如何在独立服务器中嵌入bokeh服务器 [英] How to embed a bokeh server in a standalone
问题描述
I'm trying to embed a bokeh server in a standalone document as presented here. I'm quite lost and couldn't wrap my head around the example provided. I tried to implement it in the following example, but when I run it doesn't show the application. Could someone show me how to create this standalone?
谢谢
from bokeh.io import show, curdoc
from bokeh.models import ColumnDataSource, Legend, CustomJS, Select
from bokeh.plotting import figure
from bokeh.palettes import Category10
from bokeh.layouts import row
import pandas as pd
from bokeh.server.server import Server
def test(doc):
df0 = pd.DataFrame({'x': [1, 2, 3], 'Ay' : [1, 5, 3], 'A': [0.2, 0.1, 0.2], 'By' : [2, 4, 3], 'B':[0.1, 0.3, 0.2]})
columns = ['A', 'B']
tools_to_show = 'box_zoom,save,hover,reset'
p = figure(plot_height =300, plot_width = 1200,
toolbar_location='above',
tools=tools_to_show)
legend_it = []
color = Category10[10]
columns = ['A', 'B']
source = ColumnDataSource(df0)
c = []
for i, col in enumerate(columns):
c.append(p.line('x', col, source=source, name=col, color=color[i]))
legend_it.append((col, [c[i]]))
legend = Legend(items=legend_it, location=(5,114))#(0, -60))
p.add_layout(legend, 'right')
select = Select(title="color", value=color[0],
options = color)
callbacks = CustomJS(args=dict(renderer=c[0], select=select), code ="""
renderer.glyph.line_color = select.value;
renderer.trigger('change')
""")
select.callback = callbacks
layout = row(select, p)
curdoc().add_root(layout)
server = Server(test)
server.start()
根据接受的答案,我修改了代码,它可以正常工作:
Based on the accepted answer I adapted the code and it works:
from bokeh.models import ColumnDataSource, Legend, CustomJS, Select
from bokeh.plotting import figure
from bokeh.palettes import Category10
from bokeh.layouts import row
import pandas as pd
from bokeh.server.server import Server
def test(doc):
df0 = pd.DataFrame({'x': [1, 2, 3], 'Ay' : [1, 5, 3], 'A': [0.2, 0.1, 0.2], 'By' : [2, 4, 3], 'B':[0.1, 0.3, 0.2]})
columns = ['A', 'B']
tools_to_show = 'box_zoom,save,hover,reset'
p = figure(plot_height =300, plot_width = 1200,
toolbar_location='above',
tools=tools_to_show)
legend_it = []
color = Category10[10]
columns = ['A', 'B']
source = ColumnDataSource(df0)
c = []
for i, col in enumerate(columns):
c.append(p.line('x', col, source=source, name=col, color=color[i]))
legend_it.append((col, [c[i]]))
legend = Legend(items=legend_it, location=(5,114))#(0, -60))
p.add_layout(legend, 'right')
select = Select(title="color", value=color[0],
options = color)
callbacks = CustomJS(args=dict(renderer=c[0], select=select), code ="""
renderer.glyph.line_color = select.value;
renderer.trigger('change')
""")
select.callback = callbacks
layout = row(select, p)
doc.add_root(layout)
server = Server({'/': test}, num_procs=1)
server.start()
server.io_loop.add_callback(server.show, "/")
server.io_loop.start()
推荐答案
在bokeh github站点上有一个完整的工作示例,用于以编程方式运行bokeh服务器而无需使用"bokeh serve ...":
There is a full working example for programmatically running a bokeh server without using "bokeh serve ..." on the bokeh github site:
https://github.com/bokeh/bokeh/blob/master/examples/howto/server_embed/standalone_embed.py
from bokeh.layouts import column
from bokeh.models import ColumnDataSource, Slider
from bokeh.plotting import figure
from bokeh.server.server import Server
from bokeh.themes import Theme
from bokeh.sampledata.sea_surface_temperature import sea_surface_temperature
def modify_doc(doc):
df = sea_surface_temperature.copy()
source = ColumnDataSource(data=df)
plot = figure(x_axis_type='datetime', y_range=(0, 25), y_axis_label='Temperature (Celsius)',
title="Sea Surface Temperature at 43.18, -70.43")
plot.line('time', 'temperature', source=source)
def callback(attr, old, new):
if new == 0:
data = df
else:
data = df.rolling('{0}D'.format(new)).mean()
source.data = ColumnDataSource(data=data).data
slider = Slider(start=0, end=30, value=0, step=1, title="Smoothing by N Days")
slider.on_change('value', callback)
doc.add_root(column(slider, plot))
doc.theme = Theme(filename="theme.yaml")
# Setting num_procs here means we can't touch the IOLoop before now, we must
# let Server handle that. If you need to explicitly handle IOLoops then you
# will need to use the lower level BaseServer class.
server = Server({'/': modify_doc}, num_procs=4)
server.start()
if __name__ == '__main__':
print('Opening Bokeh application on http://localhost:5006/')
server.io_loop.add_callback(server.show, "/")
server.io_loop.start()
如果我们以此为模板并集成您的代码,则它看起来像这样:
If we take this a template and integrate your code, it looks like this:
from bokeh.models import ColumnDataSource, Legend, CustomJS, Select
from bokeh.plotting import figure
from bokeh.palettes import Category10
from bokeh.layouts import row
import pandas as pd
from bokeh.server.server import Server
from bokeh.sampledata.sea_surface_temperature import sea_surface_temperature
def test(doc):
df0 = pd.DataFrame({'x': [1, 2, 3], 'Ay' : [1, 5, 3], 'A': [0.2, 0.1, 0.2], 'By' : [2, 4, 3], 'B':[0.1, 0.3, 0.2]})
columns = ['A', 'B']
tools_to_show = 'box_zoom,save,hover,reset'
p = figure(plot_height =300, plot_width = 1200,
toolbar_location='above',
tools=tools_to_show)
legend_it = []
color = Category10[10]
columns = ['A', 'B']
source = ColumnDataSource(df0)
c = []
for i, col in enumerate(columns):
c.append(p.line('x', col, source=source, name=col, color=color[i]))
legend_it.append((col, [c[i]]))
legend = Legend(items=legend_it, location=(5,114))#(0, -60))
p.add_layout(legend, 'right')
select = Select(title="color", value=color[0],
options = color)
callbacks = CustomJS(args=dict(renderer=c[0], select=select), code ="""
renderer.glyph.line_color = select.value;
renderer.trigger('change')
""")
select.callback = callbacks
layout = row(select, p)
doc.add_root(layout)
server = Server({'/': test}, num_procs=1)
server.start()
if __name__ == '__main__':
print('Opening Bokeh application on http://localhost:5006/')
server.io_loop.add_callback(server.show, "/")
server.io_loop.start()
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