551 lines
19 KiB
Python
551 lines
19 KiB
Python
# https://bigdata-sk.tistory.com/10
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from datetime import datetime, timedelta
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import os
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import pandas as pd
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import re
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import json
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import sqlite3
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import requests
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from time import sleep
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import time
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from pandas_datareader import data as pdr
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# 닐짜 형식으로 바뀐 this_date값을 확인 가능
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# 읽어온 날짜 정보를 date형식으로 바꿀 일이 계속 생기므로 이 기능을 함수로 정의해줌.
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# 함수명은 date_format()
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class StockCrawler:
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header = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36'}
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historical_prices = None
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special_pattern = None
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fnGuideCrawler = None
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limit_page_count = 1000000
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START_DATE = None
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def __init__(self, START_DATE):
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self.historical_prices = dict()
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self.special_pattern = (
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'[', '!', '@', '#', '$', '%', '^', '&', '*', '(', ')', ',', '.', '?', '"', ':', ';', '{', '}', '|', '<', '>',
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']', '+', '-', '/', '=', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9')
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self.START_DATE = START_DATE
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return
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def clean_str(self, string):
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string = re.sub(r"\\", " ", string)
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string = re.sub(r"\'", " ", string)
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string = re.sub(r"\"", " ", string)
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string = re.sub(r"`", " ", string)
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string = re.sub(r"-", " ", string)
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string = re.sub(r"\(.*?\)", " ", string)
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string = re.sub(r" ", " ", string)
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return string.strip().lower()
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def getStockInfo(self):
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#code_df = pd.read_html('http://kind.krx.co.kr/corpgeneral/corpList.do?method=download&searchType=13', header=0)[0]
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code_df = pd.read_html(requests.get('http://kind.krx.co.kr/corpgeneral/corpList.do?method=download&searchType=13', headers=self.header, timeout=30).text)[0]
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# code_df = pd.read_excel('../resources/stock/상장법인목록.xls')
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# 종목코드가 6자리이기 때문에 6자리를 맞춰주기 위해 설정해줌
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code_df.종목코드 = code_df.종목코드.map('{:06d}'.format)
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# 우리가 필요한 것은 회사명과 종목코드이기 때문에 필요없는 column들은 제외해준다.
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code_df = code_df[['회사명', '종목코드']]
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# 한글로된 컬럼명을 영어로 바꿔준다.
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code_df = code_df.rename(columns={'회사명': 'name', '종목코드': 'code'})
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###print (code_df.head())
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return code_df
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# 종목 이름을 입력하면 종목에 해당하는 코드를 불러와
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# 네이버 금융(http://finance.naver.com)에 넣어줌
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def get_url(self, item_name, code_df):
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code = code_df.query("name=='{}'".format(item_name))['code'].to_string(index=False).strip()
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url = 'http://finance.naver.com/item/sise_day.nhn?code={code}'.format(code=code.strip())
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return code, url
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def date_format(slef, d):
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d = str(d).replace('-', '.')
