Exemplo n.º 1
0
def load_index(index, query_func, data_path):
  data_file = os.path.join(data_path, index, 'stocks.csv')

  if os.path.exists(data_file):
    return load_stocks_from_file(data_file)

  lg = bs.login()

  if lg.error_code != '0':
    raise ValueError('baostock login failed:{}, {}'.format(lg.error_code, lg.error_msg))

  try:
    rs = query_func()
    if rs.error_code != '0':
      raise ValueError('baostock query {} failed:{}, {}'.format(index, rs.error_code, rs.error_msg))

    index_stocks = []
    while (rs.error_code == '0') & rs.next():
      index_stocks.append(rs.get_row_data())

      if rs.error_code != '0':
        raise ValueError('baostock query {} failed:{}, {}'.format(index, rs.error_code, rs.error_msg))

      result = pd.DataFrame(index_stocks, columns=rs.fields)

      pathlib.Path(os.path.join(data_path, index)).mkdir(parents=True, exist_ok=True)

      result.to_csv(data_file, encoding="utf-8", index=False)

      return load_stocks_from_file(data_file)
  finally:
    bs.logout()
def refresh_all_stock_day_k_noadjust(start_date="2020-03-27",
                                     current_date="2020-03-30"):
    bs.login()

    stock_rs = bs.query_all_stock(day=current_date)
    stock_df = stock_rs.get_data()
    data_list = []
    for code in stock_df["code"]:
        k_rs = bs.query_history_k_data_plus(
            code,
            "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ,psTTM,pcfNcfTTM,isST",
            start_date=start_date,
            end_date='',
            frequency="d",
            adjustflag="3")
        while (k_rs.error_code == '0') & k_rs.next():
            data_list.append(k_rs.get_row_data())
        print('query_history_k_data_plus no adjust code:' + code)
    bs.logout()
    db_conn = create_engine(common.db_path_sqlalchemy)

    db_conn.execute(
        r'''
    INSERT OR REPLACE INTO stock_day_k_noadjust VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
    ''', data_list)
Exemplo n.º 3
0
def query_trade_dates(start_date, end_date):
    """
    交易日查询:query_trade_dates()
    方法说明:查询股票交易日信息信息,可以通过参数设置获取起止年份数据,提供2014-2018年数据。 
    返回类型:pandas的DataFrame类型。
    """
    #### 登陆系统 ####
    lg = bs.login()
    # 显示登陆返回信息
    #print('login respond error_code:'+lg.error_code)
    #print('login respond  error_msg:'+lg.error_msg)

    #### 获取交易日信息 ####
    rs = bs.query_trade_dates(start_date=start_date, end_date=end_date)
    #print('query_trade_dates respond error_code:'+rs.error_code)
    #print('query_trade_dates respond  error_msg:'+rs.error_msg)

    #### 打印结果集 ####
    data_list = []
    while (rs.error_code == '0') & rs.next():
        # 获取一条记录,将记录合并在一起
        data_list.append(rs.get_row_data())
    result = pd.DataFrame(data_list, columns=rs.fields)

    #### 结果集输出到csv文件 ####
    result.to_csv(path + "trade_dates.csv", encoding="gbk", index=False)

    #### 登出系统 ####
    bs.logout()
    return
Exemplo n.º 4
0
def get_stock_data(t1, t2, stock_name):
    lg = bs.login()
    print('login respond error_code:' + lg.error_code)
    print('login respond  error_msg:' + lg.error_msg)

    #### 获取沪深A股历史K线数据 ####
    # 详细指标参数,参见baostock
    rs = bs.query_history_k_data(
        stock_name,
        "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
        start_date=t1,
        end_date=t2,
        frequency="d",
        adjustflag="3")
    print('query_history_k_data respond error_code:' + rs.error_code)
    print('query_history_k_data respond  error_msg:' + rs.error_msg)

