init

hts/BS.py

@@ -0,0 +1,259 @@
+import pandas as pd
+from stockpredictor.analysis.Common import Common
+from stockpredictor.analysis.Stochastic import Stochastic
+from stockpredictor.analysis.RSI import RSI
+
+class BS:
+
+    common = None
+    stochastic = None
+    rsi = None
+
+    def __init__(self):
+        self.common = Common()
+        self.stochastic = Stochastic()
+        self.rsi = RSI()
+
+        return
+
+    def checkStatus(self, STOCK, last_index):
+        status = set()
+
+        # 정배열 체크
+        temp_status = self.common.check_RightArrange(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 돌파 체크
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "20")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "60")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "120")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "240")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "60")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "120")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "240")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "60", "120")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "60", "240")
+        if temp_status != "":
+            status.add(temp_status)
+        temp_status = self.common.check_Dolpa(STOCK, last_index, "120", "240")
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 20일선 돌파
+        temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '20')
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 60일선 돌파
+        temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '60')
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 120일선 돌파
+        temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '120')
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 240일선 돌파
+        #temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '240')
+        #if temp_status != "":
+        #    status.add(temp_status)
+
+        # 20일선 지지 매수가 추천
+        temp_status = self.common.check_Dolpa_Jiji_20(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 음봉인데 어제보다 종가가 더 높은 경우
+        # 이 경우 정배열 상태인지도 함께 체크를 한다.
+        higher_umbong_status = self.common.checkHigherUmbong(STOCK, last_index)
+        if higher_umbong_status != "":
+            status.add(temp_status)
+
+        # GOLDENCROSS#1은 바로 매수하지 않고, 이 시점 이후로 5일선이 20일선을 하방으로 뚫었다가 다시 20일선을 상방으로 뚫는 순간 매수를 시도한다.
+        # GOLDENCROSS#2은 바로 매수 가능
+        # GOLDENCROSS#3은 바로 매수 가능
+        temp_status = self.common.check_golded_cross(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # YANGBONG
+        # 어제 음봉 이후 장대양봉이었다면, 매수
+        temp_status =  self.common.checkLongYangBongAfterUmBong(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # Doji
+        # 하락 추세에서 도지가 나오면 매수
+        temp_status = self.common.checkDoji(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # Gravestone
+        # 상승 추세에서 그레이브스톤이 나오면 매도
+        temp_status = self.common.checkGravestone(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # Dragonfly
+        # 하락 추세에서 드레곤플라이가 나오면 매수
+        temp_status = self.common.checkDragonfly(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # Hammer
+        temp_status = self.common.checkHammer(STOCK, last_index)
+        # 하락 추세에서 해머가 나오면 매수
+        if temp_status != "":
+            status.add(temp_status)
+
+        # Hangingman
+        temp_status = self.common.checkHangingman(STOCK, last_index)
+        # 상승 추세에서 행잉맨이 나오면 매도
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 상승장악형 (Engulfing) - 다음 날도 양봉이라면 매수
+        # 하락 추세에서 상승장악형이 나오면 매수
+        temp_status = self.common.checkEngulfingHigh(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 하락장악형 (Engulfing)
+        # 상승 추세에서 하락장악형이 나오면 매도
+        temp_status = self.common.checkEngulfingLow(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 상승 포아형 (Harami)
+        # 하락 추세에서 상승포아형이 나오면 매수
+        temp_status = self.common.checkHaramiHigh(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 하락 포아형 (Harami)
+        # 상승 추세에서 하락포아형이 나오면 매도
+        temp_status = self.common.checkHaramiLow(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 관통형 (piercing)
+        # 하락 추세에서 관통형이 나오면 매수
+        temp_status = self.common.checkPiercing(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 흑운형 (Dark-cloud)
+        # 상승 추세에서 흑운형이 나오면 매도
+        temp_status = self.common.checkDarkCloud(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 샛별 (Morning start)
+        # 하락 추세에서 샛별형이 나오면 매수
+        temp_status = self.common.checkMorningstar(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        # 저녁별 (Evening start)
+        # 상승 추세에서 저녁별형이 나오면 매도
+        temp_status = self.common.checkEveningstar(STOCK, last_index)
+        if temp_status != "":
+            status.add(temp_status)
+
+        return status
+
+    def analyze(self, result):
+        df = pd.DataFrame(result["close"])
+
+        max20 = df.rolling(window=10).mean()
+        stddev20 = df.rolling(window=10).std()
+        upper_df = max20 + (stddev20 * 2)                  # 상단 볼린저 밴드
+        lower_df = max20 - (stddev20 * 2)                  # 하단 볼린저 밴드
+
+        window = 5
+        open = result["open"]
+        close = result["close"]
+        high = result["high"]
+        low = result["low"]
+        vol = result["vol"]
+
+        close_df = pd.DataFrame(close)
+        avg1_list = close_df.rolling(window=1).mean().fillna(close[0]).values.tolist()
+        avg1 = [item[0] for item in avg1_list]
+        avg2_list = close_df.rolling(window=2).mean().fillna(close[0]).values.tolist()
+        avg2 = [item[0] for item in avg2_list]
+        avg5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
+        avg5 = [item[0] for item in avg5_list]
+        avg10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
+        avg10 = [item[0] for item in avg10_list]
+        avg20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
+        avg20 = [item[0] for item in avg20_list]
+        avg30_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
+        avg30 = [item[0] for item in avg30_list]
+        avg40_list = close_df.rolling(window=40).mean().fillna(close[0]).values.tolist()
+        avg40 = [item[0] for item in avg40_list]
+        avg50_list = close_df.rolling(window=50).mean().fillna(close[0]).values.tolist()
+        avg50 = [item[0] for item in avg50_list]
+        avg60_list = close_df.rolling(window=60).mean().fillna(close[0]).values.tolist()
+        avg60 = [item[0] for item in avg60_list]
+
+        upper, lower = [], []
+        for i in range(len(upper_df)):
+            if i < window:
+                upper.append(upper_df.values[window - 1][0])
+                lower.append(lower_df.values[window - 1][0])
+            else:
+                upper.append(upper_df.values[i][0])
+                lower.append(lower_df.values[i][0])
+
+        point_temp = result["time"]
+
+        STOCK = []
+        for i in range(len(result["open"])):
+            STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i],
+                          'high': high[i], 'low': low[i], 'avg5': avg2[i],
+                          'avg20': avg5[i], 'avg60': avg10[i], 'avg120': avg20[i],
+                          'avg240': avg30[i]})
+
+        # stochastic 계산
+        stochastic_df = self.stochastic.apply(pd.DataFrame(STOCK))
+        stochastic_df = stochastic_df.fillna(100)
+        fast_k = stochastic_df['fast_k'].values.tolist()
+        slow_k = stochastic_df['slow_k'].values.tolist()
+        slow_d = stochastic_df['slow_d'].values.tolist()
+
+        # rsi 계산
+        rsi_df = self.rsi.apply(pd.DataFrame(STOCK))
+        rsi_df = rsi_df.fillna(100)
+        rsi = rsi_df['rsi'].values.tolist()
+        rsis = rsi_df['rsis'].values.tolist()
+
+        temp = {"Date": point_temp,
+                "Open": open, "High": high, "Low": low, "Close": close, "Volume": vol,
+                "upper": upper, "lower": lower,
+                "avg1": avg1, "avg2": avg2, "avg5": avg5, "avg10": avg10, "avg20": avg20, "avg30": avg30, "avg40": avg40, "avg50": avg50, "avg60": avg60,
+                "fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,
+                "rsi": rsi, "rsis": rsis}
+        data = pd.DataFrame(temp)
+        df_final_time = pd.DatetimeIndex(point_temp)
+        data.index = df_final_time
+
+        return data

