Develop Reference

Executing code on server while shutting down the computer

I have Python code that I want to run on a GPU server. Running it is time-consuming and sometimes, I get disconnected from the Internet or server and I have to re-run it. So, I need to let it run and shut down my computer. Is there any way?

You can use screen to maintain a session and achieve the goal that allows you to run the code on the server.
Refer to this: https://www.gnu.org/software/screen/
Some basic commands:
Create session named RunWork
screen -S RunWork
List all sessions:
screen -ls
Open a session
screen -r SessionID
...

If it is a windows server create a bat file.
Run the python script and the shutdown command. You will have to be an admin to shutdown the computer from a script.
bat file
c:\python27\python.exe c:\somescript.py %*
shutdown /s /f /t 0

If you are Linux-based OS then Tmux can help you.
Tmux is a terminal multiplexer. It lets you switch easily between several programs in one terminal, detach them (they keep running in the background) and reattach them to a different terminal.
https://github.com/tmux/tmux/wiki

cannot quit jupyter notebook server running

I am using Jupyter Notebook for a project. Since I ssh into a linux cluster at work I use
ssh -Y -L 8000:localhost:8888 user#host
Then I start the notebook with jupyter notebook --no-browser & so that I can continue using the terminal. Then on my local machine I open to localhost:8000 and go about my work.
My problem is that I forgot several times to close the server by foregrounding the process and killing it with Ctrl-C. Instead I just logged out of the ssh session. Now when I run jupyter notebook list I get
Currently running servers:
http://localhost:8934/ :: /export/home/jbalsells
http://localhost:8870/ :: /export/home/jbalsells
http://localhost:8892/ :: /export/home/jbalsells
http://localhost:8891/ :: /export/home/jbalsells
http://localhost:8890/ :: /export/home/jbalsells
http://localhost:8889/ :: /export/home/jbalsells
http://localhost:8888/ :: /export/home/jbalsells
I obviously do not want all of these servers running on my work's machine, but I do not know how to close them!
When I run ps I get nothing:
PID TTY TIME CMD
12678 pts/13 00:00:00 bash
22584 pts/13 00:00:00 ps
I have Jupyter 4.1.0 installed.

So I found a solution.
Since jupyter notebook list tells you which ports the notebook servers are running on I looked for the PIDs using netstat -tulpn I got the information from http://www.cyberciti.biz/faq/what-process-has-open-linux-port/
Active Internet connections (only servers)
Proto Recv-Q Send-Q Local Address Foreign Address State
PID/Program name
tcp 0 0 0.0.0.0:8649 0.0.0.0:* LISTEN
-
tcp 0 0 0.0.0.0:139 0.0.0.0:* LISTEN
-
tcp 0 0 0.0.0.0:33483 0.0.0.0:* LISTEN
-
tcp 0 0 0.0.0.0:5901 0.0.0.0:* LISTEN
39125/Xvnc
Without looking too hard I was able to find the ports I knew to look for from jupyter notebook list and the processes running them (you could use grep if it were too hard to find them). Then I killed them with
kill 8337 (or whatever number was associated).

Windows Systems commands on Command Prompt
Be careful to save all the changes made in your notebooks prior to kill the jupyter notebook server process.
i) find the port number used by jupyter notebook server
jupyter notebook list
ex.)
jupyter notebook list
Currently running servers:
http://127.0.0.1:8888/ :: D:\kimkk\Documents\JupyterNotebook
ii) find process ids that use the found port number of jupyter notebook
netstat -ano | find "found portnumber"
ex.)
netstat -ano | find "8888"
TCP 127.0.0.1:8888 0.0.0.0:0 LISTENING 24140
TCP 127.0.0.1:8888 127.0.0.1:55588 ESTABLISHED 24140
TCP 127.0.0.1:8888 127.0.0.1:55612 ESTABLISHED 24140
TCP 127.0.0.1:55588 127.0.0.1:8888 ESTABLISHED 6492
TCP 127.0.0.1:55612 127.0.0.1:8888 ESTABLISHED 6492
find rows with second column value equals to "8888". In above example first, second, and third rows are target rows. In those rows, you can find PID in the last column (ex. 24140).
iii) kill jupyter notebook process with found PID
taskkill /PID found_PID /F
ex.)
taskkill /PID 24140 /F
/F means forcely kill the process.
FYI, Jupyter notebook from version 5.1 supports stop command as follows:
jupyter notebook stop 8888
refer to https://github.com/jupyter/notebook/issues/1950

Use the following command to stop Jupyter notebook running on port 8888:
fuser -k 8888/tcp

This might help:
run jupyter notebook list to get the port number jupyter uses.
run lsof -n -i4TCP:[port-number] to get PID.
The PID is the second field in the output.
run kill -9 [PID] to kill this process.

