def T1452(idx=0, isToday=1):
# Exit Condition
idxTemp = int(idx)
print("idxTemp = ", idxTemp)
if idxTemp >= 280:
return
instXAQueryT1452 = win32com.client.DispatchWithEvents(
"XA_DataSet.XAQuery", XAQueryEventsT1452)
instXAQueryT1452.ResFileName = "Res\\t1452.res"
instXAQueryT1452.SetFieldData("t1452InBlock", "gubun", 0,
"1") # 1: KOPSPI 2:KOSDAQ
instXAQueryT1452.SetFieldData("t1452InBlock", "jnilgubun", 0, isToday)
instXAQueryT1452.SetFieldData("t1452InBlock", "ediff", 0, "7")
instXAQueryT1452.SetFieldData("t1452InBlock", "jc_num", 0, "139608960")
instXAQueryT1452.SetFieldData("t1452InBlock", "eprice", 0, "100000")
instXAQueryT1452.SetFieldData("t1452InBlock", "idx", 0, idx)
instXAQueryT1452.Request(1)
while instXAQueryT1452.query_state == 0:
pythoncom.PumpWaitingMessages()
time.sleep(0.1)
XAQueryEventsT1452.query_state = 0 # 중요
idx = instXAQueryT1452.GetFieldData("t1452OutBlock", "idx", 0)
count = instXAQueryT1452.GetBlockCount("t1452OutBlock1")
print("idx = ", idx, " count = ", count)
#sql = "insert into DailyVolume(hname,price,sign,diff,volume,vol,shcode,jnilvolume,bef_diff,date) values (?,?,?,?,?,?, ?,?,?,?)"
tempDate = "%04d-%02d-%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
for i in range(count):
hname = instXAQueryT1452.GetFieldData("t1452OutBlock1", "hname", i)
price = instXAQueryT1452.GetFieldData("t1452OutBlock1", "price", i)
sign = instXAQueryT1452.GetFieldData("t1452OutBlock1", "sign", i)
diff = instXAQueryT1452.GetFieldData("t1452OutBlock1", "diff", i)
volume = instXAQueryT1452.GetFieldData("t1452OutBlock1", "volume",
i) # 누적거래량
vol = instXAQueryT1452.GetFieldData("t1452OutBlock1", "vol",
i) # 회전율
shcode = instXAQueryT1452.GetFieldData("t1452OutBlock1", "shcode",
i)
jnilvolume = instXAQueryT1452.GetFieldData("t1452OutBlock1",
"jnilvolume", i)
bef_diff = instXAQueryT1452.GetFieldData("t1452OutBlock1",
"bef_diff", i)
listT1452[idxTemp + i] = [
hname, price, sign, diff, volume, vol, shcode, jnilvolume,
bef_diff
]
print(i, hname, price, sign, diff, volume, vol, shcode, jnilvolume,
bef_diff)
print(
"------------------------------------------------------------------------"
)
print("재귀호출] idx ", idx)
if int(
idx
) == 0: # Xing API 응답에서 40개 미만의 데이터를 주고 끝나는 경우 idx가 0으로 응답된다. 무한재귀 호출에 빠지지 않도록 idx에 끝값을 대입한다.
T1452(280, isToday=1)
else:
T1452(idx, isToday=1) # recursive call
def ttsAlert(self, alertCode, hname, diff):
client = texttospeech.TextToSpeechClient()
# Set the text input to be synthesized
tmpStr = hname + " 매도 경고" # + str(diff)
print(tmpStr + str(diff))
synthesis_input = texttospeech.SynthesisInput(text=tmpStr)
if not os.path.exists("alert"):
os.mkdir("alert")
if os.path.isfile("alert/" + alertCode + ".mp3") == True:
playsound("alert/" + alertCode + ".mp3")
else: # 해당 종목코드 mp3가 존재하지 않을경우,
# Build the voice request, select the language code ("en-US") and the ssml
# voice gender ("neutral")
voice = texttospeech.VoiceSelectionParams(
language_code="ko-KR",
ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL)
# Select the type of audio file you want returned
audio_config = texttospeech.AudioConfig(
audio_encoding=texttospeech.AudioEncoding.MP3)
# Perform the text-to-speech request on the text input with the selected
# voice parameters and audio file type
response = client.synthesize_speech(input=synthesis_input,
voice=voice,
audio_config=audio_config)
with open("alert/" + alertCode + ".mp3", "wb") as out:
# Write the response to the output file.
out.write(response.audio_content)
playsound("alert/" + alertCode + ".mp3")
def upperLimitCheck(self, shcode):
df1475 = orderManager.t1475(shcode)
if df1475.shape[0] == 0:
print("t1475 responded null")
return 0
if float(df1475['등락율'].values[0]) > 23:
print("전일대비 과열(23% 초과)로 매수 제외:", float(df1475['등락율'].values[0]))
return 1
def strategy2(_shcode, tempDate, refname=''):
print("종목명:", refname)
if checkExcludedList(refname) == True:
return
now = time.localtime()
strTempTime = "%02d%02d%02d" % (now.tm_hour, now.tm_min, now.tm_sec)
# tdf8412 = orderManager.t8412(단축코드=_shcode, 단위="10", 요청건수="60", 시작일자="", 종료일자="99999999", cts_date="",
# comp_yn="N")
# if tdf8412.shape[0] == 0:
# print('[ERR] 8412 주식차트(10분) 조회 불가')
# return
# tempX = list(range(tdf8412.shape[0]))
# tempY = list(map(int, tdf8412["종가"]))
# tempX = tempX[-10:-1]
# tempY = tempY[-10:-1]
# grad, intercept, r_square, p_value, std_err = stats.linregress(tempX, tempY)
# print(grad, intercept, r_square, p_value, std_err)
#
# if grad < 0:
# return
#
# ma60 = ta.MA(np.asarray(tdf8412['종가']), timeperiod=60)
# ma60 = ma60[~np.isnan(ma60)]
# if len(ma60) == 0:
# print("MA60 Error")
# return
# print("regression result(10분봉): ", grad, intercept, r_square, p_value, std_err)
# print("10분봉 종가", tdf8412["종가"].values[-1], "VS 60MA", ma60[-1])
# if int(tdf8412["종가"].values[-1]) <= int(ma60[-1]):
# return
rsiRes = rsiCheck(_shcode=_shcode, hname=refname)
if rsiRes == 2 or rsiRes == 3:
close15mma = "0" # round(tdf8412["종가"].values[-1], 2)
close60dma = "0" # round(ma60[-1], 2)
beepsound(freq=1000, dur=1500)
now = time.localtime()
if now.tm_hour <= 15:
if now.tm_hour == 15 and now.tm_min >= 30:
pass
else:
dbInstance.insertObserverList(_shcode, tempDate,
strTempTime, '', '', '', '',
"1", str(rsiRes))
tmpStr = "KOSPI 종목: " + refname + " 포착시각 : " + str(
now.tm_hour) + ":" + str(
now.tm_min) # +" 현재가: "+str(tdf8412["종가"].values[-1])
print(tmpStr)
# botManager.sendTeleMsg(tmpStr)
dbInstance.insertDailyRecommendList(_shcode, tempDate, "KOSPI",
str(close15mma),
str(close60dma), str(g_rsiTgt),
str(g_simpleMA9Tgt),
strTempTime, refname,
str(rsiRes))
def msmdVolumeCheck(self, _shcode):
df1471o, df1471ob = orderManager.t1471(
종목코드=_shcode, 분구분="00", 자료개수="001") # 30초 단위 매수/매도 호가물량 점검
totofferrem = df1471ob["총매도"].values[0]
totbidrem = df1471ob["총매수"].values[0]
msrate = df1471ob["매수비율"].values[0]
print("현재가", df1471o["현재가"].values[0], "총매도:", totofferrem, "총매수:",
totbidrem, "체결강도:", msrate, "매도우선잔량",
df1471ob["매도우선잔량"].values[0], "매수우선잔량",
df1471ob["매수우선잔량"].values[0])
if totofferrem * 2 < totbidrem or float(msrate) < 100.0:
return True
def rollout():
now = time.localtime()
start = time.time()
tempDate = "%04d%02d%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
dbInstance = dbManager.dbManager()
