def get_bars(self,
order_book_id,
dt,
bar_count=1,
frequency='1d',
fields=None,
skip_suspended=True,
include_now=False,
adjust_type='pre',
adjust_orig=None,
convert_to_dataframe=False,
time_format='datetime'):
order_book_id = to_order_book_id(order_book_id)
dt = to_date_object(dt) #TODO if we want minute bar?
if fields is None:
fields = [
'datetime', 'open', 'high', 'low', 'close', 'volume',
'total_turnover'
]
bars = super(DataSource,
self).history_bars(order_book_id=order_book_id,
bar_count=bar_count,
frequency=frequency,
field=fields,
dt=dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=adjust_orig)
if convert_to_dataframe:
df = pd.DataFrame.from_dict(bars)
if 'datetime' in df.columns:
if time_format == 'datetime':
df['datetime'] = df['datetime'].map(
lambda x: convert_int_to_datetime(x))
if time_format == 'int' and frequency == '1d':
df['datetime'] = df['datetime'].map(lambda x: x / 1000000)
df.set_index('datetime', inplace=True)
# df.index.name = ''
# df.index[0] is like: Timestamp('2005-01-04 00:00:00'),type is pandas._libs.tslib.Timestamp
return df
return bars # type(bars): numpy.ndarray
def get_bars_all(self,
order_book_id,
dt=None,
frequency='1d',
fields=None,
skip_suspended=True,
include_now=False,
adjust_type='pre',
adjust_orig=None,
convert_to_dataframe=False):
order_book_id = to_order_book_id(order_book_id)
if dt is None:
dt = datetime.datetime.now()
dt = to_date_object(dt)
if fields is None:
fields = [
'datetime', 'open', 'high', 'low', 'close', 'volume',
'total_turnover'
]
bars = super(DataSource,
self).get_bars_all(order_book_id=order_book_id,
frequency=frequency,
field=fields,
dt=dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=adjust_orig)
if convert_to_dataframe:
df = pd.DataFrame.from_dict(bars)
if 'datetime' in df.columns:
df['datetime'] = df['datetime'].map(
lambda x: convert_int_to_datetime(x))
df.set_index('datetime', inplace=True)
df.index.name = ''
return df
return bars
def history_bars(self,
order_book_id,
bar_count,
frequency,
field,
dt,
skip_suspended=True,
include_now=False,
adjust_type='pre',
adjust_orig=None):
order_book_id = to_order_book_id(order_book_id)
dt = to_date_object(dt)
bars = super(DataSource,
self).history_bars(order_book_id=order_book_id,
bar_count=bar_count,
frequency=frequency,
field=field,
dt=dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=adjust_orig)
return bars
def get_bar(self, order_book_id, dt, frequency='1d'):
order_book_id = to_order_book_id(order_book_id)
dt = to_date_object(dt)
return super(DataSource, self).get_bar(order_book_id=order_book_id,
dt=dt,
frequency=frequency)