I ran into the same issue and followed the solution posted above. Just wanted to clearify the solution a little bit.
netstat -tulpn
will list all the active connections.
tcp 0 0 0.0.0.0:8888 0.0.0.0:* LISTEN 19524/python
you will need the PID "19524" in this case. you can even use the following to get the PID of the port you are trying to shut down
fuser 8888/tcp
this will give you 19524 as well.
kill 19524
will shut down the port

Section 3.3 should be applicable to this.
http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/execute.html
When a notebook is opened, its “computational engine” (called the kernel) is automatically started. Closing the notebook browser tab, will not shut down the kernel, instead the kernel will keep running until is explicitly shut down.
To shut down a kernel, go to the associated notebook and click on menu File -> Close and Halt. Alternatively, the Notebook Dashboard has a tab named Running that shows all the running notebooks (i.e. kernels) and allows shutting them down (by clicking on a Shutdown button).

Here's a bash script that will kill ALL active Jupyter notebook servers at one go, based on the answers given by #Joalito and #Hongsoog:
#!/bin/bash
jupyter notebook list | {
while IFS= read -r line
do
port=`echo "$line" | grep -o -P '(?<=localhost:).*(?=/ :)'`
echo "killing jn in port $port"
if [ -z "$port" ]
then
netstat -tulpn | grep "$port" | grep -o -P '(?<=LISTEN ).*(?=/py)' | xargs kill -15
fi
done
}

On your notebook the welcoming page is named "Files" and you can see "Running" next to it. There is where you would want to shutdown and see the running notebooks

What worked for me was
jupyter notebook list, which in my case returned:
http://localhost:8889/?token=77d01d687da830b74eba946060660d :: /gpfs/blah/
http://localhost:8889/?token=1243162854ee3648e3154b26643794 :: /ifs/hello/world/
netstat -tulpn | grep "8888", which in my case returned:
tcp 7 0 127.0.0.1:8888 0.0.0.0:* LISTEN 17602/python3.9
And I found the PID in the last column: 17602.
kill -9 17602, which freed up the port.

python socket doesn't work after restart application

I have a python script server->client, and for some reasons i used py2exe to make an exe from py so i can use on machines without python installed.
And i have and update system:
I send command update to server and server start a bat file:
suprocess.Popen("C:/Server/server.bat", shell=False) #
and server.bat contains:
#echo off
taskkill /f /im "dServer.exe"
echo D | xcopy /s /y \\netpath\share\Server\c:\Server
start dServer.exe
exit
First time when i start dServer.exe it's working, i can send command from client to server and recieve answer. But after update and dServer.exe starts again, server will not work, i got socket.timeout error and can't send commands.
Does anybody know why it's not working second time?
p.s I have command : server.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
Thanks!

Problem was that socket server doesn't close so quickly and second server start to fast and can't because port it's used.
I modified dServer.py and now before i call server.bat i close the socket.

edX LMS port 8000 already in use (even after killing processes)

I got the following issue when I try to run my edX LMS (port 8000):
Error: That port is already in use
So in my vagrant account I found and did kill -9 on process which was using 8000. But as soon as I killed them, the process was automatically restarting and using port 8000 and I am unable to run LMS.

When that happens, I just do:
vagrant reload
(You will have to logout from SSH before by typing logout)
It is equivalent to:
vagrant halt
vagrant up

I've had times on OS/X with Vagrant where I've had to kill not only the vagrant process, but also virtualbox, when vagrant reload hasn't worked.
On your machine (not the guest VM):
ps -eaf | fgrep -i vagrant
ps -eaf | fgrep -i virtualbox
Then kill all those processes and "vagrant up."

vagrant halt is enough to kill all the processes related to the used port.

