Julia — Pluto.jl notebooks

Experimenting with Julia and Pluto notebooks.

Julia

The Julia programming language aims to create an unprecedented combination of ease-of-use, power, and efficiency in a single language. Julia is an open source project with over 1,000 contributors. In addition to the above, some advantages of Julia over comparable systems include:

  • Free and open source (MIT licensed)
  • User-defined types are as fast and compact as built-ins
  • No need to vectorize code for performance; devectorized code is fast
  • Designed for parallelism and distributed computation
  • Lightweight "green" threading (coroutines)
  • Unobtrusive yet powerful type system
  • Elegant and extensible conversions and promotions for numeric and other types
  • Efficient support for Unicode, including but not limited to UTF-8
  • Call C functions directly (no wrappers or special APIs needed)
  • Powerful shell-like capabilities for managing other processes
  • Lisp-like macros and other metaprogramming facilities

Installing Juliajuliaup

Pluto

Pluto — simple reactive notebooks for Julia. Writing a notebook is not just about writing the final document — Pluto empowers the experiments and discoveries that are essential to getting there.

Explore models and share results in a notebook that is reactive - when changing a function or variable, Pluto automatically updates all affected - cells; lightweight - Pluto is written in pure Julia and is easy to install; simple - no hidden workspace state; friendly UI.

Install Pluto on your own computer

Example

Based on the Reddit post 45° really does max range — example Jupyter notebook using JuliaKinematics Fundamentals with Julia.

You can use a Julia REPL to start Pluto, as follows:

1# Once to install Pluto
2import Pkg; Pkg.add("Pluto")
3
4# To start Pluto server and browser session.
5import Pluto; Pluto.run()

Open the downloaded Julia kinematics_fundamentals.jl file in the web browser session.

Screendump

kinematics_fundamentals