(self, index, period, ticker, row):
        """
        Obtain all elements of the bar from a row of dataframe
        and return a BarEvent
        """
        open_price = PriceParser.parse(row["Open"])
        high_price = PriceParser.parse(row["High"])
        low_price = PriceParser.parse(row["Low"])
        close_price = PriceParser.parse(row["Close"])
        adj_close_price = PriceParser.parse(row["Adj Close"])
        volume = int(row["Volume"])
        bev = BarEvent(
            ticker, index, period, open_price,
            high_price, low_price, close_price,
            volume, adj_close_price
        )
        return bev

def _create_event(self, index, period, ticker, row):
        """
        Obtain all elements of the bar from a row of dataframe
        and return a BarEvent
        """
        open_price = PriceParser.parse(row["Open"])
        high_price = PriceParser.parse(row["High"])
        low_price = PriceParser.parse(row["Low"])
        close_price = PriceParser.parse(row["Close"])
        adj_close_price = PriceParser.parse(row["Adj Close"])
        volume = int(row["Volume"])
        bev = BarEvent(
            ticker, index, period, open_price,
            high_price, low_price, close_price,
            volume, adj_close_price
        )
        return bev

def _create_event(self, index, ticker, row):
        """
        Obtain all elements of the bar a row of dataframe
        and return a TickEvent
        """
        bid = PriceParser.parse(row["Bid"])
        ask = PriceParser.parse(row["Ask"])
        tev = TickEvent(ticker, index, bid, ask)
        return tev

def subscribe_ticker(self, ticker):
        """
        Subscribes the price handler to a new ticker symbol.
        """
        if ticker not in self.tickers:
            self._open_ticker_price(ticker)
            dft = self.tickers_data[ticker]
            row0 = dft.iloc[0]

            close = PriceParser.parse(row0["Close"])
            adj_close = PriceParser.parse(row0["Adj Close"])

            ticker_prices = {
                "close": close,
                "adj_close": adj_close,
                "timestamp": dft.index[0]
            }
            self.tickers[ticker] = ticker_prices
        else:
            print(
                "Could not subscribe ticker %s "
                "as is already subscribed." % ticker
            )