def import_info_table(type_name): """ 调用 get_all_securities 获取指定 type 的信息 type: 'stock', 'fund', 'index', 'futures', 'etf', 'lof', 'fja', 'fjb'。types为空时返回所有股票, 不包括基金,指数和期货 :param type_name: :return: """ table_name = f'jq_{type_name}_info' logging.info("更新 %s 开始", table_name) # has_table = engine_md.has_table(table_name) param_list = [ ('jq_code', String(20)), ('display_name', String(20)), ('name', String(20)), ('start_date', Date), ('end_date', Date), ] # 设置 dtype dtype = {key: val for key, val in param_list} # 数据提取 # types: list: 用来过滤securities的类型, list元素可选: # 'stock', 'fund', 'index', 'futures', 'etf', 'lof', 'fja', 'fjb'。types为空时返回所有股票, 不包括基金,指数和期货 # date: 日期, 一个字符串或者 [datetime.datetime]/[datetime.date] 对象, # 用于获取某日期还在上市的股票信息. 默认值为 None, 表示获取所有日期的股票信息 stock_info_all_df = get_all_securities(types=type_name) stock_info_all_df.index.rename('jq_code', inplace=True) stock_info_all_df.reset_index(inplace=True) logging.info('%s 数据将被导入', stock_info_all_df.shape[0]) data_count = bunch_insert(stock_info_all_df, table_name=table_name, dtype=dtype, primary_keys=['jq_code']) logging.info("更新 %s 完成 存量数据 %d 条", table_name, data_count)
def import_tushare_index_basic(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_index_basic' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) fields = [ 'ts_code', 'name', 'fullname', 'market', 'publisher', 'index_type', 'category', 'base_date', 'base_point', 'list_date', 'weight_rule', 'desc', 'exp_date' ] market_list = list( ['MSCI', 'CSI', 'SSE', 'SZSE', 'CICC', 'SW', 'CNI', 'OTH']) for mkt in market_list: # trade_date = datetime_2_str(trddate[i], STR_FORMAT_DATE_TS) data_df = invoke_index_basic(market=mkt, fields=fields) if len(data_df) > 0: data_count = bunch_insert(data_df, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_INDEX_BASIC, primary_keys=['ts_code']) logging.info("%s 更新 %s 结束 %d 条信息被更新", mkt, table_name, data_count) else: logging.info("%s 无数据信息可被更新", mkt)
def import_fut_basic(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_future_basic' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) exchange_list = ['DCE', 'CZCE', 'SHFE', 'CFFEX', 'INE'] try: for i in range(len(exchange_list)): exchange_name = exchange_list[i] data_df = invoke_fut_basic(exchange=exchange_name) if len(data_df) > 0: data_count = bunch_insert(data_df, table_name=table_name, dtype=DTYPE_TUSHARE_FUTURE_BASIC, primary_keys=['ts_code']) logging.info("更新 %s 期货合约基础信息结束, %d 条信息被更新", exchange_name, data_count) else: logging.info("无数据信息可被更新") finally: logger.info('%s 表 数据更新完成', table_name)
def save_data_2_daily_table(data_new_s_list: list, table_name, dtype: dict): df = pd.DataFrame(data_new_s_list) data_count = bunch_insert(df, table_name, dtype=dtype, primary_keys=['id', 'trade_date']) return data_count
def import_tushare_adj_factor(chain_param=None, ): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_daily_adj_factor' primary_keys = ["ts_code", "trade_date"] logging.info("更新 %s 开始", table_name) # 进行表格判断,确定是否含有 table_name has_table = engine_md.has_table(table_name) # sqlite_file_name = 'eDB_adjfactor.db' check_sqlite_db_primary_keys(table_name, primary_keys) if has_table: sql_str = """ select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(trade_date) FROM {table_name})) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = [row[0] for row in table.fetchall()] trade_date_count, data_count_tot = len(trade_date_list), 0 try: for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) data_df = pro.adj_factor(ts_code='', trade_date=trade_date) if data_df is not None and data_df.shape[0] > 0: data_count = bunch_insert( data_df, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_DAILY_ADJ_FACTOR, primary_keys=primary_keys) data_count_tot += data_count logging.info("%d/%d) %s 表 %s %d 条信息被更新", num, trade_date_count, table_name, trade_date, data_count) else: logging.info("%d/%d) %s 表 %s 数据信息可被更新", num, trade_date_count, table_name, trade_date) except: logger.exception("更新 %s 异常", table_name) finally: logging.info("%s 表 %d 条记录更新完成", table_name, data_count_tot)
def import_tushare_suspend(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_daily_suspend' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_suspend # 下面一定要注意引用表的来源,否则可能是串,提取混乱!!!比如本表是tushare_daily_basic,所以引用的也是这个,如果引用错误,就全部乱了l if has_table: sql_str = """ select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(suspend_date) FROM {table_name} )) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = list(row[0] for row in table.fetchall()) try: trade_date_list_len = len(trade_date_list) for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) data_df = pro.suspend(ts_code='', suspend_date=trade_date, resume_date='', fields='') if len(data_df) > 0: data_count = bunch_insert(data_df, table_name=table_name, dtype=DTYPE_TUSHARE_SUSPEND, primary_keys=['ts_code', 'suspend_date']) logging.info("%d/%d) %s 更新 %s 结束 %d 条信息被更新", num, trade_date_list_len, trade_date, table_name, data_count) else: logging.info("%s 当日无停牌股票", trade_date_list_len) except: logger.exception('更新 %s 表异常', table_name)
def import_tushare_daily_basic(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_daily_basic' primary_keys = ["ts_code", "trade_date"] logging.info("更新 %s 开始", table_name) check_sqlite_db_primary_keys(table_name, primary_keys) has_table = engine_md.has_table(table_name) # 下面一定要注意引用表的来源,否则可能是串,提取混乱!!! # 比如本表是 tushare_daily_basic,所以引用的也是这个,如果引用错误,就全部乱了 if has_table: sql_str = """ select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(trade_date) FROM {table_name} )) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = list(row[0] for row in table.fetchall()) try: for_count = len(trade_date_list) for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) data_df = invoke_daily_basic(ts_code='', trade_date=trade_date) if data_df is not None and data_df.shape[0] > 0: data_count = bunch_insert( data_df, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_DAILY_BASIC, primary_keys=primary_keys) logging.info("%d/%d) %s 更新 %s 结束 %d 条信息被更新", num, for_count, trade_date, table_name, data_count) else: logging.info("%d/%d) %s 无数据信息可被更新", num, for_count, trade_date) except: logger.exception("更新 %s 表异常", table_name)
