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