res = dbInstance.selectDailyRecommendList("KOSPI", tempDate)
for idx, row in enumerate(res):
print(">>>", idx, "shcode", row["shcode"])
# strategy1(row["shcode"], tempDate, '', '', '', '',skip=False, refname=row["hname"])
strategy2(row["shcode"], tempDate, row["hname"])
# time.sleep(3)
print("rollout 수행 시간: ", time.time() - start)
def prgCheck(self, _shcode=""):
dbInstance = dbManager.dbManager()
res = dbInstance.selectGubunRecommendList(_shcode)
if len(res) != 0:
gubun = res[0]["gubun"] == "KOSPI" and "0" or "1"
else:
print("no info exists in recommendList")
return False
df = orderManager.t1636(구분=gubun, 종목코드=_shcode)
tmpDf = df['종목코드'] == _shcode
df = df[tmpDf]
if df.shape[0] == 0:
print("프로그램 추세 정보 알 수 없음(%s)" % _shcode)
return False
# for i in range(0, df.shape[0]):
# if df["종목코드"].values[i] == _shcode:
print("종목명:", df["종목명"].values[0], "종목코드:", _shcode)
print("순위:", df["순위"].values[0], "종목명:", df["종목명"].values[0], "현재가:", df["현재가"].values[0], \
"대비구분:", df["대비구분"].values[0], "대비:", df["대비"].values[0], "등락률:", df["등락률"].values[0], \
"거래량:", df["거래량"].values[0], "순매수수량:", df["순매수수량"].values[0], "비중:",
df["비중"].values[0],
"순매수금액", df["순매수금액"].values[0], "매수금액", df["매수금액"].values[0])
if float(df["순매수금액"].values[0]) <= 0:
return True # 매도
else:
return False
def calcADI(df):
res = []
for i in range(0, df.shape[0]):
# print(df['종가'].values[i], df['시가'].values[i], df['고가'].values[i], df['저가'].values[i])
tmp = float(df['종가'].values[i]) - float(df['시가'].values[i])
if float(df['고가'].values[i]) == float(df['저가'].values[i]):
print("[ADI] 고가 = 저가", df['고가'].values[i],
float(df['저가'].values[i]))
tmp /= 1
else:
tmp /= (float(df['고가'].values[i]) - float(df['저가'].values[i]))
tmp *= float(df['거래량'].values[i])
res.append(tmp)
adi = DataFrame(data=res, columns=["ADI"])
return adi
def searchCandidates(condtion=1):
now = time.localtime()
tempDate = "%04d%02d%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
# strategy1("078860", tempDate, '', '', '', '', skip=False, refname="아이오케이")
if condtion == 1:
dft1533 = orderManager.t1533("1")
for i in range(0, 3):
df = orderManager.t1537(dft1533["테마코드"].values[i])
for j in range(0, df.shape[0]):
print("[테마] 종목명", df["종목명"].values[j], "종목코드",
df["종목코드"].values[j])
strategy2(df["종목코드"].values[j],
tempDate,
refname=df["종목명"].values[j])
df1, df2 = orderManager.t1825(검색코드="6412",
구분="2") #양음양 6006 # 거래량 6412
for i in range(0, df2.shape[0]):
# strategy1(df2["종목코드"].values[i], tempDate, '', '', '', '',skip=False,refname=df2["종목명"].values[i])
strategy2(df2["종목코드"].values[i],
tempDate,
refname=df2["종목명"].values[i])
df1, df2 = orderManager.t1825(검색코드="6306", 구분="2") #프로그램순매수 100
for i in range(0, df2.shape[0]):
# strategy1(df2["종목코드"].values[i], tempDate, '', '', '', '', skip=True, refname=df2["종목명"].values[i])
strategy2(df2["종목코드"].values[i],
tempDate,
refname=df2["종목명"].values[i])
else:
for idx, row in enumerate(listT1452):
# t1471i = T1471.XAT1471()
# ret = T1471.T1471_SearchBuyCandidates(row[6])
# if ret == None:
# pass
# else:
# (_shcode, tempDate, strTempTime, msrate, bidrem1, offerrem1, price) = ret
# strategy1(_shcode, tempDate, strTempTime, msrate, bidrem1, offerrem1, price)
print(">>>", idx, row[0])
if row[0] == "null":
return
# strategy1(row[6], tempDate, '', '', '', '',skip=False, refname=row[0])
strategy2(row[6], tempDate, row[0])
def checkBaseLine(self, df='', curPrice=0):
# dfnew = dfnew.apply(pd.to_numeric)
if df.shape[0] < 10:
print("df size is under 10")
return False
df = df.iloc[:10, :]
print(df.shape[0])
for i in range(df.shape[0] - 1, 2, -1):
print(i)
print("종가", df["종가"].values[i], "종가 -1봉", df["종가"].values[i - 1],
"종가 -2봉", df["종가"].values[i - 2])
if float(df["종가"].values[i]) >= float(
df["종가"].values[i - 1]) * 1.01 or float(
df["종가"].values[i]) >= float(
df["종가"].values[i - 2]) * 1.01:
basePrice = float(df["종가"].values[i]) / 2
if basePrice > curPrice:
print("저지선", basePrice, "> 현재가", curPrice)
return True
return False
def getOneUnderHoga(self, shcode, price): # 1: KOPSI, 2:KOSDAQ
price = int(price)
ret = price
dbInstance = dbManager.dbManager()
res = dbInstance.selectGubunRecommendList(shcode)
if len(res) == 0:
print("unknown code yet in recommend list")
return ret
print("[호가조정] 종목명: ", res[0]['hname'], " 구분: ", res[0]['gubun'])
gubun = res[0]['gubun']
if price < 1000:
ret -= 1
elif price >= 1000 and price < 5000:
ret -= 5
elif price >= 5000 and price < 10000:
ret -= 10
elif price >= 10000 and price < 50000:
ret -= 50
elif price >= 50000 and price < 100000:
ret -= 100
elif price >= 100000 and price < 500000:
temp = gubun == 1 and 500 or 100
ret -= temp
elif price >= 500000:
temp = gubun == 1 and 1000 or 100
ret -= temp
else:
print("호가 알 수 없음")
return str(ret)
def weirdConditionCheck(self, shcode, hname):
totcnt = 0
totmdvolume = totmsvolume = 0
for i in range(0, 5):
if i == 0:
df, df1 = orderManager.t1310(종목번호=shcode)
# print(df1.head(20))
else:
df, df1 = orderManager.t1310(종목번호=shcode,
종료시간=df["시간CTS"].values[0],
CTS=df["시간CTS"].values[0])
# print(df1.head(20))
if df1.shape[0] == 0:
print("t1310 responded null and we skip abnormal tr check")
return False
df1 = df1.apply(pd.to_numeric)
tmpdf = df1[df1['체결수량'].lt(12)]
totcnt += int(tmpdf.shape[0])
totmdvolume += (df1['매도체결수량'].values[0] - df1['매도체결수량'].values[-1])
totmsvolume += (df1['매수체결수량'].values[0] - df1['매수체결수량'].values[-1])
print("이상 매매 건수:", totcnt, "총매도체결수량:", totmdvolume, "총매수체결수량:",
totmsvolume)
if totmdvolume > totmsvolume:
print("매도세 우위로 매수 포기")
SellAgent.ttsAlert(self, shcode, hname, totmdvolume - totmsvolume)
return True
else:
return False
def T8430(gubun=1):
instXAQueryT8430 = win32com.client.DispatchWithEvents(
"XA_DataSet.XAQuery", XAQueryEventsT8430)
instXAQueryT8430.ResFileName = "C:\\eBEST\\xingAPI\\Res\\t8430.res"
instXAQueryT8430.SetFieldData("t8430InBlock", "gubun", 0, gubun)
instXAQueryT8430.Request(0)
while XAQueryEventsT8430.query_state == 0:
pythoncom.PumpWaitingMessages()
XAQueryEventsT8430.query_state = 0
count = instXAQueryT8430.GetBlockCount("t8430OutBlock")
print("# of codes = ", count)
myShcode = []
for i in range(count):
hname = instXAQueryT8430.GetFieldData("t8430OutBlock", "hname", i)
shcode = instXAQueryT8430.GetFieldData("t8430OutBlock", "shcode",
