def get_kdata(entity_id=None,
level=IntervalLevel.LEVEL_1DAY.value,
provider='joinquant',
columns=None,
return_type='df',
start_timestamp=None,
end_timestamp=None,
filters=None,
session=None,
order=None,
limit=None,
index='timestamp'):
entity_type, exchange, code = decode_entity_id(entity_id)
data_schema: Mixin = get_kdata_schema(entity_type, level=level)
return data_schema.query_data(entity_id=entity_id,
level=level,
provider=provider,
columns=columns,
return_type=return_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
filters=filters,
session=session,
order=order,
limit=limit,
index=index)
def get_one_day_trading_minutes(entity_id: str = None, entity_type: str = None):
if entity_type is None:
entity_type, _, _ = decode_entity_id(entity_id)
if entity_type == 'coin':
return 24 * 60
if entity_type == 'stock':
return 4 * 60
def draw_kline(self, plotly_layout=None, annotation_df=None, render='html', file_name=None, width=None, height=None,
title=None, keep_ui_state=True, indicators=[], property_map=None, **kwargs):
data = []
for entity_id, df in self.normal_data.entity_map_df.items():
entity_type, _, code = decode_entity_id(entity_id)
trace_name = '{}_kdata'.format(code)
if entity_type == 'stock':
open = df.loc[:, 'qfq_open']
close = df.loc[:, 'qfq_close']
high = df.loc[:, 'qfq_high']
low = df.loc[:, 'qfq_low']
else:
open = df.loc[:, 'open']
close = df.loc[:, 'close']
high = df.loc[:, 'high']
low = df.loc[:, 'low']
data.append(
go.Candlestick(x=df.index, open=open, close=close, low=low, high=high, name=trace_name, **kwargs))
# append indicators
for indicator in indicators:
if indicator in df.columns:
trace_name = '{}_{}'.format(code, indicator)
ydata = df.loc[:, indicator].values.tolist()
data.append(go.Scatter(x=df.index, y=ydata, mode='lines', name=trace_name))
return self.show(plotly_data=data, plotly_layout=plotly_layout, annotation_df=annotation_df, render=render,
file_name=file_name, width=width,
height=height, title=title, keep_ui_state=keep_ui_state)
def draw_compare(self, chart: str, plotly_layout=None, annotation_df=None, render='html', file_name=None,
width=None, height=None, title=None, keep_ui_state=True, property_map=None, **kwargs):
data = []
layout_params = {}
for entity_id, df in self.normal_data.entity_map_df.items():
_, _, code = decode_entity_id(entity_id)
for col in df.columns:
trace_name = '{}_{}'.format(code, col)
ydata = df.loc[:, col].values.tolist()
# set y axis
yaxis, layout, col_chart = self.get_yaxis_layout_chart(col, property_map)
if yaxis and layout:
layout_params[f'yaxis{yaxis[-1]}'] = layout
if not col_chart:
col_chart = chart
if col_chart == 'line':
trace = go.Scatter(x=df.index, y=ydata, mode='lines', name=trace_name, yaxis=yaxis, **kwargs)
elif col_chart == 'scatter':
trace = go.Scatter(x=df.index, y=ydata, mode='markers', name=trace_name, yaxis=yaxis, **kwargs)
elif col_chart == 'area':
trace = go.Scatter(x=df.index, y=ydata, mode='none', fill='tonexty', name=trace_name, yaxis=yaxis,
**kwargs)
elif col_chart == 'bar':
trace = go.Bar(x=df.index, y=ydata, name=trace_name, yaxis=yaxis, **kwargs)
data.append(trace)
return self.show(plotly_data=data, plotly_layout=plotly_layout, annotation_df=annotation_df, render=render,
file_name=file_name, width=width,
height=height, title=title, keep_ui_state=keep_ui_state, **layout_params)
