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dsyoon
2023-01-30 09:49:11 +09:00
parent 41fe45c4eb
commit 7f052708dd
3 changed files with 71 additions and 75 deletions
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101
HTS_etf.py
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@@ -98,71 +98,68 @@ class HTS_etf (HTS):
if datetime.strptime(today + " 090000", '%Y%m%d %H%M%S') < THIS_TIME < datetime.strptime(today + " 151500", '%Y%m%d %H%M%S'):
# 3시 까지만 매수를 시도한다.
if THIS_TIME.strftime('%S') == "03":
# 매분 3초마다 실행한다.
for stock in stocks:
for stock in stocks:
# 데이터를 가지고 온다.
result = self.getRealTime(stock['stock_code'], today, LAST_DATA[stock['stock_code']])
# 데이터를 가지고 온다.
result = self.getRealTime(stock['stock_code'], today, LAST_DATA[stock['stock_code']])
result_5 = self.makeTickData(result, mins=5)
result_30 = self.makeTickData(result, mins=30)
result_5 = self.makeTickData(result, mins=5)
result_30 = self.makeTickData(result, mins=30)
data = self.buySellChecker.analyze(result)
data.drop(data.index[:len(data) - analyzed_day], inplace=True)
data = self.buySellChecker.analyze(result)
data.drop(data.index[:len(data) - analyzed_day], inplace=True)
# 5분 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다.
data_5 = self.buySellChecker.analyze(result_5)
# 분석일 데이터만 활용한다 (이전 데이터는 제거)
data_5.drop(data_5.index[:len(data_5) - analyzed_day], inplace=True)
# 5분 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다.
data_5 = self.buySellChecker.analyze(result_5)
# 분석일 데이터만 활용한다 (이전 데이터는 제거)
data_5.drop(data_5.index[:len(data_5) - analyzed_day], inplace=True)
# 30분 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다.
data_30 = self.buySellChecker.analyze(result_30)
# 분석일 데이터만 활용한다 (이전 데이터는 제거)
data_30.drop(data_30.index[:len(data_30) - analyzed_day], inplace=True)
# 30분 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다.
data_30 = self.buySellChecker.analyze(result_30)
# 분석일 데이터만 활용한다 (이전 데이터는 제거)
data_30.drop(data_30.index[:len(data_30) - analyzed_day], inplace=True)
# 사야 할 시점과 팔아야 할 시점을 체크한다.
bsLine = self.buySellChecker.checkTransaction(data, data_5, data_30, isRealTime=True)
bs_buy_price = bsLine['buy'][0]
bs_buy_weight = bsLine['buy_weight'][0]
bs_sell_price = bsLine['sell'][0]
# 사야 할 시점과 팔아야 할 시점을 체크한다.
bsLine = self.buySellChecker.checkTransaction(data, data_5, data_30, isRealTime=True)
bs_buy_price = bsLine['buy'][0]
bs_buy_weight = bsLine['buy_weight'][0]
bs_sell_price = bsLine['sell'][0]
# 미체결 기록을 가져와서 10분 이상 된 매수 주문을 취소 한다.
ORDER_LIST = self.requestOrderList()
orderListToCancel = self.orderChecker.cancel(today, stock['stock_code'], ORDER_LIST)
# 미체결 기록을 가져와서 10분 이상 된 매수 주문을 취소 한다.
ORDER_LIST = self.requestOrderList()
orderListToCancel = self.orderChecker.cancel(today, stock['stock_code'], ORDER_LIST)
if len(orderListToCancel) > 0:
self.cancelOrderList(orderListToCancel)
if bs_buy_price > 0:
buy_count = int(self.MAX_BUY_PRICE/bs_buy_price)
if bs_buy_price > 0:
buy_count = int(self.MAX_BUY_PRICE/bs_buy_price)
# 매수를 주문한다.
orderNum = self.requestOrder(OrderType.buy, stock['stock_code'], buy_count , bs_buy_price)
self.orderChecker.buy(today, stock['stock_code'], buy_count, bs_buy_price, orderNum)
