- A self-study guide with Pluto -
This is a personal learning-diary when exploring Julia by exploiing SICP. I used Lisp and especially Scheme regularly from time to time. I loved Scheme for its elegance and minimalism. But for production purposes in various scientic projects I had to use other languages for pragmatic reasons, like Fortran, Prolog, R, Javascript, Bugs, Stan, WebPPL and even Python. But I was always looking for a language as elegant as Scheme but with a greater usability and usefulness. Several year ago David Barber gave advice to give Julia a try. In the end I stumbled across the fascinating probabilistic programming languages Gen and Turing, both embedded in Julia. That was the starting point to deal with Julia to have a solid fundament for modeling in Gen and Turing.
Here we present transpilations of SICP-Scheme-scripts into Julia as well as alternatives exploiting idiomatic JULIA constructs within a Pluto.jl-embedding. Pluto.jl offers reactive notebooks very suitable for educational purposes.
We use Pluto.jl as a learning environment for self-guided learning Julia. The original SICP is expected to be the accompanying study-guide. All SICP-Scheme-scripts are reconstructed in Julia in a stepwise manner. Furthermore idiomatic Julia scripts are added to demonstrate solutions made possible by advanced Julia features.
In the end it is guaranteed that the learner has acquired several competencies. S|he is competent in understanding CS-concepts, reading Scheme-scripts, and developing new scripts in Julia/Pluto.jl.
Learners expecting a gamified learning environment (https://en.wikipedia.org/wiki/Gamification_of_learning) will be disappointed. This is a rather academic (dry ;) ) learning experience. So your intrinsic motivation in studying Julia should be rather high.
The time investment needed is not trivial. Of course this depends on the preknowledge and the aspiration of the learner. We estimate that a newbee to programming needs 1-2 hours/day over a 12 month period (2 semesters), whereas an expert (in say Python) will need only a few weeks.
C.M.
P.S.: The electronic version of SICP can be found here (https://sarabander.github.io/sicp/html/Foreword.xhtml#Foreword) and here (https://mitp-content-server.mit.edu/books/content/sectbyfn/books_pres_0/6515/sicp.zip/index.html).