75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
import os
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import shutil
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import datetime
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import time
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from stockpredictor.crawler.sQLite.FnGuideCrawler import FnGuideCrawler
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from stockpredictor.crawler.sQLite.MetaCrawler import MetaCrawler
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from stockpredictor.crawler.sQLite.StockCrawler import StockCrawler
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from stockpredictor.analysis.AnalyzerSqlite import AnalyzerSqlite
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today = datetime.datetime.now().strftime("%Y-%m-%d")
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# DB Browser for SQLite: http://hleecaster.com/python-sqlite3/
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PROJECT_HOME = os.path.join(os.path.dirname(os.path.join(os.path.dirname(os.path.join(os.path.dirname(os.path.join(os.path.dirname(__file__))))))))
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START_DATE = "1900.01.01"
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start = time.time()
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stockFileName = PROJECT_HOME + '/resources/stock.db'
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# 재무제표는 3개월마다 다운로드를 한다.
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fnGuideCrawler = FnGuideCrawler(START_DATE)
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print("[KOSPI 상장기업 재무제표 다운로드]")
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fnGuideCrawler.crawl_fnguide(stockFileName)
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metaCrawler = MetaCrawler(START_DATE)
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print("\n[증시자금동향 (신용잔고, 펀드자금 잔고)]")
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metaCrawler.crawl_money_trend(stockFileName)
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print("\n[국내 시장금리]")
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metaCrawler.crawl_interest_rates(stockFileName)
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print("\n[투자자별 매매동향(Trading_Trend)]")
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metaCrawler.crawl_trading_trend(stockFileName)
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print("\n[환율 (USD, JPY, EUR, CNY)]")
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metaCrawler.crawl_exchange(stockFileName)
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print("\n[원유 (WTI), 국제금, COPPER, NATURALGAS, CORN, SOYBEAN]")
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metaCrawler.crawl_meterials(stockFileName)
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print("\n[종목 다운로드]")
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stockCrawler = StockCrawler(START_DATE)
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stockCrawler.crawl_etf_stocks(stockFileName)
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stockCrawler.crawl_stocks(stockFileName)
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#stockCrawler.crawl_special_stocks(stockFileName)
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print("\n[종목 분석]")
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# S: 분석까지 진행
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inFileName = PROJECT_HOME + '/resources/stock.db'
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analyzerSqlite = AnalyzerSqlite(PROJECT_HOME, stockFileName)
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stocks = analyzerSqlite.analyzeDaily()
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analyzerSqlite.analyzeWeekly(stocks)
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analyzerSqlite.analyzeMonthly(stocks)
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analyzerSqlite = AnalyzerSqlite(PROJECT_HOME, stockFileName)
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print("\n[종목 결정]")
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day = datetime.datetime.today().strftime("%Y%m%d")
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outPath = PROJECT_HOME + "/resources/analysis/" + day
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if os.path.isdir(outPath):
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shutil.rmtree(outPath)
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os.mkdir(outPath)
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print("print to Html...")
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analyzerSqlite.findCandidate(outPath)
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# E: 분석까지 진행
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print("time : %6.2f 초", (time.time() - start))
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print ("done...")
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