def import_yahoofinance2():
# import stock_info module from yahoo_fin
from yahoo_fin import stock_info as si
# get live price of Apple
si.get_live_price("aapl")
# or Amazon
si.get_live_price("amzn")
# or any other ticker
si.get_live_price(ticker)
# get quote table back as a data frame
si.get_quote_table("aapl", dict_result = False)
# or get it back as a dictionary (default)
si.get_quote_table("aapl")
si.get_top_crypto()
# get most active stocks on the day
si.get_day_most_active()
# get biggest gainers
si.get_day_gainers()
# get worst performers
si.get_day_losers()
def getTickerData(stocks):
tickerData = {}
for c in stocks:
#td[c]=si.get_quote_table(c, dict_result=False)
price = si.get_quote_table(c)["Quote Price"]
pc = si.get_quote_table(c)["Previous Close"]
pct_ch = "%.2f" % ((price / pc - 1) * 100) + '%'
tickerData[c] = {'price': "{:.0f}".format(price), 'pct_ch': pct_ch}
return tickerData
def indices_v2():
dow_quote = get_quote_table('^dji')
sp_500_quote = get_quote_table('^gspc')
nasdaq_quote = get_quote_table('^ixic')
# russell_2000_quote = get_quote_table('^rut')
# vix = get_quote_table('^vix')
return jsonify({
'dow': _transform_data(dow_quote),
'nasdaq': _transform_data(nasdaq_quote),
'sp500': _transform_data(sp_500_quote),
# 'russell2000': _transform_data(russell_2000_quote),
# 'vix': _transform_data(vix)
}), 200
def get_precos():
acoes = Acao.objects.all()
for acao in acoes:
try:
print(str(acao))
preco = get_quote_table(str(acao))
#print(preco)
p = acao.preco_set.create(preco=preco["Quote Price"])
p.save()
#print("limites")
try:
limite = Perfil.objects.get(pk=acao.id)
except Perfil.DoesNotExist:
limite = False
#print(getattr(limite, "limInf"))
if limite:
lSup = float(getattr(limite, "limSup"))
lInf = float(getattr(limite, "limInf"))
print(str(lInf) + ' \ ' + str(lSup))
if float(preco["Quote Price"]) >= float(lSup):
manda_email("sup", str(acao), lSup, preco["Quote Price"])
if float(preco["Quote Price"]) <= float(lInf):
manda_email("inf", str(acao), lInf, preco["Quote Price"])
else:
print("Limite de {} não adicionado".format(str(acao)))
except Exception as e:
print("Error")
pass
atualizar()
def get_yahoo_quotes():
"""
[
{'52 Week Range': '157.13 - 186.99', 'Ask': '0.00 x 4000', 'Avg. Volume': 8064500.0, 'Beta (5Y Monthly)': 0.09, 'Bid': '0.00 x 1300', "Day's Range": '166.90 - 170.19', 'Expense Ratio (net)': '0.40%', 'Inception Date': '2004-11-18', 'NAV': 166.84, 'Net Assets': '59.26B', 'Open': 167.58, 'PE Ratio (TTM)': 28.63, 'Previous Close': 167.67, 'Quote Price': 170.19000244140625, 'Volume': 10036431.0, 'YTD Daily Total Return': '-6.43%', 'Yield': '0.00%'},
{'52 Week Range': '319.80 - 450.65', 'Ask': '0.00 x 1200', 'Avg. Volume': 61116292.0, 'Beta (5Y Monthly)': 1.0, 'Bid': '0.00 x 3100', "Day's Range": '447.07 - 450.65', 'Expense Ratio (net)': '0.09%', 'Inception Date': '1993-01-22', 'NAV': 439.23, 'Net Assets': '374.03B', 'Open': 447.12, 'PE Ratio (TTM)': 3.12, 'Previous Close': 446.26, 'Quote Price': 450.25, 'Volume': 77235113.0, 'YTD Daily Total Return': '19.94%', 'Yield': '1.30%'},
