init

stockpredictor/analysis/Analyzer.py

@@ -3,17 +3,13 @@ import os
 import time
 import shutil
 from stockpredictor.analysis.Common import Common
-from stockpredictor.analysis.MACD import MACD
-from stockpredictor.analysis.RSI import RSI
 from stockpredictor.analysis.Stochastic import Stochastic
-from stockpredictor.analysis.IchimokuCloud import IchimokuCloud
 import matplotlib.pyplot as plt
 import datetime
 import sqlite3
 from datetime import datetime
 
 from matplotlib import rc
-import math
 
 rc('font', family='AppleGothic')
 plt.rcParams['axes.unicode_minus'] = False
@@ -30,10 +26,7 @@ class Analyzer:
     stocks = None
     candidate = None
 
-    macd = None
-    rsi = None
     stochastic = None
-    ichimokuCloud = None
 
     common = None
     inFileName = None
@@ -51,10 +44,7 @@ class Analyzer:
 
         self.common = Common()
 
-        self.macd = MACD()
-        self.rsi = RSI()
         self.stochastic = Stochastic()
-        self.ichimokuCloud = IchimokuCloud()
 
         self.readFnguide()
         return
@@ -97,57 +87,29 @@ class Analyzer:
         if last_index > 300:
             index = 300  # 최대 300일치 그래프 확인
             df_stock = pd.DataFrame(stock["PRICE"][len(stock["PRICE"]) - index:])
-            df_macd = pd.DataFrame(stock["MACD"][len(stock["MACD"]) - index:last_index+1])
             df_stochastic = pd.DataFrame(stock["STOCHASTIC"][len(stock["STOCHASTIC"]) - index:last_index+1])
-            df_rsi = pd.DataFrame(stock["RSI"][len(stock["RSI"]) - index:last_index+1])
-            df_ichimoku = pd.DataFrame(stock["ICHIMOKU"][len(stock["ICHIMOKU"]) - index:])
         else:
             index = last_index
             df_stock = pd.DataFrame(stock["PRICE"][:index+1])
-            df_macd = pd.DataFrame(stock["MACD"][:index+1])
             df_stochastic = pd.DataFrame(stock["STOCHASTIC"][:index+1])
-            df_ichimoku = pd.DataFrame(stock["ICHIMOKU"][:index+1])
-            df_rsi = pd.DataFrame(stock["RSI"][:index+1])
 
         # general
         volume = go.Bar(x=df_stock.DATE, y=df_stock['volume'], name="volume")
         volume_data = [volume]
 
-        leadingSpan1 = go.Scatter(x=df_ichimoku.DATE, y=df_ichimoku['leadingSpan1'], name="선행스팬", line_color='#8B4513')
-        leadingSpan2 = go.Scatter(x=df_ichimoku.DATE, y=df_ichimoku['leadingSpan2'], name="후행스팬", line_color='#4169E1')
-        cnadle = go.Candlestick(x=df_stock.DATE, open=df_stock.open, high=df_stock.high, low=df_stock.low, close=df_stock.close, increasing_line_color= 'red', decreasing_line_color= 'blue')
-        ichimokuCloud_data = [leadingSpan1, leadingSpan2, cnadle]
-
-        # macd
-        macd = go.Scatter(x=df_macd.DATE, y=df_macd['macd'], name="MACD", line_color='#8B4513')
-        macd_signal = go.Scatter(x=df_macd.DATE, y=df_macd['macds'], name="MACD Signal", line_color='#4169E1')
-        oscillator = go.Bar(x=df_macd.DATE, y=df_macd['macdo'], name="oscillator")
-        macd_data = [macd, macd_signal, oscillator]
-
         # stochastic
         slow_k = go.Scatter(x=df_stochastic.DATE, y=df_stochastic['slow_k'], name="Slow%K", line_color='#8B4513')
         slow_d = go.Scatter(x=df_stochastic.DATE, y=df_stochastic['slow_d'], name="Slow%D", line_color='#4169E1')
         stochastic_data = [slow_k, slow_d]
 
-        # rsi
-        rsi = go.Scatter(x=df_macd.DATE, y=df_rsi['rsi'], name="RSI", line_color='#8B4513')
-        rsi_signal = go.Scatter(x=df_macd.DATE, y=df_rsi['rsis'], name="RSI Signal", line_color='#4169E1')
-        rsi_data = [rsi, rsi_signal]
+        fig = subplots.make_subplots(rows=2, cols=1, subplot_titles=('거래량', 'Stochastic'))
 
