A REPL interface to communicate with Jupyter kernels in Emacs or CLI.

Table of Contents

• Installation
• Quickstart
  • Command Line Interface
  • Emacs Interface

Installation

inf-ipy is made up of two parts. Python part that handles communication with Jupyter and provides two REPL interfaces one specialized for use in command line and one specialized for in Emacs.

Machines that will run the kernels or connect to them only requires SSH and Jupyter to be installed. Tested on Linux / Windows.

Using Package Managers

Python

pip install inf-ipy

Emacs Using quelpa

(quelpa
 '(inf-ipy
   :fetcher github
   :repo "nakkaya/inf-ipy"
   :files ("src/emacs/*.el")))

Emacs from MELPA (Pending Approval)

M-x package-install RET inf-ipy RET

Manual

Clone this repository then install individual parts.

For python,

cd src/python
pip install .

For Emacs,

(load-file "src/emacs/inf-ipy.el")

Quickstart

Create a configuration file config.ini that describes how to login and launch a kernel on a machine.

[SERVER]
;; SSH IP
host = 10.9.0.150
;; SSH User
user = core
;; Use named kernel connection file instead of random file name
file = server.json

For a complete list of options use inf-ipy --help. All options can be supplied via the configuration file or command line switches.

To start a kernel and download the connection file.

inf-ipy --start

To stop the kernel.

inf-ipy --stop

To select a different kernel other than Python --kernel option can be used. To start a Matlab kernel use.

inf-ipy --start --kernel matlab_kernel.kernel.MatlabKernel

CLI

To interact with the kernel via command line.

inf-ipy --repl

Emacs

(require 'inf-ipy)

Once a kernel is started (using a configuration file) an Emacs REPL to that kernel can be created using M-x inf-ipy-repl.

Integration with org-babel can be enabled using,

;; Enable org-babel support for Python and Matlab
(inf-ipy-configure-kernel python)
(inf-ipy-configure-kernel matlab)

To interact with a python kernel you would create a new source block using,

#+BEGIN_SRC inf-ipy-python :results output
%matplotlib inline

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = plt.axes()

x = np.linspace(0, 10, 1000)
ax.plot(x, np.sin(x));
#+END_SRC