527 lines
20 KiB
Python
527 lines
20 KiB
Python
import json
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import os
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import time
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import shutil
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from stockpredictor.analysis.Common import Common
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from stockpredictor.analysis.Stochastic import Stochastic
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import matplotlib.pyplot as plt
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import datetime
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import sqlite3
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from datetime import datetime
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from matplotlib import rc
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rc('font', family='AppleGothic')
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plt.rcParams['axes.unicode_minus'] = False
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import pandas as pd
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import plotly.graph_objs as go
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from plotly import tools, subplots
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import plotly.io as po
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class Analyzer:
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tableName = 'stock'
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PROJECT_HOME = None
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stocks = None
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candidate = None
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stochastic = None
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common = None
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inFileName = None
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fnguideFileName = None
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fnguide = {}
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def __init__(self, PROJECT_HOME, inFileName, fnguideFileName):
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self.PROJECT_HOME = PROJECT_HOME
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self.inFileName = inFileName
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self.fnguideFileName = fnguideFileName
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self.stocks = []
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self.candidate = []
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self.common = Common()
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self.stochastic = Stochastic()
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self.readFnguide()
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return
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def readFnguide(self):
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conn = sqlite3.connect(self.fnguideFileName)
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cursor = conn.cursor()
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today = datetime.today()
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year1 = str(today.year - 1) + ".12.01"
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year2 = str(today.year - 2) + ".12.01"
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year3 = str(today.year - 3) + ".12.01"
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rowid = 1
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cursor.execute('SELECT * FROM fnguide WHERE rowid=?', (rowid,))
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result = cursor.fetchone()
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while result != None:
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if result[2] == "227950":
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print (1)
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data = json.loads(result[2])
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self.fnguide[result[0]] = True
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if (year1 in data and year2 in data and year3 in data):
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if (data[year1]['영업이익'] < 0 or data[year2]['영업이익'] < 0 or data[year3]['영업이익'] < 0):
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# and 3년 연속 영업이익이 적자이면 매수하지 않는다.
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# or: 3년 중 1번이라도 영업이익이 적자이면 매수하지 않는다.
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self.fnguide[result[0]] = False
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if (data[year1]['영업이익'] < -100):
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# 전년 영억적자가 100억 이상이면 매수하지 않는다.
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self.fnguide[result[0]] = False
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rowid += 1
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cursor.execute('SELECT * FROM fnguide WHERE rowid=?', (rowid,))
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result = cursor.fetchone()
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cursor.close()
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conn.close()
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return
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def draw(self, stock):
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last_index = self.get_last_index(stock)
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if last_index > 300:
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index = 300 # 최대 300일치 그래프 확인
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df_stock = pd.DataFrame(stock["PRICE"][len(stock["PRICE"]) - index:])
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df_stochastic = pd.DataFrame(stock["STOCHASTIC"][len(stock["STOCHASTIC"]) - index:last_index+1])
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else:
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index = last_index
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df_stock = pd.DataFrame(stock["PRICE"][:index+1])
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df_stochastic = pd.DataFrame(stock["STOCHASTIC"][:index+1])
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# general
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volume = go.Bar(x=df_stock.DATE, y=df_stock['volume'], name="volume")
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volume_data = [volume]
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# stochastic
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slow_k = go.Scatter(x=df_stochastic.DATE, y=df_stochastic['slow_k'], name="Slow%K", line_color='#8B4513')
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slow_d = go.Scatter(x=df_stochastic.DATE, y=df_stochastic['slow_d'], name="Slow%D", line_color='#4169E1')
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stochastic_data = [slow_k, slow_d]
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fig = subplots.make_subplots(rows=2, cols=1, subplot_titles=('거래량', 'Stochastic'))
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for trace in volume_data:
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fig.append_trace(trace, 1, 1)
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for trace in stochastic_data:
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fig.append_trace(trace, 2, 1)
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fig.update_layout(height=800)
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return fig
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def get_last_index(self, stock):
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for i in range(0, len(stock['PRICE'])):
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if (stock['PRICE'][i]['close'] == 0 and stock['PRICE'][i]['open'] == 0 and stock['PRICE'][i]['volume'] == 0):
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return i-1
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return len(stock['PRICE']) - 1
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def analyzeStochastic(self):
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conn = sqlite3.connect(self.inFileName)
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cursor = conn.cursor()
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# 기존 분석 데이터를 모두 지움
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cursor.execute('update ' + self.tableName + ' set STOCHASTIC = ""')
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rowid = 1
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cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
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result = cursor.fetchone()
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while result != None:
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stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2])}
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results = self.stochastic.analyze(stock)
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text = json.dumps(results, ensure_ascii=False)
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cursor.execute("UPDATE " + self.tableName + " SET STOCHASTIC=? WHERE CODE=?", (text, stock["CODE"]))
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print("#analyzeStochastic", rowid, stock['NAME'])
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rowid += 1
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cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
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result = cursor.fetchone()
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conn.commit()
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cursor.close()
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conn.close()
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return
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def analyzeFinalScore(self, last_index, STOCK, STOCHASTIC):
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"""
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매수 조건
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#0. 최소 매수 조건은 거래량은 20만건, 종가는 2천원 이상인 종목이어야 한다.