{'52 Week Range': '133.19 - 167.24', 'Ask': '0.00 x 1100', 'Avg. Volume': 15720817.0, 'Beta (5Y Monthly)': 3.36, 'Bid': '0.00 x 2200', "Day's Range": '148.34 - 149.48', 'Expense Ratio (net)': '0.15%', 'Inception Date': '2002-07-22', 'NAV': 149.23, 'Net Assets': '15.15B', 'Open': 148.57, 'PE Ratio (TTM)': nan, 'Previous Close': 148.45, 'Quote Price': 149.4600067138672, 'Volume': 15384740.0, 'YTD Daily Total Return': '-5.12%', 'Yield': '1.50%'}
]
"""
try:
quotes = []
for quote in ['gld', 'spy', 'tlt', 'tqqq', 'upro', 'tmf']:
quote_table = si.get_quote_table(quote)
quotes.append({
"symbol":
quote,
"previousClose":
quote_table.get('Previous Close'),
"open":
quote_table.get('Open'),
"latestPrice":
quote_table.get('Quote Price'),
"week52Low":
float(quote_table.get('52 Week Range').split(" - ")[0]),
"week52High":
float(quote_table.get('52 Week Range').split(" - ")[1]),
"ytdChange":
quote_table.get('YTD Daily Total Return'),
})
with open('static/quote.json', 'w') as fp:
json.dump(quotes, fp, sort_keys=True, indent=4)
except:
return
def check_stock(stock, row):
print("check_stock->" + stock)
print("will update row->" + str(row))
try:
price = get_live_price(stock)
except:
stock_mx[row][0] = 0
stock_mx[row][1] = 0
return
try:
prev_price = get_quote_table(stock)['Previous Close']
except:
stock_mx[row][0] = 0
stock_mx[row][1] = 0
if price > prev_price:
print(stock + " up")
stock_mx[row][0] = 0
stock_mx[row][1] = 1
return (True)
else:
print(stock + " down")
stock_mx[row][0] = 1
stock_mx[row][1] = 0
return (False)
def queryPrices(symbs, cur, conn):
# query the prices from api and push to database
# symbs : list of ticker symbols
# cur : cursor
# conn : connection
symb_cnt = len(symbs)
new_sks = getPriceSK(cur, conn, symbCount) # pull list of fresh SKs
for indx, tickerSymb in enumerate(symbs):
ticker = tickerSymb.rstrip().replace('.', '')
try:
qt = si.get_quote_table(ticker)
except:
print("[error] Cannot pull quot table for %s." % ticker)
if qt is not None:
pushPrice(
cur, # cursor
conn, # connection
int(newSKs[indx]), # new price SK
ticker, # ticker symbol
str(qt["Quote Price"]).replace(',', ''), # quote price
str(qt["Ask"]).replace(',', '').split(' ', 1)[0], # ask price
str(qt["Bid"]).replace(',', '').split(' ', 1)[0], # bid price
qt["Volume"]) # cumulative day volume
def current_stock_price(stock, value):
''' Takes company's Yahoo Finance ticker and intrinsic value of company
Returns Value per share '''
df = si.get_quote_table(stock)
cmp = df['Quote Price']
market_cap = df['Market Cap']
if market_cap[-1] == 'T':
market_cap = float(market_cap[:-1]) * 10**12 / 10**7
elif market_cap[-1] == 'B':
market_cap = float(market_cap[:-1]) * 10**9 / 10**7
elif market_cap[-1] == 'M':
market_cap = float(market_cap[:-1]) * 10**6 / 10**7
else:
market_cap = float(market_cap)
print('Market Capitalisation (in Crs):', market_cap)
share_out = market_cap / cmp
print('Shares Outstanding (in Crs):', round(share_out, 3))
print('-----------------------------------------------------')
print('CMP : Rs ', round(cmp, 3))
value_per_share = value / share_out
print('Value per share: Rs ', round(value_per_share, 3))
print('-----------------------------------------------------')
if value_per_share <= cmp:
print('The Stock is OVER PRICED')
else:
print('The Stock is UNDER PRICED')