    #### 打印结果集 ####
    data_list = []
    while (rs.error_code == '0') & rs.next():
        # 获取一条记录,将记录合并在一起
        data_list.append(rs.get_row_data())
    result = pd.DataFrame(data_list, columns=rs.fields)
    print(result)

    #### 结果集输出到csv文件 ####
    result.to_csv("history_A_stock_k_data.csv", index=False)
    print(result)

    #### 登出系统 ####
    bs.logout()
    result['date'] = pd.to_datetime(result['date'])
    result.set_index("date", inplace=True)
    return result
Exemplo n.º 5
0
def download(stockCode, beginDate, endDate, fileName, isCsv):
    #### 登陆系统 ####
    lg = bs.login()
    # 显示登陆返回信息
    print('login respond error_code:' + lg.error_code)
    print('login respond  error_msg:' + lg.error_msg)

    #### 获取沪深A股历史K线数据 ####
    # 详细指标参数,参见“历史行情指标参数”章节;“分钟线”参数与“日线”参数不同。
    # 分钟线指标:date,time,code,open,high,low,close,volume,amount,adjustflag
    # code:股票代码,sh或sz.+6位数字代码,或者指数代码,如:sh.601398。sh:上海;sz:深圳。此参数不可为空;
    # fields:指示简称,支持多指标输入,以半角逗号分隔,填写内容作为返回类型的列。详细指标列表见历史行情指标参数章节,日线与分钟线参数不同。此参数不可为空;
    # start:开始日期(包含),格式“YYYY-MM-DD”,为空时取2015-01-01;
    # end:结束日期(包含),格式“YYYY-MM-DD”,为空时取最近一个交易日;
    # frequency:数据类型,默认为d,日k线;d=日k线、w=周、m=月、5=5分钟、15=15分钟、30=30分钟、60=60分钟k线数据,不区分大小写;指数没有分钟线数据;周线每周最后一个交易日才可以获取,月线每月最后一个交易日才可以获取。
    # adjustflag:复权类型,默认不复权:3;1:后复权;2:前复权。已支持分钟线、日线、周线、月线前后复权。 BaoStock提供的是涨跌幅复权算法复权因子,具体介绍见:
    rs = bs.query_history_k_data_plus(
        stockCode,
        "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ,psTTM,pcfNcfTTM,isST",
        start_date="2006-01-01",
        end_date=endDate,
        frequency="d",
        adjustflag="2")
    print('query_history_k_data_plus respond error_code:' + rs.error_code)
    print('query_history_k_data_plus respond  error_msg:' + rs.error_msg)

    if isCsv:
        saveToCsv(rs, fileName)
    else:
        saveToMysql(rs)

    #### 登出系统 ####
    bs.logout()
Exemplo n.º 6
0
def start_tk_crawl():
    global dm
    dm = DBManager("history_k_data")

    # 初始化baostock
    bs.login()
    # 获取股票代码列表
    code_list = dm.get_code_list()
    for item in code_list:
        max_try = 8  # 失败重连次数
        ticker = item["ticker"]
        print("开始加载股票数据:" + str(ticker))
        for tries in range(max_try):
            rs = bs.query_history_k_data_plus(
                ticker,
                "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
                start_date='2008-01-01',
                end_date='2019-05-31',
                frequency="d",
                adjustflag="3")
            if rs.error_code == '0':
                parse_pager(rs, ticker)  # 解析数据
                break
            elif tries < (max_try - 1):
                sleep(2)
                continue
            else:
                print("加载股票数据失败:" + str(ticker))
    print("加载股票数据完成")
    bs.logout()
Exemplo n.º 7
0
def Kget(stockcode, checkdate1, checkdate2):
    import pandas as pd
    import baostock as bs
    #### 登陆系统 ####
    lg = bs.login()
    # 显示登陆返回信息
    # print('login respond error_code:'+lg.error_code)
    # print('login respond  error_msg:'+lg.error_msg)