hts/HTS.py

@@ -1,14 +1,11 @@
-#import win32com.client
+import win32com.client
 import time
 import os
 from datetime import datetime, timedelta
 import pandas as pd
 from enum import Enum
-import plotly.graph_objects as go
-from stockpredictor.analysis.Common import Common
 
-from stockpredictor.analysis.Stochastic import Stochastic
+from BS import BS
-from stockpredictor.analysis.RSI import RSI
 
 # enum 주문 상태 세팅용
 class EorderBS(Enum):
@@ -33,16 +30,11 @@ class HTS:
 
     objCpCybos = None
     objCpCodeMgr = None
-    common = None
 
-    stochastic = None
+    bs = None
-    rsi = None
 
     def __init__(self):
-        self.common = Common()
+        self.bs = BS()
-        self.stochastic = Stochastic()
-        self.rsi = RSI()
-
         #self.connect()
         return
 
@@ -530,492 +522,54 @@ class HTS:
 
         return
 
-    def getCSV(self, fileName, given_day, result):
+    def checkTransaction(self, data):
-        data = pd.read_csv(fileName)
-
-        days = data.날짜
-        time = data.시간
-        open = data.시가
-        close = data.종가
-        high = data.고가
-        low = data.저가
-        vol = data.거래량
-        start_time = datetime.strptime(given_day + " 090000", '%Y%m%d %H%M%S')
-
-        for i in range(len(data)):
-            temp = datetime.strptime(str(days[i]) + " " + str(time[i]).zfill(4)+"00", '%Y%m%d %H%M%S')
-            if temp < start_time:
-                continue
-
-            if temp not in result["check"]:
-                result["check"].add(temp)
-                result["time"].append(temp)
-                result["open"].append(open[i])
-                result["close"].append(close[i])
-                result["high"].append(high[i])
-                result["low"].append(low[i])
-                result["vol"].append(vol[i])
-        return
-
-    def analyze(self, result):
-        df = pd.DataFrame(result["close"])
-
-        max20 = df.rolling(window=10).mean()
-        stddev20 = df.rolling(window=10).std()
-        upper_df = max20 + (stddev20 * 2)                  # 상단 볼린저 밴드
-        lower_df = max20 - (stddev20 * 2)                  # 하단 볼린저 밴드
-
-        window = 5
-        open = result["open"]
-        close = result["close"]
-        high = result["high"]
-        low = result["low"]
-        vol = result["vol"]
-
-        close_df = pd.DataFrame(close)
-        avg1_list = close_df.rolling(window=1).mean().fillna(close[0]).values.tolist()
-        avg1 = [item[0] for item in avg1_list]
-        avg2_list = close_df.rolling(window=2).mean().fillna(close[0]).values.tolist()
-        avg2 = [item[0] for item in avg2_list]
-        avg5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
-        avg5 = [item[0] for item in avg5_list]
-        avg10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
-        avg10 = [item[0] for item in avg10_list]
-        avg20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
-        avg20 = [item[0] for item in avg20_list]
-        avg30_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
-        avg30 = [item[0] for item in avg30_list]
-        avg40_list = close_df.rolling(window=40).mean().fillna(close[0]).values.tolist()
-        avg40 = [item[0] for item in avg40_list]
-        avg50_list = close_df.rolling(window=50).mean().fillna(close[0]).values.tolist()
-        avg50 = [item[0] for item in avg50_list]
-        avg60_list = close_df.rolling(window=60).mean().fillna(close[0]).values.tolist()
-        avg60 = [item[0] for item in avg60_list]
-
-        upper, lower = [], []
-        for i in range(len(upper_df)):
-            if i < window:
-                upper.append(upper_df.values[window - 1][0])
-                lower.append(lower_df.values[window - 1][0])
-            else:
-                upper.append(upper_df.values[i][0])
-                lower.append(lower_df.values[i][0])
-
-        point_temp = result["time"]
-
-        STOCK = []
-        for i in range(len(result["open"])):
-            STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i],
-                          'high': high[i], 'low': low[i], 'avg5': avg2[i],
-                          'avg20': avg5[i], 'avg60': avg10[i], 'avg120': avg20[i],
-                          'avg240': avg30[i]})
-
-        # stochastic 계산
-        stochastic_df = self.stochastic.apply(pd.DataFrame(STOCK))
-        stochastic_df = stochastic_df.fillna(0)
-        fast_k = stochastic_df['fast_k'].values.tolist()
-        slow_k = stochastic_df['slow_k'].values.tolist()
-        slow_d = stochastic_df['slow_d'].values.tolist()
-
-        # rsi 계산
-        rsi_df = self.rsi.apply(pd.DataFrame(STOCK))
-        rsi_df = rsi_df.fillna(0)
-        rsi = rsi_df['rsi'].values.tolist()
-        rsis = rsi_df['rsis'].values.tolist()
-
-        temp = {"Date": point_temp,
-                "Open": open, "High": high, "Low": low, "Close": close, "Volume": vol,
-                "avg1": avg1, "avg2": avg2, "avg5": avg5, "avg10": avg10, "avg20": avg20, "avg30": avg30, "avg40": avg40, "avg50": avg50, "avg60": avg60,
-                "fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,
-                "rsi": rsi, "rsis": rsis}
-        data = pd.DataFrame(temp)
-        df_final_time = pd.DatetimeIndex(point_temp)
-        data.index = df_final_time
-
-        return data, upper, lower
-
-    def draw(self, stock_code, given_day, data, upper, lower, bsLine):
-        buy_line = bsLine['buy']
-        sell_line = bsLine['sell']
-
-        # 그래프 설정을 위한 변수를 생성한다.
-        data['Open'] = pd.to_numeric(data['Open'])
-        data['High'] = pd.to_numeric(data['High'])
-        data['Low'] = pd.to_numeric(data['Low'])
-        data['Close'] = pd.to_numeric(data['Close'])
-        data['Volume'] = pd.to_numeric(data['Volume'])
-        data['avg1'] = pd.to_numeric(data['avg1'])
-        data['avg2'] = pd.to_numeric(data['avg2'])
-        data['avg5'] = pd.to_numeric(data['avg5'])
-        data['avg10'] = pd.to_numeric(data['avg10'])
-        data['avg20'] = pd.to_numeric(data['avg20'])
-        data['avg30'] = pd.to_numeric(data['avg30'])
-        data['avg40'] = pd.to_numeric(data['avg40'])
-        data['avg50'] = pd.to_numeric(data['avg50'])
-        data['avg60'] = pd.to_numeric(data['avg60'])
-
-        buy_colors = []
-        for i in range(len(buy_line)):
-            if buy_line[i] < 0:
-                buy_colors.append("#ffffff")
-                buy_line[i] = lower[0]
-            else:
-                buy_colors.append("#ff00ff")
-        sell_colors = []
-        for i in range(len(sell_line)):
-            if sell_line[i] < 0:
-                sell_colors.append("#ffffff")
-                sell_line[i] = lower[0]
