Beispiel #1
0
def get_adj_rate(code, fuquan_df):
    frow = fuquan_df.head(1)
    rt = td.get_realtime_quotes(code)
    if rt is None:
        return None
    if ((float(rt['high']) == 0) & (float(rt['low']) == 0)):
        preClose = float(rt['pre_close'])
    else:
        if du.is_holiday(du.today()):
            preClose = float(rt['price'])
        else:
            if (du.get_hour() > 9) & (du.get_hour() < 18):
                preClose = float(rt['pre_close'])
            else:
                preClose = float(rt['price'])

    rate = float(frow['fqprice']) / preClose
    return rate
def get_adj_rate(code,stock_list,fuquan_df):
    frow = fuquan_df.head(1)
    rt = stock_list[stock_list.code == code]
    if rt.empty:
        return None
    if ((float(rt['high']) == 0) & (float(rt['low']) == 0)):
        preClose = float(rt['settlement'])
    else:
        if du.is_holiday(du.today()):
            preClose = float(rt['trade'])
        else:
            if (du.get_hour() > 9) & (du.get_hour() < 18):
                preClose = float(rt['settlement'])
            else:
                preClose = float(rt['trade'])
    
    rate = float(frow['fqprice']) / preClose
    return rate
Beispiel #3
0
def get_adj_rate(code, stock_list, fuquan_df):
    frow = fuquan_df.head(1)
    rt = stock_list[stock_list.code == code]
    if rt.empty:
        return None
    if ((float(rt['high']) == 0) & (float(rt['low']) == 0)):
        preClose = float(rt['settlement'])
    else:
        if du.is_holiday(du.today()):
            preClose = float(rt['trade'])
        else:
            if (du.get_hour() > 9) & (du.get_hour() < 18):
                preClose = float(rt['settlement'])
            else:
                preClose = float(rt['trade'])

    rate = float(frow['fqprice']) / preClose
    return rate
Beispiel #4
0
def get_adj_rate(code,fuquan_df):
    frow = fuquan_df.head(1)
    rt = td.get_realtime_quotes(code)
    if rt is None:
        return None
    if ((float(rt['high']) == 0) & (float(rt['low']) == 0)):
        preClose = float(rt['pre_close'])
    else:
        if du.is_holiday(du.today()):
            preClose = float(rt['price'])
        else:
            if (du.get_hour() > 9) & (du.get_hour() < 18):
                preClose = float(rt['pre_close'])
            else:
                preClose = float(rt['price'])
    