def import_tushare_stock_index_daily(chain_param=None, ts_code_set=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_index_daily_md' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_stock_daily if has_table: sql_str = """ SELECT ts_code, date_frm, if(exp_date<end_date, exp_date, end_date) date_to FROM ( SELECT info.ts_code, ifnull(trade_date, base_date) date_frm, exp_date, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM tushare_stock_index_basic info LEFT OUTER JOIN (SELECT ts_code, adddate(max(trade_date),1) trade_date FROM {table_name} GROUP BY ts_code) daily ON info.ts_code = daily.ts_code ) tt WHERE date_frm <= if(exp_date<end_date, exp_date, end_date) ORDER BY ts_code""".format(table_name=table_name) else: sql_str = """ SELECT ts_code, date_frm, if(exp_date<end_date, exp_date, end_date) date_to FROM ( SELECT info.ts_code, base_date date_frm, exp_date, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM tushare_stock_index_basic info ) tt WHERE date_frm <= if(exp_date<end_date, exp_date, end_date) ORDER BY ts_code""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取每只股票需要获取日线数据的日期区间 table = session.execute(sql_str) # 计算每只股票需要获取日线数据的日期区间 begin_time = None # 获取date_from,date_to,将date_from,date_to做为value值 code_date_range_dic = { ts_code: (date_from if begin_time is None else min([date_from, begin_time]), date_to) for ts_code, date_from, date_to in table.fetchall() if ts_code_set is None or ts_code in ts_code_set } # data_len = len(code_date_range_dic) data_df_list, data_count, all_data_count, data_len = [], 0, 0, len( code_date_range_dic) logger.info('%d stocks will been import into tushare_stock_index_daily_md', data_len) # 将data_df数据,添加到data_df_list try: for num, (ts_code, (date_from, date_to)) in enumerate(code_date_range_dic.items(), start=1): logger.debug('%d/%d) %s [%s - %s]', num, data_len, ts_code, date_from, date_to) data_df = invoke_index_daily( ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS), end_date=datetime_2_str(date_to, STR_FORMAT_DATE_TS)) # data_df = df if data_df is not None and data_df.shape[0] > 0: while try_2_date(data_df['trade_date'].iloc[-1]) > date_from: last_date_in_df_last, last_date_in_df_cur = try_2_date( data_df['trade_date'].iloc[-1]), None df2 = invoke_index_daily( ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS), end_date=datetime_2_str( try_2_date(data_df['trade_date'].iloc[-1]) - timedelta(days=1), STR_FORMAT_DATE_TS)) if len(df2 > 0): last_date_in_df_cur = try_2_date( df2['trade_date'].iloc[-1]) if last_date_in_df_cur < last_date_in_df_last: data_df = pd.concat([data_df, df2]) # df = df2 elif last_date_in_df_cur == last_date_in_df_last: break if data_df is None: logger.warning( '%d/%d) %s has no data during %s %s', num, data_len, ts_code, date_from, date_to) continue logger.info('%d/%d) %d data of %s between %s and %s', num, data_len, data_df.shape[0], ts_code, date_from, date_to) else: break # 把数据攒起来 data_count += data_df.shape[0] data_df_list.append(data_df) # 仅调试使用 if DEBUG and len(data_df_list) > 5: break # 大于阀值有开始插入 if data_count >= 500: data_df_all = pd.concat(data_df_list) bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_INDEX_DAILY_MD, primary_keys=["ts_code", "trade_date"]) all_data_count += data_count data_df_list, data_count = [], 0 finally: # 导入数据库 if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_INDEX_DAILY_MD, primary_keys=["ts_code", "trade_date"]) all_data_count += data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_moneyflow_hsgt(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_moneyflow_hsgt' logging.info("更新 %s 开始", table_name) param_list = [ ('trade_date', Date), ('ggt_ss', DOUBLE), ('ggt_sz', DOUBLE), ('hgt', DOUBLE), ('sgt', DOUBLE), ('north_money', DOUBLE), ('south_money', DOUBLE), ] has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_daily_basic # 下面一定要注意引用表的来源,否则可能是串,提取混乱!!!比如本表是tushare_daily_basic,所以引用的也是这个,如果引用错误,就全部乱了l if has_table: sql_str = """ select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(trade_date) FROM {table_name})) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE' AND cal_date>='2014-11-17') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_trade_date 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = list(row[0] for row in table.fetchall()) # 设置 dtype dtype = {key: val for key, val in param_list} try: trade_date_list_len = len(trade_date_list) for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) data_df = invoke_moneyflow_hsgt(trade_date=trade_date) if len(data_df) > 0: data_count = bunch_insert( data_df, table_name=table_name, dtype=dtype, primary_keys=['trade_date']) logging.info("%d/%d) %s 更新 %s 结束 %d 条信息被更新", num, trade_date_list_len, trade_date, table_name, data_count) else: logging.info("无数据信息可被更新") except: logger.exception('更新 %s 表异常', table_name)