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#yyyy = int(d.split('.')[0])
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#mm = int(d.split('.')[1])
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#dd = int(d.split('.')[2])
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#this_date = dt.date(yyyy, mm, dd)
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return d
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def getCodeIndex(self, stocks, item_code):
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for i, stock in enumerate(stocks):
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if item_code == stock['CODE']:
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return i
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return -1
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def crawl_etf_stocks(self, inFileName):
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tableName = 'stock'
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conn = sqlite3.connect(inFileName)
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cursor = conn.cursor()
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# 테이블 생성
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cursor.execute("CREATE TABLE IF NOT EXISTS " + tableName + " (CODE text, NAME text, ymd text, close REAL, diff REAL, open REAL, high REAL, low REAL, volume REAL)")
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# 키 생성
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create_key = "CREATE INDEX IF NOT EXISTS " + tableName + "_idx on " + tableName + " (CODE, ymd) "
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cursor.execute(create_key)
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stocks = []
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stocks.append({"NAME": 'KODEX 코스닥150선물인버스', "CODE": "251340"})
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stocks.append({"NAME": 'KODEX 코스닥150 레버리지', "CODE": "233740"})
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stocks.append({"NAME": 'KODEX 200선물인버스2X', "CODE": "252670"})
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stocks.append({"NAME": 'KODEX 레버리지', "CODE": "122630"})
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stocks.append({"NAME": 'KODEX 인버스', "CODE": "114800"})
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stocks.append({"NAME": 'KODEX 중국본토CSI300', "CODE": "283580"})
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stocks.append({"NAME": 'KODEX 심천ChiNext(합성)', "CODE": "256750"})
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stocks.append({"NAME": 'KINDEX 블룸버그베트남VN30선물레버리지(H)', "CODE": "371130"})
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stocks.append({"NAME": 'KODEX 미국S&P바이오(합성)', "CODE": "185680"})
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stocks.append({"NAME": 'KODEX 미국S&P에너지(합성)', "CODE": "218420"})
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stocks.append({"NAME": 'KODEX 골드선물(H)', "CODE": "132030"})
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stocks.append({"NAME": 'KODEX 콩선물(H)', "CODE": "138920"})
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stocks.append({"NAME": 'KODEX 3대농산물선물(H)', "CODE": "271060"})
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stocks.append({"NAME": 'KODEX 건설', "CODE": "117700"})
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stocks.append({"NAME": 'KODEX 헬스케어', "CODE": "266420"})
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stocks.append({"NAME": 'KODEX 글로벌4차산업로보틱스(합성)', "CODE": "276990"})
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stocks.append({"NAME": 'KODEX 바이오', "CODE": "244580"})
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stocks.append({"NAME": 'KODEX 반도체', "CODE": "091160"})
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stocks.append({"NAME": 'KODEX 보험', "CODE": "140700"})
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stocks.append({"NAME": 'KODEX 필수소비재', "CODE": "266410"})
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stocks.append({"NAME": 'KODEX 2차전지산업', "CODE": "305720"})
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stocks.append({"NAME": 'KODEX 경기소비재', "CODE": "266390"})
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stocks.append({"NAME": 'KODEX 철강', "CODE": "117680"})
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stocks.append({"NAME": 'KODEX 에너지화학', "CODE": "117460"})
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stocks.append({"NAME": 'KODEX 은행', "CODE": "091170"})
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stocks.append({"NAME": 'TIGER 탄소효율그린뉴딜', "CODE": "376410"})
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start_time = time.time()
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for i, stock in enumerate(stocks):
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print (i, stock["NAME"], stock["CODE"], (time.time()-start_time), "s")
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start_time = time.time()
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cursor.execute('SELECT ymd FROM ' + tableName + ' WHERE CODE=? order by ymd desc', (stock["CODE"],))
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result = cursor.fetchone()
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ymd = self.START_DATE
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if result is not None:
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ymd = result[0]
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stock_data = self.crawl_specific_stock(stock["CODE"], ymd)
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for item in stock_data:
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cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=? and ymd=?', (stock["CODE"],item['ymd'],))
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result = cursor.fetchone()
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if result == None:
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cursor.execute("INSERT INTO " + tableName + "(CODE, NAME, ymd, close, diff, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?)", (stock["CODE"], stock["NAME"], item['ymd'], item['close'], item['diff'], item['open'], item['high'], item['low'], item['volume']))
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#else:
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# cursor.execute("UPDATE " + tableName + " SET close=?, diff=?, open=?, high=?, low=?, volume=? WHERE CODE=? and ymd=?", (item['close'], item['diff'], item['open'], item['high'], item['low'], item['volume'], stock["CODE"], item['ymd']))
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sleep(0.05)
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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 crawl_stocks(self, inFileName):
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tableName = 'stock'
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conn = sqlite3.connect(inFileName)
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cursor = conn.cursor()
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# 테이블 생성
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cursor.execute("CREATE TABLE IF NOT EXISTS " + tableName + " (CODE text, NAME text, ymd text, close REAL, diff REAL, open REAL, high REAL, low REAL, volume REAL)")
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# 키 생성
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create_key = "CREATE INDEX IF NOT EXISTS " + tableName + "_idx on " + tableName + " (CODE, ymd) "
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cursor.execute(create_key)
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conn.commit()
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cursor.close()
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conn.close()