    #### 获取沪深A股历史K线数据 ####
    # 详细指标参数,参见“历史行情指标参数”章节;“分钟线”参数与“日线”参数不同。
    # 分钟线指标:date,time,code,open,high,low,close,volume,amount,adjustflag
    rs = bs.query_history_k_data_plus(
        stockcode,
        "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM",
        start_date=checkdate1,
        end_date=checkdate2,
        frequency="d",
        adjustflag="3")
    # print('query_history_k_data_plus respond error_code:'+rs.error_code)
    # print('query_history_k_data_plus respond  error_msg:'+rs.error_msg)

    #### 打印结果集 ####
    data_list = []
    while (rs.error_code == '0') & rs.next():
        # 获取一条记录,将记录合并在一起
        data_list.append(rs.get_row_data())
    result = pd.DataFrame(data_list, columns=rs.fields)
    #### 结果集输出到csv文件 ####
    result.to_csv("history_A_stock_k_data.csv", encoding="utf8", index=False)
    # print(result)
    #### 登=出系统 ####
    bs.logout()
Exemplo n.º 8
0
def getBasicInfoByName(name):
    # 登陆系统
    lg = bs.login()
    # 显示登陆返回信息
    print('login respond error_code:' + lg.error_code)
    print('login respond  error_msg:' + lg.error_msg)

    # 获取证券基本资料
    rs = bs.query_stock_basic(code_name=name)  # 支持模糊查询
    print('query_stock_basic respond error_code:' + rs.error_code)
    print('query_stock_basic respond  error_msg:' + rs.error_msg)

    obj = {}

    if (rs.error_code != '0'):
        obj['error_code'] = rs.error_code
        obj['error_msg'] = rs.error_msg
        return obj

    #print(type(rs))#<class 'baostock.data.resultset.ResultData'>
    #打印结果集
    data_list = []
    while (rs.error_code == '0' and rs.next()):
        #获取一条记录,将记录合并在一起
        data_list.append(rs.get_row_data())
    obj['error_code'] = '0'
    obj['data_list'] = data_list
    #登出系统
    bs.logout()

    return obj
Exemplo n.º 9
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def start_pe_crawl():
    global dm, log
    log = Logger()
    dm = DBManager("em_pe_database")

    log.logger.info("开始更新指数数据")
    bs.login()
    code_list = dm.get_code_list()
    for item in code_list:
        ticker = item["ticker"]
        max_try = 8
        for tries in range(max_try):
            rs = bs.query_history_k_data(
                ticker,
                "date,code,close,peTTM,pbMRQ,psTTM,pcfNcfTTM",
                frequency="d",
                adjustflag="2")
            if rs.error_code == "0":
                parse_pager(rs, ticker)
                break
            elif tries < (max_try - 1):
                sleep(2)
                continue
            else:
                log.logger.error("更新股票指数数据:" + str(ticker))
    log.logger.info("结束更新指数数据")
    bs.logout()
Exemplo n.º 10
0
def update_stock_daily(history=False):
    try:
        et = utils.get_recently_trade_date()
        st = et
        if history:
            st = settings.START_DATE
        print(st, et)
        # 登陆系统 ####
        lg = bs.login()
        # 显示登陆返回信息
        print('login respond error_code:' + lg.error_code + ', error_msg:' +
              lg.error_msg)
        stock = redisUtils.get("Ashare")
        stockJson = json.loads(stock)
        for code in stockJson:
            name = stockJson[code][1]
            if "ST" in name:
                continue
            print("Downloading :" + code + " , name :" + name)
            k_rs = bs.query_history_k_data_plus(code,
                                                settings.STOCK_FIELDS,
                                                start_date=st,
                                                end_date=et)
            # print(k_rs.get_data())
            stock_records = k_rs.get_data().to_dict('records')
            for record in stock_records:
                rJsonStr = json.dumps(record, indent=4,
                                      ensure_ascii=False).encode('utf-8')
                r = redisUtils.sadd(code, rJsonStr)
            print("{} redis add finish".format(code))
        bs.logout()
    except IOError:
        print("Update Data Error ")
Exemplo n.º 11
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def update_trades():
    try:
        et = stock_utils.get_recently_trade_date()
        st = ConfigUtils.get_stock("START_DATE")
        # 登陆系统 ####
        lg = bs.login()
        # 显示登陆返回信息
        print('login respond error_code:' + lg.error_code + ', error_msg:' +
              lg.error_msg)

        pd_names = pd.read_csv(ConfigUtils.get_stock("STOCK_NAME"))
        data = list(pd_names.iterrows())