return value_per_share, market_cap, share_out, cmp
def get():
sym = {}
batch_id = 0
batch_size = 1
small_dict = {}
mid_dict = {}
large_dict = {}
while batch_id < len(companies):
sym = companies[batch_id:batch_id + batch_size]
if sym[0]['marketCap'] < 20000000:
small_dict[sym[0]['symbol']] = sym[0]['marketCap']
elif sym[0]['marketCap'] < 100000000 and sym[0]['marketCap'] > 20000000:
mid_dict[sym[0]['symbol']] = sym[0]['marketCap']
else:
large_dict[sym[0]['symbol']] = sym[0]['marketCap']
batch_id = batch_id + batch_size
small_dict = dict(itertools.islice(small_dict.items(), 5))
mid_dict = dict(itertools.islice(mid_dict.items(), 5))
large_dict = dict(itertools.islice(large_dict.items(), 5))
#m = (input)("Enter cap : ")
m = request.args.get('cap')
comp = {}
if m == "smallcap":
for key, value in small_dict.items():
comp[key] = filterfunc(key)
comp = dict(
sorted(comp.items(), key=operator.itemgetter(1), reverse=True))
elif m == "midcap":
for key in mid_dict.items():
comp[key] = filterfunc(key)
comp = dict(
sorted(comp.items(), key=operator.itemgetter(1), reverse=True))
elif m == "largecap":
for key in large_dict.items():
comp[key] = filterfunc(key)
comp = dict(
sorted(comp.items(), key=operator.itemgetter(1), reverse=True))
print("filtered")
print(comp)
Com = []
for key, value in comp.items():
quote = si.get_quote_table(key)
c = Company(key, quote.get('1y Target Est'),
quote.get('52 Week Range'), quote.get('Ask'),
quote.get('Avg. Volume'), quote.get('Beta (5Y Monthly)'),
quote.get('Bid'), quote.get("Day's Range"),
quote.get('EPS (TTM)'), quote.get('Earnings Date'),
quote.get('Ex-Dividend Date'),
quote.get('Forward Dividend & Yield'),
quote.get('Market Cap'), quote.get('Open'),
quote.get('PE Ratio (TTM)'), quote.get('Previous Close'),
quote.get('Price'), quote.get('Volume'))
Com.append(c.toJSON())
print(c.toJSON())
return jsonify(Com)
def getCurrentMarketData(self, tickerList):
"""
get real-time market data, you can use this with my two reporters
:param tickerList: list of tickers, like: ["AAPL","IBM","JPM"]
:return: dataframe of accessed data
"""
ans = pd.DataFrame(columns=[
"Best Ask Price", "Best Ask Amount", "Best Bid Price",
"Best Bid Amount", "Quote Price", "Open", "Previous Close",
"Volume"
])
temp_dict = {}
keys = [
"Ask", "Bid", "Open", "Previous Close", "Quote Price", "Volume"
]
for ticker in tickerList:
try:
temp_dict[ticker] = si.get_quote_table(ticker)
except:
warnings.warn("{}'s market data not found!".format(ticker))
for ticker, data in temp_dict.items():
values = list(itemgetter(*keys)(data))
organized_values = list(map(float, values[0].split("x"))) + \
list(map(float, values[1].split("x"))) + \
[round(values[4], 4)] + \
values[2:4] + \
values[5:]
ans.loc[ticker] = organized_values
with pd.option_context('display.max_rows', None, 'display.max_columns',
None):
print(ans)
return ans
def priceDiv(ticker):
try:
price = si.get_live_price(ticker)
div = si.get_quote_table(ticker)['Forward Dividend & Yield'][:4]
return price, div
except:
raise Exception('There was a problem updating %s...' % (ticker))
def update1(self):
input_stocklv = self.lineEditlive.text()
df = si.get_quote_table(input_stocklv, dict_result=False)