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code_df = self.getStockInfo()
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items = code_df.values
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start_time = time.time()
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idx = 0
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for item in items:
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idx += 1
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conn = sqlite3.connect(inFileName)
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cursor = conn.cursor()
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item_name = item[0]
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item_code = item[1]
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cursor.execute('SELECT ymd FROM ' + tableName + ' WHERE CODE=? order by ymd desc', (item_code,))
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result = cursor.fetchone()
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stock = {"CODE": item_code, "NAME": item_name}
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#ymd = (datetime.today() - timedelta(days=300)).strftime('%Y-%m-%d')
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ymd = self.START_DATE.replace(".", "-")
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if result is not None:
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ymd = result[0]
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stock_data = self.crawl_specific_stock(item_code, ymd)
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for item in stock_data:
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cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=? and ymd=?', (stock["CODE"],item['ymd'],))
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result = cursor.fetchone()
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if result == None:
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cursor.execute("INSERT INTO " + tableName + "(CODE, NAME, ymd, close, diff, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?)", (stock["CODE"], stock["NAME"], item['ymd'], item['close'], item['diff'], item['open'], item['high'], item['low'], item['volume']))
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#else:
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# cursor.execute("UPDATE " + tableName + " SET close=?, diff=?, open=?, high=?, low=?, volume=? WHERE CODE=? and ymd=?", (item['close'], item['diff'], item['open'], item['high'], item['low'], item['volume'], stock["CODE"], item['ymd']))
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conn.commit()
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cursor.close()
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conn.close()
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print(idx, item_name, item_code, (time.time() - start_time), "s")
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start_time = time.time()
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sleep(0.05)
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return
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def crawl_special_stocks(self, inFileName):
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tableName = 'stock'
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conn = sqlite3.connect(inFileName)
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cursor = conn.cursor()
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# 테이블 생성
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cursor.execute("CREATE TABLE IF NOT EXISTS " + tableName + " (CODE text, NAME text, ymd text, close REAL, diff REAL, open REAL, high REAL, low REAL, volume REAL)")
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# 키 생성
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create_key = "CREATE INDEX IF NOT EXISTS " + tableName + "_idx on " + tableName + " (CODE, ymd) "
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cursor.execute(create_key)
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conn.commit()
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cursor.close()
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conn.close()
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start_time = time.time()
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pd.options.display.float_format = '{:.4f}'.format
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pd.set_option('display.max_columns', None)
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special_stocks = {
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'^KS11': 'Kospi',
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'^KQ11': 'Kosdak',
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'SQQQ': 'ProShares UltraPro Short QQQ',
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'TQQQ': 'ProShares UltraPro QQQ',
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'SCO': 'ProShares UltraShort Bloomberg Crude Oil',
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'UCO': 'ProShares Ultra Bloomberg Crude Oil',
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'GLL': 'ProShares UltraShort Gold',
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'UGL': 'ProShares Ultra Gold',
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'SOXS': 'Direxion Daily Semiconductor Bear -3X Shares',
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'SOXL': 'Direxion Daily Semiconductor Bull 3X Shares',
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'FNGD': 'MicroSectors™ FANG+™ Index -3X Inverse Leveraged ETN',
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'FNGU': 'MicroSectors™ FANG+™ Index 3X Leveraged ETN',
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'AAPL': 'Apple',
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'MSFT': 'Microsoft',
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'GOOG': 'Alphabet C',
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'AMZN': 'Amazon.com',
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'AVGO': 'Broadcom',
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'FB': 'Meta Platforms',
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'NVDA': 'NVIDIA',
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'UNH': 'UnitedHealth',
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'TSM': 'Taiwan Semiconductor',
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'JNJ': 'Johnson & Johnson (JNJ)',
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'TCTZF': 'Tencent Holdings',
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'V': 'Visa A',
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'WMT': 'Walmart',
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'XOM': 'Exxon Mobil',
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'JPM': 'JPMorgan',
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'MA': 'Mastercard',
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'CVX': 'Chevron Corp',
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'HD': 'Home Depot',
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'BAC': 'Bank of America',
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'KO': 'Coca-Cola',
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'COST': 'Costco',
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'DIS': 'Walt Disney',
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'VZ': 'Verizon',
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'CSCO': 'Cisco',
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'ORCL': 'Oracle',
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'NKE': 'Nike',
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'ACN': 'Accenture',
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'ADBE': 'Adobe',
