经过大量的试验和错误，我能够让它工作。我创建了一个 git 存储库，其中包含您入门所需的一切，但它肯定不足以用于生产：
https://github.com/denson/bokeh_beanstalk_helloworld
Docker 文件：
# docker build -t standalone_embed .
# docker image ls
# docker run -p 80:5006 standalone_embed
# List all containers (only IDs) docker ps -aq.
# Stop all running containers. docker stop $(docker ps -aq)
# Remove all containers. docker rm $(docker ps -aq)
# Remove all images. docker rmi $(docker images -q)
FROM continuumio/miniconda3
# Set the ENTRYPOINT to use bash
# (this is also where you’d set SHELL,
# if your version of docker supports this)
ENTRYPOINT [ “/bin/bash”, “-c” ]
EXPOSE 5006
COPY . /
WORKDIR /
# Conda supports delegating to pip to install dependencies
# that aren’t available in anaconda or need to be compiled
# for other reasons. In our case, we need psycopg compiled
# with SSL support. These commands install prereqs necessary
# to build psycopg.
RUN apt-get update && apt-get install -y \
libpq-dev \
build-essential \
&& rm -rf /var/lib/apt/lists/*
# Install pyviz
# http://pyviz.org/installation.html
# update conda and install pyviz
RUN conda update conda
RUN conda update conda
# RUN conda install -c pyviz/label/dev pyviz
# install flask and Bokeh
RUN conda install -c conda-forge bokeh
RUN conda install -c anaconda flask
RUN conda install -c anaconda pandas
# We set ENTRYPOINT, so while we still use exec mode, we don’t
# explicitly call /bin/bash
ENTRYPOINT ["python", "./standalone_embed.py"]
# https://github.com/lukauskas/docker-bokeh
# https://github.com/bokeh/bokeh/issues/7724
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.
# To allow connections only from a trusted domain set allow_websocket_origin to the domain
# server = Server({'/': modify_doc}, num_procs=1, address="0.0.0.0", port=5006, allow_websocket_origin=["flaskhelloworld-env.gktytvudba.us-east-2.elasticbeanstalk.com"])
# to allow connections from anywhere
server = Server({'/': modify_doc}, num_procs=1, address="0.0.0.0", port=5006, allow_websocket_origin=["*"])
server.start()
if __name__ == '__main__':
print('Opening Bokeh application on http://0.0.0.0:5006/')
server.io_loop.add_callback(server.show, "/")
server.io_loop.start()