-            else:
-                sell_colors.append("#00ced1")
-
-        # 그래프를 설정한다.
-        buy_check = go.Scatter(x=data['Date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0))
-        sell_check = go.Scatter(x=data['Date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
-        bolinger_upper = go.Scatter(x=data['Date'], y=upper, name="upper", line_color='#8B4513')
-        bolinger_lower = go.Scatter(x=data['Date'], y=lower, name="lower", line_color='#8B4513')
-        avg1 = go.Scatter(x=data['Date'], y=data['avg1'], name="avg1", line_color='#FF0000')
-        avg2 = go.Scatter(x=data['Date'], y=data['avg2'], name="avg2", line_color='#A200FF')
-        avg5 = go.Scatter(x=data['Date'], y=data['avg5'], name="avg5", line_color='#0800FF')
-        avg10 = go.Scatter(x=data['Date'], y=data['avg10'], name="avg10", line_color='#FF7C00')
-        avg20 = go.Scatter(x=data['Date'], y=data['avg20'], name="avg20", line_color='#00AAFF')
-        avg30 = go.Scatter(x=data['Date'], y=data['avg30'], name="avg30", line_color='#FFD100')
-        avg40 = go.Scatter(x=data['Date'], y=data['avg40'], name="avg40", line_color='#A600FF')
-        avg50 = go.Scatter(x=data['Date'], y=data['avg50'], name="avg50", line_color='#FF00E0')
-        avg60 = go.Scatter(x=data['Date'], y=data['avg60'], name="avg60", line_color='#000000')
-
-
-        candle_stick = go.Candlestick(x=data['Date'], open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], increasing_line_color='red', decreasing_line_color='blue')
-
-        # 그래프를 그린다.
-        fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, avg1, avg2, avg5, avg10, avg20, avg30, avg40, avg50, avg60])
-        fig.update_layout(title=stock_code + "_" + given_day)
-        fig.show()
-        return
-
-    def checkStatus(self, STOCK, last_index):
-        status = set()
-
-        # 정배열 체크
-        temp_status = self.common.check_RightArrange(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 돌파 체크
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "20")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "60")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "120")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "240")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "60")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "120")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "240")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "60", "120")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "60", "240")
-        if temp_status != "":
-            status.add(temp_status)
-        temp_status = self.common.check_Dolpa(STOCK, last_index, "120", "240")
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 20일선 돌파
-        temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '20')
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 60일선 돌파
-        temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '60')
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 120일선 돌파
-        temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '120')
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 240일선 돌파
-        #temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '240')
-        #if temp_status != "":
-        #    status.add(temp_status)
-
-        # 20일선 지지 매수가 추천
-        temp_status = self.common.check_Dolpa_Jiji_20(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 음봉인데 어제보다 종가가 더 높은 경우
-        # 이 경우 정배열 상태인지도 함께 체크를 한다.
-        higher_umbong_status = self.common.checkHigherUmbong(STOCK, last_index)
-        if higher_umbong_status != "":
-            status.add(temp_status)
-
-        # GOLDENCROSS#1은 바로 매수하지 않고, 이 시점 이후로 5일선이 20일선을 하방으로 뚫었다가 다시 20일선을 상방으로 뚫는 순간 매수를 시도한다.
-        # GOLDENCROSS#2은 바로 매수 가능
-        # GOLDENCROSS#3은 바로 매수 가능
-        temp_status = self.common.check_golded_cross(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # YANGBONG
-        # 어제 음봉 이후 장대양봉이었다면, 매수
-        temp_status =  self.common.checkLongYangBongAfterUmBong(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # Doji
-        # 하락 추세에서 도지가 나오면 매수
-        temp_status = self.common.checkDoji(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # Gravestone
-        # 상승 추세에서 그레이브스톤이 나오면 매도
-        temp_status = self.common.checkGravestone(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # Dragonfly
-        # 하락 추세에서 드레곤플라이가 나오면 매수
-        temp_status = self.common.checkDragonfly(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # Hammer
-        temp_status = self.common.checkHammer(STOCK, last_index)
-        # 하락 추세에서 해머가 나오면 매수
-        if temp_status != "":
-            status.add(temp_status)
-
-        # Hangingman
-        temp_status = self.common.checkHangingman(STOCK, last_index)
-        # 상승 추세에서 행잉맨이 나오면 매도
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 상승장악형 (Engulfing) - 다음 날도 양봉이라면 매수
-        # 하락 추세에서 상승장악형이 나오면 매수
-        temp_status = self.common.checkEngulfingHigh(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 하락장악형 (Engulfing)
-        # 상승 추세에서 하락장악형이 나오면 매도
-        temp_status = self.common.checkEngulfingLow(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 상승 포아형 (Harami)
-        # 하락 추세에서 상승포아형이 나오면 매수
-        temp_status = self.common.checkHaramiHigh(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 하락 포아형 (Harami)
-        # 상승 추세에서 하락포아형이 나오면 매도
-        temp_status = self.common.checkHaramiLow(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 관통형 (piercing)
-        # 하락 추세에서 관통형이 나오면 매수
-        temp_status = self.common.checkPiercing(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 흑운형 (Dark-cloud)
-        # 상승 추세에서 흑운형이 나오면 매도
-        temp_status = self.common.checkDarkCloud(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 샛별 (Morning start)
-        # 하락 추세에서 샛별형이 나오면 매수
-        temp_status = self.common.checkMorningstar(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        # 저녁별 (Evening start)
-        # 상승 추세에서 저녁별형이 나오면 매도
-        temp_status = self.common.checkEveningstar(STOCK, last_index)
-        if temp_status != "":
-            status.add(temp_status)
-
-        return status
-
-    def checkTransaction_Realtime(self, data, upper, lower):
         size = len(data["Close"])
-        STOCK = []
-        for i in range(size):
-            STOCK.append({'volume': data['Volume'][i], 'close': data["Close"][i], 'open': data["Open"][i], 'high': data["High"][i], 'low': data["Low"][i], 'avg2': data["avg2"][i], 'avg5': data["avg5"][i], 'avg10': data["avg10"][i], 'avg20': data["avg20"][i], 'avg30': data["avg30"], 'avg40': data["avg40"], 'avg50': data["avg50"], 'avg60': data["avg60"][i]})
 