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'CRM': 'Salesforce.com',
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'INTC': 'Intel',
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'QCOM': 'Qualcomm',
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'AMD': 'AMD',
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'MS': 'Morgan Stanley',
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'T': 'AT&T',
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'HON': 'Honeywell',
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'IBM': 'IBM',
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'DQ': 'Daqo New Energy Corp ADR',
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'EBAY': 'eBay Inc',
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'NTAP': 'NetApp Inc',
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'ASML': 'ASML Holding NV ADR',
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'BABA': 'Alibaba Group Holdings Ltd ADR'}
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conn = sqlite3.connect(inFileName)
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cursor = conn.cursor()
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us_sotck_data = {}
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for ticker in special_stocks:
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cursor.execute('SELECT ymd FROM ' + tableName + ' WHERE CODE=? order by ymd desc', (ticker,))
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result = cursor.fetchone()
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if result is not None:
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start_day = result[0].replace(".", "-")
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end_day = datetime.today().strftime('%Y-%m-%d')
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else:
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#start_day = pd.to_datetime('2017-01-01')
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start_day = self.START_DATE.replace(".", "-")
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end_day = datetime.today().strftime('%Y-%m-%d')
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data = None
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while True:
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try:
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data = pdr.get_data_yahoo(ticker, start_day, end_day)
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break
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except:
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print(ticker)
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continue
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us_sotck_data[ticker] = {
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'close': data['Close'].to_dict(),
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'open': data['Open'].to_dict(),
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'high': data['High'].to_dict(),
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'low': data['Low'].to_dict(),
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'volume': data['Volume'].to_dict()
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}
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cursor.close()
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conn.close()
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dateList = list(us_sotck_data['SQQQ']['close'])
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for idx, item_code in enumerate(us_sotck_data):
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stock_data = []
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stock = us_sotck_data[item_code]
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for i, ymd in enumerate(dateList):
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if i > 0:
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if ymd in stock['close'] and dateList[i-1] in stock['close']:
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diff = stock['close'][ymd] - stock['close'][dateList[i-1]]
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else:
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continue
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else:
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if ymd in stock['close']:
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diff = stock['close'][ymd]
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else:
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continue
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stock_data.append({
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'CODE':item_code, 'NAME':special_stocks[item_code], 'ymd': ymd.strftime('%Y.%m.%d'),
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'close': round(stock['close'][ymd], 2), 'diff': round(diff, 2), 'open': round(stock['open'][ymd], 2),
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'high': round(stock['high'][ymd], 2), 'low': round(stock['low'][ymd], 2), 'volume': stock['volume'][ymd]
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})
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stock_data = reversed(stock_data)
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conn = sqlite3.connect(inFileName)
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cursor = conn.cursor()
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for item in stock_data:
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cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=? and ymd=?', (item["CODE"],item['ymd'],))
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result = cursor.fetchone()
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if result == None:
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cursor.execute("INSERT INTO " + tableName + "(CODE, NAME, ymd, close, diff, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?)", (item["CODE"], item["NAME"], item['ymd'], item['close'], item['diff'], item['open'], item['high'], item['low'], item['volume']))
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#else:
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# cursor.execute("UPDATE " + tableName + " SET close=?, diff=?, open=?, high=?, low=?, volume=? WHERE CODE=? and ymd=?", (item['close'], item['diff'], item['open'], item['high'], item['low'], item['volume'], stock["CODE"], item['ymd']))
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conn.commit()
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cursor.close()
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conn.close()
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print(idx, item_code, special_stocks[item_code], (time.time() - start_time), "s")
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start_time = time.time()
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sleep(0.05)
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return
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def get_data(self, code, lastDay):
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url = 'http://finance.naver.com/item/sise_day.nhn?code={code}'.format(code=code.strip())
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stock = []
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# 일자 데이터를 담을 df라는 DataFrame 정의
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df = pd.DataFrame()
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date_set = set()
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lastPage = False
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# 1페이지에서 1000페이지의 데이터만 가져오기
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for page in range(1, self.limit_page_count):
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# 최근 상장 기업의 마지막 반복되는 페이지를 제외시킨다.
