Python yahoo_finance.Share方法代码示例

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def getStockData(theTicker, startDate):
    stock = Share(theTicker)
    print("Getting Data for ... " + theTicker)
    now = datetime.now()
    DateNow = str(now.year) + "-" + str(now.month) + "-" + str(now.day)
    data = stock.get_historical(startDate, DateNow)
    stockData = []
    for d in data:
        tmp = []
        volume = int(d['Volume'])
        adjclose = float(d['Adj_Close'])
        high = float(d['High'])
        low = float(d['Low'])
        close = float(d['Close'])
        date = d['Date']
        open = float(d['Open'])
        tmp.append(date)
        tmp.append(open)
        tmp.append(high)
        tmp.append(low)
        tmp.append(close)
        tmp.append(adjclose)
        tmp.append(volume)
        stockData.append(tmp)
    return stockData 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def stock_Prices():
    # exit if the output already existed
    # if os.path.isfile('./input/stockPrices.json'):
    #     sys.exit("Prices data already existed!")

    priceSet = {}
    fin = open('./input/tickerList.csv')
    for num, line in enumerate(fin):
        line = line.strip().split(',')
        ticker, name, exchange, MarketCap = line
        if 1:
            print(num, ticker)
            yahoo = Share(ticker)
            time.sleep(np.random.poisson(3))
            prices = yahoo.get_historical('2005-01-01', '2020-01-01')
            priceDt = {}
            for i in range(len(prices)):
                date = ''.join(prices[i]['Date'].split('-'))
                priceDt[date] = round(log(float(prices[i]['Close']) / float(prices[i]['Open'])), 6)
            priceSet[ticker] = priceDt
        #except:
            #continue

    with open('./input/stockPrices.json', 'w') as outfile:
        json.dump(priceSet, outfile, indent=4) 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def get_stock_info_and_historical_data(symbol):
    """Retrieve stock info and historical data for `symbol`

    Leverages yahoo-finance for Python
    https://github.com/lukaszbanasiak/yahoo-finance
    """
    share = yahoo_finance.Share(symbol)
    info = share.get_info()
    start_date = info['start']
    end_date = info['end']
    historical = share.get_historical(start_date, end_date)
    data = {
        'info' : info,
        'historical' : historical,
    }
    return data 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def get_quote(self, session, stock, data=None):
        update_time = pd.Timestamp(datetime.datetime.now()) - pd.DateOffset(minutes=15)
        if stock is None or not hasattr(stock, 'quotes') or not hasattr(stock, 'symbol'):
            return None
        seconds = self.seconds_until_market_open()
        quote = self.get_quote_latest(session, stock)

        market_closed = (seconds > 15*60)
        if quote is None \
                or (not market_closed and quote.date_inserted <= update_time)\
                or (market_closed and quote.date_inserted.minute < 30 and quote.date_inserted.hour == 13):
            if data is None:
                data = get_stock_data(Share(stock.symbol), field_map)
            quote = Quote(**{k: v
                             for k, v in data.items()
                             if k in quote_keys})
            logger.info("UPDATED QUOTE: {}".format(quote))
            stock.quotes.append(quote)

        else:
            logging.info("EXISTING QUOTE: {}".format(quote))

        return quote 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def getReturns(stocks = 'MSFT,AAPL,NFLX,JPM,UVXY,RSX,TBT', period_days = 100, end = '2016-12-09'):
    stocks = stocks.split(",")
    index = 'SPY'
    stocks.append(index)
    if end is None:
        end = datetime.today().strftime("%Y-%m-%d")
    start = (datetime.today() - timedelta(period_days)).strftime("%Y-%m-%d")
        
    i = 0
    w= pd.DataFrame()
    t = []
    for s in stocks:
        z = Share(s)
        px = pd.DataFrame(z.get_historical(start,end))[['Close','Date']]
        px['Close']=px['Close'].astype(float)
        px.index = px['Date']
        del px['Date']
        px.columns = [s]
        t.append(px)
    w = pd.concat(t,axis=1, join='inner')
    w = w.sort_index().pct_change()  #returns => w.cov() covariance matrix of returns
    #calculate betas
    betas = []
    for s in stocks:
        if s != index:
            col = np.column_stack((w[s],w[index]))
            b = np.cov(col)/np.var(w[index])
            betas.append(b)  
    stocks.remove(index)
    del w[index]
    returns = w
    return returns,stocks,np.round(betas,4) 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def get_stock_price(symbol):
    """Retrieve the latest price for `symbol` representing stock
    """
    share = yahoo_finance.Share(symbol)
    price = share.get_price()
    return price 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def _add_stock(self, session, name, data=None):
        if data is None:
            try:
                data = get_stock_data(Share(name), field_map)
            except:
                return None

        stock = Stock(**{k: v for k, v in data.items() if k in stock_keys})
        try:
            session.add(stock)
        except:
            pass
        return data 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def update_historical(self, session, stock, start_date, end_date):
        share = Share(stock.symbol)
        try:
            data = get_stock_data_historical(share, start_date, end_date)
        except YQLResponseMalformedError as e:
            logger.error(e)
            return None
        matching_quotes = session.query(Quote).filter(and_(Quote.stock_id == stock.id,
                                                           Quote.date_last_traded >= pd.Timestamp(start_date),
                                                           Quote.date_last_traded <= pd.Timestamp(end_date)))\
                                 .order_by(Quote.date_inserted.asc())
        dates = [pd.Timestamp(q.date_last_traded).date() for q in matching_quotes.all()
                 if pd.Timestamp(q.date_last_traded).hour > 13]

        quotes = []
        for record in data:
            try:
                if record[Quote.date_last_traded.name].date() not in dates:
                    quote = Quote(**{k: v
                                     for k, v in record.items()
                                     if k in quote_keys})
                    quote.symbol_name = stock.symbol_name
                    quote.stock_exchange = stock.stock_exchange
                    quote.trade_currency = stock.trade_currency
                    quotes.append(quote)
                    stock.quotes.append(quote)
            except (KeyError, ValueError) as e:
                logger.error("Error parsing historical quote - {} - {}".format(e, record))
        [session.add(q) for q in quotes]
        return quotes 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def generate_stock_updates(file_path=None):
    if file_path is None:
        file_path = 'C:/Users/Zeke/Google Drive/Documents/Financial/td_ameritrade/'\
                    'Watchlist_Uranium_2017-02-18.xlsx'
    df = read_excel(file_path)

    new_data = []
    for i in range(df.index.size):
        row = df.iloc[i]
        share = Share(row['Symbol'])
        new_data.append(share.__dict__.get('data_set', {}))

    path_out = os.path.splitext(file_path)[0] + '-updated.csv'
    new_df = DataFrame(new_data, index=range(len(new_data)))
    new_df.to_csv(path_out) 

# 需要导入模块: import yahoo_finance [as 别名]
# 或者: from yahoo_finance import Share [as 别名]
def get_quotes(self):
        self.debug("getting quotes")
        try:
            quotes = {}
            for i in self.assets:
                yahoo = Share(i)
                quotes[i] = {
                    "source": "yahoo",
                    "last": float(yahoo.get_price())
                }
            return quotes
        except OSError:
            self.error("Network Error")