i)
#expcode = instXAQueryT8430.GetFieldData("t8430OutBlock", "expcode", i)
#etfgubun = instXAQueryT8430.GetFieldData("t8430OutBlock", "etfgubun", i)
myShcode.append(shcode)
print(i, hname, shcode)
return myShcode
def upperBoundCheck(self, df, upper, middle, low, curPrice):
print("볼린저 상:", upper[-1], "중", middle[-1], "하", low[-1], "종가:",
df['종가'].values[-1], "현재가", curPrice)
if float(upper[-1]) < float(curPrice) or float(upper[-1]) < float(
df['종가'].values[-1]):
print("BB 상한 초과")
return 2
# elif float(middle[-1]) >= float(df['종가'].values[-1]):
# print("BB 중간 이하")
# return 0
# elif float(df['종가'].values[-1]) * 1.013 >= float(upper[-1]) :
# print("종가 수익예상이 BB 상한 초과")
# return 1
elif (float(upper[-1]) + float(middle[-1])) / 2 >= float(curPrice) or (
float(upper[-1]) + float(middle[-1])) / 2 >= float(
df['종가'].values[-1]):
print("BB 중상 이하")
return 0 # 매수 가능
else:
print("BB 중상 이상")
return 1
def checkAccount(self):
# [START] 자산 조회 로직 0424는 추정단계, 12300은 확정단계
orderInstance = orderManager.t0424(BuyAgent.accountNumber,
BuyAgent.accountPwd) # 계좌번호, 비밀번호
if orderInstance[0].shape[0] == 0:
print("0424 account record info error")
return False
df1, df2 = orderManager.CSPAQ12200(레코드갯수='1',
관리지점번호='',
계좌번호=BuyAgent.accountNumber,
비밀번호=BuyAgent.accountPwd,
잔고생성구분='0')
# BuyAgent.balanced2 = orderInstance[0]["추정D2예수금"].values[0]
BuyAgent.netAssest = orderInstance[0]["추정순자산"].values[0]
if df2.shape[0] == 0:
print("CSPAQ12200 info error")
return False
BuyAgent.balanced2 = df2['D2예수금'].values[0]
print("예수금(D2) : ", BuyAgent.balanced2, "추정순자산 : ", BuyAgent.netAssest)
# [END] 자산 조회 로직
# [START] 미체결 주문금액을 반영한 자산 반영 로직 -> 13700 오동작
# res1, res2, res3 = orderManager.CSPAQ13700(계좌번호=BuyAgent.accountNumber, 입력비밀번호=BuyAgent.password)
# balanced2 에서 미체결 주문금액을 빼야 함
# db 조회 후, 확인한 종목코드, 주문수량, 주문총액 - 해당 종목의 t0425 totrem
now = time.localtime()
tempDate = "%04d%02d%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
dbInstance = dbManager.dbManager()
res = dbInstance.selectbuylistford2(tempDate, '2')
tempAmount = 0
for i in res:
time.sleep(2)
shcode = i["shcode"]
ordqty = i["ordqty"]
ordprc = i["ordprc"]
df, df1 = orderManager.t0425(계좌번호=BuyAgent.accountNumber,
비밀번호=BuyAgent.accountPwd,
종목번호=shcode,
체결구분='2',
매매구분='2',
정렬순서='2',
주문번호='')
tmpCnt = 0
while df.shape[0] == 0:
#if df.shape[0] == 0 :
time.sleep(2)
df, df1 = orderManager.t0425(계좌번호=BuyAgent.accountNumber,
비밀번호=BuyAgent.accountPwd,
종목번호=shcode,
체결구분='2',
매매구분='2',
정렬순서='2',
주문번호='')
tmpCnt += 1
if tmpCnt > 2:
dbInstance.updateBuyListford2(shcode,
tempDate) # 미체결 수량 없음
break
# else:
#
now = time.localtime()
for i in range(0, df1.shape[0]):
tmpOrderTime = df1['주문시간'].values[i]
print("주문번호:", df1['주문번호'].values[i], " 종목번호:",
df1['종목번호'].values[i], "주문시간", tmpOrderTime, " 주문수량:",
df1['주문수량'].values[i])
print("현재 시각: ", now.tm_hour, ":", now.tm_min)
delayedCancel = False
if now.tm_hour - int(tmpOrderTime[:2]) == 1:
print(int(now.tm_min) + 60 - int(tmpOrderTime[2:4]))
if int(now.tm_min) + 60 - int(tmpOrderTime[2:4]) >= 2:
delayedCancel = True
elif now.tm_hour - int(tmpOrderTime[:2]) > 1:
delayedCancel = True
elif int(tmpOrderTime[:2]) == now.tm_hour and int(
now.tm_min) != int(tmpOrderTime[2:4]):
if int(now.tm_min) - int(tmpOrderTime[2:4]) >= 2:
delayedCancel = True
else:
tempAmount += ((int(ordprc) / int(ordqty)) *
int(df['총미체결수량'].values[0]))
print('[미체결 정보] 종목번호', shcode, '주문수량', ordqty, '주문가격',
ordprc, '미체결수량', df['총미체결수량'].values[0])
print('누적 미체결 금액 : ', tempAmount)
if delayedCancel == True:
now = time.localtime()
print("매수취소 시도: ", now.tm_hour, ":", now.tm_min)
calcelRes = orderManager.CSPAT00800(
df1['주문번호'].values[i], BuyAgent.accountNumber,
BuyAgent.accountPwd, df1['종목번호'].values[i],
df['총미체결수량'].values[0]) #df1['주문수량'].values[i])
if calcelRes[1]["주문번호"].values[0] == 0:
print("매수취소 주문접수 불가")
tempAmount += ((int(ordprc) / int(ordqty)) *
int(df['총미체결수량'].values[0]))
print('[미체결 정보] 종목번호', shcode, '주문수량', ordqty, '주문가격',
ordprc, '미체결수량', df['총미체결수량'].values[0])
print('누적 미체결 금액 : ', tempAmount)
else:
print("매수취소 주문접수 완료")
print(df1['종목번호'].values[i], df1['주문수량'].values[i],
"0", df1['주문번호'].values[i], tempDate,
calcelRes[1]["주문시각"].values[0],
calcelRes[1]["종목명"].values[0], "3", "0")
# `shcode`, `ordqty`, `ordprc`, `ordno`, `orderdate`, `ordtime`, `isunm`,`bnstpcode`,`strategy`)
#dbInstance.insertOrderList(str(df1['종목번호'].values[i]), str(df1['주문수량'].values[i]), "0", str(df1['주문번호'].values[i]), tempDate, str(calcelRes[1]["주문시각"].values[0]), str(calcelRes[1]["종목명"].values[0]), "3","0") # 취소
dbInstance.deleteOrderList(tempDate,
df1['종목번호'].values[i])
BuyAgent.balanced2 -= tempAmount
print("미체결금액 반영한 D2 : ", BuyAgent.balanced2)
# [END] 미체결 주문금액을 반영한 자산 반영 로직
return True
def rsiCheck(_shcode="", hname=''):
global g_rsiTgt
global g_simpleMA9Tgt
now = time.localtime()
tempToday = "%04d%02d%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
if not os.path.exists(tempToday):
os.mkdir(tempToday)
df1475 = orderManager.t1475(_shcode)
if df1475.shape[0] == 0:
print("t1475 responded null")
elif df1475.shape[0] != 0 and float(df1475['당일VP'].values[0]) < 100:
strTemp = "체결강도 100 미만으로 후보 탈락:" + hname
print(strTemp)
# botManager.sendTeleMsg(strTemp)
return 0
df = orderManager.t8412(단축코드=_shcode, 단위="2", 요청건수="36")
if df.shape[0] > 0: # rsi 9 구하기
try:
taadx = ta.ADX(df['고가'], df['저가'], df['종가'], 9)
taadxSig = ta.MA(taadx, timeperiod=9)
taadx = np.asarray(taadx)
taadxSig = np.asarray(taadxSig)
print("ADX ", taadx)
print("ADX Sig", taadxSig)
if float(taadx[-1]) <= float(taadxSig[-1]):
print("ADX condition mismatched")
return 0
adxgrad, intercept, adi_r_square, p_value, std_err = stats.linregress(
list(range(len(taadx[-30:-1]))), taadx[-30:-1])
if adxgrad < 0:
print("ADX downturn")
return 0
except Exception as e:
print("Exception Occur : ", e)
# adi = calcADI(df)
# # mincond = adi['ADI'] < 0
# # adi = adi[mincond]
# tempY = list(map(float, np.asarray(adi)))
# sortTemp = sorted(tempY)
# sortTemp = sortTemp[0:5]
# print("저점 ADI: ",sortTemp)
# newTempY = []
# for i in tempY:
# if i in sortTemp:
# newTempY.append(i)
# print("저점 정렬 ADI: ", newTempY)
# tempX = list(range(len(newTempY)))
# adigrad, intercept, adi_r_square, p_value, std_err = stats.linregress(tempX, newTempY)
# print("adi 저점정보", adigrad, intercept, adi_r_square, p_value, std_err)
rsi9 = ta.RSI(np.asarray(df['종가']), 9)