         bsLine = {}
         bsLine['buy']  = [-1 for i in range(size)]
+        bsLine['weight'] = [-1 for i in range(size)]
         bsLine['sell'] = [-1 for i in range(size)]
 
         i = size - 1
-        """
+        if i > 20:
-        status = self.checkStatus(STOCK, i)
+            if data["High"][i] > data["upper"][i]:
-        count_1 = 0
+                bsLine['sell'][i] = data["High"][i]
-        # if "GOLDEN#2_" in status: count_1 += 1
-        # if "arrange_" in status: count_1 += 1
-        # if "UMYANG_" in status: count_1 += 1
-        # if "5-20_" in status: count_1 += 1
-        if "5_20_" in status: count_1 += 1
-        if "5_60_" in status: count_1 += 1
-        if "5_120_" in status: count_1 += 1
-        if "5_240_" in status: count_1 += 1
-        if "20_60_" in status: count_1 += 1
-        if "20_120_" in status: count_1 += 1
-        if "20_240_" in status: count_1 += 1
-        if "60_120_" in status: count_1 += 1
-        if "60_240_" in status: count_1 += 1
-        if "120_240_" in status: count_1 += 1
-        if "arrange_" in status and "HIGHERUMBONG_" in status: count_1 += 1
-        if "20_" in status: count_1 += 1
-        if "60_" in status: count_1 += 1
-        if "120_" in status: count_1 += 1
-        if "240_" in status: count_1 += 1
-        if "GOLDEN#3_" in status: count_1 += 1
-        if "DOJI_" in status: count_1 += 1
-        if "DRAGONEFLY_" in status: count_1 += 1
-        if "HAMMER_" in status: count_1 += 1
-        if "ENHIGH_" in status: count_1 += 1
-        if "HAHIGH_" in status: count_1 += 1
-        if "PIERCING_" in status: count_1 += 1
-        if "MORNINGSTAR_" in status: count_1 += 1
-        count_0 = 0
-        if "GRAVESTONE_" in status: count_0 += 1
-        if "HANGINGMAN_" in status: count_0 += 1
-        if "ENLOW_" in status: count_0 += 1
-        if "HALOW_" in status: count_0 += 1
-        if "DARKCLOUD_" in status: count_0 += 1
-        if "EVENINGSTAR" in status: count_0 += 1
 
-        # real time 에서는 현재 기점에 사고 파는 가격을 표기한다.
+            if data["slow_k"][i] <= 36:
-        if count_0 == 0 and count_1 > 0:
+                if data["Low"][i] < data["lower"][i]:
-            bsLine['buy'][i] = STOCK[i]['close'] - 5
+                    bsLine['buy'][i] = data["Close"][i] - 5
-            bsLine['sell'][i] = STOCK[i]['close']
+                if data["slow_k"][i] <= 25:
-        if count_0 > 0:
+                    if data["slow_k"][i - 1] < data["slow_d"][i - 1] and data["slow_d"][i] < data["slow_k"][i]:
-            bsLine['buy'][i] = 0
+                        bsLine['buy'][i] = data["Close"][i] - 5
-            bsLine['sell'][i] = STOCK[i]['close'] + 5
-        """
 
-        if STOCK[i]['low'] < lower[i]:
+            # rsi가 rsis 위로 올라오며 15 이하일 경우 10배로 주문함 (14:30 이전)
-            bsLine['buy'][i] = STOCK[i]['close'] - 5
+            if data["rsi"][i] < 15 and data["rsis"][i] < 15 and data["rsi"][i - 1] < data["rsis"][i - 1] and data["rsis"][i] < data["rsi"][i]:
-        if STOCK[i]['close'] > upper[i]:
+                bsLine['buy'][i] = data["Close"][i] - 5
-            bsLine['sell'][i] = STOCK[i]['close'] + 5
+                bsLine['weight'][i] = 10
-        return bsLine['buy'][i], bsLine['sell'][i]
 
+            if data["slow_k"][i] == 1:
+                bsLine['weight'][i] = 8
+            elif data["slow_k"][i] in(2,3):
+                bsLine['weight'][i] = 7
+            elif data["slow_k"][i] in(4,5,6):
+                bsLine['weight'][i] = 6
+            elif data["slow_k"][i] in(7,8,9,10):
+                bsLine['weight'][i] = 5
+            elif data["slow_k"][i] in(11,12,13,14,15):
+                bsLine['weight'][i] = 4
+            elif data["slow_k"][i] in(16,17,18,19,20,21):
+                bsLine['weight'][i] = 3
+            elif data["slow_k"][i] in(22,23,24,25,26,27,28):
+                bsLine['weight'][i] = 2
+            elif data["slow_k"][i] in(29,30,31,32,33,34,35,36):
+                bsLine['weight'][i] = 1
+            if data["rsi"][i] < 10:
+                bsLine['weight'][i] = 8
+            if i<=20:
+                bsLine['weight'][i] = 1
 