-        fig = subplots.make_subplots(rows=5, cols=1, subplot_titles=('MACD', 'Stochastic', 'RSI', '거래량', '일목균형표'))
-
-        for trace in macd_data:
+        for trace in volume_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)
-        for trace in volume_data:
-            fig.append_trace(trace, 4, 1)
-        for trace in ichimokuCloud_data:
-            fig.append_trace(trace, 5, 1)
 
-        fig.update_layout(height=2000)
+        fig.update_layout(height=800)
 
         return fig
 
@@ -157,63 +119,6 @@ class Analyzer:
                 return i-1
         return len(stock['PRICE']) - 1
 
-    def analyzeMACD(self):
-        conn = sqlite3.connect(self.inFileName)
-        cursor = conn.cursor()
-
-        # 기존 분석 데이터를 모두 지움
-        cursor.execute('update ' + self.tableName + ' set MACD = ""')
-
-        rowid = 1
-        cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
-        result = cursor.fetchone()
-        while result != None:
-            stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2])}
-            results = self.macd.analyze(stock)
-            text = json.dumps(results, ensure_ascii=False)
-            cursor.execute("UPDATE " + self.tableName + " SET MACD=? WHERE CODE=?", (text, stock["CODE"]))
-
-            print("#analyzeMACD", rowid, stock['NAME'])
-            rowid += 1
-            cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
-            result = cursor.fetchone()
-
-        conn.commit()
-        cursor.close()
-        conn.close()
-
-        return
-
-    def analyzeRSI(self):
-        conn = sqlite3.connect(self.inFileName)
-        cursor = conn.cursor()
-
-        # 기존 분석 데이터를 모두 지움
-        cursor.execute('update ' + self.tableName + ' set RSI = ""')
-
-        rowid = 1
-        cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
-        result = cursor.fetchone()
-        while result != None:
-            prices = json.loads(result[2])
-            for price in prices:
-                del price['diff']
-            stock = {"CODE": result[0], "NAME": result[1], "PRICE": prices}
-            results = self.rsi.analyze(stock)
-            text = json.dumps(results, ensure_ascii=False)
-            cursor.execute("UPDATE " + self.tableName + " SET RSI=? WHERE CODE=?", (text, stock["CODE"]))
-
-            print("#analyzeRSI", rowid, stock['NAME'])
-            rowid += 1
-            cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
-            result = cursor.fetchone()
-
-        conn.commit()
-        cursor.close()
-        conn.close()
-
-        return
-
     def analyzeStochastic(self):
         conn = sqlite3.connect(self.inFileName)
         cursor = conn.cursor()
@@ -240,33 +145,7 @@ class Analyzer:
         conn.close()
         return
 
-    def analyzeIchimokuCloud(self):
-        conn = sqlite3.connect(self.inFileName)
-        cursor = conn.cursor()
-
-        # 기존 분석 데이터를 모두 지움
-        cursor.execute('update ' + self.tableName + ' set ICHIMOKU = ""')
-
-        rowid = 1
-        cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
-        result = cursor.fetchone()
-        while result != None:
-            stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2])}
-            results = self.ichimokuCloud.analyze(stock)
-            text = json.dumps(results, ensure_ascii=False)
-            cursor.execute("UPDATE " + self.tableName + " SET ICHIMOKU=? WHERE CODE=?", (text, stock["CODE"]))
-
-            print("#analyzeIchimokuCloud", rowid, stock['NAME'])
-            rowid += 1
-            cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
-            result = cursor.fetchone()
-
-        conn.commit()
-        cursor.close()
-        conn.close()
-        return
-
-    def analyzeFinalScore(self, last_index, STOCK, MACD, STOCHASTIC, ICHIMOKU, RSI):
+    def analyzeFinalScore(self, last_index, STOCK, STOCHASTIC):
         """
          매수 조건
          #0. 최소 매수 조건은 거래량은 20만건, 종가는 2천원 이상인 종목이어야 한다.
@@ -290,40 +169,69 @@ class Analyzer:
         if STOCK[i]['volume'] > 100000 and STOCK[i]['close'] > 2000:
             # 거래량이 100만 이상이고, 종가가 1천원 이상인지 체크 (https://happpy-rich.tistory.com/94)
 