rsi9 = rsi9[~np.isnan(rsi9)] # remove nan
if rsi9.size == 0:
print("rsi size exception")
return 0
rsiTgt = rsi9[-1]
simpleMA9 = ta.MA(rsi9, timeperiod=9)
simpleMA9Tgt = simpleMA9[-1]
print('----------[RSI SIGNAL JUDGE]----------')
if int(rsiTgt) < int(simpleMA9Tgt): # or int(rsiTgt) >= 75:
print('rsi', rsiTgt, 'signal', simpleMA9Tgt)
return 1
# elif int(rsiTgt) > int(simpleMA9Tgt) and int(rsiTgt) <= 30:
# print('rsi > ', rsiTgt, '>', 'signal', simpleMA9Tgt)
# g_rsiTgt = round(rsiTgt, 2)
# g_simpleMA9Tgt = round(simpleMA9Tgt,2)
# return 2
obv = ta.OBV(np.asarray(df['종가'], dtype=np.double),
np.asarray(df['거래량'], dtype=np.double))
if obv[-1] < 8000:
print("latest obv cut", obv[-1])
return 1
if obv[-1] - obv[-3] <= 0 or obv[-1] - obv[-2] <= 0:
print("obv is downturned")
return 1
obvSignal = ta.MA(obv, timeperiod=9)
#obvSignal = obvSignal[~np.isnan(obvSignal)]
# if obvSignal[-1] < 0:
# print("latest obv signal is under zero")
# return 1
tempX = list(range(len(obv)))
tempY = list(map(float, obv))
obvgrad, intercept, r_square, p_value, std_err = stats.linregress(
tempX, tempY)
print("OBV ", obvgrad, intercept, r_square, p_value, std_err)
if obvgrad <= 0:
print("OBV grad <= 0")
return 1
tempXSignal = list(range(len(obvSignal)))
tempYSignal = list(map(float, obvSignal))
tempXSignal = tempXSignal[-16:-1]
tempYSignal = tempYSignal[-16:-1]
obvSignalgrad, intercept, r_square, p_value, std_err = stats.linregress(
tempXSignal, tempYSignal)
print("OBV Signal ", obvSignalgrad, intercept, r_square, p_value,
std_err)
# if obvSignalgrad <=0:
# print("obvSignalgrad grad <= 0")
# return 1
# plt.show()
# print(obv)
# print(obvSignal)
#obv always above 0, but signal can be lower than 0
if obv[-1] < obvSignal[-1] or obv[-2] < obvSignal[-2]:
print("Signal Condition Unsuited")
return 1
# if abs(obvSignal[-1]) / (obv[-1] + (obvSignal[-1] < 0 and abs(obvSignal[-1]) or 0)) > 0.9 or abs(obvSignal[-2]) / (obv[-2]+(obvSignal[-1] < 0 and abs(obvSignal[-1]) or 0)) > 0.9:
# print("OBV Gap Flattened")
# return 1
# RSI Gap Condition Check : reg grad +, abs(gap[-1]) < 10
# rsiGap = rsi9 - simpleMA9
# rsiGap = rsiGap[~np.isnan(rsiGap)]
# rsiGap = abs(rsiGap)
# print("rsi gap : ", rsiGap)
# tempX = list(range(len(rsiGap)))
# tempY = list(map(float, rsiGap))
# tempX = tempX[-8:-1]
# tempY = tempY[-8:-1]
# g_rsiTgt = round(rsiTgt, 2)
# g_simpleMA9Tgt = round(simpleMA9Tgt, 2)
# grad, intercept, r_square, p_value, std_err = stats.linregress(tempX, tempY)
# print("regression result: ", grad, intercept, r_square, p_value, std_err)
# print("type rsi... ",type(rsi9[-1]))
if rsi9[-1] - rsi9[-3] <= 0 or rsi9[-1] - rsi9[-2] <= 0:
print("rsi is downturned")
return 0
print("type simpleMA9... ", type(simpleMA9[-1]))
# if grad <= 0 and rsi9[-1] > simpleMA9[-1] and rsi9[-2] > simpleMA9[-2]: # and r_square <= -0.6 and p_value < 0.05 and rsiGap[-2] >= rsiGap[-1]:
if rsi9[-1] > simpleMA9[-1] and rsi9[-2] > simpleMA9[
-2]: # and r_square <= -0.6 and p_value < 0.05 and rsiGap[-2] >= rsiGap[-1]:
# gapFlag = 0
# for i in tempY:
# if i > 11:
# gapFlag += 1
# if gapFlag < 2:
# print("no rsi condition(gap flag is flatten) matched")
# return 0
print("RSI Gap Condition Check OK")
plt.figure(figsize=(30, 30))
plt.subplot(221)
plt.title(str(_shcode))
plt.plot(obv)
plt.plot(obvSignal)
plt.text(0, 10, "og:" + str(format(obvgrad, "8.2%")))
plt.legend(["obv", "obv signal"])
# tempStr = tempToday + "/" + str(_shcode) + " obv" + ".png"
# plt.savefig(tempStr)
# botManager.sendImage(tempStr)
plt.subplot(222)
plt.plot(rsi9)
plt.plot(simpleMA9)
# plt.text(0, 10, "rg:" + str(format(grad, "3.2%")))
plt.legend(["rsi", "rsi signal"])
# plt.subplot(413)
# plt.plot(newTempY)
# plt.text(0, newTempY[0], "g"+str(format(adigrad,"3.2%"))+"r^2:" + str(format(adi_r_square*adi_r_square,"3.2%")))
# plt.legend(["new adi"])
plt.subplot(223)
plt.plot(taadx)
plt.plot(taadxSig)
plt.text(20, taadxSig[-1], "g:" + str(format(adxgrad, "3.2%")))
plt.legend(["adx", "adx sig"])
ax = plt.subplot(224)
dfnew = df[['시가', '고가', '저가', '종가']]
day_list = range(len(df))
dfnew.insert(0, '시각', day_list)
#dfnew = dfnew.set_index('날짜')
dfnew = dfnew.apply(pd.to_numeric)
candlestick_ohlc(ax,
dfnew.values,
width=0.5,
colorup='r',
colordown='b')
plt.grid()
tempStr = tempToday + "/" + str(_shcode) + " " + hname + ".png"
plt.savefig(tempStr)
plt.close()
# botManager.sendImage(tempStr)
# msrate check added
return 3
else:
print("no rsi condition matched")
return 0
print("RSI Calc Err")
return 0
def msquantityCheck(self, shcode): # 매수잔량 검사(매수벽 확인)
df1101 = orderManager.t1101(shcode)
df1101 = df1101.apply(pd.to_numeric)
print(df1101.head())
tot = df1101.sum(axis=1).values[0]
print('매수호가수량1', df1101['매수호가수량1'].values[0], '매수호가수량2',
df1101['매수호가수량2'].values[0], '총매수잔량', tot)
if df1101['매수호가수량1'].values[0] < 2000 or df1101['매수호가수량2'].values[
0] < 2000:
print("매수잔량 점검 부적격 < 2000")
return True
if df1101['매수호가수량1'].values[0] < tot * 0.005 or df1101[
'매수호가수량2'].values[0] < tot * 0.005:
print("매수잔량 점검 부적격")
return True
df1471o, df1471ob = orderManager.t1471(
종목코드=shcode, 분구분="00", 자료개수="001") # 30초 단위 매수/매도 호가물량 점검
totofferrem = df1471ob["총매도"].values[0]
totbidrem = df1471ob["총매수"].values[0]
msrate = df1471ob["매수비율"].values[0]
print("현재가", df1471o["현재가"].values[0], "총매도:", totofferrem, "총매수:",
totbidrem, "체결강도:", msrate, "매도우선잔량",
df1471ob["매도우선잔량"].values[0], "매수우선잔량",
df1471ob["매수우선잔량"].values[0])
if int(totofferrem) * 2 < int(totbidrem):
print("총매수/매도 확인 점검 부적격")
return True
if float(msrate) < 100.0:
print("순간 체결 강도 100 미만 부적격")
return True
def weirdConditionCheck(self, shcode):
totcnt = 0
totmdvolume = totmsvolume = 0
price = 0
for i in range(0, 3):
if i == 0:
df, df1 = orderManager.t1310(종목번호=shcode)
print(df1.tail())
price = int(df1['현재가'].values[0])
if price > 100000: # 현재가 100000 초과인 경우 체결빈도, 단주매매 검사 스킵
return False
tmpTopHour = int(df1['시간'].values[0][:2])
tmpBottomHour = int(df1['시간'].values[-1][:2])
tmpGap = 0
if tmpTopHour == tmpBottomHour:
tmpGap = int(df1['시간'].values[0]) - int(
df1['시간'].values[-1])
else:
tmpGap = int(df1['시간'].values[0]) - 4000 - int(
df1['시간'].values[-1]) # 1시간 빼고 , 60분 더해주고.
