def get_tdx_exp_all_LastDF(codeList, dt=None, ptype="low"): time_t = time.time() # df = rl.get_sina_Market_json(market) # code_list = np.array(df.code) # if type==0: # results = cct.to_mp_run(get_tdx_day_to_df_last, codeList) # else: if dt is not None: if len(str(dt)) < 8: dl = int(dt) + changedays df = get_tdx_day_to_df("999999").sort_index(ascending=False) dt = get_duration_price_date("999999", dt=dt, ptype=ptype, df=df) dt = df[df.index <= dt].index.values[changedays] log.info("LastDF:%s,%s" % (dt, dl)) else: if len(str(dt)) == 8: dt = cct.day8_to_day10(dt) df = get_tdx_day_to_df("999999").sort_index(ascending=False) dl = len(get_tdx_Exp_day_to_df("999999", start=dt)) + changedays dt = df[df.index <= dt].index.values[changedays] log.info("LastDF:%s,%s" % (dt, dl)) results = cct.to_mp_run_async(get_tdx_exp_low_or_high_price, codeList, dt, ptype, dl) # results = get_tdx_exp_low_or_high_price(codeList[0], dt,ptype,dl) # results=[] # for code in codeList: # results.append(get_tdx_exp_low_or_high_price(code, dt, ptype, dl)) else: # results = cct.to_mp_run_async(get_tdx_exp_low_or_high_price,codeList) results = cct.to_mp_run_async(get_tdx_Exp_day_to_df, codeList, "f", None, None, None, 1) # print results df = pd.DataFrame(results, columns=ct.TDX_Day_columns) df = df.set_index("code") df.loc[:, "open":] = df.loc[:, "open":].astype(float) # df.vol = df.vol.apply(lambda x: x / 100) log.info("get_to_mp:%s" % (len(df))) log.info("TDXTime:%s" % (time.time() - time_t)) if dt != None: print ("TDXE:%0.2f" % (time.time() - time_t)), return df
def get_tdx_all_StockList_DF(code_list, dayl=1, type=0): time_t = time.time() # df = rl.get_sina_Market_json(market) # code_list = np.array(df.code) # log.info('code_list:%s' % len(code_list)) results = cct.to_mp_run_async(get_tdx_day_to_df_last, code_list, dayl, type) log.info("get_to_mp_op:%s" % (len(results))) # df = pd.DataFrame(results, columns=ct.TDX_Day_columns) # df = df.set_index('code') # print df[:1] print "t:", time.time() - time_t return results
def get_tdx_all_day_DayL_DF(market="cyb", dayl=1): time_t = time.time() df = rl.get_sina_Market_json(market) code_list = np.array(df.code) log.info("code_list:%s" % len(code_list)) results = cct.to_mp_run_async(get_tdx_day_to_df_last, code_list, dayl) log.info("get_to_mp_op:%s" % (len(results))) # df = pd.DataFrame(results, columns=ct.TDX_Day_columns) # df = df.set_index('code') # print df[:1] # print len(df),df[:1] # print "<2015-08-25",len(df[(df.date< '2015-08-25')]) # print "06-25-->8-25'",len(df[(df.date< '2015-08-25')&(df.date > '2015-06-25')]) print "t:", time.time() - time_t return results
def get_tdx_all_day_LastDF(codeList, type=0, dt=None, ptype="low"): time_t = time.time() # df = rl.get_sina_Market_json(market) # code_list = np.array(df.code) # if type==0: # results = cct.to_mp_run(get_tdx_day_to_df_last, codeList) # else: if dt is not None: if len(str(dt)) != 8: df = get_tdx_day_to_df("999999").sort_index(ascending=False) dt = get_duration_price_date("999999", dt=dt, ptype=ptype, df=df) dt = df[df.index <= dt].index.values[changedays] dl = len(df[df.index >= dt]) log.info("LastDF:%s" % dt) else: # dt = int(dt)+10 df = get_tdx_day_to_df("999999").sort_index(ascending=False) dt = get_duration_price_date("999999", dt=dt, ptype=ptype, df=df) dt = df[df.index <= dt].index.values[changedays] dl = len(df[df.index >= dt]) log.info("LastDF:%s" % dt) else: dl = None results = cct.to_mp_run_async(get_tdx_day_to_df_last, codeList, 1, type, dt, ptype, dl) # results=[] # for code in codeList: # results.append(get_tdx_day_to_df_last(code, 1, type, dt,ptype)) df = pd.DataFrame(results, columns=ct.TDX_Day_columns) df = df.set_index("code") df.loc[:, "open":] = df.loc[:, "open":].astype(float) # df.vol = df.vol.apply(lambda x: x / 100) log.info("get_to_mp:%s" % (len(df))) log.info("TDXTime:%s" % (time.time() - time_t)) if dt != None: print ("TDX:%0.2f" % (time.time() - time_t)), return df