-            # 5-20
-            days20_line_buying1_status = self.common.check_days5_20_line_buying(STOCK, i)
-            if days20_line_buying1_status != "":
+            # 정배열 체크
+            temp_status = self.common.check_RightArrange(STOCK, i)
+            if temp_status != "":
                 #if STOCHASTIC[i]['slow_k'] < 40:
-               status += days20_line_buying1_status
+               status += temp_status
 
-            # 5-60
-            days60_line_buying1_status = self.common.check_days5_60_line_buying(STOCK, i)
-            if days60_line_buying1_status != "":
-                # if STOCHASTIC[i]['slow_k'] < 40:
-                status += days60_line_buying1_status
-
-            # 5-120
-            days120_line_buying1_status = self.common.check_days5_120_line_buying(STOCK, i)
-            if days120_line_buying1_status != "":
-                # if STOCHASTIC[i]['slow_k'] < 40:
-                status += days120_line_buying1_status
-
-            # 5-240
-            days240_line_buying1_status = self.common.check_days5_240_line_buying(STOCK, i)
-            if days240_line_buying1_status != "":
-                # if STOCHASTIC[i]['slow_k'] < 40:
-                status += days240_line_buying1_status
-
-            # 20-60
-            days60_line_buying2_status = self.common.check_days20_60_line_buying(STOCK, i)
-            if days60_line_buying2_status != "":
+            # 20
+            temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '20')
+            if temp_status != "":
                 #if STOCHASTIC[i]['slow_k'] < 40:
-               status += days60_line_buying2_status
+               status += temp_status
+
+            # 60
+            temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '60')
+            if temp_status != "":
+                #if STOCHASTIC[i]['slow_k'] < 40:
+               status += temp_status
+
+            # 120
+            temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '120')
+            if temp_status != "":
+                #if STOCHASTIC[i]['slow_k'] < 40:
+               status += temp_status
+
+            # 240
+            temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '240')
+            if temp_status != "":
+                #if STOCHASTIC[i]['slow_k'] < 40:
+               status += temp_status
+
+            # 270일 최고가 돌파
+            temp_status = self.common.check_highest_270(STOCK, i)
+            if temp_status != "":
+                # if STOCHASTIC[i]['slow_k'] < 40:
+                status += temp_status
+
+            # 20일선 지지 매수가 추천
+            temp_status = self.common.check_Dolpa_Jiji_20(STOCK, i)
+            if temp_status != "":
+                # if STOCHASTIC[i]['slow_k'] < 40:
+                status += temp_status
+
+            # 단타 #1
+            temp_status = self.common.check_Danta1(STOCK, i)
+            if temp_status != "":
+                # if STOCHASTIC[i]['slow_k'] < 40:
+                status += temp_status
+
+            # 단타 #2
+            temp_status = self.common.check_Danta2(STOCK, i)
+            if temp_status != "":
+                # if STOCHASTIC[i]['slow_k'] < 40:
+                status += temp_status
 
             all_upper_cross_status = self.common.checkAllUpperCross(STOCK, i)
             if all_upper_cross_status != "":
                 status += all_upper_cross_status
 
+            # 1주일 동안 몇 10% 이상 오른 종목
+            w1Rate = self.common.check_W1Rate(STOCK, i)
+            if w1Rate != "":
+                status += w1Rate
+
             # 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
@@ -337,11 +245,6 @@ class Analyzer:
             if bearmarket_buying_status != "":
                 status += bearmarket_buying_status
 