def import_tushare_stock_fina_indicator(chain_param=None, ts_code_set=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_fin_indicator' logging.info("更新 %s 开始", table_name) primary_keys = ['ts_code', 'ann_date', 'end_date'] has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_stock_daily if has_table: sql_str = """ SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to FROM ( SELECT info.ts_code, ifnull(ann_date, list_date) date_frm, delist_date, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM tushare_stock_info info LEFT OUTER JOIN (SELECT ts_code, adddate(max(ann_date),1) ann_date FROM {table_name} GROUP BY ts_code) fina_indicator ON info.ts_code = fina_indicator.ts_code ) tt WHERE date_frm <= if(delist_date<end_date, delist_date, end_date) ORDER BY ts_code""".format(table_name=table_name) else: sql_str = """ SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to FROM ( SELECT info.ts_code, list_date date_frm, delist_date, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM tushare_stock_info info ) tt WHERE date_frm <= if(delist_date<end_date, delist_date, end_date) ORDER BY ts_code""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取每只股票需要获取日线数据的日期区间 table = session.execute(sql_str) # 计算每只股票需要获取日线数据的日期区间 begin_time = None # 获取date_from,date_to,将date_from,date_to做为value值 code_date_range_dic = { ts_code: (date_from if begin_time is None else min([date_from, begin_time]), date_to) for ts_code, date_from, date_to in table.fetchall() if ts_code_set is None or ts_code in ts_code_set } fields = 'ts_code', 'ann_date', 'end_date', 'eps', 'dt_eps', 'total_revenue_ps', 'revenue_ps', 'capital_rese_ps', 'surplus_rese_ps', \ 'undist_profit_ps', 'extra_item', 'profit_dedt', 'gross_margin', 'current_ratio', 'quick_ratio', 'cash_ratio', 'invturn_days', 'arturn_days', \ 'inv_turn', 'ar_turn', 'ca_turn', 'fa_turn', 'assets_turn', 'op_income', 'valuechange_income', 'interst_income', 'daa', 'ebit', 'ebitda', 'fcff', \ 'fcfe', 'current_exint', 'noncurrent_exint', 'interestdebt', 'netdebt', 'tangible_asset', 'working_capital', 'networking_capital', 'invest_capital', \ 'retained_earnings', 'diluted2_eps', 'bps', 'ocfps', 'retainedps', 'cfps', 'ebit_ps', 'fcff_ps', 'fcfe_ps', 'netprofit_margin', 'grossprofit_margin', \ 'cogs_of_sales', 'expense_of_sales', 'profit_to_gr', 'saleexp_to_gr', 'adminexp_of_gr', 'finaexp_of_gr', 'impai_ttm', 'gc_of_gr', 'op_of_gr', \ 'ebit_of_gr', 'roe', 'roe_waa', 'roe_dt', 'roa', 'npta', 'roic', 'roe_yearly', 'roa2_yearly', 'roe_avg', 'opincome_of_ebt', 'investincome_of_ebt', \ 'n_op_profit_of_ebt', 'tax_to_ebt', 'dtprofit_to_profit', 'salescash_to_or', 'ocf_to_or', 'ocf_to_opincome', 'capitalized_to_da', 'debt_to_assets', \ 'assets_to_eqt', 'dp_assets_to_eqt', 'ca_to_assets', 'nca_to_assets', 'tbassets_to_totalassets', 'int_to_talcap', 'eqt_to_talcapital', 'currentdebt_to_debt', \ 'longdeb_to_debt', 'ocf_to_shortdebt', 'debt_to_eqt', 'eqt_to_debt', 'eqt_to_interestdebt', 'tangibleasset_to_debt', 'tangasset_to_intdebt', \ 'tangibleasset_to_netdebt', 'ocf_to_debt', 'ocf_to_interestdebt', 'ocf_to_netdebt', 'ebit_to_interest', 'longdebt_to_workingcapital', 'ebitda_to_debt', \ 'turn_days', 'roa_yearly', 'roa_dp', 'fixed_assets', 'profit_prefin_exp', 'non_op_profit', 'op_to_ebt', 'nop_to_ebt', 'ocf_to_profit', 'cash_to_liqdebt', \ 'cash_to_liqdebt_withinterest', 'op_to_liqdebt', 'op_to_debt', 'roic_yearly', 'total_fa_trun', 'profit_to_op', 'q_opincome', 'q_investincome', 'q_dtprofit', \ 'q_eps', 'q_netprofit_margin', 'q_gsprofit_margin', 'q_exp_to_sales', 'q_profit_to_gr', 'q_saleexp_to_gr', 'q_adminexp_to_gr', 'q_finaexp_to_gr', \ 'q_impair_to_gr_ttm', 'q_gc_to_gr', 'q_op_to_gr', 'q_roe', 'q_dt_roe', 'q_npta', 'q_opincome_to_ebt', 'q_investincome_to_ebt', 'q_dtprofit_to_profit', \ 'q_salescash_to_or', 'q_ocf_to_sales', 'q_ocf_to_or', 'basic_eps_yoy', 'dt_eps_yoy', 'cfps_yoy', 'op_yoy', 'ebt_yoy', 'netprofit_yoy', 'dt_netprofit_yoy', \ 'ocf_yoy', 'roe_yoy', 'bps_yoy', 'assets_yoy', 'eqt_yoy', 'tr_yoy', 'or_yoy', 'q_gr_yoy', 'q_gr_qoq', 'q_sales_yoy', 'q_sales_qoq', 'q_op_yoy', 'q_op_qoq', \ 'q_profit_yoy', 'q_profit_qoq', 'q_netprofit_yoy', 'q_netprofit_qoq', 'equity_yoy', 'rd_exp' data_df_list, data_count, all_data_count, data_len = [], 0, 0, len( code_date_range_dic) logger.info('%d 财务指标信息将被插入 tushare_stock_fin_indicator 表', data_len) # 将data_df数据,添加到data_df_list Cycles = 1 try: for num, (ts_code, (date_from, date_to)) in enumerate(code_date_range_dic.items(), start=1): logger.debug('%d/%d) %s [%s - %s]', num, data_len, ts_code, date_from, date_to) data_df = invoke_fina_indicator( ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS), end_date=datetime_2_str(date_to, STR_FORMAT_DATE_TS), fields=fields) # logger.info(' %d data of %s between %s and %s', df.shape[0], ts_code, date_from, date_to) if data_df is not None and len( data_df) > 0 and data_df['ann_date'].iloc[-1] is not None: while try_2_date(data_df['ann_date'].iloc[-1]) > date_from: last_date_in_df_last = try_2_date( data_df['ann_date'].iloc[-1]) df2 = invoke_fina_indicator( ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS), end_date=datetime_2_str( try_2_date(data_df['ann_date'].iloc[-1]) - timedelta(days=1), STR_FORMAT_DATE_TS), fields=fields) if len(df2) > 0 and df2['ann_date'].iloc[-1] is not None: last_date_in_df_cur = try_2_date( df2['ann_date'].iloc[-1]) if last_date_in_df_cur < last_date_in_df_last: data_df = pd.concat([data_df, df2]) elif last_date_in_df_cur == last_date_in_df_last: break elif len(df2) <= 0: break if data_df is None: logger.warning('%d/%d) %s has no data during %s %s', num, data_len, ts_code, date_from, date_to) continue elif data_df is not None: logger.info('%d/%d) %d 条 %s 财务指标已提取,起止时间 %s 和 %s', num, data_len, data_df.shape[0], ts_code, date_from, date_to) # 把数据攒起来 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 1000 and len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_STOCK_FINA_INDICATOR, primary_keys=primary_keys) all_data_count += data_count logger.info('%d 条财务指标将数据插入 %s 