def get_trading_time(target_list: 'list',
frequency: 'str',
fre_num: 'int',
begin_date,
end_date=''):
if isinstance(target_list, str):
target_list = [target_list]
new_targets = todictmc(target_list)
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
if isinstance(end_date, str) and end_date.strip() == '':
new_end_date = to_int_now_date('%Y%m%d')
else:
new_end_date = convert_str_or_datetime_to_int_date(end_date)
if frequency in ('day', 'week', 'month') and fre_num != 1:
raise ValueError(text.ERROR_INPUT_FREQUENCY_FREQNUM)
if 0 < new_end_date < new_begin_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
t, d = _history.get_trading_time(new_targets, frequency, new_begin_date,
new_end_date, fre_num)
if gv.freuency_to_int(frequency) >= gv.KFreq_Day:
d = np.arange(0, t.size, 1, dtype=np.int)
else:
d -= 1
return history_cvt.convert_trading_time_to_df(t, d)
def get_factor_by_code(factor_list: 'list', target: 'str', begin_date,
end_date):
if isinstance(factor_list, str):
factor_list = [factor_list]
targets = check_target(todictmc([target]))
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
new_end_date = convert_str_or_datetime_to_int_date(end_date)
if begin_date != 0 and new_begin_date > new_end_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
check_begin_end_date(new_begin_date, new_end_date)
factor_dict = _factors.get_factor_by_code(factor_list, targets,
new_begin_date, new_end_date)
factor_df = factor_cvt.convert_factor_by_code_to_df(
factor_dict) if factor_dict is not None else None
return factor_df
def get_factor_by_factor(factor: 'str', target_list: 'list', begin_date,
end_date):
if isinstance(target_list, str):
target_list = [target_list]
targets = check_target(todictmc(target_list))
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
new_end_date = convert_str_or_datetime_to_int_date(end_date)
if begin_date != 0 and new_begin_date > new_end_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
check_begin_end_date(new_begin_date, new_end_date)
factor_dict = _factors.get_factor_by_factor(factor, targets,
new_begin_date, new_end_date)
result_df = factor_cvt.convert_factor_by_factor_to_df(
factor_dict,
todotmc(targets)) if factor_dict['date'].size > 0 else None
return result_df
def get_kdata_n(target_list: 'list',
frequency: 'str',
fre_num: 'int',
n: 'int',
end_date: 'str',
fq=0,
fill_up=False,
df=False,
sort_by_date=False):
if isinstance(target_list, str):
target_list = [target_list]
if len(target_list) < 1:
raise ValueError(
text.ERROR_INPUT_EMPTY_PARAM.format(PARAMNAME='target_list'))
if isinstance(end_date, str) and end_date.strip() == '':
end_date = to_int_now_date('%Y%m%d')
else:
end_date = convert_str_or_datetime_to_int_date(end_date)
new_targets = todictmc(target_list)
fq = convert_internal_fq_to_atcore(fq)
if frequency in ('day', 'week', 'month') and fre_num != 1:
raise ValueError(text.ERROR_INPUT_FREQUENCY_FREQNUM)
results = [None] * len(new_targets)
for idx, target in enumerate(new_targets):
kdata = _history.get_k_data_n([target], frequency, fre_num, n,
end_date, fill_up, fq)
results[idx] = history_cvt.convert_k_data_to_df(
kdata[0], target_list[idx],
cnt.env.get_target_type(todotmc(target)))
if df:
data_df = pd.concat(results, ignore_index=True) # type: pd.DataFrame
if sort_by_date:
data_df = data_df.sort_values(
'time', ascending=True,
na_position='first') # type: pd.DataFrame
data_df.index = range(data_df.shape[0])
return data_df
else:
return {target: results[idx] for idx, target in enumerate(target_list)}
def get_kdata(target_list: 'list',
frequency: 'str',
fre_num: 'int',
begin_date,
end_date,
fq=enums.FQ_NA,
fill_up=False,
df=False,
sort_by_date=False):
if isinstance(target_list, str):
target_list = [target_list]
if len(target_list) < 1:
raise ValueError(
text.ERROR_INPUT_EMPTY_PARAM.format(PARAMNAME='target_list'))
begin_date = convert_str_or_datetime_to_int_date(begin_date)
end_date = convert_str_or_datetime_to_int_date(end_date)
new_targets = todictmc(target_list)
fq = convert_internal_fq_to_atcore(fq)
if frequency in ('day', 'week', 'month') and fre_num != 1:
raise ValueError(text.ERROR_INPUT_FREQUENCY_FREQNUM)
if 0 < end_date < begin_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
results = [None] * len(new_targets)
data_list = _history.get_k_data(new_targets, frequency, fre_num,
begin_date, end_date, fill_up, fq)
for idx, data in enumerate(data_list):
results[idx] = history_cvt.convert_k_data_to_df(
data, target_list[idx],
cnt.env.get_target_type(todotmc(new_targets[idx])))
if df:
data_df = pd.concat(results, ignore_index=True) # type: pd.DataFrame
if sort_by_date:
data_df = data_df.sort_values(
'time', ascending=True,
na_position='first') # type: pd.DataFrame
data_df.index = range(data_df.shape[0])
return data_df
else:
return {target: results[idx] for idx, target in enumerate(target_list)}
def get_factor_by_day(factor_list: 'list', target_list: 'list', date=''):
if isinstance(factor_list, str):
factor_list = [factor_list]
if isinstance(target_list, str):
target_list = [target_list]
targets = check_target(todictmc(target_list))
if date == '':
new_date = to_int_now_date()
else:
new_date = convert_str_or_datetime_to_int_date(date)
check_begin_end_date(new_date, new_date)
factor_dict = _factors.get_factor_by_day(factor_list, targets, new_date)
factor_df = factor_cvt.convert_factor_by_day_to_df(
factor_dict) if factor_dict is not None else None
return factor_df
def get_main_contract(main_code: 'str', begin_date, end_date):
begin_date = convert_str_or_datetime_to_int_date(begin_date)
if isinstance(end_date, str) and end_date.strip() == '':
end_date = to_int_now_date('%Y%m%d')
else:
end_date = convert_str_or_datetime_to_int_date(end_date)
new_targets = todictmc(main_code)
if begin_date > end_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
ls = _history.get_main_contract(new_targets['Market'], new_targets['Code'],
begin_date, end_date)
ls = [
t for t in ls
if str.lower(t['TargetIns']) != str.lower(new_targets['Code'])
]
return history_cvt.convert_main_contract_to_df(ls, new_targets['Market'])
def get_history_instruments(target_list: 'list',
begin_date,
end_date='',
df=False,
sort_by_date=True):
if isinstance(target_list, str):
target_list = [target_list]
targets = check_target(todictmc(target_list))
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
new_end_date = to_int_now_date(
) if end_date == '' else convert_str_or_datetime_to_int_date(end_date)
if begin_date != 0 and new_begin_date > new_end_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
data_matrix = _history.get_history_instruments(targets, new_begin_date,
new_end_date)
return history_cvt.convert_history_instrument_matrix_to_output(
target_list, data_matrix, df, sort_by_date)