def get_kdata(entity_id,
level=IntervalLevel.LEVEL_1DAY.value,
provider='eastmoney',
columns=None,
return_type='df',
start_timestamp=None,
end_timestamp=None,
filters=None,
session=None,
order=None,
limit=None):
entity_type, exchange, code = decode_entity_id(entity_id)
data_schema = get_kdata_schema(entity_type, level=level)
return get_data(data_schema=data_schema,
entity_id=entity_id,
level=level,
provider=provider,
columns=columns,
return_type=return_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
filters=filters,
session=session,
order=order,
limit=limit)
def draw_histogram(self, plotly_layout=None, annotation_df=None, render='html', file_name=None, width=None,
height=None,
title=None, keep_ui_state=True, property_map=None, **kwargs):
data = []
annotations = []
for entity_id, df in self.normal_data.entity_map_df.items():
_, _, code = decode_entity_id(entity_id)
for col in df.columns:
trace_name = '{}_{}'.format(code, col)
x = df[col].tolist()
trace = go.Histogram(
x=x,
name=trace_name,
histnorm='probability',
**kwargs
)
annotation = dict(
x=x[-1],
y=0,
xref='x',
yref='y',
text=f'current:{x[-1]}',
showarrow=True,
align='center',
arrowhead=2,
arrowsize=1,
arrowwidth=2,
# arrowcolor='#030813',
# ax=-0.02,
# ay=-0.02,
bordercolor='#c7c7c7',
borderwidth=1,
opacity=0.8
)
data.append(trace)
annotations.append(annotation)
# just support one entity
break
if keep_ui_state:
uirevision = True
else:
uirevision = None
layout = go.Layout(showlegend=True,
uirevision=uirevision,
height=height,
width=width,
title=title,
annotations=annotations,
barmode='overlay')
return self.show(plotly_data=data, plotly_layout=layout, render=render, file_name=file_name, width=width,
height=height, title=title, keep_ui_state=keep_ui_state)
def to_high_level_kdata(kdata_df: pd.DataFrame, to_level: IntervalLevel):
def to_close(s):
if pd_is_not_null(s):
return s[-1]
def to_open(s):
if pd_is_not_null(s):
return s[0]
def to_high(s):
return np.max(s)
def to_low(s):
return np.min(s)
def to_sum(s):
return np.sum(s)
original_level = kdata_df['level'][0]
entity_id = kdata_df['entity_id'][0]
provider = kdata_df['provider'][0]
name = kdata_df['name'][0]
code = kdata_df['code'][0]
entity_type, _, _ = decode_entity_id(entity_id=entity_id)
assert IntervalLevel(original_level) <= IntervalLevel.LEVEL_1DAY
assert IntervalLevel(original_level) < IntervalLevel(to_level)
df: pd.DataFrame = None
if to_level == IntervalLevel.LEVEL_1WEEK:
# loffset='-2' 用周五作为时间标签
if entity_type == 'stock':
df = kdata_df.resample('W', loffset=pd.DateOffset(days=-2)).apply({'close': to_close,
'open': to_open,
'high': to_high,
'low': to_low,
'volume': to_sum,
'turnover': to_sum})
else:
df = kdata_df.resample('W', loffset=pd.DateOffset(days=-2)).apply({'close': to_close,
'open': to_open,
'high': to_high,
'low': to_low,
'volume': to_sum,
'turnover': to_sum})
df = df.dropna()
# id entity_id timestamp provider code name level
df['entity_id'] = entity_id
df['provider'] = provider
df['code'] = code
df['name'] = name
return df
def get_close_time(entity_id: str):
"""
:param entity_id:
:type entity_id: str
:return:0,0 means never stop
:rtype: Tuple[int, int]
"""
entity_type, _, _ = decode_entity_id(entity_id)
if entity_type == 'coin':
return 0, 0
if entity_type == 'stock':
return 15, 0
