blocks|key|4401042|text|你需要在0.0.0.0：jupyter+notebook+-i+0.0.0.0上运行你的笔记本。在localhost上运行使其只能从容器内部使用。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4401043|entityMap^0|4|7|C|R|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]|$9|K|A|L|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|M|8|@]|D|@]|E|$]]]|G|$]]

You need to run your notebook on <code>0.0.0.0</code>: <code>jupyter notebook -i 0.0.0.0</code>. Running on localhost make it available only from inside the container.

blocks|key|4400817|text|要获取指向Jupyter笔记本服务器的链接，请执行以下操作：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4400818|在您的docker+run命令之后，应该会自动生成一个超链接。它看起来像这样：http://localhost:8888/?token=f3a8354eb82c92f5a12399fe1835bf8f31275f917928c8d2+::+/home/jovyan/work|offset|length|style|CODE|4400819|如果您想在以后再次获得该链接，可以输入docker+exec+-it+<docker_container_name>+jupyter+notebook+list。|4400820|entityMap^0|0|3|A|13|2Q|0|J|1P|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@$D|N|E|O|F|G]|$D|P|E|Q|F|G]]|9|@]|A|$]]|$1|H|3|I|5|6|7|R|8|@$D|S|E|T|F|G]]|9|@]|A|$]]|$1|J|3|-4|5|6|7|U|8|@]|9|@]|A|$]]]|K|$]]

To get the link to your Jupyter notebook server:

After your <code>docker run</code> command, a hyperlink should be automatically generated. It looks something like this: <code>http://localhost:8888/?token=f3a8354eb82c92f5a12399fe1835bf8f31275f917928c8d2 :: /home/jovyan/work</code>

If you want to get the link again later down the line, you can type <code>docker exec -it &lt;docker_container_name&gt; jupyter notebook list</code>.

blocks|key|4400893|text|在容器中，您可以运行以下命令以使其在本地计算机上可用(使用docker计算机的ip地址)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4400894|jupyter笔记本--ip+0.0.0.0+--allow-root|4400895|根据容器的设置，您可能不需要提供--allow-root标志。|4400896|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

In the container you can run the following to make it available on your local machine (using your docker machine's ip address). 

jupyter notebook --ip 0.0.0.0 --allow-root

You may not need to provide the --allow-root flag depending on your container's setup.

blocks|key|4400924|text|主机：docker+run+-it+-p+8888:8888+image:version|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4400925|容器内部：jupyter+notebook+--ip+0.0.0.0+--no-browser+--allow-root|4400926|主机访问此url：localhost:8888/tree‌​|4400927|当您第一次登录时，终端上会显示一个使用令牌登录的链接。|4400928|entityMap^0|3|15|0|5|1J|0|9|L|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@$9|O|A|P|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|Q|8|@$9|R|A|S|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|T|8|@$9|U|A|V|B|C]]|D|@]|E|$]]|$1|J|3|K|5|6|7|W|8|@]|D|@]|E|$]]|$1|L|3|-4|5|6|7|X|8|@]|D|@]|E|$]]]|M|$]]

Host machine: <code>docker run -it -p 8888:8888 image:version</code> 

Inside the Container : <code>jupyter notebook --ip 0.0.0.0 --no-browser --allow-root</code> 

Host machine access this url : <code>localhost:8888/tree‌​</code> 

When you are logging in for the first time there will be a link displayed on the terminal to log on with a token.

blocks|key|4401210|text|您可以使用命令jupyter+notebook+--allow-root++--ip[of+your+container]或使用选项--ip0.0.0.0授予对所有ip的访问权限。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4401211|entityMap^0|7|1I|1U|B|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]|$9|K|A|L|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|M|8|@]|D|@]|E|$]]]|G|$]]

You can use the command <code>jupyter notebook --allow-root --ip[of your container]</code> or give access to all ip using option <code>--ip0.0.0.0</code>.

blocks|key|4400997|text|docker+run命令是为容器打开端口以允许从主机浏览器进行连接所必需的，使用-p将端口分配给docker容器，然后从docker+images中选择您的jupyter图像。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4400998|docker+run+-it+-p+8888:8888+image:version|code-block|syntax|javascript|4400999|在容器内部启动notebook，分配您打开的端口：|4401000|jupyter+notebook+--ip+0.0.0.0+--port+8888+--no-browser+--allow-root|4401001|通过http://localhost:8888上的桌面浏览器访问笔记本。笔记本将提示您输入在创建笔记本时生成的令牌。|4401002|entityMap|0|LINK|mutability|MUTABLE|url|http://localhost:8888/^0|0|A|1O|D|0|0|0|0|2|L|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@$9|Z|A|10|B|C]|$9|11|A|12|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|13|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|14|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|15|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|16|8|@]|D|@$9|17|A|18|1|19]]|E|$]]|$1|Q|3|-4|5|6|7|1A|8|@]|D|@]|E|$]]]|R|$S|$5|T|U|V|E|$W|X]]]]

The <code>docker run</code> command is mandatory to open a port for the container to allow the connection from a host browser, assigning the port to the docker container with -p, select your jupyter image from your <code>docker images</code>. 

