프로그래머 라이프

import pandas as pd
from pathlib import Path

class SingletonType(type):
    def __call__(cls, *args, **kwargs):
        try:
            return cls.__instance
        except AttributeError:
            cls.__instance = super(SingletonType, cls).__call__(*args, **kwargs)
            return cls.__instance

class CodeMan(object, metaclass=SingletonType):

    FILENAME = 'codelist.csv'

    def __init__(self):
        self.code_df = self.get_code_list()

    def get_code_list(self):

        code_df = None

        if Path(CodeMan.FILENAME).is_file():
            print('READ CSV')
            code_df = self.read_csv()
        else:
            print('LOAD DATA')
            code_df = pd.read_html('http://kind.krx.co.kr/corpgeneral/corpList.do?method=download&searchType=13', header=0)[0]
            code_df.종목코드 = code_df.종목코드.map('{:06d}'.format)
            code_df = code_df[['회사명', '종목코드']]
            code_df = code_df.rename(columns={'회사명': 'name', '종목코드': 'code'})
            self.write_csv(code_df)

        return code_df

    def show(self):
        print(self.code_df)

    def write_csv(self, df):
        print('WRITE DATA')
        data_df = pd.DataFrame(df, columns=['code', 'name'])
        data_df.to_csv(CodeMan.FILENAME, index=False)

    def read_csv(self):
        df = pd.DataFrame.from_csv(CodeMan.FILENAME, header=0, parse_dates=False)
        df.reset_index(inplace=True)
        df.code =df.code.map('{:06d}'.format)

        return df

    def get_daily_url(self, item_name):
        code = self.code_df.query("name=='{}'".format(item_name))['code'].to_string(index=False)
        url = 'http://finance.naver.com/item/sise_day.nhn?code={code}'.format(code=code)
        print("요청 URL = {}".format(url))
        return url

    def get_price_data(self, item_name, pageno):

        url = self.get_daily_url(item_name)
        df = pd.DataFrame()

        for page in range(1, pageno+1):
            pg_url = '{url}&page={page}'.format(url=url, page=page)
            df = df.append(pd.read_html(pg_url, header=0)[0], ignore_index=True)

        df = df.dropna()

        df = df.rename(columns= {'날짜': 'Date', '종가': 'Close', '전일비': 'Diff', '시가': 'Open', '고가': 'High', '저가': 'Low', '거래량': 'Volume'})

        df[['Close', 'Diff', 'Open', 'High', 'Low', 'Volume']] = df[['Close', 'Diff', 'Open', 'High', 'Low', 'Volume']].astype(int)

        df['Date'] = pd.to_datetime(df['Date'])

        df = df.sort_values(by=['Date'], ascending=True)

        print(df.head())
        return df

    def get_min_url(self, item_name, thistime):
        code = self.code_df.query("name=='{}'".format(item_name))['code'].to_string(index=False)
        url = 'https://finance.naver.com/item/sise_time.nhn?code={code}&thistime={thistime}'.format(code=code, thistime=thistime)
        print("요청 URL = {}".format(url))
        return url

    def get_min_price_data(self, item_name, date, pageno):

        url = self.get_min_url(item_name, date)
        df = pd.DataFrame()

        for page in range(1, pageno+1):
            pg_url = '{url}&page={page}'.format(url=url, page=page)
            # print(pg_url)
            subdf = pd.read_html(pg_url, header=0)[0]
            subdf = subdf.dropna()
            df = df.append(subdf, ignore_index=True)

            if len(subdf)<10:
                break

        df = df.rename(columns= {'체결시각': 'Date', '체결가': 'Price', '전일비': 'Diff', '매도': 'Ask', '매수': 'Bid', '거래량': 'Volume', '변동량': 'Qty'})
        df[['Price', 'Diff','Qty', 'Ask', 'Bid', 'Volume']] = df[['Price', 'Diff','Qty', 'Ask', 'Bid', 'Volume']].astype(int)
        df['Date'] = pd.to_datetime(df['Date'])

        df =df.set_index(['Date'])
        # print(df_volume)
        df = df.sort_values(by=['Date'], ascending=True)

        return df

    def get_ohlc(self, df, period):
        df_ohlc = df['Price'].resample(period).ohlc()
        # df_ohlc = df.resample('30T', how={'price': 'ohlc'})
        df_qty = df['Qty'].resample(period).sum()

        frames = [df_ohlc, df_qty]
        df2 = pd.concat(frames, axis=1)
        return df2


    def step1(self, name, date, pageno):
        df = self.get_min_price_data(name, date, pageno)
        df2 = self.get_ohlc(df, '5T')
        print(df2)

# CodeMan.__call__().write_csv()
# CodeMan.__call__().get_price_data('코리안리', 5)
# CodeMan.__call__().get_min_price_data('코리안리', '2018082223', 3)
CodeMan.__call__().step1('코리안리', '2018082223', 100)

------------- 결과 ----------------

                        open     high      low    close    Qty

Date                                                          

2018-08-23 09:00:00  10750.0  10750.0  10700.0  10750.0  11020

2018-08-23 09:05:00  10700.0  10700.0  10700.0  10700.0    735

2018-08-23 09:10:00  10700.0  10700.0  10700.0  10700.0   1647

.....