    rate = float(frow['fqprice']) / preClose
    return rate
Beispiel #5
0
def get_today_ticks(code=None, retry_count=3, pause=0.001):
    """
        获取当日分笔明细数据
    Parameters
    ------
        code:string
                  股票代码 e.g. 600848
        retry_count : int, 默认 3
                  如遇网络等问题重复执行的次数
        pause : int, 默认 0
                 重复请求数据过程中暂停的秒数,防止请求间隔时间太短出现的问题
     return
     -------
        DataFrame 当日所有股票交易数据(DataFrame)
              属性:成交时间、成交价格、价格变动,成交手、成交金额(元),买卖类型
    """
    if code is None or len(code) != 6:
        return None
    symbol = _code_to_symbol(code)
    date = du.today()
    try:
        request = Request(ct.TODAY_TICKS_PAGE_URL % (date, symbol))
        data_str = urlopen(request, timeout=10).read()
        data_str = data_str.decode('GBK')
        data_str = data_str[1:-1]
        data_str = eval(
            data_str,
            type('Dummy', (dict, ), dict(__getitem__=lambda s, n: n))())
        data_str = json.dumps(data_str)
        data_str = json.loads(data_str)
        pages = len(data_str['detailPages'])
        data = pd.DataFrame()
        ct._write_head()
        for pNo in range(1, pages):
            data = data.append(_today_ticks(symbol, date, pNo, retry_count,
                                            pause),
                               ignore_index=True)
    except Exception as er:
        print(str(er))
    return data
Beispiel #6
0
def get_today_ticks(code=None, retry_count=3, pause=0.001):
    """
        获取当日分笔明细数据
    Parameters
    ------
        code:string
                  股票代码 e.g. 600848
        retry_count : int, 默认 3
                  如遇网络等问题重复执行的次数
        pause : int, 默认 0
                 重复请求数据过程中暂停的秒数,防止请求间隔时间太短出现的问题
     return
     -------
        DataFrame 当日所有股票交易数据(DataFrame)
              属性:成交时间、成交价格、价格变动,成交手、成交金额(元),买卖类型
    """
    if code is None or len(code)!=6 :
        return None
    symbol = _code_to_symbol(code)
    date = du.today()
    try:
        request = Request(ct.TODAY_TICKS_PAGE_URL % ( date,symbol))
        data_str = urlopen(request, timeout=10).read()
        data_str = data_str.decode('GBK')
        data_str = data_str[1:-1]
        data_str = eval(data_str, type('Dummy', (dict,), 
                                       dict(__getitem__ = lambda s, n:n))())
        data_str = json.dumps(data_str)
        data_str = json.loads(data_str)
        pages = len(data_str['detailPages'])
        data = pd.DataFrame()
        ct._write_head()
        for pNo in range(1, pages):
            data = data.append(_today_ticks(symbol, date, pNo,
                                            retry_count, pause), ignore_index=True)
    except Exception as er:
        print(str(er))
    return data
Beispiel #7
0
def get_h_data(code, start=None, end=None, autype='qfq',
               index=False, retry_count=3, pause=0.001):
    '''
    获取历史复权数据
    Parameters
    ------
      code:string
                  股票代码 e.g. 600848
      start:string
                  开始日期 format:YYYY-MM-DD 为空时取当前日期
      end:string
                  结束日期 format:YYYY-MM-DD 为空时取去年今日
      autype:string
                  复权类型,qfq-前复权 hfq-后复权 None-不复权,默认为qfq
      retry_count : int, 默认 3
                 如遇网络等问题重复执行的次数 
      pause : int, 默认 0
                重复请求数据过程中暂停的秒数,防止请求间隔时间太短出现的问题
    return
    -------
      DataFrame
          date 交易日期 (index)
          open 开盘价
          high  最高价
          close 收盘价
          low 最低价
          volume 成交量
          amount 成交金额
          factor 后复权因子
    '''
    
    start = du.today_last_year() if start is None else start
    end = du.today() if end is None else end
    qs = du.get_quarts(start, end)
    qt = qs[0]
    ct._write_head()
    data = _parse_fq_data(_get_index_url(index, code, qt), index,
                          retry_count, pause)
    if len(qs)>1:
        for d in range(1, len(qs)):
            qt = qs[d]
            ct._write_console()
            df = _parse_fq_data(_get_index_url(index, code, qt), index,
                                retry_count, pause)
            data = data.append(df, ignore_index=True)
    if len(data) == 0 or len(data[(data.date>=start)&(data.date<=end)]) == 0:
        return None
    data = data.drop_duplicates('date')
    if index:
        data = data[(data.date>=start) & (data.date<=end)]
        data = data.set_index('date')
        data = data.sort_index(ascending=False)
        return data
    if autype == 'hfq':
        #data = data.drop('factor', axis=1)
        data = data[(data.date>=start) & (data.date<=end)]
        for label in ['open', 'high', 'close', 'low']:
            data[label] = data[label].map(ct.FORMAT)
            data[label] = data[label].astype(float)
        data = data.set_index('date')
        data = data.sort_index(ascending = False)
        return data
    else:
        if autype == 'qfq':
            #data = data.drop('factor', axis=1)
            df = _parase_fq_factor(code, start, end)
            df = df.drop_duplicates('date')
            df = df.sort('date', ascending=False)
            frow = df.head(1)
            rt = get_realtime_quotes(code)
            if rt is None:
                return None
            if ((float(rt['high']) == 0) & (float(rt['low']) == 0)):
                preClose = float(rt['pre_close'])
            else:
                if du.is_holiday(du.today()):
                    preClose = float(rt['price'])
                else:
                    if (du.get_hour() > 9) & (du.get_hour() < 18):
                        preClose = float(rt['pre_close'])
                    else:
                        preClose = float(rt['price'])
            