def draw_bar(self, x='columns', plotly_layout=None, annotation_df=None, render='html', file_name=None, width=None,
height=None,
title=None, keep_ui_state=True, **kwargs):
data = []
for entity_id, df in self.normal_data.entity_map_df.items():
_, _, code = decode_entity_id(entity_id)
for col in df.columns:
trace_name = '{}_{}'.format(code, col)
ydata = df.loc[:, col].values.tolist()
data.append(go.Bar(x=df.index, y=ydata, name=trace_name, **kwargs))
return self.show(plotly_data=data, plotly_layout=plotly_layout, annotation_df=annotation_df, render=render,
file_name=file_name, width=width,
height=height, title=title, keep_ui_state=keep_ui_state)
def draw_bar(self,
x='columns',
plotly_layout=None,
annotation_df=None,
render='html',
file_name=None,
width=None,
height=None,
title=None,
keep_ui_state=True,
property_map=None,
**kwargs):
data = []
layout_params = {}
for entity_id, df in self.normal_data.entity_map_df.items():
_, _, code = decode_entity_id(entity_id)
for col in df.columns:
trace_name = '{}_{}'.format(code, col)
ydata = df.loc[:, col].values.tolist()
# set y axis
yaxis, layout, _ = self.get_yaxis_layout_chart(
col, property_map)
if yaxis and layout:
layout_params[f'yaxis{yaxis[-1]}'] = layout
data.append(
go.Bar(x=df.index,
y=ydata,
name=trace_name,
yaxis=yaxis,
**kwargs))
return self.show(plotly_data=data,
plotly_layout=plotly_layout,
annotation_df=annotation_df,
render=render,
file_name=file_name,
width=width,
height=height,
title=title,
keep_ui_state=keep_ui_state,
**layout_params)
def get_current_price(entity_ids=None, entity_type='coin'):
result = {}
if entity_type == 'coin':
if entity_ids:
for entity_id in entity_ids:
a, exchange, code = decode_entity_id(entity_id)
assert a == entity_type
ccxt_exchange = CCXTAccount.get_ccxt_exchange(exchange_str=exchange)
if not ccxt_exchange:
raise Exception('{} not support'.format(exchange))
orderbook = ccxt_exchange.fetch_order_book(code)
bid = orderbook['bids'][0][0] if len(orderbook['bids']) > 0 else None
ask = orderbook['asks'][0][0] if len(orderbook['asks']) > 0 else None
entity_id = f'coin_{exchange}_{code}'
result[entity_id] = (bid, ask)
return result
def get_open_time(entity_id: str):
entity_type, _, _ = decode_entity_id(entity_id)
if entity_type == 'coin':
return 0, 0
if entity_type == 'stock':
return 9, 30
def _draw(self,
main_chart='kline',
sub_chart='bar',
mode='markers',
width=None,
height=None,
title=None,
keep_ui_state=True,
**kwargs):
if self.sub_data is not None and not self.sub_data.empty():
subplot = True
fig = make_subplots(rows=2,
cols=1,
row_heights=[0.8, 0.2],
vertical_spacing=0.08,
shared_xaxes=True)
else:
subplot = False
fig = go.Figure()
traces = []
sub_traces = []
for entity_id, df in self.main_data.entity_map_df.items():
entity_type, _, code = decode_entity_id(entity_id)
if main_chart == 'kline':
trace_name = '{}_kdata'.format(code)
trace = go.Candlestick(x=df.index,
open=df['open'],
close=df['close'],
low=df['low'],
high=df['high'],
name=trace_name,
**kwargs)
traces.append(trace)
elif main_chart == 'scatter':
for col in df.columns:
trace_name = '{}_{}'.format(code, col)
ydata = df[col].values.tolist()
traces.append(
go.Scatter(x=df.index,
y=ydata,
mode=mode,
name=trace_name,
**kwargs))
if subplot:
# 绘制幅图
sub_df = self.sub_data.entity_map_df.get(entity_id)
if pd_is_not_null(sub_df):