-            # BUYINGSTOCHASTIC#1은 바로 매수 가능
-            stochastic_buying_status = self.common.check_stochastic_buying(STOCK, STOCHASTIC, ICHIMOKU, i)
-            if stochastic_buying_status != "":
-                status += stochastic_buying_status
-
             # STOCHASTIC
             stochastic_status = self.common.check_stochastic(STOCK, STOCHASTIC, i)
             if stochastic_status != "":
@@ -376,51 +279,74 @@ class Analyzer:
             if ((item_code in self.fnguide and not self.fnguide[item_code]) or (item_code == "KOSPI" or item_code == "KOSDAK") or result[3] == ''):
                 rowid += 1
                 # 다음 종목을 가져옴
-                cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
+                cursor.execute('SELECT CODE, NAME, PRICE, STOCHASTIC FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
                 result = cursor.fetchone()
                 continue
 
             result_3 = result[3]
-            result_4 = result[4]
-            result_5 = result[5]
-            result_6 = result[6]
-            if result[3] != result[3]: result_3 = result[3].replace("NaN", "0")
-            if result[4] != result[4]: result_4 = result[4].replace("NaN", "0")
-            if result[5] != result[5]: result_5 = result[5].replace("NaN", "0")
-            if result[6] != result[6]: result_6 = result[6].replace("NaN", "0")
+            if result[3] != result[3]:
+                result_3 = result[3].replace("NaN", "0")
+            if result[3]==None:
+                rowid += 1
+                cursor.execute('SELECT CODE, NAME, PRICE, STOCHASTIC FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
+                result = cursor.fetchone()
+                continue
 
-            stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2]), "MACD": json.loads(result_3), "STOCHASTIC": json.loads(result_4), "ICHIMOKU": json.loads(result_5), "RSI": json.loads(result_6)}
+            stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2]), "STOCHASTIC": json.loads(result_3)}
 
             last_index = self.get_last_index(stock)
             STOCK = stock['PRICE']
-            MACD = stock['MACD']
             STOCHASTIC = stock['STOCHASTIC']
-            ICHIMOKU = stock['ICHIMOKU']
-            RSI = stock['RSI']
 
             stochastic_score = STOCHASTIC[last_index]['slow_k']
             if stochastic_score < 50:
-                macd_score = MACD[last_index]['macd']
-                rsi_score = RSI[last_index]['rsi']
-                ichimoku_score = ICHIMOKU[last_index]['ichimoku_buy']
 
                 # 종목 상태 체크 분석
-                state, buy_price = self.analyzeFinalScore(last_index, STOCK, MACD, STOCHASTIC, ICHIMOKU, RSI)
+                state, buy_price = self.analyzeFinalScore(last_index, STOCK, STOCHASTIC)
 
                 if state != "":
                     fig = self.draw(stock)
-                    title = "%s (%s), %s, buy_price (%d), stochastic(%.3f), rsi(%.3f), macd(%.3f), ichimoku(%d) 차트" % (item_name, item_code, state, buy_price, stochastic_score, rsi_score, macd_score, ichimoku_score)
+                    title = "%s (%s), %s, buy_price (%d), stochastic(%.3f) 차트" % (item_name, item_code, state, buy_price, stochastic_score)
                     fig['layout'].update(title=title)
-                    fileName = "%s/%s__%.3f__%.3f__%s_%s.html" % (outPath, state, stochastic_score, rsi_score, item_name.replace(" ", ""), item_code)
+                    fileName = "%s/%s__%.3f__%s_%s.html" % (outPath, state, stochastic_score, item_name.replace(" ", ""), item_code)
                     po.write_html(fig, file=fileName, auto_open=False)
                 else:
-                    if (RSI[last_index]['rsi_buy'] == 1) and STOCK[last_index]['volume'] > 1000000:
+                    if STOCK[last_index]['volume'] > 1000000:
                         fig = self.draw(stock)
-                        title = "%s (%s) buy_price (%d), stochastic(%.3f), rsi(%.3f), macd(%.3f), ichimoku(%d) 차트"%(item_name, item_code, buy_price, stochastic_score, rsi_score, macd_score, ichimoku_score)
+                        title = "%s (%s) buy_price (%d), stochastic(%.3f) 차트"%(item_name, item_code, buy_price, stochastic_score)
                         fig['layout'].update(title=title)
-                        fileName = "%s/%.3f__%.3f__%s_%s.html"%(tmp_path, stochastic_score, rsi_score, item_name.replace(" ", ""), item_code)
+                        fileName = "%s/%.3f__%s_%s.html"%(tmp_path, stochastic_score, item_name.replace(" ", ""), item_code)
                         po.write_html(fig, file=fileName, auto_open=False)
+            """
+            try:
+                stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2]), "STOCHASTIC": json.loads(result_3)}
 