# 매수를 주문한다.
orderNum = self.requestOrder(OrderType.buy, stock['stock_code'], buy_count , bs_buy_price)
self.orderChecker.buy(today, stock['stock_code'], buy_count, bs_buy_price, orderNum)
# slackbot에 메시지를 보냄
self.slackBot.post_to_slack(stock['stock_code'], stock['stock_name'], "BUY", bsLine['buy'][len(bsLine['buy']) - 1], buy_count)
# 로그 출력
print("BUY", THIS_TIME.strftime('%Y%m%d %H%M%S'), orderNum, stock['stock_code'], stock['stock_name'], bs_buy_price, buy_count)
if bs_sell_price > 0:
# 매도한다.
orderNum = self.getSellingPrice(THIS_TIME, stock['stock_code'], bs_sell_price, without_loss=True)
self.orderChecker.sell(today, stock['stock_code'])
# slackbot에 메시지를 보냄
self.slackBot.post_to_slack(stock['stock_code'], stock['stock_name'], "SELL", bsLine['sell'][len(bsLine['sell']) - 1], -1)
# 로그 출력
print("SELL", THIS_TIME.strftime('%Y%m%d %H%M%S'), str(orderNum), stock['stock_code'], stock['stock_name'], bs_sell_price)
# slackbot에 메시지를 보냄
self.slackBot.post_to_slack(stock['stock_code'], stock['stock_name'], "BUY", bsLine['buy'][len(bsLine['buy']) - 1], buy_count)
# 로그 출력
print("TIMECHECK: %s, code: %s, name: %s, buy: %d, sell: %d, avg5: %.2f, avg30: %.2f, open: %d, high: %d, low: %d, slow_k: %.2f, slow_k_5: %.2f, slow_k_30: %.2f" %
(str(THIS_TIME), stock['stock_code'], stock['stock_name'], bs_buy_price, bs_sell_price, data["avg5"][0], data["avg30"][0],
data["open"][0], data["high"][0], data["low"][0], data["slow_k"][0], data_5["slow_k"][0], data_30["slow_k"][0]))
print("BUY", THIS_TIME.strftime('%Y%m%d %H%M%S'), orderNum, stock['stock_code'], stock['stock_name'], bs_buy_price, buy_count)
if bs_sell_price > 0:
# 매도한다.
orderNum = self.getSellingPrice(THIS_TIME, stock['stock_code'], bs_sell_price, without_loss=True)
self.orderChecker.sell(today, stock['stock_code'])
# slackbot에 메시지를 보냄
self.slackBot.post_to_slack(stock['stock_code'], stock['stock_name'], "SELL", bsLine['sell'][len(bsLine['sell']) - 1], -1)
# 로그 출력
print("SELL", THIS_TIME.strftime('%Y%m%d %H%M%S'), str(orderNum), stock['stock_code'], stock['stock_name'], bs_sell_price)
# 로그 출력
print("TIMECHECK: %s, code: %s, name: %s, buy: %d, sell: %d, avg5: %.2f, avg30: %.2f, open: %d, high: %d, low: %d, slow_k: %.2f, slow_k_5: %.2f, slow_k_30: %.2f" %
(str(THIS_TIME), stock['stock_code'], stock['stock_name'], bs_buy_price, bs_sell_price, data["avg5"][0], data["avg30"][0],
data["open"][0], data["high"][0], data["low"][0], data["slow_k"][0], data_5["slow_k"][0], data_30["slow_k"][0]))
elif datetime.strptime(today + " 151530", '%Y%m%d %H%M%S') < THIS_TIME < datetime.strptime(today + " 151600", '%Y%m%d %H%M%S'):