for col in sub_df.columns:
trace_name = '{}_{}'.format(code, col)
ydata = sub_df[col].values.tolist()
def color(i):
if i > 0:
return 'red'
else:
return 'green'
colors = [color(i) for i in ydata]
bar = go.Bar(x=sub_df.index,
y=ydata,
name=trace_name,
yaxis='y2',
marker_color=colors)
sub_traces.append(bar)
if subplot:
fig.add_traces(traces,
rows=[1] * len(traces),
cols=[1] * len(traces))
fig.add_traces(sub_traces,
rows=[2] * len(sub_traces),
cols=[1] * len(sub_traces))
else:
fig.add_traces(traces)
fig.update_layout(
self.gen_plotly_layout(width=width,
height=height,
title=title,
keep_ui_state=keep_ui_state,
subplot=subplot))
fig.show()
def draw_histogram(
self,
entity_in_subplot: bool = False,
plotly_layout=None,
render='html',
file_name=None,
width=None,
height=None,
title=None,
keep_ui_state=True,
# one of ( "" | "percent" | "probability" | "density" | "probability density" )
histnorm='',
**kwargs):
annotations = []
fig, total_rows = self.generate_fig(entity_in_subplot)
row = 1
for entity_id, df in self.main_data.entity_map_df.items():
_, _, code = decode_entity_id(entity_id)
traces = []
rows = []
for col in df.columns:
trace_name = '{}_{}'.format(code, col)
x = df[col].tolist()
trace = go.Histogram(x=x,
name=trace_name,
histnorm=histnorm,
**kwargs)
if row > 1:
yref = f'y{row}'
else:
yref = 'y'
annotation = dict(x=x[-1],
y=0,
xref='x',
yref=yref,
text=f'current:{x[-1]}',
showarrow=True,
align='center',
arrowhead=2,
arrowsize=1,
arrowwidth=2,
bordercolor='#c7c7c7',
borderwidth=1,
opacity=0.8)
traces.append(trace)
rows.append(row)
annotations.append(annotation)
# add the traces for row
if entity_in_subplot and (total_rows > 1):
fig.add_traces(traces, rows=rows, cols=[1] * len(rows))
row = row + 1
else:
fig.add_traces(traces)
if keep_ui_state:
uirevision = True
else:
uirevision = None
layout = go.Layout(showlegend=True,
uirevision=uirevision,
height=height,
width=width,
title=title,
annotations=annotations,
barmode='overlay')
fig.update_layout(layout)
fig.show()
def draw_scatter(self,
mode='markers',
plotly_layout=None,
render='html',
file_name=None,
width=None,
height=None,
title=None,
keep_ui_state=True,
**kwargs):
if self.sub_data is not None and not self.sub_data.empty():
subplot = True
fig = make_subplots(rows=2,
cols=1,
row_heights=[0.8, 0.2],
vertical_spacing=0.08,
shared_xaxes=True)
else:
subplot = False
fig = go.Figure()
traces = []
sub_traces = []
for entity_id, df in self.main_data.entity_map_df.items():
entity_type, _, code = decode_entity_id(entity_id)
for col in df.columns:
trace_name = '{}_{}'.format(code, col)
ydata = df[col].values.tolist()
traces.append(
go.Scatter(x=df.index,
y=ydata,
mode=mode,
name=trace_name,
**kwargs))
if subplot:
# 绘制幅图
sub_df = self.sub_data.entity_map_df.get(entity_id)
if pd_is_not_null(sub_df):
for col in sub_df.columns:
trace_name = '{}_{}'.format(code, col)
ydata = sub_df[col].values.tolist()
sub_traces.append(
go.Bar(x=sub_df.index,
y=ydata,
name=trace_name,
yaxis='y2'))
if subplot:
fig.add_traces(traces,
rows=[1] * len(traces),
cols=[1] * len(traces))
fig.add_traces(sub_traces,
rows=[2] * len(sub_traces),
cols=[1] * len(sub_traces))
else:
fig.add_traces(traces)
fig.update_layout(
self.get_plotly_layout(width=width,
height=height,
title=title,
keep_ui_state=keep_ui_state,
subplot=subplot))
fig.show()