def makeAlgs():
TradeSize = [0.25]
# Changing to use tradeCue combinations.
# Only 60 at the moment but this allows for up to 1000.
fetchCues = meSchema.tradeCue.all().fetch(1000)
TradeCues = []
for tradecue in fetchCues:
TradeCues.append(tradecue.key().name())
Cash = [100000.0]
id = 0
meList = []
count = 0
for buyCue in TradeCues:
for sellCue in TradeCues:
if sellCue != buyCue:
for size in TradeSize:
for meCash in Cash:
id += 1
key_name = meSchema.buildAlgKey(id)
alg = meSchema.meAlg(key_name = key_name,
TradeSize = size,
BuyCue = buyCue,
SellCue = sellCue,
Cash = meCash)
meList.append(alg)
meSchema.batchPut(meList)
def algorithmDo(keyname,step):
keyname = meSchema.buildAlgKey(keyname)
dna = meSchema.memGet(meSchema.meAlg,keyname)
tradesize = dna.TradeSize
buy = dna.BuyDelta
sell = dna.SellDelta
for stckID in [1,2,3,4]:
deltakey = str(stckID) + "_" + str(step) # Must eventually change key to 0-padded.
cval = meSchema.decompCval(deltakey)
if cval is None or len(cval) < dna.TimeDelta + 1:
return None
cue = cval[dna.TimeDelta]
buysell = buySell(tradesize,buy,sell,cue)
if buysell in (-1,1):
recent = recency(keyname,step,stckID,buysell,dna.TimeDelta)
if not recent:
action = makeDesire(stckID,keyname,step,buysell,tradesize,dna.Cash)
recency_key = "desire_" + keyname + "_" + str(buysell) + "_" + str(stckID)
value = step
meSchema.memcacheSet(recency_key, value)
return action # add action/desire to list and return list ?
return None