+                last_index = self.get_last_index(stock)
+                STOCK = stock['PRICE']
+                STOCHASTIC = stock['STOCHASTIC']
+
+                stochastic_score = STOCHASTIC[last_index]['slow_k']
+                if stochastic_score < 50:
+
+                    # 종목 상태 체크 분석
+                    state, buy_price = self.analyzeFinalScore(last_index, STOCK, STOCHASTIC)
+
+                    if state != "":
+                        fig = self.draw(stock)
+                        title = "%s (%s), %s, buy_price (%d), stochastic(%.3f) 차트" % (item_name, item_code, state, buy_price, stochastic_score)
+                        fig['layout'].update(title=title)
+                        fileName = "%s/%s__%.3f__%s_%s.html" % (outPath, state, stochastic_score, item_name.replace(" ", ""), item_code)
+                        po.write_html(fig, file=fileName, auto_open=False)
+                    else:
+                        if STOCK[last_index]['volume'] > 1000000:
+                            fig = self.draw(stock)
+                            title = "%s (%s) buy_price (%d), stochastic(%.3f) 차트"%(item_name, item_code, buy_price, stochastic_score)
+                            fig['layout'].update(title=title)
+                            fileName = "%s/%.3f__%s_%s.html"%(tmp_path, stochastic_score, item_name.replace(" ", ""), item_code)
+                            po.write_html(fig, file=fileName, auto_open=False)
+            except:
+                print ("error")
+            """
             rowid += 1
             cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
             result = cursor.fetchone()
@@ -434,7 +360,7 @@ class Analyzer:
         cursor = conn.cursor()
 
         # 기존 분석 데이터를 모두 지움
-        cursor.execute('update ' + self.tableName + ' set ICHIMOKU = "", MACD = "", STOCHASTIC = "", RSI = ""')
+        cursor.execute('update ' + self.tableName + ' set STOCHASTIC = ""')
 
         rowid = 1
         cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
@@ -443,17 +369,8 @@ class Analyzer:
             stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2])}
 
             try:
-                results_ICHIMOKU = self.ichimokuCloud.analyze(stock)
-                text_ICHIMOKU = json.dumps(results_ICHIMOKU, ensure_ascii=False)
-
-                results_MACD = self.macd.analyze(stock)
-                text_MACD = json.dumps(results_MACD, ensure_ascii=False)
-
                 results_STOCHASTIC = self.stochastic.analyze(stock)
                 text_STOCHASTIC = json.dumps(results_STOCHASTIC, ensure_ascii=False)
-
-                results_RSI = self.rsi.analyze(stock)
-                text_RSI = json.dumps(results_RSI, ensure_ascii=False)
             except:
                 print("#", rowid, stock['NAME'])
                 rowid += 1
@@ -461,7 +378,7 @@ class Analyzer:
                 result = cursor.fetchone()
                 continue
 
-            cursor.execute("UPDATE " + self.tableName + " SET ICHIMOKU=?, MACD=?, STOCHASTIC=?, RSI=? WHERE CODE=?", (text_ICHIMOKU,text_MACD,text_STOCHASTIC,text_RSI, stock["CODE"]))
+            cursor.execute("UPDATE " + self.tableName + " SET STOCHASTIC=? WHERE CODE=?", (text_STOCHASTIC, stock["CODE"]))
             print("#", rowid, stock['NAME'])
             rowid += 1
             cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
@@ -483,14 +400,8 @@ if __name__ == "__main__":
 
     # 분석 & update DB
     """
-    #print ("analyze IchimokuCloud...")
-    analyzer.analyzeIchimokuCloud()
-    #print ("analyze MACD...")
-    analyzer.analyzeMACD()
     #print ("analyze Stochastic...")
     analyzer.analyzeStochastic()
-    #print ("analyze RSI...")
-    analyzer.analyzeRSI()
     """
 
     ###analyzer.analyze()

stockpredictor/analysis/Common.py

@@ -229,124 +229,127 @@ class Common:
                         return "STOCHASTIC#2_"
         return ""
 