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pg_url = '{url}&page={page}'.format(url=url, page=page)
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#html = pd.read_html(pg_url, header=0)
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html = None
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while True:
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try:
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html = pd.read_html(requests.get(pg_url, headers=self.header, timeout=30).text)
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sleep(0.5)
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break
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except:
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print(pg_url)
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if page > 200:
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break
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continue
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for date in html[0].날짜.values:
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if type(date) is str:
|
|
if date in date_set:
|
|
lastPage = True
|
|
break
|
|
date_set.add(date)
|
|
|
|
if date == lastDay:
|
|
lastPage = True
|
|
df = pd.concat((df, html[0]), ignore_index=True)
|
|
break
|
|
df = pd.concat((df, html[0]), ignore_index=True)
|
|
df = df.dropna()
|
|
if (lastPage) or (len(df) < 1) or ("날짜" not in df) or (df.날짜[1]==''):
|
|
print("\t- lastpage:", page)
|
|
break
|
|
|
|
# df.dropna()를 이용해 결측값 있는 행 제거
|
|
df = df.dropna()
|
|
|
|
# 상위 5개 데이터 확인하기
|
|
###print (df.head())
|
|
|
|
# 한글로 된 컬럼명을 영어로 바꿔줌
|
|
df = df.rename(columns={'날짜': 'date', '종가': 'close', '전일비': 'diff', '시가': 'open', '고가': 'high', '저가': 'low', '거래량': 'volume'})
|
|
|
|
# 데이터의 타입을 int형으로 바꿔줌
|
|
df[['close', 'diff', 'open', 'high', 'low', 'volume']] = df[['close', 'diff', 'open', 'high', 'low', 'volume']].astype(int)
|
|
|
|
for values in df.values:
|
|
day = str(values[0]).split(' ')[0]
|
|
if lastDay == day:
|
|
break
|
|
stock.append({
|
|
"ymd": day,
|
|
df.columns[1]: values[1],
|
|
df.columns[2]: values[2],
|
|
df.columns[3]: values[3],
|
|
df.columns[4]: values[4],
|
|
df.columns[5]: values[5],
|
|
df.columns[6]: values[6],
|
|
})
|
|
|
|
# stock = sorted(stock, key=lambda x: x['ymd'], reverse=True)
|
|
stock = sorted(stock, key=lambda x: x['ymd'])
|
|
return stock
|
|
|
|
def crawl_specific_stock(self, code, ymd):
|
|
# 데이터 수집
|
|
stock = self.get_data(code, ymd)
|
|
|
|
# 이동 평균 계산
|
|
#self.get_moving_avg(stock)
|
|
|
|
return stock
|
|
|
|
def update(self, inFileName, outFileName):
|
|
"""
|
|
Full json 데이터를 db에 import 시킴
|
|
inFileName = PROJECT_HOME + '/resources/stock.json.full'
|
|
outFileName = PROJECT_HOME + '/resources/stock.db'
|
|
crawler = StockCrawler()
|
|
crawler.update(inFileName, outFileName)
|
|
|
|
:param inFileName:
|
|
:param outFileName:
|
|
:return:
|
|
"""
|
|
tableName = 'stock'
|
|
conn = sqlite3.connect(outFileName, isolation_level=None)
|
|
cursor = conn.cursor()
|
|