-    def checkTransaction_Simulation(self, data, upper, lower):
+        return bsLine['buy'][i], bsLine['weight'][i], bsLine['sell'][i]
-        size = len(data["Close"])
-        STOCK = []
-        for i in range(size):
-            STOCK.append({'volume': data['Volume'][i], 'close': data["Close"][i], 'open': data["Open"][i], 'high': data["High"][i], 'low': data["Low"][i], 'avg5': data["avg2"][i], 'avg20': data["avg5"][i], 'avg60': data["avg10"][i], 'avg120': data["avg20"][i], 'avg240': data["avg30"][i]})
 
-        bsLine = {}
-        bsLine['buy'] = [-1 for i in range(len(lower))]
-        bsLine['sell'] = [-1 for i in range(len(lower))]
-
-        for i in range(5, size-5):
-            """
-            status = self.checkStatus(STOCK, i)
-            count_1 = 0
-            #if "GOLDEN#2_" in status: count_1 += 1
-            #if "arrange_" in status: count_1 += 1
-            #if "UMYANG_" in status: count_1 += 1
-            #if "5-20_" in status: count_1 += 1
-            if "5_20_" in status: count_1 += 1
-            if "5_60_" in status: count_1 += 1
-            if "5_120_" in status: count_1 += 1
-            if "5_240_" in status: count_1 += 1
-            if "20_60_" in status: count_1 += 1
-            if "20_120_" in status: count_1 += 1
-            if "20_240_" in status: count_1 += 1
-            if "60_120_" in status: count_1 += 1
-            if "60_240_" in status: count_1 += 1
-            if "120_240_" in status: count_1 += 1
-            if "arrange_" in status and "HIGHERUMBONG_" in status: count_1 += 1
-            if "20_" in status: count_1 += 1
-            if "60_" in status: count_1 += 1
-            if "120_" in status: count_1 += 1
-            if "240_" in status: count_1 += 1
-            if "GOLDEN#3_" in status: count_1 += 1
-            if "DOJI_" in status: count_1 += 1
-            if "DRAGONEFLY_" in status: count_1 += 1
-            if "HAMMER_" in status: count_1 += 1
-            if "ENHIGH_" in status: count_1 += 1
-            if "HAHIGH_" in status: count_1 += 1
-            if "PIERCING_" in status: count_1 += 1
-            if "MORNINGSTAR_" in status: count_1 += 1
-            count_0 = 0
-            if "GRAVESTONE_" in status: count_0 += 1
-            if "HANGINGMAN_" in status: count_0 += 1
-            if "ENLOW_" in status: count_0 += 1
-            if "HALOW_" in status: count_0 += 1
-            if "DARKCLOUD_" in status: count_0 += 1
-            if "EVENINGSTAR" in status: count_0 += 1
-
-            # 시뮬레이션은 이번에 사고 파는 것으로 판단했기 때문에, 다음 봉에서 사고 판 위치를 표시한다.
-            if count_0 == 0 and count_1 > 0:
-                bsLine['buy'][i + 1] = STOCK[i]['close'] - 5
-                #bsLine['sell'][i + 2] = STOCK[i]['close']
-            #if count_0 > 0:
-            #    bsLine['sell'][i + 2] = STOCK[i]['close'] + 5
-            if data["avg60"][i - 1] > data["avg60"][i]:
-                bsLine['sell'][i] = STOCK[i]['close']
-            """
-
-            if STOCK[i]['low'] < lower[i]:
-                bsLine['buy'][i] = STOCK[i]['close'] - 5
-            if STOCK[i]['close'] > upper[i]:
-                bsLine['sell'][i] = STOCK[i]['close'] + 5
-        return bsLine
-
-
-    def simulate(self, stock_code, given_day):
-        #timecheckList = pd.read_csv("timecheck.csv").values.tolist()
-        #timecheck = {datetime.strptime(given_day + " " + str(second).zfill(6), '%Y%m%d %H%M%S'): False for second, check in timecheckList}
-
-        result = {"check": set(),
-                  "time": [],
-                  "open": [],
-                  "close": [],
-                  "high": [],
-                  "low": [],
-                  "vol": []}
-
-        # 데이터를 가지고 온다.
-        self.getCSV("./data/"+stock_code+"_"+given_day+".csv", given_day, result)
-
-        # 분석을 통해서 볼린저밴드 상/하단을 계산한다.
-        data, upper, lower = self.analyze(result)
-
-        # 사야 할 시점과 팔아야 할 시점을 체크한다.
-        bsLine = self.checkTransaction_Simulation(data, upper, lower)
-
-        # 그래프를 그린다.
-        self.draw(stock_code, given_day, data, upper, lower, bsLine)
-
-        # 가져온 만큼 데이터를 누적해서 파일로 작성한다.
-        # self.write(given_day, result)
-
-        return
 
     def getSellingPrice(self, final_price):
         # 만약 잔고가 있으면 장부가보다 5원 높게 매도한다.
@@ -1071,9 +625,9 @@ class HTS:
                     self.getRealTime(stock_code, given_day, result)
 