表', data_count, table_name) data_df_list, data_count = [], 0 # 仅调试使用 Cycles = Cycles + 1 if DEBUG and Cycles > 10: break finally: # 导入数据库 if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_STOCK_FINA_INDICATOR, primary_keys=primary_keys) all_data_count += data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_stock_cashflow(chain_param=None, ts_code_set=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_cashflow' primary_keys = ['ts_code', 'ann_date', 'end_date'] logging.info("更新 %s 开始", table_name) check_sqlite_db_primary_keys(table_name, primary_keys) has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_stock_daily if has_table: sql_str = """ SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to FROM ( SELECT info.ts_code, ifnull(ann_date, list_date) date_frm, delist_date, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM tushare_stock_info info LEFT OUTER JOIN (SELECT ts_code, adddate(max(ann_date),1) ann_date FROM {table_name} GROUP BY ts_code) cashflow ON info.ts_code = cashflow.ts_code ) tt WHERE date_frm <= if(delist_date<end_date, delist_date, end_date) ORDER BY ts_code""".format(table_name=table_name) else: sql_str = """ SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to FROM ( SELECT info.ts_code, list_date date_frm, delist_date, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM tushare_stock_info info ) tt WHERE date_frm <= if(delist_date<end_date, delist_date, end_date) ORDER BY ts_code""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取每只股票需要获取日线数据的日期区间 table = session.execute(sql_str) # 计算每只股票需要获取日线数据的日期区间 begin_time = None # 获取date_from,date_to,将date_from,date_to做为value值 code_date_range_dic = { ts_code: (date_from if begin_time is None else min([date_from, begin_time]), date_to) for ts_code, date_from, date_to in table.fetchall() if ts_code_set is None or ts_code in ts_code_set } data_df_list, data_count, all_data_count, data_len = [], 0, 0, len( code_date_range_dic) logger.info('%d data will been import into %s', data_len, table_name) # 将data_df数据,添加到data_df_list cycles = 1 try: for num, (ts_code, (date_from, date_to)) in enumerate(code_date_range_dic.items(), start=1): logger.debug('%d/%d) %s [%s - %s]', num, data_len, ts_code, date_from, date_to) df = invoke_cashflow( ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS), end_date=datetime_2_str(date_to, STR_FORMAT_DATE_TS)) # logger.info(' %d data of %s between %s and %s', df.shape[0], ts_code, date_from, date_to) data_df = df if data_df is not None and len(data_df) > 0: while try_2_date(df['ann_date'].iloc[-1]) > date_from: last_date_in_df_last, last_date_in_df_cur = try_2_date( df['ann_date'].iloc[-1]), None df2 = invoke_cashflow( ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS), end_date=datetime_2_str( try_2_date(df['ann_date'].iloc[-1]) - timedelta(days=1), STR_FORMAT_DATE_TS)) if len(df2) > 0: last_date_in_df_cur = try_2_date( df2['ann_date'].iloc[-1]) if last_date_in_df_cur < last_date_in_df_last: data_df = pd.concat([data_df, df2]) df = df2 elif last_date_in_df_cur == last_date_in_df_last: break elif len(df2) <= 0: break if data_df is None: logger.warning('%d/%d) %s has no data during %s %s', num, data_len, ts_code, date_from, date_to) continue elif data_df is not None: logger.info('%d/%d) %d 条 %s 的现金流被提取,起止时间为 %s 和 %s', num, data_len, data_df.shape[0], ts_code, date_from, date_to) # 把数据攒起来 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 1000 and len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_CASHFLOW, primary_keys=primary_keys) logger.info('%d 条现金流数据已插入 %s 表', data_count, table_name) all_data_count += data_count data_df_list, data_count = [], 0 # # 数据插入数据库 # data_count = bunch_insert_on_duplicate_update(data_df, table_name, engine_md, DTYPE_TUSHARE_CASHFLOW) # logging.info("更新 %s 结束 %d 条信息被更新", table_name, data_count) # 仅调试使用 cycles = cycles + 1 if DEBUG and cycles > 10: break finally: # 导入数据库 if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_CASHFLOW, primary_keys=primary_keys) all_data_count = all_data_count + data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_fut_wsr(chain_param=None, ts_code_set=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_fut_wsr' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_stock_daily if has_table: sql_str = """ select cal_date FROM ( select * from tushare_future_trade_cal trddate where( cal_date>(SELECT max(trade_date) FROM {table_name})) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) ) """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_future_trade_cal trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND cal_date>'19950414') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trddate = list(row[0] for row in table.fetchall()) # data_len = len(code_date_range_dic) data_df_list, data_count, all_data_count, data_len = [], 0, 0, len(trddate) logger.info('%d 日的期货仓单数据将被导入数据库', data_len) # 将data_df数据,添加到data_df_list fields = 'trade_date,symbol,fut_name,warehouse,wh_id,pre_vol,vol,vol_chg,area,year,grade,brand,place,pd,is_ct,unit,exchange' try: for i in range(len(trddate)): trade_date = datetime_2_str(trddate[i], STR_FORMAT_DATE_TS) data_df = invoke_fut_wsr(trade_date=trade_date, fields=fields) logging.info(" 提取 %s 日 %d 条期货仓单数据", trade_date, data_df.shape[0]) # 把数据攒起来 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 1000: data_df_all = pd.concat(data_df_list) bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_FUTURE_WSR, primary_keys=['symbol', 'trade_date']) logging.info(" 更新%s表%d条期货仓单数据", table_name, data_count) all_data_count += data_count data_df_list, data_count = [], 0 finally: # 导入数据库 if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_FUTURE_WSR, primary_keys=['symbol', 'trade_date']) all_data_count = all_data_count + data_count logging.info("更新 %s 结束 %d 条仓单信息被更新", table_name, all_data_count)