-    def check_days5_20_line_buying(self, stock, i):
-        """
-        5일 선이 20일 선을 뚫고 올라온 순간 체크
-        5일선이 다시 20선 아래로 내려가는 순간 손걸한다.
-        """
-        if stock[i]['close'] == stock[i]['high']:
-            # 윗꼬리 없는 양봉이어야 한다.
+    def check_highest_270(self, stock, i):
+        # 270일 기준으로 최고가를 기록하는 순간 매수를 시도한다.
+        # https://docs.google.com/presentation/d/1MVuaeRNljqLCdn4dPZmvVdtl2Ab09Zwg/edit#slide=id.gc7b796e645_0_27
+        upper_index = 0
+        if len(stock) > 271:
+            top = 0
+            for idx in range(2, 271):
+                # 최근 270일 중 최고가를 구한다.
+                if top < stock[-idx]['close']:
+                    top = stock[-idx]['close']
+
+            if top < stock[i]['close']:
+                return "highest_"
         return ""
 
+    def check_Dolpa_Jiji(self, stock, i, day='20'):
+        upper_index = 0
+        if len(stock) > 5:
+            for idx in range(1, 5):
+                # day선을 돌파하는 양봉이고, 종가가 최고가 보다 100 이내이어야 한다.
+                if stock[-idx]['open'] < stock[-idx]["avg"+day] < stock[-idx]['close'] and stock[-idx]['high'] - 100 <= stock[-idx]['close']:
+                    upper_index = idx
+                    break
+            if upper_index != 0:
+                for cidx in range(1, upper_index):
+                    # 해당일의 종가보다 현재의 시가가 높거나 같아야 하며, 현재가는 양봉이어야 한다.
+                    if stock[-upper_index]['close'] <= stock[-cidx]['open'] and stock[-cidx]['open'] < stock[-cidx]['close']:
+                        # 해당 기준일 선은 상승이어야 한다.
+                        if stock[-upper_index]['avg'+day] < stock[-cidx]['avg'+day]:
+                            return day + "_"
+        return ""
+
+    def check_Dolpa_Jiji_20(self, stock, i):
+        """
+        top: 이전 5일선이 20일선 위에 있을 때 최고가
+        top일 체크 사항 (20일 < 5일선)
+        5일선이 20일 선으로 내려왔다가 다시 20일선 위로 올라왔고, top < 오늘 시가 + 100
+        top < 시가 < 종가 라면 다음날 매수한다.
+        # https://docs.google.com/presentation/d/1MVuaeRNljqLCdn4dPZmvVdtl2Ab09Zwg/edit#slide=id.gc7b796e645_0_80
+        """
         if len(stock) > 61:
-            # 오늘 종가가 20일선을 뚫고 올라왔다. (20일선<오늘종가 and (어제종가<20 or 어제5일선<20))
-            # 오늘 종가는 양봉이어야 한다.
-            # 어제부터 index1일까지 20일선이 5일선 위에 있었다.
-            # index1일부터 index2일까지 5일선이 20일선 위에 있었다.
-            # 이전 5일선이 20일선을 뚫었던 종가보다 오늘 뚫은 종가가 높거나 혹은 오늘 종가가 더 낮더라도 장대 양봉어어야 한다.
-            # 주봉의 20일 평균이 이전 주봉의 20일 평균 보다 높아야 한다.
-            if stock[i]['avg20'] < stock[i]['close'] and (stock[i-1]['close'] < stock[i]['avg20'] or stock[i-1]['avg5'] < stock[i]['avg20']):
-                if (stock[i-3]['avg5'] < stock[i-3]['avg20'] or stock[i-2]['avg5'] < stock[i-2]['avg20'] or stock[i-1]['avg5'] < stock[i-1]['avg20']):
-                #if (stock[i - 1]['avg5'] < stock[i - 1]['avg20']):
-                    if stock[i]['open'] < stock[i]['close']:
+            if stock[i]['avg20'] < stock[i]['close'] and stock[i]['avg20'] < stock[i]['open']:
+                if stock[i]['avg5'] < stock[i]['avg20']:
                     index1 = -1
                     for j in range(1, 61):
                         if stock[i-j]['avg20'] < stock[i-j]['avg5']:
                             index1 = j
                             break
-                        index2 = -1
+                    top = 0
                     for j in range(index1+1, 61):
+                        if stock[i - j]['open'] < stock[i - j]['close']:
+                            if top < stock[i - j]['close']:
+                                top = stock[i - j]['close']
+                        else:
+                            if top < stock[i - j]['open']:
+                                top = stock[i - j]['open']
                         if stock[i-j]['avg5'] < stock[i-j]['avg20']:
-                                index2 = j
                             break
-                        if (index2 != -1 and ((stock[i-index2]['close'] < stock[i]['close']) or (stock[i]['high']-stock[i]['close'] < stock[i]['open']-stock[i]['low']))):
-                            # 주봉의 20일 평균이 이전 주봉의 20일 평균 보다 높아야 한다.
                     return "5-20_"
         return ""
 
