Awesome

Clojure polyglot clj-template

Quickstart - Get a working clojure repl supporting Python, R and Julia in 5 lines

Only requirements is clojure and docker installed.

1. Create Clojure polyglot project from template

clojure -Sdeps '{:deps {com.github.seancorfield/clj-new {:mvn/version "1.2.362"}}}' -M -m clj-new.create clj-py-r-template me/my-app

2.Build and run Docker image, which starts a headless repl on port 12345 in a docker container

This assumes a Linux OS and bash as shell. It might be slightly different on other platforms or shell.

cd my-app
docker build -t my-app  .
docker run -it -p  12345:12345 my-app

(in most situations you want to mount some host drives and make the user id of 'user' match your user id, so the invocations becomes (for Linux): )

docker build -t my-app --build-arg USER_ID=$(id -u) --build-arg GROUP_ID=$(id -g) .
docker run -it --rm -v $HOME/.m2:/home/user/.m2 -v "$(pwd):/workdir" -p  12345:12345 -w /workdir my-app

3. In other shell: Connect normal repl to it

clj -Sdeps '{:deps {cider/cider-nrepl {:mvn/version "0.25.2"} }}' -m nrepl.cmdline  --middleware "[cider.nrepl/cider-middleware]" -c -p 12345

😀 Have fun with some interop code: 😀

;; go from clj -> python -> clj -> R
(require '[libpython-clj2.require :refer [require-python]]
         '[libpython-clj2.python :as py]
         '[clojisr.v1.r :as r :refer [r require-r]])

(require-python '[numpy :as np])
(require-r '[base :as base-r])

(def r-matrix
 (-> (np/array [[1 2 3 4] [5 6 7 8] [9 10 11 12]])
     (py/->jvm)
     (r/clj->java->r)
     (base-r/simplify2array)
     (base-r/t)))

(println
 (base-r/dim r-matrix))

For non Linux users:

The docker run commands above assume a Linux OS and bash as shell The same is true for the Dockerfile produced by this template. Line 15-19 of the Dockerfile https://github.com/behrica/clj-py-r-template/blob/2f1ec12690c09917c4c7608d6f625e8032d0d294/src/clj/new/clj_py_r_template/Dockerfile#L15 and the docker run id settings play together and this works as-is only on Linux.

Line 15-19 of the Dockerfile and the -build-arg USER_ID=$(id -u) --build-arg GROUP_ID=$(id -g) are only needed if volume is mounted as in the example. Without these, any file written to the shared volume by the container gets wrong permissions, which is inconvenient.

Motivation

This template is the easiest way to use R, python and Julia from Clojure.

In the world of Java / Clojure usage of containers is not that common, because on the JVM platform using Docker instead of a JVM dependency manger (maven, lein, gradle ...) is not really required.

This situation changes, the moment we add R / python or Julia into our stack, because both might have operating system dependencies in their packages.

Then containers can be very helpfull to get started quickly and work in a reproducible manner.

This template contains a Dockerfile / singularity definition file which has Clojure and all dependencies for ClojisR, libpython-clj, julia-clj and libapl-clj plus a deps.edn file containing working versions of ClojisR,libpython-clj and Julia-clj.

Clojure and Docker (or other container technology)

Containers can be used in Clojure Devlopment for several purposes:

1. Create a (production) runtime environment for a Clojure application
2. Create a (polyglot) development environment for Clojure
   • Flavor a: Run only a nrepl inside container
   • Flavor b: Run all (nrepl, editor, git ,...) inside container

This project is about 2a). A potential solution for 2b) can be container/ docker based coding platforms such as VSCode, Gitpod, Codespaces or extensions of the container spec files here and custom addition of the development tools.

Usage

Clojure projects including libpython-clj, ClojisR and Julia-clj can now be created quickly in 2 ways from the latest stable template:

• without clj-new installed in user deps.edn

clj -Sdeps '{:deps {com.github.seancorfield/clj-new {:mvn/version "1.2.362"}}}' \
  -m clj-new.create clj-py-r-template appcompany.funapp

• with clj-new installed in user deps.edn (recommended)

clj  -X:new :template clj-py-r-template  :name appcompany.funapp

• with clj-new installed as Clojure Tool

clj -Tclj-new create :template clj-py-r-template :name appcompany.funapp

Specific versions of this template can be used by adding something like "-V 1.0.2" to the upper commands

The templates provided config files for three different ways to run the container:

1. Docker (typically on local machine)
2. Singularity (typically on local machine)
3. Gitpod (one way to run Docker cntainers in cloud)

Run polyglot nrepl via Docker

The template creates a Dockerfile in the project folder. The docker image can be build with

cd appcompany.funapp
docker build -t funapp --build-arg USER_ID=$(id -u) --build-arg GROUP_ID=$(id -g) .

