remote_ikernel 0.3.1

Running IPython kernels through batch queues

Launch Jupyter kernels on remote systems so that they can be used with local noteboooks.

Kernels start through interactive jobs in batch queue systems (SGE, SLURM, PBS…) or through SSH connections. Once the kernel is started, SSH tunnels are created for the communication ports are so the notebook can talk to the kernel as if it was local.

Commands for managing the kernels are included. There are also options for managing kernels from different virtual environments or different python implementations.

Install with pip install remote_ikernel. Requires notebook (as part of Jupyter), version 4.0 or greater and pexpect. Passwordless ssh to the remote machines is also required.

Note

Version 0.3 of this package depends on the split Jupyter and IPython version 4 and later when installing with pip. If you are upgrading from an older version of IPython, Jupyter will probably migrate your existing kernels (to ~/.local/share/jupyter/kernels/), but not profiles. If you need to stick with IPython 3 series, use an older version of remote_ikernel or install without using pip/setuptools.

# Install the module ('python setup.py install' also works)

pip install remote_ikernel

# Set up the kernels you'd like to use

remote_ikernel manage

# Add a new kernel running through GrideEngine

remote_ikernel manage --add \
    --kernel_cmd="ipython kernel -f {connection_file}" \
    --name="Python 2.7" --cpus=2 --pe=smp --interface=sge

# Add an SSH connection to a remote machine running IJulia

remote_ikernel manage --add \
    --kernel_cmd="/home/me/julia-79599ada44/bin/julia -i -F /home/me/.julia/v0.3/IJulia/src/kernel.jl {connection_file}" \
    --name="IJulia 0.3.8" --interface=ssh \
    --host=[e-mail] --workdir='/home/me/Workdir' --language=julia

# Set up kernels for your local virtual environments that can be run
# from a single notebook server.

remote_ikernel manage --add \
    --kernel_cmd="/home/me/Virtualenvs/dev/bin/ipython kernel -f {connection_file}" \
    --name="Python 2 (venv:dev)" --interface=local

The kernel spec files will be installed so that the new kernel appears in the drop-down list in the notebook.

Warning

IJulia kernels don’t seem to close properly, so you may have julia processes lingering on your systems. To work around this edit the file ~/.julia/v0.3/IJulia/src/handlers.jl so that shutdown_request calls run(`kill $(getpid())`) instaed of exit().

Changes for v0.3

• Updated pip requirements to pull in the notebook package. Use an earlier version if you need to use IPython 3.

• Remote process is polled for output which will show up when --verbose if used as a kernel option.

Changes for v0.2

• Version 0.2.11 is the last version to support IPython notebook version 3. pip requirements enforce versions less than 4. Use a more recent version to ensure compatibility with the Jupyter split.

• Support for PBS/Torque through qsub -I.

• Tunnels are kept alive better, if something is not responding try waiting 20 seconds to see if a tunnel had dies. (Tunnels no longer depend on pyzmq, instead they are launched through pexpect and monitored until they die.)

• --remote-launch-args can be used to set qlogin parameters or similar.

• --remote-precmd allows execution of an extra command on the remote host before launching a kernel.

• Better compatibility with Python 3.

• Kernel output on terminals with --verbose option for debugging.

• Connect to a host with ssh, slurm, or local kernels.

• Changed prefix to rik_.

• kernel_cmd now requires the {connection_file} argument.

• remote_ikernel manage --show command to show existing kernels.

• Specify the working directory on the remote machine with --workdir.

• kernel-uuid.json is copied to the working director for systems where there is no access to the frontend filesystem.

• Added compatibility layer to get rid of Jupyter warnings.