diff --git a/stock/analysis/AnalyzerSqlite.py b/stock/analysis/AnalyzerSqlite.py index 7d5b1ff..f08ec56 100644 --- a/stock/analysis/AnalyzerSqlite.py +++ b/stock/analysis/AnalyzerSqlite.py @@ -146,6 +146,8 @@ class AnalyzerSqlite: disparity_avg20 = list(reversed(stock['disparity_avg20'])) disparity_avg60 = list(reversed(stock['disparity_avg60'])) disparity_avg120 = list(reversed(stock['disparity_avg120'])) + disparity_avg240 = list(reversed(stock['disparity_avg240'])) + disparity_avg480 = list(reversed(stock['disparity_avg480'])) macd = list(reversed(stock['macd'])) macdo = list(reversed(stock['macdo'])) macds = list(reversed(stock['macds'])) @@ -165,23 +167,25 @@ class AnalyzerSqlite: ichimokucloud_leadingSpan1 = list(reversed(stock['ichimokucloud_leadingSpan1'])) ichimokucloud_leadingSpan2 = list(reversed(stock['ichimokucloud_leadingSpan2'])) trend = list(reversed(stock['trend'])) + trend_s = list(reversed(stock['trend_s'])) + trend_k = list(reversed(stock['trend_k'])) # general candle_stick = go.Candlestick(x=ymd, open=open, high=high, low=low, close=close, increasing_line_color='red', decreasing_line_color='blue') #avg3 = go.Scatter(x=ymd, y=avg3, name="avg3", line_color='#085F1B') #avg4 = go.Scatter(x=ymd, y=avg4, name="avg4", line_color='#085F1B') - avg5 = go.Scatter(x=ymd, y=avg5, name="avg5", line_color='#F73B13') + avg5 = go.Scatter(x=ymd, y=avg5, name="avg5", line_color='#ff0000') #avg6 = go.Scatter(x=ymd, y=avg6, name="avg6", line_color='#698D09') avg10 = go.Scatter(x=ymd, y=avg10, name="avg10", line_color='#8013ED') #avg12 = go.Scatter(x=ymd, y=avg12, name="avg12", line_color='#000000') - avg20 = go.Scatter(x=ymd, y=avg20, name="avg20", line_color='#0A86F4') + avg20 = go.Scatter(x=ymd, y=avg20, name="avg20", line_color='#0000ff') #avg36 = go.Scatter(x=ymd, y=avg36, name="avg36", line_color='#370557') #avg40 = go.Scatter(x=ymd, y=avg40, name="avg40", line_color='#041366') #avg48 = go.Scatter(x=ymd, y=avg48, name="avg48", line_color='#7A1E66') - avg60 = go.Scatter(x=ymd, y=avg60, name="avg60", line_color='#f89543') - avg120 = go.Scatter(x=ymd, y=avg120, name="avg120", line_color='#0ed604') - avg240 = go.Scatter(x=ymd, y=avg240, name="avg240", line_color='#FF00F7') - avg480 = go.Scatter(x=ymd, y=avg480, name="avg480", line_color='#00FF49') + avg60 = go.Scatter(x=ymd, y=avg60, name="avg60", line_color='#ff00ff') + avg120 = go.Scatter(x=ymd, y=avg120, name="avg120", line_color='#cd4025') + avg240 = go.Scatter(x=ymd, y=avg240, name="avg240", line_color='#38761d') + avg480 = go.Scatter(x=ymd, y=avg480, name="avg480", line_color='#656565') bolinger_upper = go.Scatter(x=ymd, y=bolingerband_upper, name="bol_upper", line_color='#8B4513') bolinger_lower = go.Scatter(x=ymd, y=bolingerband_lower, name="bol_lower", line_color='#8B4513') env_upper = go.Scatter(x=ymd, y=envelope_upper, name="env_upper", line_color='#FF33A2') @@ -192,21 +196,24 @@ class AnalyzerSqlite: leadingSpan1 = go.Scatter(x=ymd, y=ichimokucloud_leadingSpan1, name='leadingSpan1', line_color='black') leadingSpan2 = go.Scatter(x=ymd, y=ichimokucloud_leadingSpan2, name='leadingSpan2', line_color='black') trend = go.Scatter(x=ymd, y=trend, name="trend", line_color='#574e4c') + trend_k = go.Scatter(x=ymd, y=trend_k, name="trend_k", line_color='#ff0000') + trend_s = go.Scatter(x=ymd, y=trend_s, name="trend_s", line_color='#0000ff') - candle_data = [candle_stick, trend, avg5, avg20, avg60, avg120, avg240, avg480, bolinger_upper, bolinger_lower, changeLine, baseLine, laggingSpan] - #candle_data = [candle_stick, trend, avg5, avg10, avg20, avg60, avg120, avg240, bolinger_upper, bolinger_lower, env_upper, env_lower, changeLine, baseLine] - #candle_data = [avg5, avg20, trend, changeLine, baseLine, laggingSpan, candle_stick] + candle_data = [candle_stick, trend, trend_k, trend_s, avg5, avg20, avg60, avg120, avg240, avg480, bolinger_upper, bolinger_lower, changeLine, baseLine, laggingSpan] + #candle_data = [candle_stick, trend, trend_k, trend_s, avg5, avg10, avg20, avg60, avg120, avg240, bolinger_upper, bolinger_lower, env_upper, env_lower, changeLine, baseLine] + #candle_data = [avg5, avg20, trend, trend_k, trend_s, changeLine, baseLine, laggingSpan, candle_stick] volume = go.Bar(x=ymd, y=volume, marker_color='red', name="volume") volume_data = [volume] - disparity_avg5 = go.Scatter(x=ymd, y=disparity_avg5, name="disparity_avg5", line_color='#8F8203') - disparity_avg10 = go.Scatter(x=ymd, y=disparity_avg10, name="disparity_avg10", line_color='#089B5B') - disparity_avg20 = go.Scatter(x=ymd, y=disparity_avg20, name="disparity_avg20", line_color='#ff00ff') - disparity_avg60 = go.Scatter(x=ymd, y=disparity_avg60, name="disparity_avg60", line_color='#1469F4') - disparity_avg120 = go.Scatter(x=ymd, y=disparity_avg120, name="disparity_avg120", line_color='#000000') - disparity_data = [disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120] + disparity_avg5 = go.Scatter(x=ymd, y=disparity_avg5, name="disparity_avg5", line_color='#ff0000') + disparity_avg20 = go.Scatter(x=ymd, y=disparity_avg20, name="disparity_avg20", line_color='#0000ff') + disparity_avg60 = go.Scatter(x=ymd, y=disparity_avg60, name="disparity_avg60", line_color='#ff00ff') + disparity_avg120 = go.Scatter(x=ymd, y=disparity_avg120, name="disparity_avg120", line_color='#cd4025') + disparity_avg240 = go.Scatter(x=ymd, y=disparity_avg240, name="disparity_avg240", line_color='#38761d') + disparity_avg480 = go.Scatter(x=ymd, y=disparity_avg480, name="disparity_avg480", line_color='#656565') + disparity_data = [disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120, disparity_avg240, disparity_avg480] # macd macd_line = go.Scatter(x=ymd, y=macd, line=dict(color='red', width=2), name='macd') @@ -357,7 +364,7 @@ class AnalyzerSqlite: sql += ' rsi, rsis, ' sql += ' macd, macds, macdo, ' sql += ' mfi, ' - sql += ' trend ' + sql += ' trend, trend_k, trend_s ' sql += ' FROM ' + TableName + ' where CODE=? order by ymd desc limit 512 ' cursor.execute(sql, (CODE,)) prices = cursor.fetchall() @@ -376,7 +383,7 @@ class AnalyzerSqlite: rsi, rsis = [], [] macd, macds, macdo = [], [], [] mfi = [] - trend = [] + trend, trend_k, trend_s = [], [], [] for price in prices: ymd.append(price[0]) @@ -434,6 +441,8 @@ class AnalyzerSqlite: macdo.append(price[52]) mfi.append(price[53]) trend.append(price[54]) + trend_k.append(price[55]) + trend_s.append(price[56]) stock = { "ymd": ymd, @@ -447,7 +456,7 @@ class AnalyzerSqlite: "rsi": rsi, "rsis": rsis, "macd": macd, "macds": macds, "macdo": macdo, "mfi": mfi, - "trend": trend + "trend": trend, "trend_k": trend_k, "trend_s": trend_s } return stock @@ -720,7 +729,9 @@ class AnalyzerSqlite: "macds": -1, "macdo": -1, "mfi": -1, - "trend": -1 + "trend": -1, + "trend_k": -1, + "trend_s": -1 } ) previous_close = weekDict['close'][ts] @@ -734,7 +745,7 @@ class AnalyzerSqlite: stockAnalysisTableName = 'stock_analysis_' + type # 테이블 생성 - cursor.execute("CREATE TABLE IF NOT EXISTS " + stockAnalysisTableName + " (CODE text, NAME text, ymd text, close REAL, diff REAL, open REAL, high REAL, low REAL, volume REAL, avg3 REAL, avg4 REAL, avg5 REAL, avg6 REAL, avg10 REAL, avg12 REAL, avg20 REAL, avg36 REAL, avg40 REAL, avg48 REAL, avg60 REAL, avg120 REAL, avg200 REAL, avg240 REAL, avg300 REAL, avg360 REAL, avg480 REAL, avg720 REAL, avg1440 REAL, disparity_avg5 REAL, disparity_avg10 REAL, disparity_avg20 REAL, disparity_avg60 REAL, disparity_avg120 REAL, disparity_avg240 REAL, disparity_avg480, bolingerband_upper REAL, bolingerband_lower REAL, bolingerband_middle REAL, bolingerband_width REAL, bolingerband_pb REAL, envelope_upper REAL, envelope_lower REAL, envelope_middle REAL, ichimokucloud_changeLine REAL, ichimokucloud_baseLine REAL, ichimokucloud_laggingSpan REAL, ichimokucloud_leadingSpan1 REAL, ichimokucloud_leadingSpan2 REAL, stochastic_fast_k REAL, stochastic_slow_k REAL, stochastic_slow_d REAL, rsi REAL, rsis REAL, macd REAL, macds REAL, macdo REAL, mfi REAL, trend REAL)") + cursor.execute("CREATE TABLE IF NOT EXISTS " + stockAnalysisTableName + " (CODE text, NAME text, ymd text, close REAL, diff REAL, open REAL, high REAL, low REAL, volume REAL, avg3 REAL, avg4 REAL, avg5 REAL, avg6 REAL, avg10 REAL, avg12 REAL, avg20 REAL, avg36 REAL, avg40 REAL, avg48 REAL, avg60 REAL, avg120 REAL, avg200 REAL, avg240 REAL, avg300 REAL, avg360 REAL, avg480 REAL, avg720 REAL, avg1440 REAL, disparity_avg5 REAL, disparity_avg10 REAL, disparity_avg20 REAL, disparity_avg60 REAL, disparity_avg120 REAL, disparity_avg240 REAL, disparity_avg480, bolingerband_upper REAL, bolingerband_lower REAL, bolingerband_middle REAL, bolingerband_width REAL, bolingerband_pb REAL, envelope_upper REAL, envelope_lower REAL, envelope_middle REAL, ichimokucloud_changeLine REAL, ichimokucloud_baseLine REAL, ichimokucloud_laggingSpan REAL, ichimokucloud_leadingSpan1 REAL, ichimokucloud_leadingSpan2 REAL, stochastic_fast_k REAL, stochastic_slow_k REAL, stochastic_slow_d REAL, rsi REAL, rsis REAL, macd REAL, macds REAL, macdo REAL, mfi REAL, trend REAL, trend_k REAL, trend_s REAL)") # 키 생성 create_key = "CREATE INDEX IF NOT EXISTS " + stockAnalysisTableName + "_idx on " + stockAnalysisTableName + " (CODE, ymd) " @@ -758,7 +769,7 @@ class AnalyzerSqlite: close_list = [price['close'] for price in stock['PRICE']] if 200 < len(close_list): # 트렌드: 실시간 정상 작동 안됨 - size = int(len(close_list) / 20) + size = int(len(close_list) / 7) pos = round(size / 2) close_temp = close_list + [close_list[-1]] * pos decomposition_results = seasonal_decompose(close_temp, model='multiplicative', period=size) @@ -767,9 +778,32 @@ class AnalyzerSqlite: trend_list = trend_df.values.tolist() for i, price in enumerate(stock['PRICE']): price['trend'] = trend_list[i][0] + + trend_s_df = trend_df.rolling(120).mean() + trend_s_list = trend_s_df.values.tolist() + for i, price in