The Dockerfile assumes that the local project directory gets mounted into a folder in the container and that it becomes the working directory. The docker image runs a nRepl on port 12345 which can be connected to by any other nRepl compatible client (including emacs+Cider)

A typical command line for running the nRepl server in a docker container is then this:

docker run -it --rm -v "$(pwd):/code" -p 12345:12345 funapp

The template creates as well 2 bash scripts with some defaults, to:

• build the docker image from the Dockerfile
• run a repl inside Docker container

Please have a look and adapt to you needs.

Run polyglot nrepl via Singularity

This 2 lines

singularity build /tmp/my-app.sif my-project.def
singularity run /tmp/my-app.sif

build first a Singularity image containing Clojure, python, R, Julia and APL. Then the image is run, which starts a nrepl on port 12345.

To get this working the working directory needs:

• to have a deps.edn with all needed Clojure deps (as created by this template)
• be writable by singularity

How to make this sure, is installation / project dependent and can be controlled by the options to singularity run

Singularity vs Docker

Be aware that the two differ fundamentaly regarding their default settings of host / container isolation. In "our use case" here the defaults of Singularity are normaly fine, while we need to tell Docker to share volumes and ports explicitely.

Use Gitpod

The template creates as well the 2 gitpod configuration files. .gitpod.yml and .gitpod.Dockerfile. Launching a workspace pointing to a github repo with them, configures Gitpod to use the Dockerfile in .gitpod.Dockerfile. So the Gitpod workspace will have Clojure, python, R, Julia and APL setup correctly and the Clojure polyglot libraries will work out-of-the-box.

The workspace launch will start the repl automatically an we can use VSCode in browser to connect to it.

Advanced: Gitpod can be as well configured and used to expose the nrepl connection and ssh over the Internet. This allows to connect from local machine to a Gitpod workspace (nrepl + ssh filesystem) with for example Emacs (cider + tramp) This requires to use gitpod local-companion

Using ClojisR,libpython-clj,julia-clj and libapl-clj in repl

If a local repl was started as described before, Emacs (or any other nRepl client) can be connected to localhost:12345.

Example to use clj as nRepl client:

clj -Sdeps '{:deps {cider/cider-nrepl {:mvn/version "0.27.2"} }}' -m nrepl.cmdline  --middleware "[cider.nrepl/cider-middleware]" -c -p 12345

In this connected repl clojisr, libpython-clj , julia-clj and libapl-clj work out of the box:

(require '[libpython-clj2.require :refer [require-python]])
(require-python '[os :as os])
(os/getcwd)

(require '[clojisr.v1.r :refer [r]])
(r "1+1")
        
(require '[libjulia-clj.julia :as julia])
(julia/initialize!)
(def ones-fn (julia/jl "Base.ones"))
(ones-fn 3 4)

(require '[libapl-clj.apl :as apl])
(apl/+ [1 2 3] [4 5 6])

Customizing the container image

Add some libraries

The template itself should not contain instructions to install any Python, R, Julia, APL libraries but only the base tool as such. For Clojure a deps.edn is provided with all polyglot libraries and "some data science libraries from Scicloj". This should be conidered a template, to be changed.

As in the container images one single R version and one single python version is installed, libraries can be simply added by adding a few lines to the image configuration file (Dockerfile / my-project.def).

In case native dependencies are required, they can be added via "apt-get install"

The following would add a native library, a python library and a R package.

Example how to add to Dockerfile

RUN apt-get install libssl-dev

RUN pip3 install pandas

RUN Rscript -e "install.packages('dplyr')"

Example to add to Singularity .def file:

%post
apt-get install libssl-dev
pip3 install pandas
Rscript -e "install.packages('dplyr')"

The same can be done for additional Julia or APL libraries.

Change versions of Python, Julia, R, Apl

The installtion of those is done in a base image. The Dockerfile of the base image is here: https://github.com/behrica/clj-py-r-template/blob/master/docker-base/Dockerfile

So customistaion of those could be done by copy/paste of the relevant parts from this.

The latest version of clj-py-r-template itself should always install the latest released version of:

• Java
• Clojure
• Python
• Julia
• APL

The update frequency of clj-py-r-template is nevertheless independent from those and will be done as needed. Requests for updates can be done via submitting issues here.

Changing Clojure dependencies

Clojure dependencies are currently not specified in the image configuration file, but can be added as usual to the deps.edn file.

Current versions

The versions of this template contains the following versions of dependencies in either image configuration file or deps.end

1.0.2

Docker base image: rocker/r-ver:4.0.0

1.0.3

Docker base image: rocker/r-ver:4.0.0

1.0.5

Docker base image: rocker/r-ver:4.0.2

1.1.0

Docker base image: rocker/r-ver:4.0.3

1.1.1

Docker base image: rocker/r-ver:4.0.3

1.1.2

1.2.0

1.2.0

1.3.0

1.4.0

1.5.0

Added scripts for Docker

1.5.1

1.5.2

1.6.0

Only changes to the Dockerfiles Library versions state the same as in 1.5.2

1.7.0