def doDesires(step, startKey=None, stopKey=None):
global cvalDict
if stopKey is None and startKey is None:
startKey = 1
stopKey = int(meSchema.tradeCue.all(keys_only=True).order('-__key__').get().name())
elif stopKey is None or startKey is None:
raise(BaseException('Must define both startKey and stopKey, or both must be None!'))
# Check cachepy clock and sync with memcache if necessary.
syncProcessCache(step,startKey,stopKey)
# Construct cvalDict for this step.
for stckID in [1,2,3,4]:
deltakey = str(stckID) + "_" + str(step)
cvalDict[deltakey] = calculateDeltas(stckID, step)
medesires = []
count = 0
for i in range(startKey, stopKey + 1):
cuekey = meTools.buildTradeCueKey(i)
desires = doDesire(step, cuekey)
if len(desires) != 0:
medesires.extend(desires)
meTools.batchPut(medesires)
# Remove from global cvalDict since not sure how that will act with same running process.
for stckID in [1,2,3,4]:
del cvalDict[str(stckID) + '_' + str(step)]
def persistBackTestReturns(backTestReturns):
putList = []
for algKey in backTestReturns:
for startMonth in backTestReturns[algKey]['returns']:
currentResult = backTestReturns[algKey]['returns'][startMonth]
resultKey = algKey + "_" + str(startMonth).rjust(7,'0') + "_" + str(currentResult['stopStep']).rjust(7,'0')
backTestResult = meSchema.backTestResult(key_name = resultKey,
algKey = algKey,
startStep = startMonth,
stopStep = currentResult['stopStep'],
percentReturn = currentResult['return'],
lastBuy = currentResult['lastBuy'],
lastSell = currentResult['lastSell'],
numTrades = currentResult['numTrades'],
PandL = currentResult['PandL'],
PosVal = currentResult['PosVal'],
CashDelta = currentResult['CashDelta'],
Positions = currentResult['Positions'])
putList.append(backTestResult)
meTools.batchPut(putList)
def doCompounds(stopStep, startStep, entities):
putList = []
memKeys = []
model = type(entities[0])
if model == meSchema.backTestResult:
idProp = 'algKey'
prefix = 'BTR-'
elif model == meSchema.liveAlg:
idProp = 'technique'
prefix = 'LAR-'
else:
raise BaseException('Model must be backTestResult or liveAlg!')
maxR = getMaxRnum(model)
stepBacks = [week for week in range(1,maxR)]
for entity in entities:
identifier = getattr(entity, idProp)
for stepback in stepBacks:
newStop = stopStep - 400*stepback
newStart = startStep - 400*stepback
memkey = buildMemKey(newStop, newStart, identifier, prefix)
memKeys.append(memkey)
prevReturns = memGetPercentReturns(memKeys, prefix)
for entity in entities:
Rdict = {1: (1.0 + entity.percentReturn)}
for Rnum in range(2, maxR + 1):
identifier = getattr(entity,idProp)
lastPercentReturn = getRReturn(stopStep, startStep, identifier, Rnum-1, prevReturns, prefix)
if lastPercentReturn is not None:
try:
Rdict[Rnum] = Rdict[Rnum-1]*(1.0 + lastPercentReturn)
except TypeError:
memkey = buildMemKey(stopStep, startStep, identifier, prefix)
message = 'Rnum: %s, memkey: %s, entity.key().name(): %s - V2' % (Rnum, memkey, entity.key().name())
raise(BaseException(message))
else:
Rdict[Rnum] = None
setattr(entity, 'R' + str(Rnum), Rdict[Rnum])
putList.append(entity)
meTools.batchPut(putList)