在端口8888上找不到Jupyter Notebook服务器（Windows 10）

Question

I'm trying to run a Docker container as a Jupyter Notebook on Windows 10. As shown in the screen grab, the notebook appears to be running on localhost:8888, but my browsers (Chrome and Edge) return a 'connection refused' error. I've disabled my firewall (temporarily), but that didn't help. Also, netstat does not list the port as being in use. Any idea what's going on?

Answer 1

Try the following:

docker run -p 8888:8888 -it simonwalkersamuel/bloch_tf:latest

-p 8888:8888 will map container port 8888 to host port 8888.

Answer 2

TLDR make sure you mapped the ports using -p 8888:8888 . If didn't work, try 192.168.99.100:8888 instead of localhost:8888 .

Situation: I had a slightly different problem: Although I mapped the ports using -p 8888:8888 , I still see the connection error when I try to reach localhost:8888 in all browsers. The firewall is checked and seems OK. It was very confusing because exactly same docker image works on my other Win 10 laptop at work.

Solution: I have two slightly different Win 10 on my laptops. The one that has connection difficulty runs a Win 10 Home whereas the other one has a Win 10 Professional . This means, the problematic laptop only runs Docker Tools not the conventional Docker CE. Therefore, it maps communicates with the OS using 192.168.99.100 IP not the usual 127.0.0.1 or localhost . So, instead of localhost:8888 just used 192.168.99.100:8888 and it worked.

Confession! I usually use my work laptop for running Jupyter on docker. Therefore, I did not pay enough attention to the welcome message of Docker Quickstart Terminal which clearly says docker is configured to use the default machine with IP 192.168.99.100 . Hopefully, this post helps other too busy (aka careless!) people like me!

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Since both laptops have very similar apps installed, I doubt anything rather than the Docker app itself causes the difference in IP addresses.

Answer 3

Try the following commands:

run these two command
pip install --upgrade pip
pip install --upgrade jupyter