        # multi processing
        number_kernel = 1
        size = int((len(data) + number_kernel - 1) / number_kernel)
        p = Pool(number_kernel)
        for i in range(number_kernel):

            start = size * i
            _end = size * (i + 1)
            end = len(data) if _end > len(data) else _end

            p.apply_async(loading_stock, args=(data[start:end], st, et))

        p.close()
        p.join()
        print('all subprocesses done.')
        bs.logout()
    except IOError as e:
        print("Update Data Error ", e)
Exemplo n.º 12
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def load_adjfactor(symbol, data_path):
    adj_file = os.path.join(data_path, symbol, 'adj.csv')

    if os.path.exists(adj_file):
        return load_adjfactor_from_file(adj_file)

    lg = bs.login('anonymous', '123456')

    if lg.error_code != '0':
        raise ValueError('baostock login failed:{}, {}'.format(lg.error_code, lg.error_msg))

    rs_list = []
    rs_factor = bs.query_adjust_factor(convert_symbol(symbol), start_date="1990-01-01", end_date="2199-12-31")
    while (rs_factor.error_code == '0') & rs_factor.next():
        rs_list.append(rs_factor.get_row_data())

        if rs_factor.error_code != '0':
            bs.logout()
            raise ValueError('baostock read data failed:{}'.format(rs_factor.error_msg))

    bs.logout()

    result_factor = pd.DataFrame(rs_list, columns=rs_factor.fields)

    result_factor.to_csv(adj_file, encoding="utf-8", index=False)

    return load_adjfactor_from_file(adj_file)
Exemplo n.º 13
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def init_trade_date():
	settings.init()

	# 登陆系统 ####
	lg = bs.login()
	# 显示登陆返回信息
	print('login respond error_code:' + lg.error_code)
	print('login respond  error_msg:' + lg.error_msg)

	# 获取交易日信息 ####
	rs = bs.query_trade_dates(start_date=settings.START_DATE, end_date=settings.END_DATE)
	print('query_trade_dates respond error_code:' + rs.error_code)
	print('query_trade_dates respond  error_msg:' + rs.error_msg)

	# 打印结果集 ####
	data_list = []
	while (rs.error_code == '0') & rs.next():
		# 获取一条记录,将记录合并在一起
		data_list.append(rs.get_row_data())
	result = pd.DataFrame(data_list, columns=rs.fields)

	# 结果集输出到csv文件 ####
	result.to_csv(settings.STOCKS_DATE, encoding="utf-8", index=False, header=True)
	print(result)
	# 登出系统 ####
	bs.logout()
Exemplo n.º 14
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def start_tk_crawl():
    global dm, log
    log = Logger()
    dm = DBManager("em_tk_database")