                     # 분석을 통해서 볼린저밴드 상/하단을 계산한다.
-                    data, upper, lower = self.analyze(result)
+                    data = self.bs.analyze(result)
                     # 사야 할 시점/가격과 팔아야 할 시점/가격을 체크한다.
-                    bs_buy_price, bs_sell_price = self.checkTransaction_Realtime(data, upper, lower)
+                    bs_buy_price, bs_weight, bs_sell_price = self.checkTransaction(data)
                     final_price = data["Close"][len(data["Close"])-1]
 
                     if bs_buy_price > 0:
@@ -1131,23 +685,10 @@ if __name__ == "__main__":
     PROJECT_HOME = os.path.join(os.path.dirname(os.path.join(os.path.dirname(__file__))))
     RESOURCE_DIR = PROJECT_HOME + "/resources/analysis/"+today.strftime("%Y%m%d")
 
-    stock_codes = ["252670", "122630"]
-    given_days = ['20210901','20210902','20210903','20210906','20210907','20210908','20210909','20210910','20210913','20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929','20210930','20211001', '20211005']
-    given_days = ['20210901']
-
     hts = HTS()
-
+    stock_codes = ["252670", "122630"]
-    #hts.all_stocks()
+    given_day = datetime.today().strftime('%Y%m%d')
-    #hts.getChartData(stock_codes)
-    #hts.currentStock(stock_codes)
-    #for given_day in given_days:
-        #hts.writeStockData(stock_codes, given_day)
-        #for stock_code in stock_codes:
-            #hts.simulate(stock_code, given_day)
-
-    #given_day = datetime.today().strftime('%Y%m%d')
     #hts.writeStockData(stock_codes, given_day)
-    hts.simulate(stock_codes[0], given_days[0])
+    hts.buyRealTime(stock_codes[0], given_day)
-    #hts.buyRealTime(stock_codes[0], given_day)
 
     print ("done...")