# 3시 15분 30초부터 3시 16분 사이는 잔량을 매도한다.

4
HTS_stocks.py
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@@ -134,7 +134,7 @@ class HTS_Stocks (HTS):
orderNum = self.requestOrder(OrderType.buy, stock_code, buy_count, bs_buy_price)
# slackbot에 메시지를 보냄
self.slackBot.post_to_slack(stock_code, stock_name, "BUY", bsLine['buy'][len(bsLine['buy']) - 1], buy_count)
self.orderChecker.add(today, stock_code, 1, buy_count, bs_buy_price, orderNum)
self.orderChecker.buy(today, stock_code, buy_count, bs_buy_price, orderNum)
# 로그 출력
print("BUY", THIS_TIME.strftime('%Y%m%d %H%M%S'), orderNum, stock_code, stock_name, bs_buy_price, buy_count)
@@ -147,7 +147,7 @@ class HTS_Stocks (HTS):
orderNum = self.getSellingPrice(THIS_TIME, stock_code, bs_sell_price)
# slackbot에 메시지를 보냄
self.slackBot.post_to_slack(stock_code, stock_name, "SELL", bsLine['sell'][len(bsLine['sell']) - 1], -1)
self.orderChecker.delete(today, stock_code)
self.orderChecker.sell(today, stock_code)
# 로그 출력
print("SELL", THIS_TIME.strftime('%Y%m%d %H%M%S'), orderNum, stock_code, stock_name, bs_sell_price)

41
hts/OrderChecker.py
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@@ -18,12 +18,12 @@ class OrderChecker:
order_df = pd.read_csv(saveFileName)
else:
# (type) buy=0, sell=1
order_df = pd.DataFrame(columns=["datetime", "stock_code", "type", "orderNum", "count", "price"])
order_df = pd.DataFrame(columns=["datetime", "stock_code", "type", "orderNum", "canceled", "count", "price"])
if 'Unnamed: 0' in order_df.columns:
order_df.drop(['Unnamed: 0'], axis=1, inplace=True)
order_df = order_df.fillna(0)
order_df = order_df.astype({"stock_code": int, "type": int, "orderNum": int, "count": int, "price": int})
order_df = order_df.astype({"stock_code": int, "type": int, "orderNum": int, "canceled": int, "count": int, "price": int})
order_df['datetime'] = pd.to_datetime(order_df['datetime'])
return order_df
@@ -45,11 +45,9 @@ class OrderChecker:
order_df = self.read(ymd)
# 새로운 주문을 추가한다.
order_df = order_df.append(
{"stock_code": "A" + stock_code, "type": 0, "orderNum": str(orderNum), "canceled": 0, "count": count,
order_df = order_df.append({"stock_code": "A" + stock_code, "type": 0, "orderNum": str(orderNum), "canceled": 0, "count": count,
"price": price, "datetime": datetime.now()}, ignore_index=True)
order_df = order_df.astype(
{"stock_code": str, "type": int, "orderNum": str, "canceled": int, "count": int, "price": int})
order_df = order_df.astype({"stock_code": str, "type": int, "orderNum": str, "canceled": int, "count": int, "price": int})
# 파일로 기록한다.
saveFileName = os.path.join(self.RESOURCE_PATH, "etf_order", ymd + ".csv")
@@ -72,25 +70,26 @@ class OrderChecker:
def cancel(self, ymd, stock_code, ORDER_LIST, min=10):
orderListToCancel = []
order_df = self.read(ymd)
now = datetime.now() - timedelta(minutes=min)
# min 분 이상 된 시간인 내용을 가지고 옴
df = order_df.loc[(order_df.index <= now)]
# 취소가 되지 않은 것만 가지고 옴 (0: 취소 되지 않음, 1: 취소함)
df = df.loc[(order_df["canceled"] == 0)]
if len(order_df) > 0:
now = datetime.now() - timedelta(minutes=min)
# min 분 이상 된 시간인 내용을 가지고 옴
df = order_df.loc[(order_df.index <= now)]
# 취소가 되지 않은 것만 가지고 옴 (0: 취소 되지 않음, 1: 취소함)
df = df.loc[(order_df["canceled"] == 0)]
for i in range(len(df)):
order_df.loc[(order_df.index == df.index[i]), 'canceled'] = 1
for i in range(len(df)):
order_df.loc[(order_df['stock_code']=="A" + stock_code) & (order_df.index == df.index[i]), 'canceled'] = 1
saveFileName = os.path.join(self.RESOURCE_PATH, "etf_order", ymd + ".csv")
order_df.to_csv(saveFileName, index=False)
saveFileName = os.path.join(self.RESOURCE_PATH, "etf_order", ymd + ".csv")
order_df.to_csv(saveFileName, index=False)
orderListToCancel = []
if ORDER_LIST is not None and len(ORDER_LIST) > 0:
orderNumSet = set(list(df["orderNum"]))
for item in ORDER_LIST:
if item.orderNum in orderNumSet:
orderListToCancel.append(item)
if ORDER_LIST is not None and len(ORDER_LIST) > 0:
orderNumSet = set(list(df["orderNum"]))
for item in ORDER_LIST:
if item.orderNum in orderNumSet:
orderListToCancel.append(item)
return orderListToCancel