--- language: julia contributors: - ["Leah Hanson", "http://leahhanson.us"] filename: learnjulia.jl --- Julia is a new homoiconic functional language focused on technical computing. While having the full power of homoiconic macros, first-class functions, and low-level control, Julia is as easy to learn and use as Python. This is based on the current development version of Julia, as of June 29th, 2013. ```ruby # Single line comments start with a hash. #################################################### ## 1. Primitive Datatypes and Operators #################################################### # Everything in Julia is a expression. # You have numbers 3 #=> 3 (Int64) 3.2 #=> 3.2 (Float64) 2 + 1im #=> 2 + 1im (Complex{Int64}) 2//3 #=> 2//3 (Rational{Int64}) # Math is what you would expect 1 + 1 #=> 2 8 - 1 #=> 7 10 * 2 #=> 20 35 / 5 #=> 7.0 5 \ 35 #=> 7.0 5 / 2 #=> 2.5 div(5, 2) #=> 2 2 ^ 2 #=> 4 # power, not bitwise xor 12 % 10 #=> 2 # Enforce precedence with parentheses (1 + 3) * 2 #=> 8 # Bitwise Operators ~2 #=> -3 # bitwise not 3 & 5 #=> 1 # bitwise and 2 | 4 #=> 6 # bitwise or 2 $ 4 #=> 6 # bitwise xor 2 >>> 1 #=> 1 # logical shift right 2 >> 1 #=> 1 # arithmetic shift right 2 << 1 #=> 4 # logical/arithmetic shift left # You can use the bits function to see the binary representation of a number. bits(12345) #=> "0000000000000000000000000000000000000000000000000011000000111001" bits(12345.0) #=> "0100000011001000000111001000000000000000000000000000000000000000" # Boolean values are primitives true false # Boolean operators !true #=> false !false #=> true 1 == 1 #=> true 2 == 1 #=> false 1 != 1 #=> false 2 != 1 #=> true 1 < 10 #=> true 1 > 10 #=> false 2 <= 2 #=> true 2 >= 2 #=> true # Comparisons can be chained 1 < 2 < 3 #=> true 2 < 3 < 2 #=> false # Strings are created with " "This is a string." # Character literals written with ' 'a' # A string can be treated like a list of characters "This is a string"[1] #=> 'T' # Julia indexes from 1 # $ can be used for string interpolation: "2 + 2 = $(2 + 2)" #=> "2 + 2 = 4" # You can put any Julia expression inside the parenthesis. # Another way to format strings is the printf macro. @printf "%d is less than %f" 4.5 5.3 # 5 is less than 5.300000 #################################################### ## 2. Variables and Collections #################################################### # Printing is pretty easy println("I'm Julia. Nice to meet you!") # No need to declare variables before assigning to them. some_var = 5 #=> 5 some_var #=> 5 # Accessing a previously unassigned variable is an error try some_other_var #=> ERROR: some_other_var not defined catch e println(e) end # Variable name start with a letter. You can use uppercase letters, digits, # and exclamation points as well after the initial alphabetic character. SomeOtherVar123! = 6 #=> 6 # You can also use unicode characters ☃ = 8 #=> 8 # A note on naming conventions in Julia: # # * Names of variables are in lower case, with word separation indicated by # underscores ('\_'). # # * Names of Types begin with a capital letter and word separation is shown # with CamelCase instead of underscores. # # * Names of functions and macros are in lower case, without underscores. # # * Functions that modify their inputs have names that end in !. These # functions are sometimes called mutating functions or in-place functions. # Arrays store a sequence of values indexed by integers 1 through n: a = Int64[] #=> 0-element Int64 Array # 1-dimensional array literals can be written with comma-separated values. b = [4, 5, 6] #=> 3-element Int64 Array: [4, 5, 6] b[1] #=> 4 b[end] #=> 6 # 2-dimentional arrays use space-separated values and semicolon-separated rows. matrix = [1 2; 3 4] #=> 2x2 Int64 Array: [1 2; 3 4] # Add stuff to the end of a list with push! and append! push!(a,1) #=> [1] push!(a,2) #=> [1,2] push!(a,4) #=> [1,2,4] push!(a,3) #=> [1,2,4,3] append!(a,b) #=> [1,2,4,3,4,5,6] # Remove from the end with pop pop!(a) #=> 6 and b is now [4,5] # Let's put it back push!(b,6) # b is now [4,5,6] again. a[1] #=> 1 # remember that Julia indexes from 1, not 0! # end is a shorthand for the last index. It can be used in any # indexing expression a[end] #=> 6 # Function names that end in exclamations points indicate that they modify # their argument. arr = [5,4,6] #=> 3-element Int64 Array: [5,4,6] sort(arr) #=> [4,5,6]; arr is still [5,4,6] sort!