<pre><code>docker run -it -p 8888:8888 image:version
</code></pre>

Inside the container launch the notebook assigning the port you opened:

<pre><code>jupyter notebook --ip 0.0.0.0 --port 8888 --no-browser --allow-root
</code></pre>

Access the notebook through your desktops browser on <a href="http://localhost:8888" rel="noreferrer">http://localhost:8888</a>
The notebook will prompt you for a token which was generated when you create the notebook.

blocks|key|4401049|text|作为构建自己的Docker镜像的替代方案，您也可以使用ML+Workspace镜像。ML+Workspace是一个开源的web+IDE，它将Jupyter、VS+Code、桌面GUI和许多其他工具和库组合到一个方便的Docker镜像中。部署单个工作空间实例非常简单，如下所示：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4401050|docker+run+-p+8080:8080+mltooling/ml-workspace:latest|code-block|syntax|javascript|4401051|所有工具都可以从同一端口访问，并集成到Jupyter+UI中。您可以找到更多文档here。|4401052|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/ml-tooling/ml-workspace|1^0|R|C|0|0|0|14|4|1|0^^$0|@$1|2|3|4|5|6|7|T|8|@]|9|@$A|U|B|V|1|W]]|C|$]]|$1|D|3|E|5|F|7|X|8|@]|9|@]|C|$G|H]]|$1|I|3|J|5|6|7|Y|8|@]|9|@$A|Z|B|10|1|11]]|C|$]]|$1|K|3|-4|5|6|7|12|8|@]|9|@]|C|$]]]|L|$M|$5|N|O|P|C|$Q|R]]|S|$5|N|O|P|C|$Q|R]]]]

As an alternative to building your own Docker image, you can also use the <a href="https://github.com/ml-tooling/ml-workspace" rel="nofollow noreferrer">ML Workspace</a> image. The ML Workspace is an open-source web IDE that combines Jupyter, VS Code, a Desktop GUI, and many other tools &amp; libraries into one convenient Docker image. Deploying a single workspace instance is as simple as:

<pre><code>docker run -p 8080:8080 mltooling/ml-workspace:latest
</code></pre>

All tools are accessible from the same port and integrated into the Jupyter UI. You can find further documentation <a href="https://github.com/ml-tooling/ml-workspace" rel="nofollow noreferrer">here</a>.

blocks|key|4401373|text|docker运行-i+-t+-p+8888:8888继续/anaconda3+/bin/bash+-c+"/opt/conda/bin/conda安装jupyter+-y+--安静&&+mkdir+/opt/+notebook+&&+/opt/conda/bin/jupyter+notebook--notebook-dir=/opt/notebook+--ip='*‘--port=8888+--no-browser+--allow-root“|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4401374|我必须将--allow-root添加到命令中，现在它正在运行|4401375|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

docker run -i -t -p 8888:8888 continuumio/anaconda3 /bin/bash -c "/opt/conda/bin/conda install jupyter -y --quiet &amp;&amp; mkdir /opt/notebooks &amp;&amp; /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root"

i had to add --allow-root to the command and now its running

I created a docker image with python libraries and Jupyter. 
I start the container with the option <code>-p 8888:8888</code>, to link ports between host and container. 
When I launch a Jupyter kernel inside the container, it is running on <code>localhost:8888</code> (and does not find a browser). I used the command <code>jupyter notebook</code>

But from my host, what is the IP address I have to use to work with Jupyter in host's browser ? 

With the command <code>ifconfig</code>, I find <code>eth0</code>, <code>docker</code>, <code>wlan0</code>, <code>lo</code> ...

Thanks !

Access Jupyter notebook running on Docker container

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我用python库和Jupyter创建了一个docker镜像。我使用选项-p 8888:8888启动容器，以链接主机和容器之间的端口。当我在容器中启动一个Jupyter内核时，它正在localhost:8888上运行(并且没有找到浏览器)。我使用命令jupyter notebook但是在我的主机上，我必须使用什么IP地...

问访问在Docker容器上运行的Jupyter笔记本
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