hts/Simulation.py

@@ -0,0 +1,199 @@
+import os
+from datetime import datetime, timedelta
+import pandas as pd
+import plotly.graph_objects as go
+from plotly import subplots
+
+from BS import BS
+
+class Simulation:
+
+    bs = None
+    def __init__(self):
+        self.bs = BS()
+        #self.connect()
+        return
+
+    def getCSV(self, fileName, given_day, result):
+        data = pd.read_csv(fileName)
+
+        days = data.날짜
+        time = data.시간
+        open = data.시가
+        close = data.종가
+        high = data.고가
+        low = data.저가
+        vol = data.거래량
+        start_time = datetime.strptime(given_day + " 090000", '%Y%m%d %H%M%S')
+
+        for i in range(len(data)):
+            temp = datetime.strptime(str(days[i]) + " " + str(time[i]).zfill(4)+"00", '%Y%m%d %H%M%S')
+            if temp < start_time:
+                continue
+
+            if temp not in result["check"]:
+                result["check"].add(temp)
+                result["time"].append(temp)
+                result["open"].append(open[i])
+                result["close"].append(close[i])
+                result["high"].append(high[i])
+                result["low"].append(low[i])
+                result["vol"].append(vol[i])
+        return
+
+    def checkTransaction(self, data):
+        size = len(data["Close"])
+
+        bsLine = {}
+        bsLine['buy'] = [-1 for i in range(size)]
+        bsLine['weight'] = [-1 for i in range(size)]
+        bsLine['sell'] = [-1 for i in range(size)]
+
+        for i in range(21, size-5):
+            if data["High"][i] > data["upper"][i]:
+                bsLine['sell'][i] = data["High"][i]
+
+            if data["slow_k"][i] <= 36:
+                if data["Low"][i] < data["lower"][i]:
+                    bsLine['buy'][i] = data["Close"][i] - 5
+                if data["slow_k"][i] <= 25:
+                    if data["slow_k"][i - 1] < data["slow_d"][i - 1] and data["slow_d"][i] < data["slow_k"][i]:
+                        bsLine['buy'][i] = data["Close"][i] - 5
+
+            # rsi가 rsis 위로 올라오며 15 이하일 경우 10배로 주문함 (14:30 이전)
+            if data["rsi"][i] < 15 and data["rsis"][i] < 15 and data["rsi"][i - 1] < data["rsis"][i - 1] and data["rsis"][i] < data["rsi"][i]:
+                bsLine['buy'][i] = data["Close"][i] - 5
+                bsLine['weight'][i] = 10
+
+            if data["slow_k"][i] == 1:
+                bsLine['weight'][i] = 8
+            elif data["slow_k"][i] in(2,3):
+                bsLine['weight'][i] = 7
+            elif data["slow_k"][i] in(4,5,6):
+                bsLine['weight'][i] = 6
+            elif data["slow_k"][i] in(7,8,9,10):
+                bsLine['weight'][i] = 5
+            elif data["slow_k"][i] in(11,12,13,14,15):
+                bsLine['weight'][i] = 4
+            elif data["slow_k"][i] in(16,17,18,19,20,21):
+                bsLine['weight'][i] = 3
+            elif data["slow_k"][i] in(22,23,24,25,26,27,28):
+                bsLine['weight'][i] = 2
+            elif data["slow_k"][i] in(29,30,31,32,33,34,35,36):
+                bsLine['weight'][i] = 1
+            if data["rsi"][i] < 10:
+                bsLine['weight'][i] = 8
+            if i<=20:
+                bsLine['weight'][i] = 1
+
+        return bsLine
+
+    def draw(self, stock_code, given_day, data, bsLine):
+        buy_line = bsLine['buy']
+        sell_line = bsLine['sell']
+
+        # 그래프 설정을 위한 변수를 생성한다.
+        data['Open'] = pd.to_numeric(data['Open'])
+        data['High'] = pd.to_numeric(data['High'])
+        data['Low'] = pd.to_numeric(data['Low'])
+        data['Close'] = pd.to_numeric(data['Close'])
+        data['Volume'] = pd.to_numeric(data['Volume'])
+        data["fast_k"] = pd.to_numeric(data['fast_k'])
+        data["slow_k"] = pd.to_numeric(data['slow_k'])
+        data["slow_d"] = pd.to_numeric(data['slow_d'])
+        data["rsi"] = pd.to_numeric(data['rsi'])
+        data["rsis"] = pd.to_numeric(data['rsis'])
+