(arr) #=> [4,5,6]; arr is now [4,5,6] # Looking out of bounds is a BoundsError try a[0] #=> ERROR: BoundsError() in getindex at array.jl:270 a[end+1] #=> ERROR: BoundsError() in getindex at array.jl:270 catch e println(e) end # Errors list the line and file they came from, even if it's in the standard # library. If you built Julia from source, you can look in the folder base # inside the julia folder to find these files. # You can initialize arrays from ranges a = [1:5] #=> 5-element Int64 Array: [1,2,3,4,5] # You can look at ranges with slice syntax. a[1:3] #=> [1, 2, 3] a[2:] #=> [2, 3, 4, 5] # Remove arbitrary elements from a list with splice! arr = [3,4,5] splice!(arr,2) #=> 4 ; arr is now [3,5] # Concatenate lists with append! b = [1,2,3] append!(a,b) # Now a is [1, 3, 4, 5, 1, 2, 3] # Check for existence in a list with contains contains(a,1) #=> true # Examine the length with length length(a) #=> 7 # Tuples are immutable. tup = (1, 2, 3) #=>(1,2,3) # an (Int64,Int64,Int64) tuple. tup[1] #=> 1 try: tup[0] = 3 #=> ERROR: no method setindex!((Int64,Int64,Int64),Int64,Int64) catch e println(e) end # Many list functions also work on tuples length(tup) #=> 3 tup[1:2] #=> (1,2) contains(tup,2) #=> true # You can unpack tuples into variables a, b, c = (1, 2, 3) #=> (1,2,3) # a is now 1, b is now 2 and c is now 3 # Tuples are created by default if you leave out the parentheses d, e, f = 4, 5, 6 #=> (4,5,6) # Now look how easy it is to swap two values e, d = d, e #=> (5,4) # d is now 5 and e is now 4 # Dictionaries store mappings empty_dict = Dict() #=> Dict{Any,Any}() # Here is a prefilled dictionary filled_dict = ["one"=> 1, "two"=> 2, "three"=> 3] # => Dict{ASCIIString,Int64} # Look up values with [] filled_dict["one"] #=> 1 # Get all keys keys(filled_dict) #=> KeyIterator{Dict{ASCIIString,Int64}}(["three"=>3,"one"=>1,"two"=>2]) # Note - dictionary keys are not sorted or in the order you inserted them. # Get all values values(filled_dict) #=> ValueIterator{Dict{ASCIIString,Int64}}(["three"=>3,"one"=>1,"two"=>2]) # Note - Same as above regarding key ordering. # Check for existence of keys in a dictionary with contains, haskey contains(filled_dict, ("one", 1)) #=> true contains(filled_dict, ("two", 3)) #=> false haskey(filled_dict, "one") #=> true haskey(filled_dict, 1) #=> false # Trying to look up a non-existing key will raise an error try filled_dict["four"] #=> ERROR: key not found: four in getindex at dict.jl:489 catch e println(e) end # Use get method to avoid the error # get(dictionary,key,default_value) get(filled_dict,"one",4) #=> 1 get(filled_dict,"four",4) #=> 4 # Sets store sets empty_set = Set() #=> Set{Any}() # Initialize a set with a bunch of values filled_set = Set(1,2,2,3,4) #=> Set{Int64}(1,2,3,4) # Add more items to a set add!(filled_set,5) #=> Set{Int64}(5,4,2,3,1) # There are functions for set intersection, union, and difference. other_set = Set(3, 4, 5, 6) #=> Set{Int64}(6,4,5,3) intersect(filled_set, other_set) #=> Set{Int64}(3,4,5) union(filled_set, other_set) #=> Set{Int64}(1,2,3,4,5,6) setdiff(Set(1,2,3,4),Set(2,3,5)) #=> Set{Int64}(1,4) # Check for existence in a set with contains contains(filled_set,2) #=> true contains(filled_set,10) #=> false #################################################### ## 3. Control Flow #################################################### # Let's make a variable some_var = 5 # Here is an if statement. Indentation is NOT meaningful in Julia. # prints "some var is smaller than 10" if some_var > 10 println("some_var is totally bigger than 10.") elseif some_var < 10 # This elseif clause is optional. println("some_var is smaller than 10.") else # The else clause is optional too. println("some_var is indeed 10.") end # For loops iterate over iterables, such as ranges, lists, sets, dicts, strings. for animal=["dog", "cat", "mouse"] # You can use $ to interpolate into strings println("$animal is a mammal") end # prints: # dog is a mammal # cat is a mammal # mouse is a mammal # You can use in instead of =, if you want. for animal in ["dog", "cat", "mouse"] println("$animal is a mammal") end for a in ["dog"=>"mammal","cat"=>"mammal","mouse"=>"mammal"] println("$(a[1]) is $(a[2])") end for (k,v) in ["dog"=>"mammal","cat"=>"mammal","mouse"=>"mammal"] println("$k is $v") end # While loops go until a condition is no longer met. # prints: # 0 # 1 # 2 # 3 x = 0 while x < 4 println(x) x += 1 # Shorthand for x = x + 1 end # Handle exceptions with a try/except