a = df['value'][15] - df['value'][14]
#print(round(a, 2))
b = (a / df['value'][15]) * 100
#print(round(b, 2), "%")
c = "(" + str(round(b, 2)) + "%" + ")"
if df['value'][14] > df['value'][15]:
self.qplabel.setStyleSheet('color:red')
self.ndlabel.setStyleSheet('color:red')
self.nplabel.setStyleSheet('color:red')
self.qplabel.setText(str(df['value'][15]))
self.ndlabel.setText(str(round(a, 2)))
self.nplabel.setText(c)
elif df['value'][14] < df['value'][15]:
self.qplabel.setStyleSheet('color:green')
self.ndlabel.setStyleSheet('color:green')
self.nplabel.setStyleSheet('color:green')
self.qplabel.setText(str(df['value'][15]))
self.ndlabel.setText(str(round(a, 2)))
self.nplabel.setText(c)
self.model = pandasModel(df)
self.tableViewcd.setModel(self.model)
self.tableViewcd.show()
def base(request, symbol):
liveval = si.get_quote_table(symbol)
template = loader.get_template('base.html')
cnx = sqlite3.connect('db.sqlite3')
df = pd.read_sql_query("SELECT * FROM mainapp_" + symbol.lower(), cnx)
x_date = {}
for i in range(len(df['price_date'])):
key = str(i)
x_date[key] = df['price_date'][i]
json_data = json.dumps(x_date)
with open('static/data.json', 'w') as outfile:
json.dump(json_data, outfile)
df.price_date = pd.to_datetime(df.price_date)
df = df.sort_values('price_date')
#DISPLAY GRAPH
# graph(symbol,df)
secondlast_price, last_price = find_price(symbol, df)
dt = df['price_date'].values
close_date = pd.Timestamp(dt[len(dt) - 1]).date()
change = last_price - secondlast_price
sign = 0
if (change > 0):
sign = 1
per = (change / last_price) * 100
change = '%.2f' % (change)
per = '%.2f' % (per)
if change[0] != '-':
change = "+" + change
last_price = '%.2f' % (last_price)
context = {
'symbol': symbol,
'sign': sign,
'temp': df,
'change': change,
'last_price': last_price,
'per': per,
'close_date': close_date,
'close': list(df['close_price'].values),
'open': list(df['open_price'].values),
'high': list(df['high_price'].values),
'low': list(df['low_price'].values),
'val1': liveval['1y Target Est'],
'val2': liveval['52 Week Range'],
'val3': liveval['Ask'],
'val4': liveval['Avg. Volume'],
'val5': liveval['Beta (3Y Monthly)'],
'val6': liveval['Bid'],
'val7': liveval['EPS (TTM)'],
'val8': liveval['Earnings Date'],
'val9': liveval['Ex-Dividend Date'],
'val10': liveval['Forward Dividend & Yield'],
'val11': liveval['Market Cap'],
'val12': liveval['Open'],
'val13': liveval['PE Ratio (TTM)'],
'val14': liveval['Previous Close'],
'val15': '%.2f' % (liveval['Quote Price']),
'val16': liveval['Volume'],
}
return HttpResponse(template.render(context, request))
def obtenerCotizacion(self, event): #hace la consulta a la API
self.busquedaCot = last_price = si.get_quote_table(
self.lb1.GetStringSelection())["Quote Price"]
cartel = MessageBox("Ultima cotizacion de " +
self.lb1.GetStringSelection() +
" en el mercado: $" +
str(round(self.busquedaCot, 2)))
def _get_price_yahoo(symbol, mysettings):
"""
Return current price for given stock, 0 if hit an error.
Note that am using Yahoo Finance to retrieve prices.
Also note that appears that if request a symbol that they don't recognize, they return
an empty Global Quote object.
