def process_summary(self, summary: np.array):
if self.mkt_snapshot_depth > 0:
s = iqfeed_to_deque([summary], maxlen=self.mkt_snapshot_depth)
# no need for deque for the symbol
symbol = s['symbol'][0]
s['symbol'] = symbol
self.watched_symbols[symbol] = s
self.listeners({'type': 'level_1_summary', 'data': iqfeed_to_dict(summary)})
def process_update(self, update: np.array):
if self.mkt_snapshot_depth > 0:
update = update[0] if len(update) == 1 else update
symbol = update[0].decode("ascii")
data = self.watched_symbols[symbol]
for key, v in zip(data, update): # skip symbol
if key != 'symbol':
if isinstance(v, bytes):
v = v.decode('ascii')
data[key].append(v)
else:
data = iqfeed_to_dict(update)
self.total_updates = (self.total_updates + 1) % 1000000007
if self.total_updates % 1000 == 0:
logging.getLogger(__name__).debug("%d total updates" % self.total_updates)
self.listeners({'type': 'level_1_update', 'data': data})
def process_fundamentals(self, fund: np.array):
fundamentals = iqfeed_to_dict(fund)
s = fundamentals['symbol']
result[s] = fundamentals
if len(symbol - (result.keys() | invalid)) == 0:
e.set()
def process_fundamentals(self, fund: np.array):
f = iqfeed_to_dict(fund)
self.listeners({'type': 'level_1_fundamentals', 'data': f})
def process_regional_quote(self, quote: np.array):
self.listeners({'type': 'level_1_regional_quote', 'data': iqfeed_to_dict(quote)})