block try error("help") catch e println("caught it $e") end #=> caught it ErrorException("help") #################################################### ## 4. Functions #################################################### # Use the keyword function to create new functions function add(x, y) println("x is $x and y is $y") # Functions implicitly return the value of their last statement x + y end add(5, 6) #=> 11 after printing out "x is 5 and y is 6" # You can define functions that take a variable number of # positional arguments function varargs(args...) return args end varargs(1,2,3) #=> (1,2,3) # The ... is called a splat. # It can also be used in a fuction call # to splat a list or tuple out to be the arguments Set([1,2,3]) #=> Set{Array{Int64,1}}([1,2,3]) # produces a Set of Arrays Set([1,2,3]...) #=> Set{Int64}(1,2,3) # this is equivalent to Set(1,2,3) x = (1,2,3) #=> (1,2,3) Set(x) #=> Set{(Int64,Int64,Int64)}((1,2,3)) # a Set of Tuples Set(x...) #=> Set{Int64}(2,3,1) # You can define functions with optional positional arguments function defaults(a,b,x=5,y=6) return "$a $b and $x $y" end defaults('h','g') #=> "h g and 5 6" defaults('h','g','j') #=> "h g and j 6" defaults('h','g','j','k') #=> "h g and j k" try defaults('h') #=> ERROR: no method defaults(Char,) defaults() #=> ERROR: no methods defaults() catch e println(e) end # You can define functions that take keyword arguments function keyword_args(;k1=4,name2="hello") # note the ; return ["k1"=>k1,"name2"=>name2] end keyword_args(name2="ness") #=> ["name2"=>"ness","k1"=>4] keyword_args(k1="mine") #=> ["k1"=>"mine","name2"=>"hello"] keyword_args() #=> ["name2"=>"hello","k2"=>4] # You can also do both at once function all_the_args(normal_arg, optional_positional_arg=2; keyword_arg="foo") println("normal arg: $normal_arg") println("optional arg: $optional_positional_arg") println("keyword arg: $keyword_arg") end all_the_args(1, 3, keyword_arg=4) # prints: # normal arg: 1 # optional arg: 3 # keyword arg: 4 # Julia has first class functions function create_adder(x) adder = function (y) return x + y end return adder end # or equivalently function create_adder(x) y -> x + y end # you can also name the internal function, if you want function create_adder(x) function adder(y) x + y end adder end add_10 = create_adder(10) add_10(3) #=> 13 # The first two inner functions above are anonymous functions (x -> x > 2)(3) #=> true # There are built-in higher order functions map(add_10, [1,2,3]) #=> [11, 12, 13] filter(x -> x > 5, [3, 4, 5, 6, 7]) #=> [6, 7] # We can use list comprehensions for nice maps and filters [add_10(i) for i=[1, 2, 3]] #=> [11, 12, 13] [add_10(i) for i in [1, 2, 3]] #=> [11, 12, 13] #################################################### ## 5. Types and Multiple-Dispatch #################################################### # Type definition type Tiger taillength::Float64 coatcolor # no type annotation is implicitly Any end # default constructor is the properties in order # so, Tiger(taillength,coatcolor) # Type instantiation tigger = Tiger(3.5,"orange") # the type doubles as the constructor function # Abtract Types abstract Cat # just a name and point in the type hierarchy # * types defined with the type keyword are concrete types; they can be # instantiated # # * types defined with the abstract keyword are abstract types; they can # have subtypes. # # * each type has one supertype; a supertype can have zero or more subtypes. type Lion <: Cat # Lion is a subtype of Cat mane_color roar::String end type Panther <: Cat # Panther is also a subtype of Cat eye_color Panther() = new("green") # Panthers will only have this constructor, and no default constructor. end # Multiple Dispatch # In Julia, all named functions are generic functions # This means that they are built up from many small methods # For example, let's make a function meow: function meow(cat::Lion) cat.roar # access properties using dot notation end function meow(cat::Panther) "grrr" end function meow(cat::Tiger) "rawwwr" end meow(tigger) #=> "rawwr" meow(Lion("brown","ROAAR")) #=> "ROAAR" meow(Panther()) #=> "grrr" function pet_cat(cat::Cat) println("The cat says $(meow(cat))") end try pet_cat(tigger) #=> ERROR: no method pet_cat(Tiger,) catch e println(e) end pet_cat(Lion(Panther(),"42")) #=> prints "The cat says 42" ``` ## Further Reading You can get a lot more detail from [The Julia Manual](http://docs.julialang.org/en/latest/manual/)