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dosang.yoon
2022-06-23 23:30:18 +09:00
parent e6408db76f
commit 0d523678a6
3 changed files with 176 additions and 40 deletions
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186
stockpredictor/analysis/AnalyzerSqlite.py
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@@ -6,6 +6,8 @@ import datetime
import sqlite3
from datetime import datetime
from matplotlib import rc
import pandas as pd
import copy
rc('font', family='AppleGothic')
plt.rcParams['axes.unicode_minus'] = False
@@ -793,12 +795,47 @@ class AnalyzerSqlite:
return
def analyze(self):
stockTableName = 'stock'
stockAnalysisTableName = 'stock_analysis'
def convertFormat(self, weekDict):
previous_close = 0
stock_price = []
for ts in weekDict['open']:
stock_price.append(
{
"ymd": ts.strftime("%Y.%m.%d"),
"close": weekDict['close'][ts],
"diff": weekDict['close'][ts] - previous_close,
"open": weekDict['open'][ts],
"high": weekDict['high'][ts],
"low": weekDict['low'][ts],
"volume": weekDict['volume'][ts],
"avg5": -1,
"avg10": -1,
"avg20": -1,
"avg60": -1,
"avg120": -1,
"avg200": -1,
"avg240": -1,
"bolingerband_upper": -1,
"bolingerband_lower": -1,
"bolingerband_middle": -1,
"ichimokucloud_changeLine": -1,
"ichimokucloud_baseLine": -1,
"ichimokucloud_leadingSpan1": -1,
"ichimokucloud_leadingSpan2": -1,
"stochastic_fast_k": -1,
"stochastic_slow_k": -1,
"stochastic_slow_d": -1
}
)
previous_close = weekDict['close'][ts]
conn = sqlite3.connect(self.stockFileName)
cursor = conn.cursor()
return stock_price
def analyzeAdditionalInfo(self, stock, cursor, type=None):
if type==None:
stockAnalysisTableName = 'stock_analysis'
else:
stockAnalysisTableName = 'stock_analysis_' + type
# 테이블 생성
cursor.execute("CREATE TABLE IF NOT EXISTS " + stockAnalysisTableName + " (CODE text, NAME text, ymd text, avg5 REAL, avg10 REAL, avg20 REAL, avg60 REAL, avg120 REAL, avg200 REAL, avg240 REAL, bolingerband_upper REAL, bolingerband_lower REAL, bolingerband_middle REAL, ichimokucloud_changeLine REAL, ichimokucloud_baseLine REAL, ichimokucloud_leadingSpan1 REAL, ichimokucloud_leadingSpan2 REAL, stochastic_fast_k REAL, stochastic_slow_k REAL, stochastic_slow_d REAL)")
@@ -807,12 +844,48 @@ class AnalyzerSqlite:
create_key = "CREATE INDEX IF NOT EXISTS " + stockAnalysisTableName + "_idx on " + stockAnalysisTableName + " (CODE, ymd) "
cursor.execute(create_key)
# 이동 평균 계산
stock["PRICE"] = sorted(stock["PRICE"], key=lambda x: x['ymd'])
self.get_moving_average(stock["PRICE"])
self.ichimokuCloud.analyze(stock)
self.stochastic.analyze(stock)
self.bolingerBand.analyze(stock)
sorted_stock = sorted(stock["PRICE"], key=lambda x: x['ymd'], reverse=True)
for price in sorted_stock:
cursor.execute('SELECT * FROM ' + stockAnalysisTableName + ' WHERE CODE=? and ymd=?',
(stock['CODE'], price['ymd'],))
result = cursor.fetchone()
if result == None:
sql = "INSERT INTO " + stockAnalysisTableName + "(CODE, NAME, ymd, avg5, avg10, avg20, avg60, avg120, avg200, avg240, "
sql += " bolingerband_upper, bolingerband_lower, bolingerband_middle, "
sql += " ichimokucloud_changeLine, ichimokucloud_baseLine, ichimokucloud_leadingSpan1, ichimokucloud_leadingSpan2, "
sql += " stochastic_fast_k, stochastic_slow_k, stochastic_slow_d) "
sql += " VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)"
cursor.execute(sql, (
stock["CODE"], stock["NAME"], price['ymd'], price['avg5'], price['avg10'], price['avg20'],
price['avg60'], price['avg120'], price['avg200'], price['avg240'],