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#1. 골든크로스: 5일선, 20일선, 60일선, 120일선이 순서대로 나열되는 순간
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"""
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i = last_index
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buy_price = 0
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count = 0
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for idx in range(i, i-5, -1):
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if idx-1 < 0:
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break
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buy_price += STOCK[idx-1]['close'] - STOCK[idx]['low']
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count += 1
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if count == 0:
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buy_price = STOCK[i]['close']
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else:
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# 종가 - 최저가의 최근 3일 평균 가격을 산정한다.
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buy_price = round(STOCK[i]['close'] - (buy_price/count))
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status = ""
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if STOCK[i]['volume'] > 100000 and STOCK[i]['close'] > 2000:
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# 거래량이 100만 이상이고, 종가가 1천원 이상인지 체크 (https://happpy-rich.tistory.com/94)
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# 정배열 체크
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temp_status = self.common.check_RightArrange(STOCK, i)
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if temp_status != "":
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#if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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# 20일선 돌파
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temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '20')
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if temp_status != "":
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#if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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# 60일선 돌파
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temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '60')
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if temp_status != "":
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#if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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# 120일선 돌파
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temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '120')
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if temp_status != "":
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#if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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# 240일선 돌파
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temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '240')
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if temp_status != "":
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#if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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# 20일선 지지 매수가 추천
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temp_status = self.common.check_Dolpa_Jiji_20(STOCK, i)
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if temp_status != "":
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# if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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# 단타 #1
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temp_status = self.common.check_Danta1(STOCK, i)
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if temp_status != "":
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# if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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# 단타 #2
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temp_status = self.common.check_Danta2(STOCK, i)
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if temp_status != "":
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# if STOCHASTIC[i]['slow_k'] < 40:
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status += temp_status
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all_upper_cross_status = self.common.checkAllUpperCross(STOCK, i)
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if all_upper_cross_status != "":
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status += all_upper_cross_status
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# 1주일 동안 몇 10% 이상 오른 종목
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W1Rise = self.common.check_W1Rise(STOCK, i, 0.1)
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if W1Rise != "":
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status += W1Rise
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# 1일 동안 몇 10% 이상 내리 종목
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W1Fall = self.common.check_D1Fall(STOCK, i, -0.1)
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if W1Fall != "":
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status += W1Fall
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# GOLDENCROSS#1은 바로 매수하지 않고, 이 시점 이후로 5일선이 20일선을 하방으로 뚫었다가 다시 20일선을 상방으로 뚫는 순간 매수를 시도한다.