            rate = float(frow['factor']) / preClose
            data = data[(data.date >= start) & (data.date <= end)]
            for label in ['open', 'high', 'low', 'close']:
                data[label] = data[label] / rate
                data[label] = data[label].map(ct.FORMAT)
                data[label] = data[label].astype(float)
            data = data.set_index('date')
            data = data.sort_index(ascending = False)
            return data
        else:
            for label in ['open', 'high', 'close', 'low']:
                data[label] = data[label] / data['factor']
            #data = data.drop('factor', axis=1)
            data = data[(data.date>=start) & (data.date<=end)]
            for label in ['open', 'high', 'close', 'low']:
                data[label] = data[label].map(ct.FORMAT)
            data = data.set_index('date')
            data = data.sort_index(ascending=False)
            data = data.astype(float)
            return data
Beispiel #8
0
def get_h_data(code,
               start=None,
               end=None,
               autype='qfq',
               index=False,
               retry_count=3,
               pause=0.001):
    '''
    获取历史复权数据
    Parameters
    ------
      code:string
                  股票代码 e.g. 600848
      start:string
                  开始日期 format:YYYY-MM-DD 为空时取当前日期
      end:string
                  结束日期 format:YYYY-MM-DD 为空时取去年今日
      autype:string
                  复权类型,qfq-前复权 hfq-后复权 None-不复权,默认为qfq
      retry_count : int, 默认 3
                 如遇网络等问题重复执行的次数 
      pause : int, 默认 0
                重复请求数据过程中暂停的秒数,防止请求间隔时间太短出现的问题
    return
    -------
      DataFrame
          date 交易日期 (index)
          open 开盘价
          high  最高价
          close 收盘价
          low 最低价
          volume 成交量
          amount 成交金额
          factor 后复权因子
    '''

    start = du.today_last_year() if start is None else start
    end = du.today() if end is None else end
    qs = du.get_quarts(start, end)
    qt = qs[0]
    ct._write_head()
    data = _parse_fq_data(_get_index_url(index, code, qt), index, retry_count,
                          pause)
    if len(qs) > 1:
        for d in range(1, len(qs)):
            qt = qs[d]
            ct._write_console()
            df = _parse_fq_data(_get_index_url(index, code, qt), index,
                                retry_count, pause)
            data = data.append(df, ignore_index=True)
    if len(data) == 0 or len(
            data[(data.date >= start) & (data.date <= end)]) == 0:
        return None
    data = data.drop_duplicates('date')
    if index:
        data = data[(data.date >= start) & (data.date <= end)]
        data = data.set_index('date')
        data = data.sort_index(ascending=False)
        return data
    if autype == 'hfq':
        #data = data.drop('factor', axis=1)
        data = data[(data.date >= start) & (data.date <= end)]
        for label in ['open', 'high', 'close', 'low']:
            data[label] = data[label].map(ct.FORMAT)
            data[label] = data[label].astype(float)
        data = data.set_index('date')
        data = data.sort_index(ascending=False)
        return data
    else:
        if autype == 'qfq':
            #data = data.drop('factor', axis=1)
            df = _parase_fq_factor(code, start, end)
            df = df.drop_duplicates('date')
            df = df.sort('date', ascending=False)
            frow = df.head(1)
            rt = get_realtime_quotes(code)
            if rt is None:
                return None
            if ((float(rt['high']) == 0) & (float(rt['low']) == 0)):
                preClose = float(rt['pre_close'])
            else:
                if du.is_holiday(du.today()):
                    preClose = float(rt['price'])
                else:
                    if (du.get_hour() > 9) & (du.get_hour() < 18):
                        preClose = float(rt['pre_close'])
                    else:
                        preClose = float(rt['price'])

            rate = float(frow['factor']) / preClose
            data = data[(data.date >= start) & (data.date <= end)]
            for label in ['open', 'high', 'low', 'close']:
                data[label] = data[label] / rate
                data[label] = data[label].map(ct.FORMAT)
                data[label] = data[label].astype(float)
            data = data.set_index('date')
            data = data.sort_index(ascending=False)
            return data
        else:
            for label in ['open', 'high', 'close', 'low']:
                data[label] = data[label] / data['factor']
            #data = data.drop('factor', axis=1)
            data = data[(data.date >= start) & (data.date <= end)]
            for label in ['open', 'high', 'close', 'low']:
                data[label] = data[label].map(ct.FORMAT)
            data = data.set_index('date')
            data = data.sort_index(ascending=False)
            data = data.astype(float)
            return data