def import_jq_stock_daily(chain_param=None, code_set=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name_info = TABLE_NAME_INFO table_name = TABLE_NAME table_name_bak = get_bak_table_name(table_name) logging.info("更新 %s 开始", table_name) # 根据 info table 查询每只股票日期区间 sql_info_str = f""" SELECT jq_code, date_frm, if(date_to<end_date, date_to, end_date) date_to FROM ( SELECT info.jq_code, start_date date_frm, end_date date_to, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM {table_name_info} info ) tt WHERE date_frm <= if(date_to<end_date, date_to, end_date) ORDER BY jq_code""" has_table = engine_md.has_table(table_name) has_bak_table = engine_md.has_table(table_name_bak) # 进行表格判断,确定是否含有 jq_stock_daily_md if has_table: # 这里对原始的 sql语句进行了调整 # 以前的逻辑:每只股票最大的一个交易日+1天作为起始日期 # 现在的逻辑:每只股票最大一天的交易日作为起始日期 # 主要原因在希望通过接口获取到数据库中现有最大交易日对应的 factor因子以进行比对 sql_trade_date_range_str = f""" SELECT jq_code, date_frm, if(date_to<end_date, date_to, end_date) date_to FROM ( SELECT info.jq_code, ifnull(trade_date, info.start_date) date_frm, info.end_date date_to, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM {table_name_info} info LEFT OUTER JOIN (SELECT jq_code, max(trade_date) trade_date FROM {table_name} GROUP BY jq_code) daily ON info.jq_code = daily.jq_code ) tt WHERE date_frm < if(date_to<end_date, date_to, end_date) ORDER BY jq_code""" else: sql_trade_date_range_str = sql_info_str logger.warning('%s 不存在,仅使用 %s 表进行计算日期范围', table_name, table_name_info) sql_trade_date_str = """SELECT trade_date FROM jq_trade_date trddate WHERE trade_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) ORDER BY trade_date""" with with_db_session(engine_md) as session: # 获取截至当期全部交易日前 table = session.execute(sql_trade_date_str) trade_date_list = [row[0] for row in table.fetchall()] trade_date_list.sort() # 获取每只股票日线数据的日期区间 table = session.execute(sql_trade_date_range_str) # 计算每只股票需要获取日线数据的日期区间 # 获取date_from,date_to,将date_from,date_to做为value值 code_date_range_dic = { key_code: (date_from, date_to) for key_code, date_from, date_to in table.fetchall() if code_set is None or key_code in code_set } # 从 info 表中查询全部日期区间 if sql_info_str == sql_trade_date_range_str: code_date_range_from_info_dic = code_date_range_dic else: # 获取每只股票日线数据的日期区间 table = session.execute(sql_info_str) # 计算每只股票需要获取日线数据的日期区间 # 获取date_from,date_to,将date_from,date_to做为value值 code_date_range_from_info_dic = { key_code: (date_from, date_to) for key_code, date_from, date_to in table.fetchall() if code_set is None or key_code in code_set } # data_len = len(code_date_range_dic) data_df_list, data_count, all_data_count, data_len = [], 0, 0, len( code_date_range_dic) logger.info('%d stocks will been import into %s', data_len, table_name) # 将data_df数据,添加到data_df_list try: for num, (key_code, (date_from_tmp, date_to_tmp)) in enumerate(code_date_range_dic.items(), start=1): data_df = None try: for loop_count in range(2): # 根据交易日数据取交集,避免不用的请求耽误时间 date_from = get_first(trade_date_list, lambda x: x >= date_from_tmp) date_to = get_last(trade_date_list, lambda x: x <= date_to_tmp) if date_from is None or date_to is None or date_from >= date_to: logger.debug('%d/%d) %s [%s - %s] 跳过', num, data_len, key_code, date_from, date_to) break logger.debug('%d/%d) %s [%s - %s] %s', num, data_len, key_code, date_from, date_to, '第二次查询' if loop_count > 0 else '') data_df = invoke_daily(key_code=key_code, start_date=date_2_str(date_from), end_date=date_2_str(date_to)) # 该判断只在第一次循环时执行 if loop_count == 0 and has_table: # 进行 factor 因子判断,如果发现最小的一个交易日的因子不为1,则删除数据库中该股票的全部历史数据,然后重新下载。 # 因为当期股票下载的数据为前复权价格,如果股票出现复权调整,则历史数据全部需要重新下载 factor_value = data_df.sort_values('trade_date').iloc[ 0, :]['factor'] if factor_value != 1 and ( code_date_range_from_info_dic[key_code][0] != code_date_range_dic[key_code][0]): # 删除该股屏历史数据 sql_str = f"delete from {table_name} where jq_code=:jq_code" row_count = execute_sql_commit( sql_str, params={'jq_code': key_code}) date_from_tmp, date_to_tmp = code_date_range_from_info_dic[ key_code] if has_bak_table: sql_str = f"delete from {table_name_bak} where jq_code=:jq_code" row_count = execute_sql_commit( sql_str, params={'jq_code': key_code}) date_from_tmp, date_to_tmp = code_date_range_from_info_dic[ key_code] logger.info( '%d/%d) %s %d 条历史记录被清除,重新加载前复权历史数据 [%s - %s] 同时清除bak表中相应记录', num, data_len, key_code, row_count, date_from_tmp, date_to_tmp) else: logger.info( '%d/%d) %s %d 条历史记录被清除,重新加载前复权历史数据 [%s - %s]', num, data_len, key_code, row_count, date_from_tmp, date_to_tmp) # 重新设置起止日期,进行第二次循环 continue # 退出 for _ in range(2): 循环 break except Exception as exp: data_df = None logger.exception('%s [%s - %s]', key_code, date_2_str(date_from_tmp), date_2_str(date_to_tmp)) if exp.args[0].find('超过了每日最大查询限制'): break # 把数据攒起来 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 500: data_df_all = pd.concat(data_df_list) bunch_insert(data_df_all, table_name, dtype=DTYPE, primary_keys=['jq_code', 'trade_date']) all_data_count += data_count data_df_list, data_count = [], 0 if DEBUG and num >= 2: break finally: # 导入数据库 if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name, dtype=DTYPE, primary_keys=['jq_code', 'trade_date']) all_data_count = all_data_count + data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_future_daily(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_future_daily_md' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有 table_name if has_table: sql_str = """ select cal_date FROM ( select * from tushare_future_trade_cal trddate where( cal_date>(SELECT max(trade_date) FROM {table_name})) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) ) """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_future_trade_cal trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND cal_date>'19950414') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_future_trade_cal 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trddate = list(row[0] for row in table.fetchall()) # data_len = len(code_date_range_dic) data_df_list, data_count, all_data_count, data_len = [], 0, 0, len(trddate) logger.info('%d data will been import into %s', data_len, table_name) # 将data_df数据,添加到data_df_list # fields = 'ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,change1,change2,vol,amount,oi,oi_chg,delv_settle,delv_settle' fields = ','.join( [_[0] for _ in INDICATOR_PARAM_LIST_TUSHARE_FUTURE_DAILY_MD]) try: for i in range(len(trddate)): trade_date = datetime_2_str(trddate[i], STR_FORMAT_DATE_TS) data_df = invoke_future_daily(trade_date=trade_date, fields=fields) logging.info(" 提取 %s 日 %d 条期货行情数据", trade_date, data_df.shape[0]) # 把数据攒起来 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 1000: data_df_all = pd.concat(data_df_list) bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_FUTURE_DAILY_MD, primary_keys=['ts_code', 'trade_date']) logging.info(" 更新%s表%d条期货行情数据", table_name, data_count) all_data_count += data_count data_df_list, data_count = [], 0 finally: # 导入数据库 if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_FUTURE_DAILY_MD, primary_keys=['ts_code', 'trade_date']) all_data_count = all_data_count + data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_margin(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_margin' logging.info("更新 %s 开始", table_name) param_list = [ ('trade_date', Date), ('exchange_id', String(20)), ('rzye', DOUBLE), ('rzmre', DOUBLE), ('rzche', DOUBLE), ('rqye', DOUBLE), ('rqmcl', DOUBLE), ('rzrqye', DOUBLE), ] has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_daily_basic if has_table: sql_str = """ select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(trade_date) FROM {table_name})) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """.format( table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE' AND cal_date>='2010-03-31') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_trade_date 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = list(row[0] for row in table.fetchall()) # 设置 dtype dtype = {key: val for key, val in param_list} try: trade_date_list_len = len(trade_date_list) for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) for exchange_id in list(['SSE', 'SZSE']): data_df = invoke_margin(trade_date=trade_date, exchange_id=exchange_id) if len(data_df) > 0: # data_count = bunch_insert_on_duplicate_update(data_df, table_name, engine_md, dtype) # logging.info("%s更新 %s %s 结束 %d 条信息被更新", trade_date, table_name, exchange_id, data_count) data_count = bunch_insert( data_df, table_name=table_name, dtype=dtype, primary_keys=['exchange_id', 'trade_date']) logging.info("%d/%d) %s %s 更新 %s 结束 %d 条信息被更新", num, trade_date_list_len, exchange_id, trade_date, table_name, data_count) else: logging.info("%d/%d) %s %s 无数据信息可被更新 %s", num, trade_date_list_len, exchange_id, trade_date, table_name) except: logger.exception('更新 %s 表异常', table_name)
def update_df_2_db(instrument_type, table_name, data_df): """将 DataFrame 数据保存到 数据库对应的表中""" dtype = { 'trade_date': Date, 'Contract': String(20), 'ContractNext': String(20), 'Close': DOUBLE, 'CloseNext': DOUBLE, 'Volume': DOUBLE, 'VolumeNext': DOUBLE, 'OI': DOUBLE, 'OINext': DOUBLE, 'Open': DOUBLE, 'OpenNext': DOUBLE, 'High': DOUBLE, 'HighNext': DOUBLE, 'Low': DOUBLE, 'LowNext': DOUBLE, 'Amount': DOUBLE, 'AmountNext': DOUBLE, 'adj_factor_main': DOUBLE, 'adj_factor_secondary': DOUBLE, 'instrument_type': String(20), } # 为了解决 AttributeError: 'numpy.float64' object has no attribute 'translate' 错误,需要将数据类型转换成 float data_df["Close"] = data_df["Close"].apply(str_2_float) data_df["CloseNext"] = data_df["CloseNext"].apply(str_2_float) data_df["Volume"] = data_df["Volume"].apply(str_2_float) data_df["VolumeNext"] = data_df["VolumeNext"].apply(str_2_float) data_df["OI"] = data_df["OI"].apply(str_2_float) data_df["OINext"] = data_df["OINext"].apply(str_2_float) data_df["Open"] = data_df["Open"].apply(str_2_float) data_df["OpenNext"] = data_df["OpenNext"].apply(str_2_float) data_df["High"] = data_df["High"].apply(str_2_float) data_df["HighNext"] = data_df["HighNext"].apply(str_2_float) data_df["Low"] = data_df["Low"].apply(str_2_float) data_df["LowNext"] = data_df["LowNext"].apply(str_2_float) data_df["Amount"] = data_df["Amount"].apply(str_2_float) data_df["AmountNext"] = data_df["AmountNext"].apply(str_2_float) data_df["adj_factor_main"] = data_df["adj_factor_main"].apply(str_2_float) data_df["adj_factor_secondary"] = data_df["adj_factor_secondary"].apply( str_2_float) # 清理历史记录 with with_db_session(engine_md) as session: sql_str = """SELECT table_name FROM information_schema.TABLES WHERE table_name = :table_name and TABLE_SCHEMA=(select database())""" # 复权数据表 is_existed = session.execute(sql_str, params={ "table_name": table_name }).fetchone() if is_existed is not None: session.execute( "delete from %s where instrument_type = :instrument_type" % table_name, params={"instrument_type": instrument_type}) logger.debug("删除 %s 中的 %s 历史数据", table_name, instrument_type) # 插入数据库 bunch_insert(data_df, table_name=table_name, dtype=dtype, primary_keys=['trade_date', 'Contract'])