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# GOLDENCROSS#2은 바로 매수 가능
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# GOLDENCROSS#3은 바로 매수 가능
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golden_cross_status = self.common.check_golded_cross(STOCK, i)
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if golden_cross_status != "":
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status += golden_cross_status
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# BUYINGBEARMARKET#1은 바로 매수 가능
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# BUYINGBEARMARKET#2은 바로 매수 가능
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bearmarket_buying_status = self.common.check_bearmarket_buying(STOCK, STOCHASTIC, i)
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if bearmarket_buying_status != "":
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status += bearmarket_buying_status
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# STOCHASTIC
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stochastic_status = self.common.check_stochastic(STOCK, STOCHASTIC, i)
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if stochastic_status != "":
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status += stochastic_status
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# YANGBONG
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longYangBongAfterUmBong_status = self.common.checkLongYangBongAfterUmBong(STOCK, i)
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# 어제 음봉 이후 장대양봉이었다면,
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if longYangBongAfterUmBong_status != "":
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status += longYangBongAfterUmBong_status
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# Doji
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doji_status = self.common.checkDoji(STOCK, i)
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# 하락 추세에서 도지가 나오면 매수
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if doji_status != "":
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status += doji_status
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"""
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# Gravestone
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gravestone_status = self.common.checkGravestone(STOCK, i)
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# 상승 추세에서 그레이브스톤이 나오면 매도
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if gravestone_status != "":
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status += gravestone_status
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"""
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# Dragonfly
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dragonfly_status = self.common.checkDragonfly(STOCK, i)
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# 하락 추세에서 드레곤플라이가 나오면 매수
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if dragonfly_status != "":
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status += dragonfly_status
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# Hammer
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hammer_status = self.common.checkHammer(STOCK, i)
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# 하락 추세에서 해머가 나오면 매수
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if hammer_status != "":
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status += hammer_status
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"""
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# Hangingman
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hangingman_status = self.common.checkHangingman(STOCK, i)
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# 상승 추세에서 행잉맨이 나오면 매도
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if hangingman_status != "":
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status += hangingman_status
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"""
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# 상승장악형 (Engulfing) - 다음 날도 양봉이라면 매수
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engulfing_status = self.common.checkEngulfingHigh(STOCK, i)
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# 하락 추세에서 상승장악형이 나오면 매수
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if engulfing_status != "":
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status += engulfing_status
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"""
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# 하락장악형 (Engulfing)
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engulfing_status = self.common.checkEngulfingLow(STOCK, i)
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# 상승 추세에서 하락장악형이 나오면 매도
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if engulfing_status != "":
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status += engulfing_status
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"""
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# 상승 포아형 (Harami)
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harami_status = self.common.checkHaramiHigh(STOCK, i)
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# 하락 추세에서 상승포아형이 나오면 매수
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if harami_status != "":
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status += harami_status
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"""
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# 하락 포아형 (Harami)
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harami_status = self.common.checkHaramiLow(STOCK, i)
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# 상승 추세에서 하락포아형이 나오면 매도
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if harami_status != "":
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status += harami_status
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"""
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# 관통형 (piercing)
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piercing_status = self.common.checkPiercing(STOCK, i)
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# 하락 추세에서 관통형이 나오면 매수
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if piercing_status != "":
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status += piercing_status
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"""
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# 흑운형 (Dark-cloud)
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darkcloud_status = self.common.checkDarkCloud(STOCK, i)
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# 상승 추세에서 흑운형이 나오면 매도
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if darkcloud_status != "":
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status += darkcloud_status
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"""
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# 샛별 (Morning start)
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morningstar_status = self.common.checkMorningstar(STOCK, i)
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# 하락 추세에서 샛별형이 나오면 매수
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if morningstar_status != "":
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status += morningstar_status
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"""
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# 저녁별 (Evening start)
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eveningstar_status = self.common.checkEveningstar(STOCK, i)
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# 상승 추세에서 저녁별형이 나오면 매도
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if eveningstar_status != "":
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status += eveningstar_status
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"""
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# Potential Energy
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potential_energy_status = self.common.checkPotentialEnergy(STOCK, i)
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# 365일 중 가장 찾은 금액과 가장 높았던 금액 중 현재가의 위치 계산
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if potential_energy_status != "":
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status += potential_energy_status
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return status, buy_price
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# 그래프 출력
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def analyzeToHtml(self, outPath):
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tmp_path = outPath + "/tmp"
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if os.path.isdir(tmp_path):
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os.rmdir(tmp_path)
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os.mkdir(tmp_path)
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conn = sqlite3.connect(self.inFileName)
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cursor = conn.cursor()
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rowid = 1
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cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
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result = cursor.fetchone()
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while result != None:
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item_code = result[0]
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item_name = result[1]
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print("#html", rowid, item_name)
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# 부실 기업은 매수하지 않고 그냥 넘긴다.
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# kospi 지수와 kosdak 지수도 그냥 넘긴다.