    log.logger.info("开始更新股票数据")
    bs.login()
    code_list = dm.get_code_list()
    for item in code_list:
        ticker = item["ticker"]
        max_try = 8
        for tries in range(max_try):
            rs = bs.query_history_k_data(
                ticker,
                "date,code,open,high,low,close,volume,amount,adjustflag,turn,"
                "pctChg",
                frequency="w",
                adjustflag="3")
            if rs.error_code == '0':
                parse_pager(rs, ticker)
                break
            elif tries < (max_try - 1):
                sleep(2)
                continue
            else:
                log.logger.error("更新股票数据失败:" + str(ticker))
    log.logger.info("结束更新股票数据")
    bs.logout()
Exemplo n.º 15
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 def get(self, request, *args, **kwargs):
     queryset = SharesCategory.objects.all()
     if len(queryset) <= 0:
         lg = bs.login()
         rs = bs.query_stock_industry()
         # print(rs)
         data_list = []
         while (rs.error_code == '0') & rs.next():
             data_list.append(rs.get_row_data())
         result = pd.DataFrame(data_list, columns=rs.fields)
         result1 = pd.DataFrame(result['industry'])
         result1['count'] = pd.Series(np.random.randint(1, 2, 4061))
         result1['industryClassification'] = result[
             'industryClassification']
         result1 = result1.groupby('industry').sum()
         shares_cate_list = []
         for index, row in result1.iterrows():
             cate_obj = SharesCategory(industry=index,
                                       industryClassification='申万一级行业',
                                       count=row['count'])
             cate_obj.save()
             shares_cate_list.append({
                 'industry': index,
                 'industryClassification': '申万一级行业',
                 'count': float(row['count'])
             })
         bs.logout()
         return JsonResponse(shares_cate_list, safe=False)
     else:
         return JsonResponse([], safe=False)
Exemplo n.º 16
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def all_stock_list():
    #### 登陆系统 ####
    lg = bs.login()
    # 显示登陆返回信息
    print('login respond error_code:' + lg.error_code)
    print('login respond  error_msg:' + lg.error_msg)

    #### 获取证券信息 ####
    date = datetime.datetime.now()
    print(date)
    start_date = (date + datetime.timedelta(days=-5)).strftime('%Y-%m-%d')

    rs = bs.query_all_stock(day='2020-07-16')
    print('query_all_stock respond error_code:' + rs.error_code)
    print('query_all_stock respond  error_msg:' + rs.error_msg)
    #### 登出系统 ####
    bs.logout()

    #### 打印结果集 ####
    data_list = []
    while (rs.error_code == '0') & rs.next():
        # 获取一条记录,将记录合并在一起
        data = rs.get_row_data()
        if data[1] != '0':
            #data[0] = data[0].replace('.', '')
            data_list.append(data)
    result = pd.DataFrame(data_list, columns=rs.fields)
    return result
Exemplo n.º 17
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def query_stock_k_data_plus(date):
    #### 登陆系统 ####
    lg = bs.login()
    # 显示登陆返回信息
    print('login respond error_code:' + lg.error_code)
    print('login respond  error_msg:' + lg.error_msg)
    date = date.strftime("%Y-%m-%d")
    print(date)
    stock_rs = bs.query_all_stock(date)
    stock_df = stock_rs.get_data()
    print(stock_df.empty)
    if not (stock_df is None or stock_df.empty):
        data_df = pd.DataFrame()
        for code in stock_df["code"]:
            k_rs = bs.query_history_k_data_plus(
                code, "date,code,open,high,low,close,preclose,volume,"
                "amount,adjustflag,turn,tradestatus,pctChg,peTTM,"
                "pbMRQ,psTTM,pcfNcfTTM,isST", date, date)
            data_df = data_df.append(k_rs.get_data())
        data = data_df.drop_duplicates(subset={"date", "code"}, keep="last")
        common.insert_db(data, "bs_stock_k_data", False, "`date`,`code`")
        print(date + " done!")
    else:
        print(date + " no data .")
    bs.logout()
Exemplo n.º 18
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    def get_history_companies(self) -> pd.DataFrame:
        """

