/jupyternim

A Jupyter kernel for nim

Primary LanguageNimMIT LicenseMIT

logo.svg Jupyter Nim

This is a beta jupyter kernel for nim written in nim.
Works with notebook, lab, nteract, should even work in vscode-python.
If you use nteract or vscode-python, there are still some problems, please report them.
For jupyter lab, you can also install the companion extension by jupyter labextension install jupyternim-labextension
that provides syntax highlighting.

Look at example-notebook for some examples,
and at example-display for examples of displaying latex, md, etc.

NOTE: running a notebook with this creates a directory ~/.jupyternim in which it stores blocks of code, pngs, compiled outputs, etc. Compilation output should be automatically cleaned up starting from version 0.6.0.

NOTE2: nteract support is very wip, also nteract doesn't add a cellId to notebook cells so changing types is buggy, I'll work on it and maybe also provide a patch for nteract, but it's low priority, help appreciated.

Installation

TL,DR:

nimble install jupyternim -y

Done!

jupyternim -v has some details about how it was compiled.

Prereqs

  • a working nim installation ( download )
  • a zeromq installation. Currently tested only with ZeroMQ 4.2. It must be in PATH or the kernel won't run.
    • you may already have this installed, it will be checked when you install jupyternim to see if you need to install it yourself
  • some kind of jupyter environment, some examples:
    • jupyter ( I recomend miniconda3 and adding jupyter with conda install jupyter )
    • nteract (get it here)
    • vscode+vscode-python extension ( poor naming, but vscode-python also provides jupyter support )

Long version:

The kernel should be automatically compiled and registered by doing nimble install jupyternim ( or nimble install https://github.com/stisa/jupyternim if it's not in nimble yet).

Alternatively, try the following:

  • clone this repo: git clone https://github.com/stisa/jupyternim
  • then go into the cloned dir cd jupyternim
  • register to nimble with nimble install
  • compile with nimble dev, this will give you a debug version
  • run jupyternimto register the kernel
  • run jupyter notebook

Note that ZeroMQ is dinamically linked, so it needs to be installed and added to path

HotCodeReloading

To enable the very experimental hotcodereloading support, you'll need to recompile jupyternim with -d:useHcr and then overwrite the one in ~/.nimble/pkgs/jupyternim-<version> with it.
The hotcodereloading mostly works, but there are various bugs that prevent its use. For examples, printing a float crashes it.

Editing

TAB : completion request, for example p<TAB -> a pop up with possible completions
completion

TODO:

  • shift+TAB : inspection request, for example echo<shift+TAB> -> a pop with a description of echo
  • support the debugger protocol, support variable value inspection

Magics:

passing flags

#>flags < --some > < --d:flag > Pass flags to nim compiler, default is --verbosity:0 -d:release.
Passing new flags overwrites all other previous flags, even default ones. Example:

#>flags -d:test

echo "hi"
when defined test:
  echo "test defined"
else:
  echo "test not defined"

Outputs:

hi
test defined

TODO: provide a way to override default compilation output file

Delete old temp files

#>clear all

Displaying data

To send back data to display, you can use the module jupyternimpkg/display, example:

import nimPNG, jupyternimpkg/display

let file = r"..\\src\\jupyternimspec\\logo-64x64.png"
show dkPngFile, [64, 64]: # [width, height]
    file

If your file type is not supported by the display module yet, you need to implement the proc yourself. Just write to stdout a string containing a json object defined as

{   //<data> is base64 encoded for binary formats, eg png
    "data": {"<mimetype>": <data>}, 
    "metadata": {"<mimetype>": {<mimespecific>}},
    "transient": {}
}

enclosed in #<jndd># and #<outjndd># markers. For example, to display a PNG image, simply:

import json, base64
var 
  img = readFile(path).encode # encode the png file with base64
  w = 320 # displayed width
  h = 240 # displayed height
var content: JsonNode = %*{
    "data": {"image/png": img }, 
    "metadata": %*{"image/png": {"width": w, "height":h}},
    "transient": %*{}
  }

echo "#<jndd>#" & $content $ "#<outjndd>#"

Consider sending a pr for the display module if you end up having to do this.

TODO

  • Finish implementing messaging ( completion, introspection, history, update_display_data... )
  • Connect to nimsuggest via socket, parse its output for introspection requests
  • Documentation lookup magic?
    • eg. put docs in a subfolder, then #>doc sequtils opens a browser to the correct .html page ( possibly local )
  • improve hotcodereloading (probably needs work on the compiler side)
  • convince jupyter notebook maintainers to provide cellId, so I can stop patching the javascript
  • find a better way to fake a repl than re running prior code and discarding output (we have HCR! Buggy though)
  • use JNsession as name for temp files (allows multiple open kernels)
  • a better way to handle display_data than string delimiters

General structure

jupyternim

Handles init, start, stop of the various loops, as well as initial installation of the kernelspec.

jupyternimpkg/messages

Handles message specifications exposing low level procs to decode, encode messages

jupyternimpkg/sockets

Defines sockets types, how they are created, how their loops work, how they send and receive messages

jupyternimpkg/display

Handle preparing and sending back data to display

jupyternimspec

Logos for jupyter, a kernel.js file to load syntax highlight and patch jupyter notebook to send a cellId.

Internal Notes

Messages must be multipart
signature-must-be-lowercase

http://nim-lang.org/docs/tinyc.html

Jupyter Kernel Docs
IHaskell
Messaging Docs
Async logger in nim