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if ((item_code in self.fnguide and not self.fnguide[item_code]) or (item_code == "KOSPI" or item_code == "KOSDAK") or result[3] == ''):
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rowid += 1
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# 다음 종목을 가져옴
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cursor.execute('SELECT CODE, NAME, PRICE, STOCHASTIC FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
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result = cursor.fetchone()
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continue
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result_3 = result[3]
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if result[3] != result[3]:
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result_3 = result[3].replace("NaN", "0")
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if result[3]==None:
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rowid += 1
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cursor.execute('SELECT CODE, NAME, PRICE, STOCHASTIC FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
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result = cursor.fetchone()
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continue
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stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2]), "STOCHASTIC": json.loads(result_3)}
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last_index = self.get_last_index(stock)
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STOCK = stock['PRICE']
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STOCHASTIC = stock['STOCHASTIC']
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stochastic_score = STOCHASTIC[last_index]['slow_k']
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if stochastic_score < 50:
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# 종목 상태 체크 분석
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state, buy_price = self.analyzeFinalScore(last_index, STOCK, STOCHASTIC)
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if state != "":
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fig = self.draw(stock)
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title = "%s (%s), %s, buy_price (%d), stochastic(%.3f) 차트" % (item_name, item_code, state, buy_price, stochastic_score)
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fig['layout'].update(title=title)
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fileName = "%s/%s__%.3f__%s_%s.html" % (outPath, state, stochastic_score, item_name.replace(" ", ""), item_code)
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po.write_html(fig, file=fileName, auto_open=False)
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else:
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if STOCK[last_index]['volume'] > 1000000:
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fig = self.draw(stock)
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title = "%s (%s) buy_price (%d), stochastic(%.3f) 차트"%(item_name, item_code, buy_price, stochastic_score)
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fig['layout'].update(title=title)
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fileName = "%s/%.3f__%s_%s.html"%(tmp_path, stochastic_score, item_name.replace(" ", ""), item_code)
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po.write_html(fig, file=fileName, auto_open=False)
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|
"""
|
|
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()
|
|
|
|
cursor.close()
|
|
conn.close()
|
|
return
|
|
|
|
def analyze(self):
|
|
conn = sqlite3.connect(self.inFileName)
|
|
cursor = conn.cursor()
|
|
|
|
# 기존 분석 데이터를 모두 지움
|
|
cursor.execute('update ' + self.tableName + ' set STOCHASTIC = ""')
|
|
|
|
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])}
|
|
|
|
try:
|
|
results_STOCHASTIC = self.stochastic.analyze(stock)
|
|
text_STOCHASTIC = json.dumps(results_STOCHASTIC, ensure_ascii=False)
|
|
except:
|
|
print("#", rowid, stock['NAME'])
|
|
rowid += 1
|
|
cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
|
|
result = cursor.fetchone()
|
|
continue
|
|
|
|
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,))
|
|
result = cursor.fetchone()
|
|
|
|
conn.commit()
|
|
cursor.close()
|
|
conn.close()
|
|
return
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
|
start = time.time()
|
|
PROJECT_HOME = "../.."
|
|
inFileName = PROJECT_HOME + '/resources/stock.db'
|
|
inFnguideFileName = PROJECT_HOME + '/resources/fnguide.db'
|
|
analyzer = Analyzer(PROJECT_HOME, inFileName, inFnguideFileName)
|
|
|
|
# 분석 & update DB
|
|
"""
|
|
#print ("analyze Stochastic...")
|
|
analyzer.analyzeStochastic()
|
|
"""
|
|
|
|
###analyzer.analyze()
|
|
|
|
day = datetime.today().strftime("%Y%m%d")
|
|
|
|
# HTML 출력
|
|
outPath = PROJECT_HOME + "/resources/analysis/"+day
|
|
if os.path.isdir(outPath):
|
|
shutil.rmtree(outPath)
|
|
os.mkdir(outPath)
|
|
print("print to Html...")
|
|
analyzer.analyzeToHtml(outPath)
|
|
|
|
|
|
# 파일 출력
|
|
#print("print to File...")
|
|
#outFileName = PROJECT_HOME + '/resources/analysis/'+day+'.json'
|
|
#analyzer.analyzeToFile(outFileName)
|
|
|
|
print("time : %6.2f 초", (time.time() - start))
|
|
|
|
print("done...")
|