        Returns
        -------

            pd.DataFrame:
                symbol      date        type
                SH600000  2019-11-11    add
                SH600000  2020-11-10    remove
            dtypes:
                symbol: str
                date: pd.Timestamp
                type: str, value from ["add", "remove"]
        """
        bs.login()
        today = pd.datetime.now()
        date_range = pd.DataFrame(
            pd.date_range(start="2007-01-15", end=today, freq="7D"))[0].dt.date
        ret_list = []
        col = ["date", "symbol", "code_name"]
        for date in tqdm(date_range, desc="Download CSI500"):
            rs = bs.query_zz500_stocks(date=str(date))
            zz500_stocks = []
            while (rs.error_code == "0") & rs.next():
                zz500_stocks.append(rs.get_row_data())
            result = pd.DataFrame(zz500_stocks, columns=col)
            result["symbol"] = result["symbol"].apply(
                lambda x: x.replace(".", "").upper())
            result = self.get_data_from_baostock(date)
            ret_list.append(result[["date", "symbol"]])
        bs.logout()
        return pd.concat(ret_list, sort=False)
Exemplo n.º 19
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def growget(stackcode):
    import baostock as bs
    import pandas as pd
    # 登陆系统
    lg = bs.login()
    # 显示登陆返回信息
    # print('login respond error_code:'+lg.error_code)
    # print('login respond  error_msg:'+lg.error_msg)
    # 查询季频估值指标盈利能力
    growth_list = []
    for y in range(2007, 2021):
        qu = 4
        if y == 2021:
            qu = 1
        for i in range(qu):
            rs_profit = bs.query_growth_data(code=stackcode,
                                             year=y,
                                             quarter=i + 1)
            while (rs_profit.error_code == '0') & rs_profit.next():
                growth_list.append(rs_profit.get_row_data())
    result_growth = pd.DataFrame(growth_list, columns=rs_profit.fields)
    # 结果集输出到csv文件
    result.to_csv("grow_data.csv", encoding="utf8", index=False)
    # 登出系统
    bs.logout()
Exemplo n.º 20
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    def get_new_companies(self) -> pd.DataFrame:
        """

        Returns
        -------
            pd.DataFrame:

                symbol     start_date    end_date
                SH600000   2000-01-01    2099-12-31

            dtypes:
                symbol: str
                start_date: pd.Timestamp
                end_date: pd.Timestamp
        """
        logger.info("get new companies......")
        today = datetime.date.today()
        bs.login()
        result = self.get_data_from_baostock(today)
        bs.logout()
        df = result[["date", "symbol"]]
        df.columns = [self.END_DATE_FIELD, self.SYMBOL_FIELD_NAME]
        df[self.END_DATE_FIELD] = pd.to_datetime(
            df[self.END_DATE_FIELD].astype(str))
        df[self.START_DATE_FIELD] = self.bench_start_date
        logger.info("end of get new companies.")
        return df
Exemplo n.º 21
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def get_his_trade_date(start_date="2018-01-27", end_date="2019-05-01"):
    #### 登陆系统 ####
    lg = bs.login(user_id="anonymous", password="******")
    # 显示登陆返回信息
    print('login respond error_code:'+lg.error_code)
    print('login respond  error_msg:'+lg.error_msg)

    #### 获取交易日信息 ####
    rs = bs.query_trade_dates(start_date=start_date, end_date=end_date)
    print('query_trade_dates respond error_code:'+rs.error_code)
    print('query_trade_dates respond  error_msg:'+rs.error_msg)

    #### 打印结果集 ####
    data_list = []
    while (rs.error_code == '0') & rs.next():
        # 获取一条记录,将记录合并在一起
        data_list.append(rs.get_row_data())
    result = pd.DataFrame(data_list, columns=rs.fields)

    #### 登出系统 ####
    bs.logout()

    #### 结果集输出到csv文件 ####
    #result.to_csv("/data/trade_datas.csv", encoding="gbk", index=False)
    return result
Exemplo n.º 22
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def get_history_k_data(code,start_date,end_date,frequency,adjustflag):
    