+        buy_colors = []
+        for i in range(len(buy_line)):
+            if buy_line[i] < 0:
+                buy_colors.append("#ffffff")
+                buy_line[i] = data["lower"][0]
+            else:
+                buy_colors.append("#ff00ff")
+        sell_colors = []
+        for i in range(len(sell_line)):
+            if sell_line[i] < 0:
+                sell_colors.append("#ffffff")
+                sell_line[i] = data["lower"][0]
+            else:
+                sell_colors.append("#00ced1")
+
+        # 그래프를 설정한다.
+        buy_check = go.Scatter(x=data['Date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0))
+        sell_check = go.Scatter(x=data['Date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
+        bolinger_upper = go.Scatter(x=data['Date'], y=data["upper"], name="upper", line_color='#8B4513')
+        bolinger_lower = go.Scatter(x=data['Date'], y=data["lower"], name="lower", line_color='#8B4513')
+
+        candle_stick = go.Candlestick(x=data['Date'], open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], increasing_line_color='red', decreasing_line_color='blue')
+        fast_k_line = go.Scatter(x=data['Date'], y=data["fast_k"], mode='lines', name='fast_k')
+        slow_k_line = go.Scatter(x=data['Date'], y=data["slow_k"], mode='lines', name='slow_k')
+        slow_d_line = go.Scatter(x=data['Date'], y=data["slow_d"], mode='lines', name='slow_d')
+        rsi_line = go.Scatter(x=data['Date'], y=data["rsi"], mode='lines', name='rsi')
+        rsis_line = go.Scatter(x=data['Date'], y=data["rsis"], mode='lines', name='rsis')
+
+        #candle_data = [candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, avg1, avg2, avg5, avg10, avg20, avg30, avg40, avg50, avg60]
+        candle_data = [candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check]
+        stochastic_data = [slow_k_line, slow_d_line]
+        rsi_data = [rsi_line, rsis_line]
+
+        # 그래프를 그린다.
+        """
+        fig = go.Figure(data=candle_data)
+        fig.update_layout(title=stock_code + "_" + given_day)
+        fig.show()
+        """
+
+        fig = subplots.make_subplots(rows=3, cols=1, subplot_titles=('캔들', "스토캐스틱", "RSI"))
+        for trace in candle_data:
+            fig.append_trace(trace, 1, 1)
+        for trace in stochastic_data:
+            fig.append_trace(trace, 2, 1)
+        for trace in rsi_data:
+            fig.append_trace(trace, 3, 1)
+        #fig.update_xaxes(nticks=5)
+        #fig.update_layout(height=1800, title=stock_code + "_" + given_day, xaxis_rangeslider_visible=False)
+        fig.update_layout(height=1800, title=stock_code + "_" + given_day)
+        fig.show()
+
+        return
+
+    def simulate(self, stock_code, given_day):
+        result = {"check": set(),
+                  "time": [],
+                  "open": [],
+                  "close": [],
+                  "high": [],
+                  "low": [],
+                  "vol": []}
+
+        # 데이터를 가지고 온다.
+        self.getCSV("./data/"+stock_code+"_"+given_day+".csv", given_day, result)
+
+        # 분석을 통해서 볼린저밴드 상/하단을 계산한다.
+        data = self.bs.analyze(result)
+
+        # 사야 할 시점과 팔아야 할 시점을 체크한다.
+        bsLine = self.checkTransaction(data)
+
+        # 그래프를 그린다.
+        self.draw(stock_code, given_day, data, bsLine)
+
+        return
+
+if __name__ == "__main__":
+
+    today = datetime.today()
+
+    PROJECT_HOME = os.path.join(os.path.dirname(os.path.join(os.path.dirname(__file__))))
+    RESOURCE_DIR = PROJECT_HOME + "/resources/analysis/"+today.strftime("%Y%m%d")
+
+    stock_codes = ["252670", "122630"]
+    given_days = ['20210901','20210902','20210903','20210906','20210907','20210908','20210909','20210910','20210913','20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929','20210930','20211001', '20211005']
+    given_days = ['20211008']
+
+    simulation = Simulation()
+
+    simulation.simulate(stock_codes[0], given_days[0])
+
+    print ("done...")