price['bolingerband_upper'], price['bolingerband_lower'], price['bolingerband_middle'],
price['ichimokucloud_changeLine'], price['ichimokucloud_baseLine'], price['ichimokucloud_leadingSpan1'],
price['ichimokucloud_leadingSpan2'],
price['stochastic_fast_k'], price['stochastic_slow_k'], price['stochastic_slow_d'],))
else:
break
return
def analyzeDaily(self):
stockTableName = 'stock'
conn = sqlite3.connect(self.stockFileName)
cursor = conn.cursor()
cursor.execute('SELECT distinct code, name FROM ' + stockTableName + ' order by code')
items = cursor.fetchall()
cursor.close()
conn.close()
stocks = []
for rowid, item in enumerate(items):
conn = sqlite3.connect(self.stockFileName)
cursor = conn.cursor()
@@ -820,9 +893,6 @@ class AnalyzerSqlite:
stock = {"CODE": item[0], "NAME": item[1], "PRICE":[]}
print("# :", rowid, ", CODE: ", stock['CODE'], ", NAME: ", stock['NAME'])
cursor.execute('SELECT ymd FROM ' + stockAnalysisTableName + ' WHERE CODE=? order by ymd desc', (stock['CODE'],))
result = cursor.fetchone()
sql = 'SELECT ymd, close, diff, open, high, low, volume FROM ' + stockTableName + ' where CODE=? order by ymd desc '
#if result is not None:
# sql += ' limit 300'
@@ -857,35 +927,79 @@ class AnalyzerSqlite:
"stochastic_slow_k": -1,
"stochastic_slow_d": -1})
# 이동 평균 계산
stock["PRICE"] = sorted(stock["PRICE"], key=lambda x: x['ymd'])
self.get_moving_average(stock["PRICE"])
stocks.append(stock)
self.analyzeAdditionalInfo(stock, cursor)
self.ichimokuCloud.analyze(stock)
self.stochastic.analyze(stock)
self.bolingerBand.analyze(stock)
sorted_stock = sorted(stock["PRICE"], key=lambda x: x['ymd'], reverse=True)
for price in sorted_stock:
cursor.execute('SELECT * FROM ' + stockAnalysisTableName + ' WHERE CODE=? and ymd=?', (stock['CODE'], price['ymd'],))
result = cursor.fetchone()
if result == None:
sql = "INSERT INTO " + stockAnalysisTableName + "(CODE, NAME, ymd, avg5, avg10, avg20, avg60, avg120, avg200, avg240, "
sql += " bolingerband_upper, bolingerband_lower, bolingerband_middle, "
sql += " ichimokucloud_changeLine, ichimokucloud_baseLine, ichimokucloud_leadingSpan1, ichimokucloud_leadingSpan2, "
sql += " stochastic_fast_k, stochastic_slow_k, stochastic_slow_d) "
sql += " VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)"
cursor.execute(sql, (stock["CODE"], stock["NAME"], price['ymd'], price['avg5'], price['avg10'], price['avg20'], price['avg60'], price['avg120'], price['avg200'], price['avg240'],
price['bolingerband_upper'], price['bolingerband_lower'], price['bolingerband_middle'],
price['ichimokucloud_changeLine'], price['ichimokucloud_baseLine'], price['ichimokucloud_leadingSpan1'], price['ichimokucloud_leadingSpan2'],
price['stochastic_fast_k'], price['stochastic_slow_k'], price['stochastic_slow_d'],))
else:
break
conn.commit()
cursor.close()
conn.close()
return stocks
def analyzeWeekly(self, stocks):
stocks_weekly = copy.deepcopy(stocks)
conn = sqlite3.connect(self.stockFileName)
cursor = conn.cursor()
for rowid, stock in enumerate(stocks_weekly):
print("Weekly # :", rowid, ", CODE: ", stock['CODE'], ", NAME: ", stock['NAME'])
agg_dict = {'open': 'first',
'high': 'max',
'low': 'min',
'close': 'last',
'volume': 'sum'}
df = pd.DataFrame(stock['PRICE'])
df['ymd'] = pd.to_datetime(df['ymd'])
df.set_index('ymd', inplace=True)
df_week = df.resample('W-Mon').agg(agg_dict)
df_week = df_week.dropna()
df_week.merge(df, )
stock['PRICE'] = self.convertFormat(df_week.to_dict())
self.analyzeAdditionalInfo(stock, cursor, "weekly")