"""
time.sleep(mysettings.yahooCallDelay)
yahooSymbol = get_yahoo_ticker(symbol)
priceInfo = security.PriceInfo()
# Try up to three times if fail.
for i in range(0, 3):
try:
quote_table = get_quote_table(yahooSymbol)
priceInfo.currentPrice = quote_table['Quote Price']
priceInfo.lastClosePrice = quote_table['Previous Close']
priceInfo.low52Week, priceInfo.high52Week = _split_price_range(
quote_table['52 Week Range'])
break
except (ValueError, IndexError, ImportError, HTTPError) as E:
# E = sys.exc_info()[0]
print("Failed to retrieve price for ", yahooSymbol)
print(E)
E = sys.exc_info()[0]
print(E)
return priceInfo
async def check(ctx, ticker):
print('Price check command received')
live_price = str(round(si.get_live_price(ticker), 2))
today_range = si.get_quote_table(ticker).get("Day's Range")
await ctx.send("Live price: " + live_price + "\nToday's range: " +
today_range)
def get_dividend_yield(symbol):
data = si.get_quote_table(symbol , dict_result = True)
begin = data['Forward Dividend & Yield'].index('(')
try:
end = data['Forward Dividend & Yield'].index('%')
except:
return "N/A"
return (float(data['Forward Dividend & Yield'][begin+1:end]))/100
def get_pe(share):
try:
ticker = si.get_quote_table(share)['PE Ratio (TTM)']
if ticker == '' or pd.isnull(ticker):
ticker = 0
return ticker
except:
return 0
def get(ticker):
try:
logging.debug("Retrieving quote for '%s'", ticker)
data = stock_info.get_quote_table(ticker)
data["ticker"] = ticker.upper()
return StockQuote(data)
except:
logging.error("Error retrieving quote for ticker '%s'", ticker)
def fetch_stock(name):
try:
data = si.get_quote_table(name)
return data
except ValueError:
print("Invalid stock name. Check and try again.")
logging.debug("Invalid stock name.")
return None
def indices():
dow = get_quote_table('^dji')
dow['Change'] = dow['Quote Price'] - dow['Previous Close']
dow['Percent Change'] = dow['Change'] / dow['Previous Close'] * 100
sp500 = get_quote_table('^gspc')
sp500['Change'] = sp500['Quote Price'] - sp500['Previous Close']
sp500['Percent Change'] = sp500['Change'] / sp500['Previous Close'] * 100
nasdaq = get_quote_table('^ixic')
nasdaq['Change'] = nasdaq['Quote Price'] - nasdaq['Previous Close']
nasdaq['Percent Change'] = nasdaq['Change'] / \
nasdaq['Previous Close'] * 100
major_indices = {'dow': dow, 'sp500': sp500, 'nasdaq': nasdaq}
return jsonify(major_indices), 200
def quotes_genrator(n_clicks, ticker):
# info table
current_stock = yf.get_quote_table(ticker, dict_result=False)
columns = [{"name": i, "id": i} for i in current_stock.columns]
t_data = current_stock.to_dict("records")
# price
return columns, t_data
def companyinfo():
if request.method == 'POST':
stock = ''
try:
stock = str(json.loads(request.data)["stock"])
except Exception as ex:
print(ex)
try:
stock = str(request.form["stock"])
except Exception as ex:
print(ex)
obj = ''
try:
obj = Ticker(stock)
except Exception as ex:
print(ex)
val = ''
try:
val = obj.info
except Exception as ex:
print(ex)
data = dict()
try:
data["PEGratio"] = val["pegRatio"]
data["futurePEGratio"] = val["pegRatio"]
except Exception as ex:
print(ex)
try:
data["futurePEratio"] = val["forwardPE"]
data["PEratio"] = val["forwardPE"]
except Exception as ex:
print(ex)
try:
data["beta"] = val["beta"]
except Exception as ex:
print(ex)
try:
val = si.get_quote_table(stock)
except Exception as ex:
print(ex)
try:
data["PEratio"] = val["PE Ratio (TTM)"]
except Exception as ex:
print(ex)
outputdata = jsonify(data)
outputdata.headers.add("Access-Control-Allow-Origin", "*")
outputdata.headers.add("Access-Control-Allow-Headers", "*")
outputdata.headers.add("Access-Control-Allow-Methods", "*")
return outputdata
def get_quote_table_field(field, stock_ticker):
"""
This will get data from a field in the quote table.