print("tmpTopHour", tmpTopHour, "tmpBottomHour", tmpBottomHour,
" 20개 체결 간격: ", tmpGap)
if tmpGap > 70: # 100 at 1 ea / 3 sec
print("체결 빈도 검사에서 탈락 :", tmpGap)
return True
else:
df, df1 = orderManager.t1310(종목번호=shcode,
종료시간=df["시간CTS"].values[0],
CTS=df["시간CTS"].values[0])
print(df1.tail())
tmpTopHour = int(df1['시간'].values[0][:2])
tmpBottomHour = int(df1['시간'].values[-1][:2])
tmpGap = 0
if tmpTopHour == tmpBottomHour:
tmpGap = int(df1['시간'].values[0]) - int(
df1['시간'].values[-1])
else:
tmpGap = int(df1['시간'].values[0]) - 4000 - int(
df1['시간'].values[-1])
print("tmpTopHour", tmpTopHour, "tmpBottomHour", tmpBottomHour,
" 20개 체결 간격: ", tmpGap)
if tmpGap > 50: # 100 at 1 ea / 3 sec
print("체결 빈도 검사에서 탈락")
return True
if df1.shape[0] == 0:
print("t1310 responded null and we skip abnormal tr check")
return False
df1 = df1.apply(pd.to_numeric)
tmpdf = df1[df1['체결수량'].lt(12)]
totcnt += int(tmpdf.shape[0])
totmdvolume += (df1['매도체결수량'].values[0] - df1['매도체결수량'].values[-1])
totmsvolume += (df1['매수체결수량'].values[0] - df1['매수체결수량'].values[-1])
print("이상 매매 건수:", totcnt, "총매도체결수량:", totmdvolume, "총매수체결수량:",
totmsvolume)
if totcnt >= 30:
print("이상 매매 건수 초과로 매수 포기")
return True
elif totmdvolume > totmsvolume:
print("매도세 우위로 매수 포기")
return True
else:
return False
def checkmsBaseLine(df='', curPrice=0):
dfnew = df.apply(pd.to_numeric)
dfnew = dfnew.iloc[:20, :]
# dfnew['종가'].argmax()
print(dfnew.head())
basePrice = 0
max = tmp = 0
for i in range(1, df.shape[0]):
# print("종가",df["종가"].values[i],"종가 -1봉", df["종가"].values[i-1], "종가 -2봉",df["종가"].values[i-2] )
if float(df["고가"].values[i]) >= float(
df["저가"].values[i]) and float(df["고가"].values[i]) >= float(
df["저가"].values[i - 1]) * 1.05:
print("장대양봉 고가:", df["고가"].values[i], "저가:",
df["저가"].values[i])
tmp = float(df["고가"].values[i]) - float(df["저가"].values[i])
if max < tmp:
max = tmp
basePrice = float(df["고가"].values[i]) / 2
print('저지선: ', basePrice)
if basePrice > curPrice:
print("저지선", basePrice, "> 현재가", curPrice)
return True
if (float(df["고가"].values[i]) - float(df["종가"].values[i])) / (
float(df["고가"].values[i]) - float(df["저가"].values[i])) >= 0.8:
print("상승 저항이 강력하여 매수 포기")
print("고가:", df["고가"].values[i], "종가:", df["종가"].values[i], "저가",
df["저가"].values[i])
return True
if basePrice == 0 or curPrice == 0:
print("이전 20봉 이내 장대양봉 없음")
return False
return False
def run(self):
pythoncom.CoInitialize()
orderManager.Login(id=SellAgent.accountId,
pwd=SellAgent.password,
cert=SellAgent.pkpwd)
# instXAQueryT1471 = win32com.client.DispatchWithEvents("XA_DataSet.XAQuery", XAQueryEventsT1471)
# instXAQueryT1471.ResFileName = "C:\\eBEST\\xingAPI\\Res\\t1471.res"
now = time.localtime()
tempDate = "%04d%02d%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
dbInstance = dbManager.dbManager()
cnt = 0
while True:
# print(cnt, "회전(Sell Manager)")
# botManager.queryMine(isToday=True) # ,date='20201209')
cnt += 1
df1, df2 = orderManager.t0424(SellAgent.accountNumber,
SellAgent.accountPwd,
체결구분='2') # 계좌번호, 비밀번호
while df2.shape[0] == 0:
df1, df2 = orderManager.t0424(SellAgent.accountNumber,
SellAgent.accountPwd,
체결구분='2') # 계좌번호, 비밀번호
print("보유 종목 갯수 : ", df2.shape[0])
time.sleep(1)
sellyn = False
sellHalfYn = False
for i in range(0, df2.shape[0]):
tmpres = dbInstance.selectUserControlListByShcode(
df2["종목번호"].values[i], tempDate)
if len(tmpres) != 0 and tmpres[0]['undercontrol'] == 'Lock':
print('수동 컨트럴 중으로 skip')
continue
print("종목번호:", df2["종목번호"].values[i],"종목명:", df2["종목명"].values[i],"평균단가:", df2["평균단가"].values[i], \
"현재가:", df2["현재가"].values[i],"매도가능수량:", df2["매도가능수량"].values[i],"잔고수량:", df2["잔고수량"].values[i])
if df2["매도가능수량"].values[i] != df2["잔고수량"].values[i]:
# 기존 매도주문 취소 및 reset (잔고수량과 매도가능수량이 다른 경우는 이미 매도주문이 들어가서 부분 매도된 경우이다.)
# 이러한 경우는 남은 물량을 현재가로 정정주문(매도) 한다.
# 잔고 수량 - 매도가능수량
# 모의투자 정정주문은 시장가 지정 불가능
ordno = dbInstance.selectOrdNo(str(df2["종목번호"].values[i]),
tempDate)
if len(ordno) == 0: # HTS 등 타 시스템에서 주문한 경우 스킵
continue
print("[정정주문] 원주문번호: ", ordno[0]['ordno'])
orderRes = orderManager.CSPAT00700(
ordno[0]['ordno'], SellAgent.accountNumber,
SellAgent.accountPwd, str(df2["종목번호"].values[i]),
str(df2["잔고수량"].values[i] - df2["매도가능수량"].values[i]),
'00', '0',
SellAgent.getOneUnderHoga(self,
str(df2["종목번호"].values[i]),
str(df2["현재가"].values[i])))
if orderRes[1]["주문번호"].values[
0] == 0: # 장 종료 또는 기존주문 미체결 상태 등의 사유
print("정정 주문접수 불가")
# 일단 취소, 상위 반복문에서 다시 매도 시도로 연결됨
calcelRes = orderManager.CSPAT00800(
ordno[0]['ordno'], SellAgent.accountNumber,
SellAgent.accountPwd, str(df2["종목번호"].values[i]),
str(
int(df2["잔고수량"].values[i]) -
int(df2["매도가능수량"].values[i])))
if calcelRes[1]["주문번호"].values[0] == 0:
print("취소 주문접수 불가")
else:
dbInstance.insertOrderList(
str(orderRes[0]["종목번호"].values[0]),
str(orderRes[0]["주문수량"].values[0]), "0",
str(orderRes[1]["모주문번호"].values[0]), tempDate,
str(orderRes[1]["주문시각"].values[0]),
str(orderRes[1]["종목명"].values[0]), "3",
"0") # 취소
else:
print(orderRes[1]["주문번호"].values[0])
dbInstance.insertOrderList(
str(orderRes[0]["종목번호"].values[0]),
str(orderRes[0]["주문수량"].values[0]),
str(orderRes[1]["주문금액"].values[0]),
str(orderRes[1]["주문번호"].values[0]), tempDate,
str(orderRes[1]["주문시각"].values[0]),
str(orderRes[1]["종목명"].values[0]), "1", "4") # 정정
continue
if df2["매도가능수량"].values[i] == 0:
#매도가능한 수량이 없기 때문에 이후 로직을 검사할 필요가 없다.
continue
# 판단1 : 평단 < 현재가 * (1.033 - tolerance) # 매도잔량: 7273 매수잔량: 23468 체결강도: 458.71
if SellAgent.weirdConditionCheck(self, df2["종목번호"].values[i],
df2["종목명"].values[i]) == True:
print("!!!!!!!!!!!!!!!!매도 경고!!!!!!!!!!!!!!!!")
if float(df2["평균단가"].values[i]) * (
1 - (SellAgent.principalNfee -
SellAgent.tolerance)) > df2["현재가"].values[i]:
print("한계 초과로 매도")
sellyn = True
if sellyn == False and float(
df2["평균단가"].values[i]) * 1.013 <= float(
df2["현재가"].values[i]):
print("1% 수익 확보, 50% 매도시도")
sellyn = True
sellHalfYn = True
# if sellyn == False and SellAgent.weirdConditionCheck(self, df2["종목번호"].values[i]) == True:
# sellyn = True
if sellyn == False:
#if (float(totbidrem1) >= float(totofferrem1) and float(msrate) <= SellAgent.stdmsrate) or float(msrate) <= SellAgent.stdmsrate - 50 :
rsiChkRet = SellAgent.rsiCheck(
self,
df2["평균단가"].values[i],
_shcode=df2["종목번호"].values[i],
curPrice=df2["현재가"].values[i])
if rsiChkRet == 1:
print("RSI 조건에 의하여 매도")
#dbInstance.insertObserverList(df2["종목번호"].values[i], tempDate, strTempTime, msrate, bidrem1, offerrem1, price)
dbInstance.updateObserverList(df2["종목번호"].values[i],
tempDate)
sellyn = True
elif rsiChkRet == 2:
dbInstance.updateObserverList(df2["종목번호"].values[i],
tempDate)
sellyn = True
sellHalfYn = True
# if sellyn == False: #and SellAgent.prgCheck(self, _shcode=df2["종목번호"].values[i]) == True :
# print("프로그램 순매도 조건으로 매도")
# sellyn = True
# elif float(bidrem1) >= (float(offerrem1) * 3 ) :
# print("매수잔량 >= 매도잔량 * 2 매도")
# dbInstance.insertObserverList(df2["종목번호"].values[i], tempDate, strTempTime, msrate, bidrem1,
# offerrem1, price)
# dbInstance.updateObserverList(df2["종목번호"].values[i])
# sellyn = True
if sellyn == True:
# 매도
sellQuantity = sellHalfYn == True and str(
int(int(df2["매도가능수량"].values[i]) /
2)) or df2["매도가능수량"].values[i]
if sellHalfYn == True and sellQuantity == '0': # 매도가능수량이 1인 경우 예외처리
sellQuantity = df2["매도가능수량"].values[i]
try:
orderRes = orderManager.CSPAT00600(
SellAgent.accountNumber, SellAgent.accountPwd,
df2["종목번호"].values[i], sellQuantity, '', '1', '03',
'000', '0') # 시장가로 매도, df2["현재가"].values[i]
if orderRes[1]["주문번호"].values[0] == 0: # 장 종료 등의 사유
print("주문접수 불가")
else:
print(orderRes[1]["주문번호"].values[0])
dbInstance.insertOrderList(
str(orderRes[0]["종목번호"].values[0]),
str(orderRes[1]["실물주문수량"].values[0]),
str(orderRes[1]["주문금액"].values[0]),
str(orderRes[1]["주문번호"].values[0]), tempDate,
str(orderRes[1]["주문시각"].values[0]),
str(orderRes[1]["종목명"].values[0]), "1", "0")
except Exception as e:
print("Exception Occur : ", e)
sellyn = False
sellHalfYn = False
time.sleep(SellAgent.sleeptime)
pythoncom.CoUninitialize()
g_rsiTgt = 0
g_simpleMA9Tgt = 0
inXASession = win32com.client.DispatchWithEvents("XA_Session.XASession",
XASessionEvents)
inXASession.ConnectServer(server_addr, server_port)
inXASession.Login(user_id, user_pass, user_certificate_pass, server_type,
0)
dbInstance = dbManager.dbManager()
while XASessionEvents.logInState == 0:
pythoncom.PumpWaitingMessages()
num_account = inXASession.GetAccountListCount()
for i in range(num_account):
account = inXASession.GetAccountList(i)
print(account)
#listT1452=[["null" for col in range(5)] for row in range(120)]
listT1452 = [["null" for col in range(1)] for row in range(280)]
# 전날 데이터 수신 (1: today 2: yesterday)
def T1452(idx=0, isToday=1):
# Exit Condition
idxTemp = int(idx)
print("idxTemp = ", idxTemp)
if idxTemp >= 280:
return
instXAQueryT1452 = win32com.client.DispatchWithEvents(
"XA_DataSet.XAQuery", XAQueryEventsT1452)
instXAQueryT1452.ResFileName = "Res\\t1452.res"
def OnDisconnect(self):
print("OnDisconnect method is called")
def strategy1(_shcode,
tempDate,
msrate,
bidrem1,
offerrem1,
price,
skip=False,
refname=''):
print("PG 순매수 스킵여부 :", skip, "종목명:", refname)
now = time.localtime()
strTempTime = "%02d%02d%02d" % (now.tm_hour, now.tm_min, now.tm_sec)
prognetbuy = 0
if skip == False:
df = orderManager.t1636(구분="0", 종목코드=_shcode)
tmpDf = df['종목코드'] == _shcode
df = df[tmpDf]
if df.shape[0] == 0:
print("프로그램 추세 정보 알 수 없음(%s)" % _shcode)
return
# for i in range(0, df.shape[0]):
# if df["종목코드"].values[i] == _shcode:
print("종목명:", df["종목명"].values[0], "종목코드:", _shcode)
print("순위:", df["순위"].values[0], "종목명:", df["종목명"].values[0], "현재가:", df["현재가"].values[0], \
"대비구분:", df["대비구분"].values[0], "대비:", df["대비"].values[0], "등락률:", df["등락률"].values[0], \
"거래량:", df["거래량"].values[0], "순매수수량:", df["순매수수량"].values[0], "비중:",
df["비중"].values[0],
"순매수금액", df["순매수금액"].values[0], "매수금액", df["매수금액"].values[0])
prognetbuy = float(df["순매수금액"].values[0])
if skip == True or prognetbuy > 0: # float(df["등락률"].values[0]) > 0 and float(df["순매수금액"].values[0]) > 0:
tdf8412 = orderManager.t8412(단축코드=_shcode,
단위="15",
요청건수="1",
시작일자="",
종료일자="99999999",
cts_date="",
comp_yn="N")
if tdf8412.shape[0] == 0:
print('[ERR] 8412 주식차트(분) 조회 불가')
return
close15mma = tdf8412.iloc[-1]['종가']
print('close15mma', close15mma)
tdf8413 = orderManager.t8413(단축코드=_shcode, 요청건수='60')
if tdf8413.shape[0] == 0:
print('[ERR] 8413 주식차트(일) 조회 불가')
return
pandas_ma60 = tdf8413['종가'].rolling(
window=60).mean() # tdf8413.종가.rolling(window=60).mean()
close60dma = pandas_ma60.iloc[-1]
print('close60dma', close60dma)
if np.isnan(close60dma) == True:
return
if int(close15mma) > int(close60dma):
tdf8412 = orderManager.t8412(단축코드=_shcode,
단위="10",
요청건수="10",
시작일자="",
종료일자="99999999",
cts_date="",
comp_yn="N")
if tdf8412.shape[0] == 0:
print('[ERR] 8412 주식차트(10분) 조회 불가')
return