cursor.execute("CREATE TABLE IF NOT EXISTS " + tableName + " (CODE text PRIMARY KEY, NAME text, PRICE text, MACD text, STOCHASTIC text, ICHIMOKU text, RSI text, BOLINGERBAND text)")
|
|
|
|
idx = 0
|
|
inFp = open(inFileName, 'r')
|
|
for line in inFp.readlines():
|
|
if line:
|
|
idx += 1
|
|
stock = json.loads(line)
|
|
print(idx, stock["CODE"], stock["NAME"])
|
|
|
|
text = json.dumps(stock["PRICE"], ensure_ascii=False)
|
|
|
|
cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=?', (stock["CODE"],))
|
|
result = cursor.fetchone()
|
|
if result == None:
|
|
cursor.execute("INSERT INTO " + tableName + "(CODE, NAME, PRICE) VALUES(?, ?, ?)", (stock["CODE"], stock["NAME"], text))
|
|
else:
|
|
cursor.execute("UPDATE " + tableName + " SET PRICE=? WHERE CODE=?", (text, stock["CODE"]))
|
|
|
|
return
|
|
|
|
|
|
def saveIndex(self, code, inFileName, outFileName):
|
|
tableName = 'stock'
|
|
conn = sqlite3.connect(outFileName)
|
|
cursor = conn.cursor()
|
|
cursor.execute("CREATE TABLE IF NOT EXISTS " + tableName + " (CODE text PRIMARY KEY, NAME text, PRICE text, MACD text, STOCHASTIC text, ICHIMOKU text, RSI text, BOLINGERBAND text)")
|
|
|
|
stock = {"NAME": code, "CODE": code}
|
|
|
|
lastDay = ""
|
|
cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=?', (stock["CODE"],))
|
|
result = cursor.fetchone()
|
|
if result is not None:
|
|
stock["PRICE"] = json.loads(result[2])
|
|
lastDay = stock["PRICE"][len(stock["PRICE"]) - 1]["DATE"]
|
|
|
|
with open(inFileName, "r", encoding="utf-8") as inFp:
|
|
for line in inFp:
|
|
line = line.strip()
|
|
if line[0] == "#":
|
|
continue
|
|
|
|
arr = line.split("\t")
|
|
if arr[0] == lastDay:
|
|
break
|
|
|
|
price = {"DATE": arr[0], "close": float(arr[1]), "diff": float(arr[6].replace("%", "")), "open": float(arr[2]), "high": float(arr[3]), "low": float(arr[4]), "volume": 0}
|
|
price['avg3'] = 0
|
|
price['avg5'] = 0
|
|
price['avg7'] = 0
|
|
price['avg10'] = 0
|
|
price['avg20'] = 0
|
|
price['avg30'] = 0
|
|
price['avg60'] = 0
|
|
price['avg90'] = 0
|
|
price['avg100'] = 0
|
|
price['avg120'] = 0
|
|
price['avg150'] = 0
|
|
price['avg180'] = 0
|
|
price['avg200'] = 0
|
|
price['avg240'] = 0
|
|
stock["PRICE"].append(price)
|
|
|
|
stock["PRICE"] = sorted(stock["PRICE"], key=lambda x: x['DATE'])
|
|
# self.get_moving_avg(stock)
|
|
|
|
text = json.dumps(stock['PRICE'], ensure_ascii=False)
|
|
|
|
cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=?', (stock["CODE"],))
|
|
result = cursor.fetchone()
|
|
if result == None:
|
|
cursor.execute("INSERT INTO " + tableName + "(CODE, NAME, PRICE, MACD, STOCHASTIC, ICHIMOKU, RSI) VALUES(?, ?, ?, ?, ?, ?, ?)", (stock["CODE"], stock["NAME"], text, "[{}]", "[{}]", "[{}]", "[{}]"))
|
|
else:
|
|
cursor.execute("UPDATE " + tableName + " SET PRICE=?, MACD=?, STOCHASTIC=?, ICHIMOKU=?, RSI=? WHERE CODE=?", (text, "[{}]", "[{}]", "[{}]", "[{}]", stock["CODE"]))
|
|
|
|
conn.commit()
|
|
cursor.close()
|
|
conn.close()
|
|
return
|
|
|
|
if __name__ == "__main__":
|
|
stockCrawler = StockCrawler()
|
|
|
|
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__))))))))
|
|
stockFileName = PROJECT_HOME + '/resources/stock.db'
|
|
stockCrawler.crawl_us_sotck_datas(stockFileName)
|