def get_spot_price(self, symbol):
"""Returns a dictionary of data about the spot price,
which includes bid, ask, bid size, ask size, as well as some api identification"""
stock1 = Stock.fetch(self.client, symbol)
stock = StockMarketdata.quote_by_instrument(self.client,
_id=stock1['id'])
return stock
def get_option_chain(self, symbol):
"""
This returns the option chain id and an array of the expiration dates
"""
md = StockMarketdata.quote_by_symbol(self.client, symbol)
stock_id = md['instrument'].split('/')[-2]
option_chain = OptionChain.fetch(self.client, stock_id, symbol)
option_chain_id = option_chain["id"]
expiration_dates = option_chain['expiration_dates']
return option_chain_id, np.array(
expiration_dates) #.reshape(len(expiration_dates),-1)
#
with open("fast_arrow_auth.json") as f:
auth_data = json.loads(f.read())
#
# initialize client with auth_data
#
client = Client(auth_data)
#
# fetch the stock info for TLT
#
symbol = "TLT"
md = StockMarketdata.quote_by_symbol(client, symbol)
#
# get the TLT option chain info
#
stock_id = md["instrument"].split("/")[-2]
option_chain = OptionChain.fetch(client, stock_id, symbol)
option_chain_id = option_chain["id"]
expiration_dates = option_chain['expiration_dates']
#
# reduce the number of expiration dates we're interested in
#
next_3_expiration_dates = expiration_dates[0:3]
#
with open("fast_arrow_auth.json") as f:
auth_data = json.loads(f.read())
#
# initialize client with auth_data
#
client = Client(auth_data)
#
# fetch stock positions
#
symbols = ["AAPL", "MU"]
span = "week"
bounds = "regular"
data = StockMarketdata.historical_quote_by_symbols(client, symbols, span,
bounds)
if len(data) > 0:
filename = "examples/data_{}.csv".format("_".join(symbols))
csv_columns = ['open_price', 'high_price', 'low_price', 'close_price']
num_rows = len(data[0]['historicals'])
with open(filename, 'w') as csv_file:
writer = csv.writer(csv_file)
headers = ['begins_at']
for sym in symbols:
for col in csv_columns:
headers.append('{}_{}'.format(sym, col))
writer.writerow(headers)
# initialize and authenticate Client
#
client = Client(username=username, password=password)
client.authenticate()
def print_symbol_price(marketdata):
msg = "Symbol = {}. Ask price = {}. Bid price = {}".format(
marketdata['symbol'], marketdata['ask_price'], marketdata['bid_price'])
print(msg)
#
# fetch by single stock symbol
#
symbol = "AAPL"
md = StockMarketdata.quote_by_symbol(client, symbol)
print_symbol_price(md)
#
# fetch by multiple stock symbols
#
symbols = ['AAPL', 'MU', 'FB']
mds = StockMarketdata.quote_by_symbols(client, symbols)
for md in mds:
print_symbol_price(md)
#
# fetch by single 'instrument_id'
#
symbol = 'AAPL'
md = StockMarketdata.quote_by_symbol(client, symbol)
def get_quote(self, symbol):
return StockMarketdata.quote_by_symbol(self.client, symbol)
#
# get the authentication configs
#
config_file = "config.debug.ini"
config = configparser.ConfigParser()
config.read(config_file)
username = config['account']['username']
password = config['account']['password']
#
# initialize and authenticate Client
#
client = Client(username=username, password=password)
client.authenticate()
#
# fetch stock positions
#
symbol = "AAPL"
data = StockMarketdata.historical(client, symbol)
if len(data["historicals"]) > 0:
csv_columns = data["historicals"][0].keys()
filename = "examples/data_{}.csv".format(symbol)
with open(filename, 'w') as csv_file:
writer = csv.DictWriter(csv_file, fieldnames=csv_columns)
writer.writeheader()
for rec in data["historicals"]:
writer.writerow(rec)
def retrieve_current_price(client, ticker):
from fast_arrow import StockMarketdata
stock = StockMarketdata.quote_by_symbol(client, ticker)
stock_price = round(
(float(stock['ask_price']) + float(stock['bid_price'])) / 2, 2)
return stock_price