tempX = list(range(tdf8412.shape[0]))
tempY = list(map(int, tdf8412["종가"]))
grad, intercept, r_square, p_value, std_err = stats.linregress(
tempX, tempY)
print(grad, intercept, r_square, p_value, std_err)
if grad < 0:
return
tdf8412 = orderManager.t8412(단축코드=_shcode,
단위="10",
요청건수="60",
시작일자="",
종료일자="99999999",
cts_date="",
comp_yn="N")
ma60 = ta.MA(np.asarray(tdf8412['종가']), timeperiod=60)
ma60 = ma60[~np.isnan(ma60)]
print("regression result(10분봉): ", grad, intercept, r_square,
p_value, std_err)
print("10분봉 종가", tdf8412["종가"].values[-1], "VS 60MA", ma60[-1])
if int(tdf8412["종가"].values[-1]) <= int(ma60[-1]):
return
rsiRes = rsiCheck(_shcode=_shcode, hname=refname)
if rsiRes == 2 or rsiRes == 3:
close15mma = round(close15mma, 2)
close60dma = round(close60dma, 2)
beepsound(freq=500, dur=500)
beepsound(freq=1500, dur=500)
now = time.localtime()
if now.tm_hour <= 15:
if now.tm_hour == 15 and now.tm_min >= 30:
pass
else:
dbInstance.insertObserverList(
_shcode, tempDate, strTempTime, msrate,
bidrem1, offerrem1, price, "1", str(rsiRes))
if skip == True:
print("종목: ", refname, "포착시각 : ", now.tm_hour, ":",
now.tm_min)
dbInstance.insertDailyRecommendList(
_shcode, tempDate, "KOSPI", str(close15mma),
str(close60dma), str(g_rsiTgt),
str(g_simpleMA9Tgt), strTempTime, refname,
str(rsiRes))
else:
print("종목: ", df["종목명"].values[0], "포착시각 : ",
now.tm_hour, ":", now.tm_min)
dbInstance.insertDailyRecommendList(
_shcode, tempDate, "KOSPI", str(close15mma),
str(close60dma), str(g_rsiTgt),
str(g_simpleMA9Tgt), strTempTime,
df["종목명"].values[0], str(rsiRes))
def OnLogout(self):
print("OnLogout method is called")
def rsiCheck(self, msprice, _shcode="", curPrice=0):
df = orderManager.t8412(단축코드=_shcode, 단위="2", 요청건수="36")
if df.shape[0] > 0: # rsi 9 구하기
upper, middle, low = ta.BBANDS(df['종가'], 20, 2, 2)
upper = np.asarray(upper)
# middle = np.asarray(middle)
print("볼린저 상한:", upper[-1], "종가:", df['종가'].values[-1])
dbInstance = dbManager.dbManager()
now = time.localtime()
tempDate = "%04d%02d%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
if float(upper[-1]) <= float(
df['종가'].values[-1]): # mark that record
dbInstance.updateOrdListBB(_shcode, tempDate)
if msprice * 1.013 <= df['종가'].values[-1]:
print("RSI 조건(BB상단 돌파 및 1% 수익)에 의하여 50%매도")
return 2
elif float(upper[-1]) > float(df['종가'].values[-1]):
res = dbInstance.selectOrdListBB(_shcode, tempDate)
if len(res) != 0:
print("BB 상한 돌파 이력 조회 결과:", res[0]['reserve2'])
if res[0]['reserve2'] == '1':
print("BB 상한 + -> - 로 매도")
return 1
rsi9 = ta.RSI(np.asarray(df['종가']), 9)
rsi9 = rsi9[~np.isnan(rsi9)] # remove nan
if rsi9.size == 0:
print("rsi size exception")
return -1
rsiTgt = rsi9[-1]
simpleMA9 = ta.MA(rsi9, timeperiod=9)
simpleMA9Tgt = simpleMA9[-1]
# print('----------[RSI SIGNAL JUDGE]----------')
if rsiTgt < simpleMA9Tgt:
print('rsi', rsiTgt, '<', 'signal', simpleMA9Tgt)
#df = orderManager.t8412(단축코드=_shcode, 단위="5", 요청건수="36")
simpleMA5 = ta.MA(np.asarray(df['종가'], dtype=np.double),
timeperiod=5)
simpleMA20 = ta.MA(np.asarray(df['종가'], dtype=np.double),
timeperiod=20)
print("종가:", df['종가'].values[-1], "5MA: ", simpleMA5[-1],
"20MA", simpleMA20[-1])
taadx = ta.ADX(df['고가'], df['저가'], df['종가'], 9)
taadxSig = ta.MA(taadx, timeperiod=9)
taadx = np.asarray(taadx)
taadxSig = np.asarray(taadxSig)
if float(taadx[-1]) <= float(taadxSig[-1]):
if float(simpleMA5[-1]) <= float(df['종가'].values[-1]):
return 0
else:
if float(simpleMA20[-1]) <= float(df['종가'].values[-1]):
return 0
return 1 # 매도
# elif rsiTgt >= 75 and rsiTgt <= 80: # 75
# df = orderManager.t8412(단축코드=_shcode, 단위="2", 요청건수="3")
# if df.shape[0] == 0 :
# print("분봉 정보 조회 불가")
# return False
# if df['종가'].values[-1] < df['종가'].values[-2] and df['종가'].values[-2] < df['종가'].values[-3] :
# print("RSI 75~80 에서 하락 2봉으로 매도")
# return True
# SellAgent.sleeptime = 60
# return False
elif rsiTgt > 75:
# df = orderManager.t8412(단축코드=_shcode, 단위="2", 요청건수="36")
# check if close price > BB upper bound
if df['종가'].values[-1] < df['종가'].values[-2] and df[
'종가'].values[-2] < df['종가'].values[-3]:
simpleMA5 = ta.MA(np.asarray(df['종가'], dtype=np.double),
timeperiod=5)
if float(df['종가'].values[-1]) < float(simpleMA5[-1]):
print("RSI 75 초과에서 하락 2봉 + 5MA(2min) 이하로 매도 ",
simpleMA5[-1])
return 1
else:
return 0
# 매수 1,2 호가 물량 체크
# elif SellAgent.msmdVolumeCheck(self, _shcode) == True:
# print("총매수 잔량 조건으로 50% 매도")
# return 2
simpleMA10 = ta.MA(np.asarray(df['종가'], dtype=np.double),
timeperiod=10)
print("종가:", df['종가'].values[-1], "10MA(2Min.): ",
simpleMA10[-1])
if float(simpleMA10[-1]) > float(df['종가'].values[-1]):
return 1
return 0
# 장대양봉 존재할 경우, 장대양봉의 중간 지지선 붕괴 여부 검사
elif SellAgent.checkBaseLine(self, df, float(curPrice)) == True:
print("장대양봉의 지지선 붕괴로 매도")
return 1
else:
print('rsi > ', rsiTgt, '>', 'signal', simpleMA9Tgt)
return 0
return 0
def run(self):
#pythoncom.CoInitialize()
orderManager.Login(id=BuyAgent.accountId,
pwd=BuyAgent.password,
cert=BuyAgent.pkpwd)
now = time.localtime()
tempDate = "%04d%02d%02d" % (now.tm_year, now.tm_mon, now.tm_mday)
# dbInstance = dbManager.dbManager()
while False == buy.checkAccount():
time.sleep(1)
cnt = 0
while True:
dbInstance = dbManager.dbManager()
res = dbInstance.selectObserverList(tempDate, '1', tempDate)
if cnt != 0 and cnt % 3 == 0:
BuyAgent.checkAccount(self)
orderPrice = 0
#print(res)
for i in res:
nPortfolio = BuyAgent.numberOfPortfolio
# time.sleep(5)
df1, df2, df3 = orderManager.CSPAQ12300(
레코드갯수='1',
계좌번호=BuyAgent.accountNumber,
비밀번호=BuyAgent.accountPwd,
잔고생성구분='0',
수수료적용구분='1',
D2잔고기준조회구분='0',
단가구분='0')
tmpdf = df3[(df3['종목번호'] == i["shcode"])]
if tmpdf.shape[0] > 0:
print("현재 보유 중, Skip")
continue
# nPortfolio -= df3.shape[0]
# if nPortfolio <= 0 :
# print("포트폴리오 초과 매수불가")
# continue
tmpres = dbInstance.selectUserControlListByShcode(
i["shcode"], tempDate)
if len(tmpres) != 0 and tmpres[0]['undercontrol'] == 'Lock':
print('수동 컨트럴 중으로 skip')
continue
df8407 = orderManager.t8407(종목코드=i["shcode"])
print(df8407["종목명"].values[0], df8407["현재가"].values[0])
if int(df8407["현재가"].values[0]) < 1000:
print("동전주 skip")
continue
client = texttospeech.TextToSpeechClient()
# Set the text input to be synthesized
synthesis_input = texttospeech.SynthesisInput(
text=df8407["종목명"].values[0])
if not os.path.exists("audio"):
os.mkdir("audio")
# 해당 종목코드 mp3가 존재한다면,
if os.path.isfile("audio/" + i["shcode"] + ".mp3") == True:
playsound("audio/" + i["shcode"] + ".mp3")
else: # 해당 종목코드 mp3가 존재하지 않을경우,
# Build the voice request, select the language code ("en-US") and the ssml
# voice gender ("neutral")
voice = texttospeech.VoiceSelectionParams(
language_code="ko-KR",
ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL)
# Select the type of audio file you want returned
audio_config = texttospeech.AudioConfig(
audio_encoding=texttospeech.AudioEncoding.MP3)
# Perform the text-to-speech request on the text input with the selected
# voice parameters and audio file type
response = client.synthesize_speech(
input=synthesis_input,
voice=voice,
audio_config=audio_config)
with open("audio/" + i["shcode"] + ".mp3", "wb") as out:
# Write the response to the output file.
out.write(response.audio_content)
playsound("audio/" + i["shcode"] + ".mp3")
# os.remove("output.mp3") # playsound(None)
# if BuyAgent.checkExcludedList(self, df8407["종목명"].values[0]) == True :
# print("인덱스 종목 제외 ",df8407["종목명"].values[0])
# continue
BuyAgent.checkAccount(self)
#BuyAgent.ordqty = int((min(BuyAgent.balanced2, BuyAgent.netAssest) / nPortfolio) / int(df8407["현재가"].values[0]))
BuyAgent.ordqty = int(
(min(BuyAgent.balanced2, BuyAgent.netAssest)) /
int(df8407["현재가"].values[0]))
print("[INFO] ", "포폴# ", nPortfolio, "D2추정: ",
BuyAgent.balanced2, "추정순자산", BuyAgent.netAssest)
#if BuyAgent.ordqty < 1 or df2["D2예수금"].values[0] < (BuyAgent.ordqty * float(i["price"])) :
if BuyAgent.ordqty < 1 or BuyAgent.balanced2 < (
BuyAgent.ordqty * float(df8407["현재가"].values[0])):
print(
"[잔고부족] ",
"#종목코드",
str(i["shcode"]),
"예수금 ",
df2["D2예수금"].values[0],
"VS. 물량 ",
str(BuyAgent.ordqty),
"가격",
str(df8407["현재가"].values[0]),
)
dbInstance.updateObserverList(i["shcode"], tempDate)
continue
# 상한가 임박 or 단주 매수 필터 아웃
if BuyAgent.upperLimitCheck(
self, i["shcode"]
) == 1 or True == BuyAgent.weirdConditionCheck(
self, i["shcode"]) or True == BuyAgent.msquantityCheck(
self, i["shcode"]):
print("매수 포기")
dbInstance.updateObserverList(i["shcode"], tempDate)
continue
orderPrice = int(df8407["현재가"].values[0])
# 이전 장대양봉 기준선(중간값)이하일 경우 매수 포기하는 로직 -> 주석 처리 210110
# df = orderManager.t8412(단축코드=i["shcode"], 단위="2", 요청건수="36")
# if BuyAgent.checkmsBaseLine(df,float(df8407["현재가"].values[0]) ) == True:
# print("장대양봉 기준선 이하로 매수 포기")
# dbInstance.updateObserverList(i["shcode"], tempDate)
# continue
# 볼린저 밴드 상한 초과시 포기, 중상일 경우 호가를 골드라인으로 조정 -> 로직 주석 처리 210110
df8412 = orderManager.t8412(단축코드=i["shcode"],
단위="2",
요청건수="36")
upper, middle, low = ta.BBANDS(
df8412['종가'], 20, 2, 2) # 2 sigma 에서 3 sigma로 변경 210118
upper = np.asarray(upper)
middle = np.asarray(middle)
low = np.array(low)
tmpUpperCheck = BuyAgent.upperBoundCheck(
self, df8412, upper, middle, low, df8407["현재가"].values[0])
orderPrice = int(df8407["현재가"].values[0])
if tmpUpperCheck == 1:
print("매수 호가 하향 조정 시도, 현재가:", orderPrice)
while (float(upper[-1]) +
float(middle[-1])) / 2 < orderPrice:
orderPrice = int(
BuyAgent.getOneUnderHoga(self, i["shcode"],
orderPrice))
print("orderPrice: ", orderPrice)
elif tmpUpperCheck == 2:
print("매수 포기")
dbInstance.updateObserverList(i["shcode"], tempDate)
continue
print("매수시도 종목코드: ", i["shcode"], " 수량: ", BuyAgent.ordqty,
" 가격: ", orderPrice)
try:
orderRes = orderManager.CSPAT00600(BuyAgent.accountNumber,
BuyAgent.accountPwd,
i["shcode"],
BuyAgent.ordqty,
str(orderPrice), '2',
'00', '000', '0')
if orderRes[1]["주문번호"].values[0] == 0: # 장 종료 등의 사유
# observerList 테이블에서 해당 Row의 excluded칼럼을 1로 업데이트
dbInstance.updateObserverList(i["shcode"], tempDate)
continue
else:
print(orderRes[1]["주문번호"].values[0])
# bnstpcode 2: 매수, strategy 1: 전략1
dbInstance.insertOrderList(
orderRes[0]["종목번호"].values[0],
str(BuyAgent.ordqty),
str(orderRes[1]["주문금액"].values[0]),
str(orderRes[1]["주문번호"].values[0]), tempDate,
str(orderRes[1]["주문시각"].values[0]),
str(orderRes[1]["종목명"].values[0]), "2", "1")
#dbInstance.deleteOrderList(tempDate,i["shcode"])
client = texttospeech.TextToSpeechClient()
# Set the text input to be synthesized
tmpStr = df8407["종목명"].values[0] + " 매수하겠습니다."
synthesis_input = texttospeech.SynthesisInput(
text=tmpStr)
# Build the voice request, select the language code ("en-US") and the ssml
# voice gender ("neutral")
voice = texttospeech.VoiceSelectionParams(
language_code="ko-KR",
ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL)
# Select the type of audio file you want returned
audio_config = texttospeech.AudioConfig(
audio_encoding=texttospeech.AudioEncoding.MP3)
# Perform the text-to-speech request on the text input with the selected
# voice parameters and audio file type
response = client.synthesize_speech(
input=synthesis_input,
voice=voice,
audio_config=audio_config)
with open("output.mp3", "wb") as out:
# Write the response to the output file.
out.write(response.audio_content)
print('Audio content written to file "output.mp3"')
playsound("output.mp3")
os.remove("output.mp3")
except Exception as e:
print("Exception Occur : ", e)
time.sleep(5)
cnt += 1
print(str(cnt), " 회전(Buy Manager)")
def OnLogin(self, code, msg):
print("OnLogin method is called")
print(str(code))
print(str(msg))
if str(code) == '0000':
XASessionEvents.logInState = 1