Connecting to a Windows IPython kernel from Linux

I have a Windows machine where I start an IPython kernel (to do some stuff not possible on another machine).
I have a Linux machine from which I would like to connect to the IPython kernel running on the Windows machine.
I can SSH from the Linux machine to the Windows machine (using this solution: https://superuser.com/a/172299).
I have tried following: https://github.com/ipython/ipython/wiki/Cookbook:-Connecting-to-a-remote-kernel-via-ssh. Both the automatic and the manual solution gives the following:
"ERROR: Kernel did not respond"
Using the same solution, I can connect from my Linux machine to an IPython kernel running on a Linux server. Any solution to get this to work with Linux to Windows?

You don’t need SSH to connect to a remote ipython kernel, regardless of whether it’s a ipython kernel running on Windows or Linux or Mac. What you do need is to have the Ip of the remote kernel visible to the terminal from which you are trying to connect from. Here are the steps:
Find out the ip address of the server (the machine on which the ipython kernel is running i.e. where you want the computation to happen) and client (the machine from which you are trying to connect to):
1.1. If you are on Windows, open up the command prompt and do a ipconfig to find out the ip addresses. If the Windows server has a direct Internet connection/lan connection, you should see a couple of ips like 192.168.57.1 and 10.2.3.64 and 127.0.0.1.
1.2. If you are on linux, open up a terminal and type ifconfig or ip addr show. You should again see a couple of ips like 192.168.57.1 and 10.2.3.64 and 127.0.0.1.
1.3. Test that atleast one of your server ip addresses is visible from the client: Ping your server from your client, using the command ping. ping will work on either Windows or Linux terminals. If you are running the windows/Linux as a VM or is behind a firewall, it is very much possible that your client or server is not visible from the other side. You don’t have to ping the ip address 127.0.0.1. This is a loop back address, and is only visible from the same machine where you got this ip address from. For example if you ping 127.0.0.1 from the Windows machine, it will ping the same Windows machine. If your client and server instances are running on the same machine, then its fine to use this address. However, if your client or server is running on a VM or a different machine altogher, then 127.0.0.1 wont work.
Start the remote kernel:
2.1. Once you have figured out which ip address on the server is visible from the client, start a kernel on the machine using ipython kernel. The ipython kernel will startup and show that `To connect another client to this kernel, use:
--existing kernel-1234.json
2.2. Locate the kernel-1234.json file on your server by importing (https://stackoverflow.com/a/35094772/4752883)
In [1]: from jupyter_client import find_connection_file
In [2]: find_connection_file()
Out[2]: 'C:\\Users\\me\\AppData\\Roaming\\jupyter\\runtime\\kernel-1234.json'
This will work either for Linux or Windows.
Start the remote client:
3.1. Once you locate the file, copy it over to your server machine using scp in linux or pscp or winscp in windows SCP w/ ssh: copying a local file from windows to a remote server using scp
3.2. Make sure that you are the same directory as the kernel-1234.json file.
3.3. Open up the kernel-1234.json file using vim or your favorite text editor. You will notice a line saying "ip": "127.0.0.1". Change 127.0.0.1 the ip address from your server that is visible from the client, that you found in step 1.3 and save the json file.
3.4. Start up the remote kernel using jupyter console –existing=kernel-1234.json, while located in the same drive where kernel-1234.json is located.
If you have followed the steps above, you should now be able to connect to the remote ipython kernel regardless of whether the ipython kernel is running on Windows/Linux/Mac.

I tried the manual way on https://github.com/ipython/ipython/wiki/Cookbook%3a-Connecting-to-a-remote-kernel-via-ssh once again and it worked. In detail:
windows-machine$ ipython kernel -f kernel-1234.json
linux-machine$ scp windows-machine:path/to/kernel-1234.json .
linux-machine$ cat kernel-1234.json
{
"stdin_port": 55534,
"ip": "127.0.0.1",
"control_port": 58391,
"hb_port": 60540,
"signature_scheme": "hmac-sha256",
"key": "fa461cf7-f078-4c22-909f-cfa7d2a30596",
"shell_port": 60159,
"transport": "tcp",
"iopub_port": 59207
}
linux-machine$ ssh -f -N -L 55534:127.0.0.1:55534
linux-machine$ ssh -f -N -L 58391:127.0.0.1:58391
linux-machine$ ssh -f -N -L 60540:127.0.0.1:60540
linux-machine$ ssh -f -N -L 60159:127.0.0.1:60159
linux-machine$ ssh -f -N -L 59207:127.0.0.1:59207
linux-machine$ ipython console --existing kernel-1234.json