-    def check_days5_60_line_buying(self, stock, i):
+    def check_Danta1(self, stock, i):
         """
-        5일 선이 60일 선을 뚫고 올라온 순간 체크
-        5일선이 다시 60선 아래로 내려가는 순간 손걸한다.
+        어제 상한가 혹은 상승양봉이 나온다.
+        오늘 상승 출발을 해야 하며 상승 음봉이 나온다
+          - 어제 종가 = 어제 상한가 < 종가 < 시가 < 상한가
+        https://docs.google.com/presentation/d/1MVuaeRNljqLCdn4dPZmvVdtl2Ab09Zwg/edit#slide=id.gc7b796e645_0_109
+
+        만약 다음날 시작초가가 오늘 종가보다 높게 상승으로 출발한다면 매수를 한다.
+        손절가는 오늘 최저가이다.
         """
-        if stock[i]['close'] == stock[i]['high']:
-            # 윗꼬리 없는 양봉이어야 한다.
+        if stock[i-1]['open'] < stock[i-1]['close'] == stock[i-1]['high']:
+            if stock[i-1]['close'] < stock[i]['close'] < stock[i]['open'] < stock[i]['high']:
+                return "danta1_"
         return ""
 
-        if len(stock) > 61:
-            # 오늘 5일선이 60일선 위에 올라왔다.
-            # 어제부터 index1일까지 60일선이 5일선 위에 있었다.
-            # index1일부터 index2일까지 5일선이 60일선 위에 있었다.
-            if stock[i]['avg60'] < stock[i]['avg5']:
-                if (stock[i - 3]['avg5'] < stock[i - 3]['avg60'] or stock[i - 2]['avg5'] < stock[i - 2]['avg60'] or stock[i - 1]['avg5'] < stock[i - 1]['avg60']):
-                #if (stock[i - 1]['avg5'] < stock[i - 1]['avg60']):
-                    index1 = -1
-                    for j in range(1, 150):
-                        if stock[i-j]['avg60'] < stock[i-j]['avg5']:
-                            index1 = j
-                            break
-                    index2 = -1
-                    for j in range(index1+1, 150):
-                        if stock[i-j]['avg5'] < stock[i-j]['avg60']:
-                            index2 = j
-                            break
-                    if (index2 != -1 and (stock[i-index2+1]['close'] < stock[i]['close'])):
-                        return "5-60_"
-        return ""
-
-    def check_days20_60_line_buying(self, stock, i):
+    def check_Danta2(self, stock, i):
         """
-        20일 선이 60일 선을 뚫고 올라온 순간 체크
-        20일선이 다시 60선 아래로 내려가는 순간 손걸한다.
+        쐐기, 수렴, 깃대 패턴 확인
+        # https://docs.google.com/presentation/d/1MVuaeRNljqLCdn4dPZmvVdtl2Ab09Zwg/edit#slide=id.gc7b796e645_0_144
+
+        상단 추세선을 돌파하면 매수를 한다.
         """
-        if stock[i]['close'] == stock[i]['high']:
-            # 윗꼬리 없는 양봉이어야 한다.
-            return ""
-
-        if len(stock) > 151:
-            # 오늘 20일선이 60일선 위에 올라왔다.
-            # 어제부터 index1일까지 60일선이 20일선 위에 있었다.
-            # index1일부터 index2일까지 20일선이 60일선 위에 있었다.
-            if stock[i]['avg60'] < stock[i]['avg20']:
-                if (stock[i - 3]['avg20'] < stock[i - 3]['avg60'] or stock[i - 2]['avg20'] < stock[i - 2]['avg60'] or stock[i - 1]['avg20'] < stock[i - 1]['avg60']):
-                #if (stock[i - 1]['avg20'] < stock[i - 1]['avg60']):
-                    index1 = -1
-                    for j in range(1, 150):
-                        if stock[i-j]['avg60'] < stock[i-j]['avg20']:
-                            index1 = j
-                            break
-                    index2 = -1
-                    for j in range(index1+1, 150):
-                        if stock[i-j]['avg20'] < stock[i-j]['avg60']:
-                            index2 = j
-                            break
-                    if (index2 != -1 and (stock[i-index2+1]['close'] < stock[i]['close'])):
-                        return "20-60_"
-        return ""
-
-    def check_days5_120_line_buying(self, stock, i):
-        if stock[i]['close'] == stock[i]['high']:
-            # 윗꼬리 없는 양봉이어야 한다.
+        price_10 = round(stock[i]["close"] / 10)
+        if stock[-i]["open"] < stock[-i]["close"]:
+            top = stock[-i]["close"]
+            bottom = stock[-i]["open"]
+        else:
+            top = stock[-i]["open"]
+            bottom = stock[-i]["close"]
+
+        if len(stock) > 21:
+            for i in range(2, 21):
+                if stock[-i]["open"] < stock[-i]["close"]:
+                    if top < stock[-i]["close"]:
+                        top = stock[-i]["close"]
+                    if stock[-i]["open"] < bottom:
+                        bottom = stock[-i]["open"]
+                else:
+                    if top < stock[-i]["open"]:
+                        top = stock[-i]["open"]
+                    if stock[-i]["close"] < bottom:
+                        bottom = stock[-i]["close"]
+
+            if top - bottom < price_10:
+                return "danta2_"
         return ""
 