enumerate(stock['PRICE']): + price['trend_s'] = trend_s_list[i][0] + + trend_k_df = trend_df.rolling(5).mean() + trend_k_list = trend_k_df.values.tolist() + for i, price in enumerate(stock['PRICE']): + price['trend_k'] = trend_k_list[i][0] else: for i, price in enumerate(stock['PRICE']): price['trend'] = stock['PRICE'][i]['avg120'] + price['trend_s'] = stock['PRICE'][i]['avg120'] + price['trend_k'] = stock['PRICE'][i]['avg120'] + + size = int(len(close_list) / 2) + pos = round(size / 2) + close_temp = close_list + [close_list[-1]] * pos + decomposition_results = seasonal_decompose(close_temp, model='multiplicative', period=size) + trend = decomposition_results.trend[:-pos] + trend_df = pd.DataFrame(trend).fillna(close_list[0]) + trend_list = trend_df.values.tolist() + for i, price in enumerate(stock['PRICE']): + price['trend'] = trend_list[i][0] + sorted_stock = sorted(stock["PRICE"], key=lambda x: x['ymd'], reverse=True) for price in sorted_stock: @@ -785,7 +819,7 @@ class AnalyzerSqlite: sql += " stochastic_fast_k, stochastic_slow_k, stochastic_slow_d, " sql += " rsi, rsis, macd, macds, macdo, " sql += " mfi, " - sql += " trend) " + sql += " trend, trend_k, trend_s) " sql += " VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)" cursor.execute(sql, ( @@ -798,7 +832,7 @@ class AnalyzerSqlite: price['stochastic_fast_k'], price['stochastic_slow_k'], price['stochastic_slow_d'], price['rsi'], price['rsis'], price['macd'], price['macds'], price['macdo'], price['mfi'], - price['trend'], + price['trend'],price['trend_k'],price['trend_s'], )) else: @@ -812,7 +846,7 @@ class AnalyzerSqlite: sql += " rsi=?, rsis=?, " sql += " macd=?, macds=?, macdo=?, " sql += " mfi=?, " - sql += " trend=? " + sql += " trend=?, trend_k=?, trend_s=? " sql += " WHERE CODE=? and ymd=?" cursor.execute(sql, @@ -820,13 +854,13 @@ class AnalyzerSqlite: price['avg3'], price['avg4'], price['avg5'], price['avg6'], price['avg10'], price['avg12'], price['avg20'], price['avg36'], price['avg40'], price['avg48'], price['avg60'], price['avg120'], price['avg200'], price['avg240'], price['avg300'], price['avg360'], price['avg480'], price['avg720'], price['avg1440'], price['disparity_avg5'], price['disparity_avg10'], price['disparity_avg20'], price['disparity_avg60'], price['disparity_avg120'], price['disparity_avg240'], price['disparity_avg480'], price['bolingerband_upper'], price['bolingerband_lower'], price['bolingerband_middle'], price['bolingerband_width'], price['bolingerband_pb'], - price['envelope_upper'], price['envelope_lower'], price['envelope_middle'], + price['envelope_upper'], price['envelope_lower'], price['envelope_middle'], price['ichimokucloud_changeLine'], price['ichimokucloud_baseLine'], price['ichimokucloud_laggingSpan'], price['ichimokucloud_leadingSpan1'], price['ichimokucloud_leadingSpan2'], price['stochastic_fast_k'], price['stochastic_slow_k'], price['stochastic_slow_d'], price['rsi'], price['rsis'], price['macd'], price['macds'], price['macdo'], price['mfi'], - price['trend'], + price['trend'], price['trend_k'], price['trend_s'], stock["CODE"], price['ymd'],)) break @@ -890,7 +924,9 @@ class AnalyzerSqlite: "macds": -1, "macdo": -1, "mfi": -1, - "trend": -1 + "trend": -1, + "trend_k": -1, + "trend_s": -1 } def analyzeDaily(self):