conn.commit()
cursor.close()
conn.close()
return
def analyzeMonthly(self, stocks):
stocks_monthly = copy.deepcopy(stocks)
conn = sqlite3.connect(self.stockFileName)
cursor = conn.cursor()
for rowid, stock in enumerate(stocks_monthly):
print("Monthly # :", rowid, ", CODE: ", stock['CODE'], ", NAME: ", stock['NAME'])
agg_dict = {'open': 'first',
'high': 'max',
'low': 'min',
'close': 'last',
'volume': 'sum'}
df = pd.DataFrame(stock['PRICE'])
df['ymd'] = pd.to_datetime(df['ymd'])
df.set_index('ymd', inplace=True)
df_week = df.resample('M').agg(agg_dict)
df_week = df_week.dropna()
df_week.merge(df, )
stock['PRICE'] = self.convertFormat(df_week.to_dict())
self.analyzeAdditionalInfo(stock, cursor, "monthly")
conn.commit()
cursor.close()
conn.close()
return
if __name__ == "__main__":
@@ -895,7 +1009,9 @@ if __name__ == "__main__":
stockFileName = PROJECT_HOME + '/resources/stock.db'
analyzer = AnalyzerSqlite(PROJECT_HOME, stockFileName)
#analyzer.analyze()
stocks = analyzer.analyzeDaily()
analyzer.analyzeWeekly(stocks)
analyzer.analyzeMonthly(stocks)
day = datetime.today().strftime("%Y%m%d")

19
stockpredictor/analysis/IchimokuCloud.py
View File

@@ -68,8 +68,25 @@ class IchimokuCloud:
move_LeadingSpan2.insert(0, None)
# leadingSpan2에 맞추어 뒤로 빈 row를 채운다.
data = {"DATE": [], "close": [], "diff": [], "open": [], "high": [], "low": [], "volume": [], "avg5": [], "avg10": [], "avg20": [], "avg60": [], "avg120": [], "avg200": [], "avg240": []}
for i in range(len(move_LeadingSpan2) - len(df)):
df = df.append({"DATE": None, "close": None, "diff": None, "open": None, "high": None, "low": None, "volume": None, "avg3": None, "avg5": None, "avg7": None, "avg10": None, "avg20": None, "avg30": None, "avg60": None, "avg90": None, "avg100": None, "avg120": None, "avg150": None, "avg180": None, "avg200": None, "avg240": None}, ignore_index=True)
#df = df.append({"DATE": None, "close": None, "diff": None, "open": None, "high": None, "low": None, "volume": None,"avg3": None, "avg5": None, "avg7": None, "avg10": None, "avg20": None, "avg30": None, "avg60": None,"avg90": None, "avg100": None, "avg120": None, "avg150": None, "avg180": None, "avg200": None,"avg240": None}, ignore_index=True)
data["DATE"].append(None)
data["close"].append(None)
data["diff"].append(None)
data["open"].append(None)
data["high"].append(None)
data["low"].append(None)
data["volume"].append(None)
data["avg5"].append(None)
data["avg10"].append(None)
data["avg20"].append(None)
data["avg60"].append(None)
data["avg120"].append(None)
data["avg200"].append(None)
data["avg240"].append(None)
df_temp = pd.DataFrame(data)
df = pd.concat([df, df_temp])
move_changeLine = list(changeLine.values)
for i in range(len(move_LeadingSpan2) - len(move_changeLine)):
move_changeLine.append(None)

7
stockpredictor/crawler/sQLite/Crawler.py
View File

@@ -46,14 +46,17 @@ print("\n[종목 다운로드]")
stockCrawler = StockCrawler(START_DATE)
stockCrawler.crawl_etf_stocks(stockFileName)
stockCrawler.crawl_stocks(stockFileName)
stockCrawler.crawl_special_stocks(stockFileName)
#stockCrawler.crawl_special_stocks(stockFileName)
print("\n[종목 분석]")
# S: 분석까지 진행
inFileName = PROJECT_HOME + '/resources/stock.db'
analyzerSqlite = AnalyzerSqlite(PROJECT_HOME, stockFileName)
analyzerSqlite.analyze()
stocks = analyzerSqlite.analyzeDaily()
analyzerSqlite.analyzeWeekly(stocks)
analyzerSqlite.analyzeMonthly(stocks)
analyzerSqlite = AnalyzerSqlite(PROJECT_HOME, stockFileName)
print("\n[종목 결정]")