    bs.login()
    rs = bs.query_history_k_data_plus(code,
        "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
        start_date=start_date, end_date=end_date,frequency=frequency,adjustflag=adjustflag)
    data_list = []
    while (rs.error_code == '0') & rs.next() :
        data={}
        # 获取一条记录,将记录合并在一起
        rowdata = rs.get_row_data()
        data['date']=rowdata[0]
        data['code']=rowdata[1]
        data['open']=rowdata[2]
        data['high']=rowdata[3]
        data['low']=rowdata[4]
        data['close']=rowdata[5]
        data['preclose']=rowdata[6]
        data['volume']=rowdata[7]
        data['amount']=rowdata[8]
        data['adjustflag']=rowdata[10]
        data['tradestatus']=rowdata[11]
        data['pctChg']=rowdata[12]
        data['isST']=rowdata[13]
        data_list.append(data)
    return data_list
    bs.logout()
Exemplo n.º 23
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def Zijinmian():
    today = datetime.datetime.today()
    year = today.year
    month = today.month
    dic = {'m2': []}
    # 登陆系统
    lg = bs.login()
    # 获取货币供应量
    if month < 10:
        enddate = str(year) + '-' + '0' + str(month)
    else:
        enddate = str(year) + '-' + str(month)
    rs5 = bs.query_money_supply_data_month(start_date="2020-01",
                                           end_date=enddate)
    # 打印结果集
    data_list = []
    while (rs5.error_code == '0') & rs5.next():
        # 获取一条记录,将记录合并在一起
        data_list.append(rs5.get_row_data())
    result = pd.DataFrame(data_list, columns=rs5.fields)
    print(np.array(result['m2Month']))
    # 登出系统
    bs.logout()
    dic['m2'] = np.array(result['m2Month']).tolist()
    dic['m2'] = list(map(eval, dic['m2']))
    return json.dumps(dic, ensure_ascii=False)
Exemplo n.º 24
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def create_stock_industry():
    """
    BS-创建行业分类
    """
    # 登陆系统
    lg = bs.login()
    # 显示登陆返回信息
    print('login respond error_code:' + lg.error_code)
    print('login respond  error_msg:' + lg.error_msg)

    # 获取行业分类数据
    rs = bs.query_stock_industry()
    print('query_stock_industry error_code:' + rs.error_code)
    print('query_stock_industry respond  error_msg:' + rs.error_msg)

    # 打印结果集
    industry_list = []
    while (rs.error_code == '0') & rs.next():
        # 获取一条记录,将记录合并在一起
        industry_list.append(rs.get_row_data())
    result = pd.DataFrame(industry_list, columns=rs.fields)

    dtype = {
        'updateDate': String(10),
        'code': String(9),
        'code_name': String(10),
        'industry': String(4),
        'industryClassification': String(6)
    }

    result.to_sql('odl_bs_stock_industry', engine, schema=CQ_Config.DB_SCHEMA, if_exists='replace', index=False, dtype=dtype)

    # 登出系统
    bs.logout()
def refresh_all_stock_adjust(start_date="2020-03-27",
                             current_date="2020-03-30"):
    bs.login()

    db_conn = create_engine(common.db_path_sqlalchemy)
    stock_rs = bs.query_all_stock(day=current_date)
    stock_df = stock_rs.get_data()
    rs_list = []
    for code in stock_df["code"]:
        if code.startswith("sh.6") | code.startswith(
                "sz.00") | code.startswith("sz.300"):
            print('query_stock_factor code:' + code)
            rs_factor = bs.query_adjust_factor(code=code,
                                               start_date=start_date,
                                               end_date=current_date)
            while (rs_factor.error_code == '0') & rs_factor.next():
                rs_list.append(rs_factor.get_row_data())
    factor_list = []
    for d in rs_list:
        code = d[0]
        print("refresh all factor for " + code)
        rs_factor = bs.query_adjust_factor(code=code,
                                           start_date='2006-01-01',
                                           end_date=current_date)
        while (rs_factor.error_code == '0') & rs_factor.next():
            factor_list.append(rs_factor.get_row_data())
    if len(factor_list) > 0:
        db_conn.execute(
            r'''
                INSERT OR REPLACE INTO stock_adjustfactor VALUES (?, ?, ?, ?, ?)
                ''', factor_list)
    bs.logout()
Exemplo n.º 26
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def Fetch000001WithBaostock(startDate):
    #### 登陆系统 ####
    lg = bs.login()
    # 详细指标参数,参见“历史行情指标参数”章节
    rs = bs.query_history_k_data("sh.000001",
                                 "date,open,high,low,close,volume",
                                 start_date=Utils.DateForm1(startDate),
                                 end_date='',
                                 frequency="d",
                                 adjustflag="3")

