def test_align():
# -------------------------------------------------------------------------------------
# input and pre-process demo data
ds = RemoteDataService()
ds.init_from_config(data_config)
raw, msg = ds.query_lb_fin_stat('income', '600000.SH', 20151225, 20170501, 'oper_rev')
assert msg == '0,'
idx_list = ['report_date', 'symbol']
raw_idx = raw.set_index(idx_list)
raw_idx.sort_index(axis=0, level=idx_list, inplace=True)
df_ann = raw_idx.loc[pd.IndexSlice[:, :], 'ann_date']
df_ann = df_ann.unstack(level=1)
df_value = raw_idx.loc[pd.IndexSlice[:, :], 'oper_rev']
df_value = df_value.unstack(level=1)
date_arr = ds.query_trade_dates(20160101, 20170501)
df_close = pd.DataFrame(index=date_arr, columns=df_value.columns, data=1e3)
# -------------------------------------------------------------------------------------
# demo usage of parser
parser = Parser()
parser.register_function('Myfunc', lambda x: x * 0 + 1) # simultaneously test register function and align
expr_formula = 'signal / Myfunc(close)'
expression = parser.parse(expr_formula)
for i in range(100):
df_res = parser.evaluate({'signal': df_value, 'close': df_close}, df_ann, date_arr)
# -------------------------------------------------------------------------------------
sec = '600000.SH'
"""
# print to validate results
print "\n======Expression Formula:\n{:s}".format(expr_formula)
print "\n======Report date, ann_date and evaluation value:"
tmp = pd.concat([df_ann.loc[:, sec], df_value.loc[:, sec]], axis=1)
tmp.columns = ['df_ann', 'df_value']
print tmp
print "\n======Selection of result of expansion:"
print "20161028 {:.4f}".format(df_res.loc[20161028, sec])
print "20161031 {:.4f}".format(df_res.loc[20161031, sec])
print "20170427 {:.4f}".format(df_res.loc[20170427, sec])
"""
assert abs(df_res.loc[20161028, sec] - 82172000000) < 1
assert abs(df_res.loc[20161031, sec] - 120928000000) < 1
assert abs(df_res.loc[20170427, sec] - 42360000000) < 1
def test_align():
# -------------------------------------------------------------------------------------
# input and pre-process demo data
ds = RemoteDataService()
ds.init_from_config(data_config)
raw, msg = ds.query_lb_fin_stat('income', '600000.SH', 20151225, 20170501,
'oper_rev')
assert msg == '0,'
# print(raw)
idx_list = ['report_date', 'symbol']
raw_idx = raw.set_index(idx_list)
raw_idx.sort_index(axis=0, level=idx_list, inplace=True)
print(raw_idx)
df_ann = raw_idx.loc[pd.IndexSlice[:, :], 'ann_date']
df_ann = df_ann.unstack(level=1)
df_value = raw_idx.loc[pd.IndexSlice[:, :], 'oper_rev']
df_value = df_value.unstack(level=1)
date_arr = ds.query_trade_dates(20160101, 20170501)
df_close = pd.DataFrame(index=date_arr, columns=df_value.columns, data=1e3)
# -------------------------------------------------------------------------------------
# demo usage of parser
parser = Parser()
parser.register_function(
'Myfunc',
lambda x: x * 0 + 1) # simultaneously test register function and align
expr_formula = 'signal / Myfunc(close)'
expression = parser.parse(expr_formula)
for i in range(100):
df_res = parser.evaluate({
'signal': df_value,
'close': df_close
}, df_ann, date_arr)
# -------------------------------------------------------------------------------------
sec = '600000.SH'
"""
# print to validate results
print "\n======Expression Formula:\n{:s}".format(expr_formula)
print "\n======Report date, ann_date and evaluation value:"
tmp = pd.concat([df_ann.loc[:, sec], df_value.loc[:, sec]], axis=1)
tmp.columns = ['df_ann', 'df_value']
print tmp
print "\n======Selection of result of expansion:"
print "20161028 {:.4f}".format(df_res.loc[20161028, sec])
print "20161031 {:.4f}".format(df_res.loc[20161031, sec])
print "20170427 {:.4f}".format(df_res.loc[20170427, sec])
"""
assert abs(df_res.loc[20161028, sec] - 82172000000) < 1
assert abs(df_res.loc[20161031, sec] - 120928000000) < 1
assert abs(df_res.loc[20170427, sec] - 42360000000) < 1
def my_globals(request):
ds = RemoteDataService()
ds.init_from_config(data_config)
df, msg = ds.daily("000001.SH, 600030.SH, 000300.SH",
start_date=20170801,
end_date=20170820,
fields="open,high,low,close,vwap,preclose")
multi_index_names = ['trade_date', 'symbol']
df_multi = df.set_index(multi_index_names, drop=False)
df_multi.sort_index(axis=0, level=multi_index_names, inplace=True)
dfx = df_multi.loc[pd.IndexSlice[:, :], pd.IndexSlice['close']].unstack()
dfy = df_multi.loc[pd.IndexSlice[:, :], pd.IndexSlice['open']].unstack()
parser = Parser()
request.function.__globals__.update({
'parser': parser,
'dfx': dfx,
'dfy': dfy
})
if __name__ == "__main__":
ds = RemoteDataService()
ds.init_from_config(data_config)
df, msg = ds.daily("000001.SH, 600030.SH, 000300.SH",
start_date=20170801,
end_date=20170820,
fields="open,high,low,close,vwap,preclose")
ds.data_api.close()
multi_index_names = ['trade_date', 'symbol']
df_multi = df.set_index(multi_index_names, drop=False)
df_multi.sort_index(axis=0, level=multi_index_names, inplace=True)
dfx = df_multi.loc[pd.IndexSlice[:, :], pd.IndexSlice['close']].unstack()
dfy = df_multi.loc[pd.IndexSlice[:, :], pd.IndexSlice['open']].unstack()
parser = Parser()
g = globals()
g = {k: v for k, v in g.items() if k.startswith('test_') and callable(v)}
for test_name, test_func in g.items():
print("\n==========\nTesting {:s}...".format(test_name))
# try:
test_func()
# print "Successfully tested {:s}.".format(test_name)
# except Exception, e:
print("Test Complete.")