:param field: field you want data from.
:param stock_ticker: stock you want data on.
:return: data from field.
"""
quote_table = si.get_quote_table(stock_ticker)
return quote_table[field]
def index(request):
version = Version.objects.all().first()
ticker_hits = TickerHits.objects.filter(
version=version.version).order_by("-hits").first()
reddit = ticker_hits.tickers.symbol
version = IHVersion.objects.all().first()
ticker_weights = IHTickerWeights.objects.filter(
version=version.version).order_by("-weight").first()
ihub = ticker_weights.tickers.symbol
twitter_tickers = Twitter.objects.all().order_by("-created_at").first()
twitter = twitter_tickers.tickers.symbol
reddit_data = si.get_quote_table(reddit, dict_result=True)
twitter_data = si.get_quote_table(twitter, dict_result=True)
ihub_data = si.get_quote_table(ihub, dict_result=True)
now = datetime.datetime.now()
then = start_date = datetime.datetime.now() - datetime.timedelta(30)
month_data = si.get_data(reddit, then, now)
open_data = []
for data in month_data.open:
open_data.append(data)
start_dt = date(2019, 1, 21)
end_dt = date(2019, 2, 4)
data_date = []
weekdays = [5, 6]
for dt in daterange(then, now):
if dt.weekday() not in weekdays:
data_date.append(dt.strftime(str("%m-%d")))
context = {
'reddit': reddit,
'ihub': ihub,
'ihub_data': ihub_data,
'twitter': twitter,
'twitter_data': twitter_data,
'reddit_data': reddit_data,
'open_data': open_data,
'data_date': data_date,
}
return render(request, "stock_data/screener.html", context)
def write_stock_info(tickers):
for ticker in tickers:
data = si.get_quote_table(ticker)
output = "\r"
price = str(data["Quote Price"])
output += price
output += "\n I love ice cream"
output += "\0x1B[1A"
sys.stdout.write(output)
sys.stdout.flush()
def get_quote(ticker):
stockinfo = {}
stockinfo["symbol"] = ticker
stockinfo["market_price"] = yf.get_live_price(ticker)
stock_tmp = yf.get_quote_table(ticker)
stockinfo["day_range"] = stock_tmp["Day's Range"]
stockinfo["year_range"] = stock_tmp["52 Week Range"]
return stockinfo
async def outstanding_close_name(self) -> Dict[str, float]:
"""
get the price and outstandings from yahoo API the unit of outstanding is 'M'
"""
out = si.get_quote_data(self.symbol)['sharesOutstanding']
out = out / 1000000
close = round(si.get_quote_table(self.symbol)['Quote Price'], 2)
name = self.symbol
return {'out': round(out), 'close': close, 'name': name}
def stockform():
form = StockForm(request.form)
if form.validate_on_submit():
global output
output = si.get_quote_table(form.stockname.data, dict_result=False)
return output
return render_template('output.html',
title='Stock Details',
form=form,
output=output)
def _checkStock(stock_id):
""" Checks price of stock from Yahoo! Finance """
try:
try:
stock = si.get_quote_table(stock_id, dict_result=True)
except:
try:
stock = si.get_quote_table(stock_id, dict_result=True)
except:
try:
stock = si.get_quote_table(stock_id, dict_result=True)
except:
stock = si.get_quote_table(stock_id, dict_result=True)
quote_price = round(stock['Quote Price'], 2)
close_price = stock['Previous Close']
percentage = round(((quote_price - close_price) / close_price) * 100, 2)
day_range = stock["Day's Range"]
volume = int(stock['Volume'])
return (quote_price, percentage, volume, day_range)
except:
return (0,0,0,"")