    #### 打印结果集 ####
    data_list = []
    while (rs.error_code == '0') & rs.next():
        data_list.append(rs.get_row_data())
    df = pd.DataFrame(data_list, columns=rs.fields)

    for index, row in df.iterrows():
        row['date'] = row['date'].replace('-', '')

    df.rename(columns={'date': 'trade_date', 'volume': 'vol'}, inplace=True)
    dfInRange = df[(df['trade_date'] > str(startDate))]

    bs.logout()
    return dfInRange
Exemplo n.º 27
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def get_growth_data(stock_number,stock_name,year,quarter):

    print('==========================================================')
    print("开始进行: "+stock_name+"("+stock_number+")"+"的数据处理")
    print("尝试登陆baostock")
    #####login#####
    lg=bs.login(user_id="anonymous",password="******")
    if(lg.error_code == '0'):
          print("登陆成功")
    else:
          print("登录失败")


    #####get stock data#####
    rs=bs.query_growth_data(code=stock_number,year=year,quarter=quarter)

    print('请求历史数据返回代码:'+rs.error_code)
    print('请求历史数据返回信息:'+rs.error_msg)

    data_list=[]
    while(rs.error_code=='0')&rs.next():
        data_list.append(rs.get_row_data())

    result=pd.DataFrame(data_list,columns=rs.fields)
    bs.logout()
    print(stock_name+"("+stock_number+")"+"的数据处理完成")
    print('==========================================================')
    return result
Exemplo n.º 28
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def get_sz50_stocks():
    """
    获取上证50成分股数据
    """
    #删除数据
    BS_SZ50_Stocks.del_all_data()

    # 登陆系统
    lg = bs.login()
    # 显示登陆返回信息
    print('login respond error_code:' + lg.error_code)
    print('login respond  error_msg:' + lg.error_msg)

    # 获取上证50成分股
    rs = bs.query_sz50_stocks()
    print('query_sz50 error_code:' + rs.error_code)
    print('query_sz50  error_msg:' + rs.error_msg)

    # 打印结果集
    sz50_stocks = []
    while (rs.error_code == '0') & rs.next():
        # 获取一条记录,将记录合并在一起
        sz50_stocks.append(rs.get_row_data())
    result = pd.DataFrame(sz50_stocks, columns=rs.fields)

    result.to_sql('odl_bs_sz50_stocks',
                  engine,
                  schema=CQ_Config.DB_SCHEMA,
                  if_exists='append',
                  index=False)

    # 登出系统
    bs.logout()
Exemplo n.º 29
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 def logout(self):
     '''
     退出
     '''
     hide()
     bs.logout()
     show()
Exemplo n.º 30
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    def data_download(self, start_date='2017-07-01', end_date='2020-12-31'):
        #### 登陆系统 ####
        lg = bs.login()
        # 显示登陆返回信息
        print('login respond error_code:' + lg.error_code)
        print('login respond  error_msg:' + lg.error_msg)
        #### 获取沪深A股历史K线数据 ####
        rs = bs.query_history_k_data_plus(
            self.code,
            "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
            start_date=start_date,
            end_date=end_date,
            frequency="d",
            adjustflag="3")
        print('query_history_k_data_plus respond error_code:' + rs.error_code)
        print('query_history_k_data_plus respond  error_msg:' + rs.error_msg)
        #### 打印结果集 ####
        data_list = []
        while (rs.error_code == '0') & rs.next():
            # 获取一条记录,将记录合并在一起
            data_list.append(rs.get_row_data())
        self.mydata = pd.DataFrame(data_list, columns=rs.fields)

        #### 登出系统 ####
        bs.logout()