what is julia

what is julia

June 12, 2020
4 minutes read time

What is Julia?
Julia is a high-level dynamic programming language for numerical computing. It is free and open-source: under the MIT license. Although Julia is still in its youth (the current release is v1.2), Julia provides a lot of support for mathematical analysis and data science.

How hard is Julia to learn?
Julia is a fairly complex language but has some very simple behaviors which are easy to pick up. It is mainly used for data science and mathematical analysis, so those complexities come with it. You must understand some mathematical principles to use the language well. Julia uses certain expressions differently from other languages as well making it a bit harder to pick up; however, it makes sense. For example, string concatenation is done with *, and not +. Julia is heavily documented and low-level, so learning the standard syntax is easy to do by following the tutorial along with other resources.

What's so great about Julia?

  • Multiple dispatch: providing ability to define function behavior across many combinations of argument types
  • Dynamic type system: types for documentation, optimization, and dispatch
  • Good performance, approaching that of statically-compiled languages like C
  • Built-in package manager
  • Lisp-like macros and other meta-programming facilities
  • Call Python functions: use the PyCall package
  • Call C functions directly: no wrappers or special APIs
  • Powerful shell-like capabilities for managing other processes
  • Designed for parallelism and distributed computation
  • Coroutines: lightweight "green" threading
  • User-defined types are just as fast and compact as built-ins
  • Automatic generation of efficient, specialized code for different argument types
  • Elegant and extensible conversions and promotions for numeric and other types
  • Efficient support for Unicode, including but not limited to UTF-8

What platforms can Julia run on?
Julia can run on most popular platforms such as MacOSX, most Linux builds, Windows, and others. This is due to it compiling to a native binary. However, it does not have broad support for front-end development, but there is a library for Qt bindings.

The Julia download comes with a CLI environment. With the CLI you can try out Julia functions and expressions in the command line. (Binary languages rarely have a CLI, so this is pretty cool)

Code Examples:
Hello world:

println("Hello world!")


fb(x) = "Fizz" ^ (x % 3 == 0) * "Buzz" ^ (x % 5 == 0) * dec(x) ^ (x % 3 != 0 && x % 5 != 0)
println.(map(fb, 1:100))

This is just a small list of collection tools Julia has-

sum(1:100) # sum of 1-100
filter(isOdd, 1:10) # 1,3,5,7,9
intersect(1:10, 5:15) # 5,6,7,8,9,10
mean([1, 3, 5, 7]) # 4
middle([1, 3, 5]) # 3

Syntax and Operation Features:

Matrices in Julia are easy and fun!

matrix = [1 2 3; 4 5 6] #you must have a space between elements, and a semicolon between the rows
Creates a 2x3 matrix that looks like this:
1 2 3
4 5 6

Useful matrix operations:
hcat()- horizontal concatenation, it stacks 2 or more matrices horizontally.

matrix = [1 2 3; 4 5 6]
hcat(matrix, [5;5]) #remember our matrix is 2x3
#= so now this is a 2x4 matrix.
2 -4 -3 5
4 -2  1 5
You'll get an error if the matrices don't have the same number of rows. =#

vcat()- vertical concatenation, this operation stacks 2 or more matrices on top of each other.

matrix = [1 2 3; 4 5 6] #2x3 matrix
vcat(matrix, [0, 0, 0])
#= 3x3 matrix
1 2 3
4 5 6
0 0 0
Cool, right? But you'll get an error if the two matrices don't have the same number of columns. =#

A basic if statement:

if 5>=4
    print("Hello world")

The simplest if statements in Julia are: if false end, and if true end. Julia isn't whitespace sensitive, so sometimes the meaning isn't changed if you write stuff on one line.

While loops are pretty simple in Julia as well:

while false
    print("There's nothing here.")

Ranges- There is something in Julia called a range. Ranges are written in the form start:end- by default, the range increments by 1. Both the start and the end of the range are inclusive (for example, 1:5 is from 1 to 5 inclusively. To explain it in interval notation, it's [1,5].)

for x=1:5

There is a more complex form of range, written as start:step:end. The end value of the range does not have to be included. It is only included if incrementing by step lands on it- for example,

for x=0:4:12 #12 is included because 4 is a multiple of 12
    println(x) #prints 0, 4, 8, 12


for x=0:4:11
    println(x) #only prints 0, 4, 8, for obvious reasons

Julia documentation:

Try it out online!, and

More places to learn Julia: (large collection of resources for learning Julia, from Julia)

Data Science in Julia: (an intro to Julia for data science) (a walkthrough that takes you through all of the steps!)