+    def check_RightArrange(self, stock, i):
         """
-        5일 선이 120일 선을 뚫고 올라온 순간 체크
+        어제는 정배열이 아니었는데, 오늘은 정배열인 경우
         """
-        if stock[i-1]['close'] < stock[i-1]['avg120']:
-            if stock[i]['avg120'] < stock[i]['close']:
-                return "5-120_"
+        if len(stock) > 2:
+            if (not (stock[i-1]["avg120"] < stock[i-1]["avg60"] < stock[i-1]["avg20"] < stock[i-1]["avg5"]) and
+                (stock[i]["avg120"] < stock[i]["avg60"] < stock[i]["avg20"] < stock[i]["avg5"])):
+                return "arrange_"
         return ""
 
-    def check_days5_240_line_buying(self, stock, i):
-        if stock[i]['close'] == stock[i]['high']:
-            # 윗꼬리 없는 양봉이어야 한다.
+    def check_W1Rate(self, stock, i):
+        if len(stock) > 5:
+            rate = round((stock[i]["close"] - stock[i-4]["close"]) / stock[i-4]["close"],2)
+            if rate >= 0.05:
+                return "1w("+str(rate)+")_"
         return ""
-
-        """
-        5일 선이 240일 선을 뚫고 올라온 순간 체크
-        """
-        if stock[i-1]['close'] < stock[i-1]['avg240']:
-            if stock[i]['avg240'] < stock[i]['close']:
-                return "5-240_"
-        return ""
-

stockpredictor/crawler/toSQLite/Crawler.py

@@ -21,6 +21,7 @@ print("[KOSPI 상장기업 재무제표 다운로드]")
 crawler.crawl_fnguide(inFnguideFileName)
 """
 
+
 crawler = MetaCrawler()
 print("\n[환율 (USD, JPY, EUR, CNY), 원유 (WTI), 국제금]")
 inFileName = PROJECT_HOME + '/resources/meta_1.db'
@@ -52,12 +53,13 @@ crawler = StockCrawler()
 crawler.saveIndex("KOSPI", kospiFileName, outFileName)
 crawler.saveIndex("KOSDAK", kosdakFileName, outFileName)
 
+
 print("\n[종목 분석]")
 # S: 분석까지 진행
 inFileName = PROJECT_HOME + '/resources/stock.db'
 analyzer = Analyzer(PROJECT_HOME, inFileName, inFnguideFileName)
 analyzer.analyze()
-
+3
 print("\n[종목 결정]")
 day = datetime.datetime.today().strftime("%Y%m%d")
 outPath = PROJECT_HOME + "/resources/analysis/" + day
@@ -68,6 +70,7 @@ print("print to Html...")
 analyzer.analyzeToHtml(outPath)
 # E: 분석까지 진행
 
+
 print("time : %6.2f 초", (time.time() - start))
 
 print ("done...")