from sqlalchemy.orm import sessionmaker
from model import getaitraderengine
from model import CotizacionMC
from globalutils import gettimestampfromfechatexto
engine = getaitraderengine()
"""
Archivo para rellenar el campo de derivedsourcetimestamp en la tabla cotizaciones_mc
"""
Session = sessionmaker(bind=engine)
session = Session()
cotizaciones = session.query(CotizacionMC).all()
tostore = []
for c in cotizaciones:
if c.derivedsourcetimestamp == None:
c.derivedsourcetimestamp = gettimestampfromfechatexto(c.source, c)
tostore.append(c)
for c in tostore:
session.add(c)
session.commit()
#Check if continuous descent/increase in closing price afects the following day closing price and the intensity in the
#shift if any
#read the data
sql = "select distinct ticker,str_to_date(fechatexto, '%d-%m-%Y') as fecha, valorcierre, split from \
( \
select *, str_to_date(fechatexto, '%d-%m-%Y') from cotizaciones_hist_mc \
) as st1 \
order by ticker asc, fecha asc"
import pandas
from model import getaitraderengine
engine = getaitraderengine("localhost", 3306, "aitrader")
df = pandas.read_sql(sql, engine)
tikers = {}
for i in range(len(df)):
if (not df["ticker"][i] in tikers.keys()):
prevvalue = None
prevpercdiff = None
percdiff = None
lastiterationshiftsign = None
numsessions = None
tikers[df["ticker"][i]] = {}
tikers[df["ticker"][i]]["fechas"] = {}
tikers[df["ticker"][i]]["shiftaftersessionsbullish"] = {}
tikers[df["ticker"][i]]["shiftaftersessionsbearish"] = {}
tikers[df["ticker"][i]]["noshiftaftersessions"] = {}
tikers[df["ticker"][i]]["totalsessions"] = 0
mdi.consensus = consensus
mdi.forecast = forecast
mdi.date = datetime.datetime.strptime(day, pattern)
Session = sessionmaker(bind=engine)
session = Session()
session.add(mdi)
session.commit()
y = 2
y = 2
import model
engine = model.getaitraderengine()
pattern = "%d/%m/%Y"
datefromstr = "27/05/2020"
datetostr = "04/10/2020"
datefrom = datetime.datetime.strptime(datefromstr, pattern)
dateto = datetime.datetime.strptime(datetostr, pattern)
currdate = datefrom
while(currdate.strftime(pattern)!=datetostr):
if (currdate.weekday() in (0,1,2,3,4)):
print(currdate.strftime(pattern))
doextractday(currdate.strftime(pattern), pattern, engine)
currdate = currdate + timedelta(days=1)
time.sleep(5)
consolidatedata(engine)
mthprint(
"DATACONSOLIDATION: Data consolidation run successfully")
except BaseException as e:
import traceback
logexception2mail(traceback.format_exc(), e)
time.sleep(15)
else:
mthprint("DATACONSOLIDATION: Fuera de horario")
time.sleep(60)
consolidatedata(engine)
from model import getaitraderengine
engineinfobolsa = getaitraderengine()
enginebsmarkets = getaitraderengine()
enginebolsademadrid = getaitraderengine()
enginedataconsolidation = getaitraderengine()
#loading tickers dictionaries for the different sources
gettickersdictionary(INFOBOLSA, engineinfobolsa)
gettickersdictionary(BOLSADEMADRID, enginebolsademadrid)
gettickersdictionary(BSMARKETS, enginebsmarkets)
th1 = threading.Thread(None, infobolsa, args=([engineinfobolsa]))
th2 = threading.Thread(None, bolsademadrid, args=([enginebolsademadrid]))
th3 = threading.Thread(None, bsmarkets, args=([enginebsmarkets]))
# th4 = threading.Thread(None, dataconsolidation, args=([enginedataconsolidation]))
print("pasa modulo:" + __name__)