def load_data():
if environ.get('REDIS_SERVER') is not None:
redis_server = environ.get('REDIS_SERVER')
else:
redis_server = 'localhost'
if environ.get('REDIS_PORT') is not None:
redis_port = int(environ.get('REDIS_PORT'))
else:
redis_port = 6379
if environ.get('REDIS_PASSWORD') is not None:
redis_password = environ.get('REDIS_PASSWORD')
else:
redis_password = ''
rdb = redis.Redis(host=redis_server,
port=redis_port,
password=redis_password)
rb = RedisBloom(host=redis_server,
port=redis_port,
password=redis_password)
rts = RedisTimeseries(host=redis_server,
port=redis_port,
password=redis_password)
rdb.set("CONFIG", "YES")
rts.create('s-unfiltered', retention_ms=60000)
rts.create('s-filtered', retention_ms=60000)
rts.create('unfiltered', labels={'Type': 'Final'}, retention_ms=86400000)
rts.create('filtered', labels={'Type': 'Final'}, retention_ms=86400000)
rts.createrule('s-unfiltered', 'unfiltered', 'last', 1000)
rts.createrule('s-filtered', 'filtered', 'last', 1000)
for gear in ['./dedup.py']:
file = open(gear, mode='r')
g = file.read()
rdb.execute_command('RG.PYEXECUTE', g)
file.close()
if environ.get('REDIS_SCRABBLE') is not None:
for line in fileinput.input("2019_Collins_Scrabble_Words.txt"):
rb.bfAdd("Scrabble-Bloom", line.rstrip())
pool = redis.ConnectionPool(host=redis_host, port=redis_port)
r = redis.Redis(connection_pool=pool)
try:
r.xadd("mystream", {'event_type': 'startup', 'user': '******'})
r.xgroup_create("mystream", "consumerGroup", '$')
except:
print("group already exists")
while True:
msgs = r.xreadgroup("consumerGroup",
"consumerName",
streams={"mystream": '>'},
count=10,
block=1000,
noack=False)
for msg in msgs:
for m in msg[1]:
evnt = m[1]['event_type']
try:
rts.info(evnt)
except:
rts.create(evnt, retentionSecs=60, labels={'event_type': evnt})
rts.create(evnt + "_minute",
retentionSecs=0,
labels={'event_type': evnt})
rts.createrule(evnt, evnt + "_minute", 'count', 60)
rts.incrby(evnt, 1)
'PRICETYPE':'INTRADAY',
'COMPANYNAME': 'GOLDMAN_SACHS_GROUP'
})
rts.create('DAILYRSI15MINRNG:GS',
labels={
'SYMBOL': 'GS',
'DESC': 'RELATIVE_STRENGTH_INDEX',
'INDEX': 'DJIA',
'TIMEFRAME': '15_MINUTES',
'AGGREGATION': 'RANGE',
'INDICATOR': 'RSI',
'COMPANYNAME': 'GOLDMAN_SACHS_GROUP'
})
# 900 = 60 seconds * 15 min
rts.createrule('DAILYRSI:GS','DAILYRSI15MINRNG:GS','range',900)
rts.create('INTRADAYPRICES15MINRNG:GS',
labels={
'SYMBOL': 'GS',
'DESC': 'SHARE_PRICE',
'INDEX': 'DJIA',
'PRICETYPE':'RANGE',
'AGGREGATION': 'RANGE',
'DURATION': '15_MINUTES',
'COMPANYNAME': 'GOLDMAN_SACHS_GROUP'
})
rts.createrule('INTRADAYPRICES:GS','INTRADAYPRICES15MINRNG:GS','range',900)
rts.create('INTRADAYPRICES15MINSTDP:GS',
labels={
'SYMBOL': 'GS',
'DESC': 'RELATIVE STRENGTH INDEX',
'INDEX': 'DJIA',
'TIMEFRAME': '15-MINUTES',
'AGGREGATION': 'MAX',
'INDICATOR': 'RSI',
'COMPANYNAME': 'GOLDMAN_SACHS_GROUP'
})
#
# The "createrule" will apply the range, first, last, min, and max aggregations
# on the Goldman Sachs' daily RSI values and stores the aggregated value in
# the respective time series that we created above.
# You can do similar aggregations on other stocks in the market.
#
rts.createrule('DAILYRSI:GS', 'DAILYRSI15MINRNG:GS', 'range', 900 * 1000)
rts.createrule('DAILYRSI:GS', 'DAILYRSI15MINFIRST:GS', 'first', 900 * 1000)
rts.createrule('DAILYRSI:GS', 'DAILYRSI15MINLAST:GS', 'last', 900 * 1000)
rts.createrule('DAILYRSI:GS', 'DAILYRSI15MINMIN:GS', 'min', 900 * 1000)
rts.createrule('DAILYRSI:GS', 'DAILYRSI15MINMAX:GS', 'max', 900 * 1000)
#
# A Redis TimeSeries for storing the intraday prices
# for Goldman Sachs' stock price
#
#
rts.create('INTRADAYPRICES:GS',
labels={
'SYMBOL': 'GS',
'DESC': 'SHARE_PRICE',
'INDEX': 'DJIA',