def import_tushare_top_list(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_stock_top_list' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) if has_table: sql_str = """ select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(trade_date) FROM {table_name} )) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE' and cal_date>'2005-05-31') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_trade_date 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = list(row[0] for row in table.fetchall()) # 定义相应的中间变量 data_df_list, data_count, all_data_count, data_len = [], 0, 0, len(trade_date_list) try: trade_date_list_len = len(trade_date_list) for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) data_df = invoke_top_list(trade_date=trade_date) # 把数据攒起来 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 2000: data_df_all = pd.concat(data_df_list) data_count = bunch_insert( data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_TOP_LIST, primary_keys=['ts_code', 'trade_date', 'reason']) logging.info("%d/%d) 更新 %s 结束 ,截至%s日 %d 条信息被更新", num, trade_date_list_len, table_name, trade_date, all_data_count) all_data_count += data_count data_df_list, data_count = [], 0 except: logger.exception('更新 %s 表异常', table_name) finally: if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert( data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_TOP_LIST, primary_keys=['ts_code', 'trade_date', 'reason']) all_data_count = all_data_count + data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_hsgt_top10(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_hsgt_top10' logging.info("更新 %s 开始", table_name) param_list = [ ('trade_date', Date), ('ts_code', String(20)), ('name', String(20)), ('close', DOUBLE), ('change', DOUBLE), ('rank', Integer), ('market_type', String(20)), ('amount', DOUBLE), ('net_amount', DOUBLE), ('buy', DOUBLE), ('sell', DOUBLE), ] has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_daily_basic if has_table: sql_str = """ select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(trade_date) FROM {table_name})) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """.format(table_name=table_name) else: sql_str = """ SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE' AND cal_date>='2014-11-17') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_trade_date 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = list(row[0] for row in table.fetchall()) # 设置 dtype dtype = {key: val for key, val in param_list} try: trade_date_list_len = len(trade_date_list) for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) for market_type in list(['1', '3']): data_df = invoke_hsgt_top10(trade_date=trade_date, market_type=market_type) if len(data_df) > 0: data_count = bunch_insert( data_df, table_name=table_name, dtype=dtype, primary_keys=['ts_code', 'trade_date']) logging.info("%d/%d) %s更新 %s 结束 %d 条信息被更新", num, trade_date_list_len, trade_date, table_name, data_count) else: logging.info("无数据信息可被更新") break except: logger.exception('更新 %s 表异常', table_name)
def import_data(table_name, dtype, invoke_api, primary_keys=["index_symbol", "trade_date", "jq_code"], ts_code_set=None, is_debug=False, is_monthly=False): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ info_table = 'jq_index_info' # table_name = 'jq_index_stocks' # primary_keys = ["index_symbol", "trade_date", "jq_code"] logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有tushare_stock_daily if has_table: sql_str = f""" SELECT jq_code, date_from, if(date_to<end_date, date_to, end_date) date_to FROM ( SELECT info.jq_code, ifnull(trade_date, start_date) date_from, end_date date_to, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM {info_table} info LEFT OUTER JOIN (SELECT index_symbol, adddate(max(trade_date),1) trade_date FROM {table_name} GROUP BY index_symbol) daily ON info.jq_code = daily.index_symbol ) tt WHERE date_from <= if(date_to<end_date, date_to, end_date) ORDER BY jq_code""" else: sql_str = f""" SELECT jq_code, date_from, if(date_to<end_date, date_to, end_date) date_to FROM ( SELECT info.jq_code, start_date date_from, end_date date_to, if(hour(now())<16, subdate(curdate(),1), curdate()) end_date FROM {info_table} info ) tt WHERE date_from <= if(date_to<end_date, date_to, end_date) ORDER BY jq_code""" logger.warning('%s 不存在,仅使用 tushare_stock_info 表进行计算日期范围', table_name) sql_trade_date_str = """ SELECT trade_date FROM jq_trade_date trddate WHERE trade_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) ORDER BY trade_date""" with with_db_session(engine_md) as session: table = session.execute(sql_trade_date_str) trade_date_list = [row[0] for row in table.fetchall()] trade_date_list.sort() # 获取每只股票需要获取日线数据的日期区间 table = session.execute(sql_str) begin_time = None # 获取date_from,date_to,将date_from,date_to做为value值 code_date_range_dic = { ts_code: (date_from if begin_time is None else min([date_from, begin_time]), date_to) for ts_code, date_from, date_to in table.fetchall() if ts_code_set is None or ts_code in ts_code_set} # data_len = len(code_date_range_dic) data_df_list, data_count, all_data_count, data_len = [], 0, 0, len(code_date_range_dic) logger.info('%d records will been import into %s', data_len, table_name) # 将data_df数据,添加到data_df_list try: for num, (index_symbol, (date_from_tmp, date_to_tmp)) in enumerate(code_date_range_dic.items(), start=1): date_from_idx = get_first_idx(trade_date_list, lambda x: x >= date_from_tmp) date_to_idx = get_last_idx(trade_date_list, lambda x: x <= date_to_tmp) if date_from_idx is None or date_to_idx is None or date_from_idx > date_to_idx: logger.debug('%d/%d) %s [%s - %s] 跳过', num, data_len, index_symbol, trade_date_list[date_from_idx] if date_from_idx is not None else None, trade_date_list[date_to_idx] if date_to_idx is not None else None) continue if is_monthly: date_sample = trade_date_list[date_from_idx: (date_to_idx + 1)] date_sample = list( pd.Series(date_sample, index=pd.DatetimeIndex(date_sample) ).resample(rule='M', convention='end').last() ) else: date_sample = trade_date_list[date_from_idx: (date_to_idx + 1)] date_from, date_to = date_sample[0], date_sample[-1] trade_date_count = len(date_sample) logger.debug('%d/%d) 开始导入 %s [%s - %s] %d 个交易日的数据 %s', num, data_len, index_symbol, date_from, date_to, trade_date_count, '月度更新' if is_monthly else '') for trade_date in date_sample: data_df = invoke_api(index_symbol=index_symbol, trade_date=trade_date) # 把数据攒起来 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 1000: data_count = bunch_insert(data_df_list, table_name=table_name, dtype=dtype, primary_keys=primary_keys) all_data_count += data_count data_df_list, data_count = [], 0 if is_debug and len(data_df_list) > 1: break except: logger.exception("%s 获取数据异常", table_name) finally: # 导入数据库 if len(data_df_list) > 0: data_count = bunch_insert(data_df_list, table_name=table_name, dtype=dtype, primary_keys=primary_keys) all_data_count += data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_block_trade(chain_param=None): """ 插入股票日线数据到最近一个工作日-1。 如果超过 BASE_LINE_HOUR 时间,则获取当日的数据 :return: """ table_name = 'tushare_block_trade' logging.info("更新 %s 开始", table_name) param_list = [ ('trade_date', Date), ('ts_code', String(20)), ('price', DOUBLE), ('vol', DOUBLE), ('amount', DOUBLE), ('buyer', String(100)), ('seller', String(100)), ] has_table = engine_md.has_table(table_name) # 进行表格判断,确定是否含有 table_name if has_table: sql_str = f"""select cal_date FROM ( select * from tushare_trade_date trddate where( cal_date>(SELECT max(trade_date) FROM {table_name})) )tt where (is_open=1 and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) and exchange='SSE') """ else: # 2003-08-02 大宗交易制度开始实施 sql_str = """SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) AND exchange='SSE' AND cal_date>='2003-08-02') ORDER BY cal_date""" logger.warning('%s 不存在,仅使用 tushare_trade_date 表进行计算日期范围', table_name) with with_db_session(engine_md) as session: # 获取交易日数据 table = session.execute(sql_str) trade_date_list = list(row[0] for row in table.fetchall()) # 设置 dtype dtype = {key: val for key, val in param_list} try: trade_date_list_len = len(trade_date_list) for num, trade_date in enumerate(trade_date_list, start=1): trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS) data_df = invoke_block_trade(trade_date=trade_date) if len(data_df) > 0: # 当前表不设置主键,由于存在重复记录,因此无法设置主键 # 例如:002325.SZ 2014-11-17 华泰证券股份有限公司沈阳光荣街证券营业部 两笔完全相同的大宗交易 data_count = bunch_insert( data_df, table_name=table_name, dtype=dtype) logging.info("%d/%d) %s更新 %s 结束 %d 条信息被更新", num, trade_date_list_len, trade_date, table_name, data_count) else: logging.info("%d/%d) %s 无数据信息可被更新", num, trade_date_list_len, trade_date) except: logger.exception('更新 %s 表异常', table_name)
def import_tushare_future_daily_by_ts_code(ts_code_set=None): """ 补充指定合约的行情数据 :return: """ table_name = 'tushare_future_daily_md' logging.info("更新 %s 开始", table_name) has_table = engine_md.has_table(table_name) with with_db_session(engine_md) as session: # 进行表格判断,确定是否含有 table_name if has_table: latest_trade_date_sql_str = """SELECT max(trade_date) FROM {table_name}""".format( table_name=table_name) trade_date_latest = session.scalar(latest_trade_date_sql_str) else: trade_date_latest = None curr_trade_date_sql_str = """ SELECT max(cal_date) FROM tushare_future_trade_cal trddate WHERE trddate.is_open=1 AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate()) ORDER BY cal_date""" trade_date_curr = session.scalar(curr_trade_date_sql_str) if ts_code_set is None: sql_str = """select ts_code, list_date, delist_date from tushare_future_basic""" params = None else: in_clause = ', '.join( [f':arg{_}' for _ in range(len(ts_code_set))]) sql_str = f"""select ts_code, list_date, delist_date from tushare_future_basic where ts_code in ({in_clause})""" params = {f'arg{_}': code for _, code in enumerate(ts_code_set)} table = session.execute(sql_str, params=params) ts_code_date_range_pair_list = list(table.fetchall()) logger.warning('%s 不存在,仅使用 tushare_future_trade_cal 表进行计算日期范围', table_name) data_df_list, data_count, all_data_count, data_len = [], 0, 0, len( ts_code_date_range_pair_list) logger.info('%d data will been import into %s', data_len, table_name) # 将data_df数据,添加到data_df_list # fields = 'ts_code,trade_date,pre_close,pre_settle,open,high,low,close,settle,change1,change2,vol,amount,oi,oi_chg,delv_settle,delv_settle' fields = ','.join( [_[0] for _ in INDICATOR_PARAM_LIST_TUSHARE_FUTURE_DAILY_MD]) try: for num, (ts_code, date_from, date_to) in enumerate(ts_code_date_range_pair_list, start=1): # 计算截止日期 if trade_date_latest is None: date_end = min([date_to, trade_date_curr]) else: date_end = min([date_to, trade_date_curr, trade_date_latest]) # 获取数据 data_df = invoke_future_daily_by_ts_code(ts_code, date_from, date_end, fields=fields) logging.info(" 提取 %s [%s - %s] %d 条期货行情数据", ts_code, date_from, date_to, data_df.shape[0]) # 数据合并 if data_df is not None and data_df.shape[0] > 0: data_count += data_df.shape[0] data_df_list.append(data_df) # 大于阀值有开始插入 if data_count >= 1000: data_df_all = pd.concat(data_df_list) bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_FUTURE_DAILY_MD, primary_keys=['ts_code', 'trade_date']) logging.info(" 更新%s表%d条期货行情数据", table_name, data_count) all_data_count += data_count data_df_list, data_count = [], 0 finally: # 导入数据库 if len(data_df_list) > 0: data_df_all = pd.concat(data_df_list) data_count = bunch_insert(data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_FUTURE_DAILY_MD, primary_keys=['ts_code', 'trade_date']) all_data_count = all_data_count + data_count logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)