def beatspx(thedate,dbconn):
symlst = metadata.getStockList("default",dbconn)
beatspxlst = pandas.DataFrame(columns=('symbol', 'sector', 'chg'))
beapspxchg = 0.0
for symbol in symlst:
chg = perfdata.queryOneDatePerf(symbol,thedate,dbconn)
if chg>2.04:
sector = stocklist.getSector(symbol,dbconn)
#beatspxlst[symbol] = sector
beatspxlst.loc[len(beatspxlst)+1]=[symbol,sector,chg]
print "choose ",symbol,",",sector,"=",chg
# de-duplicated by sector
#lst1 = pandas.Series(beatspxlst)
beatspxlst = beatspxlst.sort_index(by="chg",ascending=False)
print beatspxlst
print "========================="
beatspxlst = beatspxlst.drop_duplicates(cols='sector')
print beatspxlst['symbol']
for symbol in beatspxlst['symbol']:
chg = perfdata.queryYtdPerf(symbol,dbconn)
beapspxchg += chg
print symbol,",",sector,"=",chg
print "beapspx YTD performance=", beapspxchg
def calc(dbconn):
resetTable(dbconn)
today = datetime.date.today()
day_ytd = today.replace(month=1,day=1)
day_5d = today-datetime.timedelta(days=5)
day_10d = today-datetime.timedelta(days=10)
day_20d = today-datetime.timedelta(days=20)
day_50d = today-datetime.timedelta(days=50)
day_100d = today-datetime.timedelta(days=100)
day_200d = today-datetime.timedelta(days=200)
day_1y = today.replace(year=today.year-1)
day_2y = today.replace(year=today.year-2)
day_5y = today.replace(year=today.year-5)
symLst = metadata.getStockList(dbconn)
for sym in symLst:
# calculate
p_today = stockeod.getLatestPrice(sym,dbconn)
p_ytd = stockeod.getClosePrice(sym,day_ytd,dbconn)
p_1y = stockeod.getClosePrice(sym,day_1y,dbconn)
p_2y = stockeod.getClosePrice(sym,day_2y,dbconn)
p_5y = stockeod.getClosePrice(sym,day_5y,dbconn)
p_5d = stockeod.getClosePrice(sym,day_5d,dbconn)
p_10d = stockeod.getClosePrice(sym,day_10d,dbconn)
p_20d = stockeod.getClosePrice(sym,day_20d,dbconn)
p_50d = stockeod.getClosePrice(sym,day_50d,dbconn)
p_100d = stockeod.getClosePrice(sym,day_100d,dbconn)
p_200d = stockeod.getClosePrice(sym,day_200d,dbconn)
pf_5y = (p_today-p_5y)*100/p_5y
pf_2y = (p_today-p_2y)*100/p_2y
pf_1y = (p_today-p_1y)*100/p_1y
pf_ytd = (p_today-p_ytd)*100/p_ytd
pf_200d = (p_today-p_200d)*100/p_200d
pf_100d = (p_today-p_100d)*100/p_100d
pf_50d = (p_today-p_50d)*100/p_50d
pf_20d = (p_today-p_20d)*100/p_20d
pf_10d = (p_today-p_10d)*100/p_10d
pf_5d = (p_today-p_5d)*100/p_5d
cursor = dbconn.cursor()
try:
tb=""
sql = "insert into perfdata(symbol,lastdate,y5d,y2d,y1d,ytd,td200,td100,td50,td20,td10,td5) \
values ('%s','%s',%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f,%.2f)" \
% (sym,today,pf_5y,pf_2y,pf_1y,pf_ytd,pf_200d,pf_100d,pf_50d,pf_20d,pf_10d,pf_5d)
cursor.execute(sql)
dbconn.commit()
except:
print "error"
tb = traceback.format_exc()
dbconn.rollback()
finally:
#print tb
return
def calc(thedate,dbconn):
symlst = metadata.getStockList("default",dbconn)
#symdict = {}
totalchg = 0.0;
top10 = 0.0
for symbol in symlst:
#print symbol
chg = perfdata.queryYtdPerf(symbol,dbconn)
print chg
totalchg += chg
if chg>2.04:
top10+=chg
#chg = perfdata.queryPerf(symbol,thedate,dbconn)
#ret = "%s=%.2f %%" % (symbol,chg)
#symdict[symbol] = chg
#print ret
print "YTD performance=", totalchg
print "TOP spx YTD performance=", top10
