--- language: Julia contributors: - ["Leah Hanson", "http://leahhanson.us"] - ["Pranit Bauva", "https://github.com/pranitbauva1997"] - ["Daniel YC Lin", "https://github.com/dlintw"] 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 Julia 1.0.0 ```julia # Single line comments start with a hash (pound) symbol. #= Multiline comments can be written by putting '#=' before the text and '=#' after the text. They can also be nested. =# #################################################### ## 1. Primitive Datatypes and Operators #################################################### # Everything in Julia is an expression. # There are several basic types of numbers. typeof(3) # => Int64 typeof(3.2) # => Float64 typeof(2 + 1im) # => Complex{Int64} typeof(2 // 3) # => Rational{Int64} # All of the normal infix operators are available. 1 + 1 # => 2 8 - 1 # => 7 10 * 2 # => 20 35 / 5 # => 7.0 10 / 2 # => 5.0 # dividing integers always results in a Float64 div(5, 2) # => 2 # for a truncated result, use div 5 \ 35 # => 7.0 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 xor(2, 4) # => 6 # bitwise xor 2 >>> 1 # => 1 # logical shift right 2 >> 1 # => 1 # arithmetic shift right 2 << 1 # => 4 # logical/arithmetic shift left # Use the bitstring function to see the binary representation of a number. bitstring(12345) # => "0000000000000000000000000000000000000000000000000011000000111001" bitstring(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 are written with ' 'a' # Strings are UTF8 encoded. Only if they contain only ASCII characters can # they be safely indexed. ascii("This is a string")[1] # => 'T' # Julia indexes from 1 # Otherwise, iterating over strings is recommended (map, for loops, etc). # $ can be used for string interpolation: "2 + 2 = $(2 + 2)" # => "2 + 2 = 4" # You can put any Julia expression inside the parentheses. # Another way to format strings is the printf macro from the stdlib Printf. using Printf @printf "%d is less than %f\n" 4.5 5.3 # => 5 is less than 5.300000 # Printing is easy println("I'm Julia. Nice to meet you!") # String can be compared lexicographically "good" > "bye" # => true "good" == "good" # => true "1 + 2 = 3" == "1 + 2 = $(1 + 2)" # => true #################################################### ## 2. Variables and Collections #################################################### # You don't 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: UndefVarError: some_other_var not defined catch e println(e) end # Variable names start with a letter or underscore. # After that, you can use letters, digits, underscores, and exclamation points. SomeOtherVar123! = 6 # => 6 # You can also use certain unicode characters ☃ = 8 # => 8 # These are especially handy for mathematical notation 2 * π # => 6.283185307179586 # A note on naming conventions in Julia: # # * Word separation can be indicated by underscores ('_'), but use of # underscores is discouraged unless the name would be hard to read # otherwise. # # * 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 = [4; 5; 6] # => 3-element Int64 Array: [4, 5, 6] b[1] # => 4 b[end] # => 6 # 2-dimensional arrays use space-separated values and semicolon-separated rows. matrix = [1 2; 3 4] # => 2x2 Int64 Array: [1 2; 3 4] # Arrays of a particular type b = Int8[4, 5, 6] # => 3-element Int8 Array: [4, 5, 6] # 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!(b) # => 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 # we also have popfirst! and pushfirst! popfirst!(a) # => 1 and a is now [2,4,3,4,5,6] pushfirst!(a, 7) # => [7,2,4,3,4,5,6] # 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] # => BoundsError: attempt to access 7-element Array{Int64,1} at index [0] a[end + 1] # => BoundsError: attempt to access 7-element Array{Int64,1} at index [8] catch e println(e) end # Errors list the line and file they came from, even if it's in the standard # library. You can look in the folder share/julia 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:end] # => [2, 3, 4, 5] # Remove elements from an array by index 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, 2, 3, 4, 5, 1, 2, 3] # Check for existence in a list with in in(1, a) # => true # Examine the length with length length(a) # => 8 # Tuples are immutable. tup = (1, 2, 3) # => (1,2,3) # an (Int64,Int64,Int64) tuple. tup[1] # => 1 try tup[1] = 3 # => ERROR: no method setindex!((Int64,Int64,Int64),Int64,Int64) catch e println(e) end # Many array functions also work on tuples length(tup) # => 3 tup[1:2] # => (1,2) in(2, tup) # => 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 even if you leave out the parentheses d, e, f = 4, 5, 6 # => (4,5,6) # A 1-element tuple is distinct from the value it contains (1,) == 1 # => false (1) == 1 # => true # 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}() # You can create a dictionary using a literal filled_dict = Dict("one" => 1, "two" => 2, "three" => 3) # => Dict{String,Int64} # Look up values with [] filled_dict["one"] # => 1 # Get all keys keys(filled_dict) # => Base.KeySet for a Dict{String,Int64} with 3 entries. Keys: # "two", "one", "three" # Note - dictionary keys are not sorted or in the order you inserted them. # Get all values values(filled_dict) # => Base.ValueIterator{Dict{String,Int64}} with 3 entries. Values: 2, 1, 3 # Note - Same as above regarding key ordering. # Check for existence of keys in a dictionary with in, haskey in(("one" => 1), filled_dict) # => true in(("two" => 3), filled_dict) # => false haskey(filled_dict, "one") # => true haskey(filled_dict, 1) # => false # Trying to look up a non-existent key will raise an error try filled_dict["four"] # => KeyError: key "four" not found catch e println(e) end # Use the get method to avoid that error by providing a default value # get(dictionary, key, default_value) get(filled_dict, "one", 4) # => 1 get(filled_dict, "four", 4) # => 4 # Use Sets to represent collections of unordered, unique values empty_set = Set() # => Set{Any}() # Initialize a set with values filled_set = Set([1, 2, 2, 3, 4]) # => Set([4, 2, 3, 1]) # Add more values to a set push!(filled_set, 5) # => Set([4, 2, 3, 5, 1]) # Check if the values are in the set in(2, filled_set) # => true in(10, filled_set) # => false # There are functions for set intersection, union, and difference. other_set = Set([3, 4, 5, 6]) # => Set([4, 3, 5, 6]) intersect(filled_set, other_set) # => Set([4, 3, 5]) union(filled_set, other_set) # => Set([4, 2, 3, 5, 6, 1]) setdiff(Set([1,2,3,4]), Set([2,3,5])) # => Set([4, 1]) #################################################### ## 3. Control Flow #################################################### # Let's make a variable some_var = 5 # Here is an if statement. Indentation is not meaningful in Julia. 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 # => prints "some var is smaller than 10" # For loops iterate over iterables. # Iterable types include Range, Array, Set, Dict, and AbstractString. for animal = ["dog", "cat", "mouse"] println("$animal is a mammal") # You can use $ to interpolate variables or expression into strings end # prints: # dog is a mammal # cat is a mammal # mouse is a mammal # You can use 'in' instead of '='. for animal in ["dog", "cat", "mouse"] println("$animal is a mammal") end # prints: # dog is a mammal # cat is a mammal # mouse is a mammal for pair in Dict("dog" => "mammal", "cat" => "mammal", "mouse" => "mammal") from, to = pair println("$from is a $to") end # prints: # dog is a mammal # cat is a mammal # mouse is a mammal for (k, v) in Dict("dog" => "mammal", "cat" => "mammal", "mouse" => "mammal") println("$k is a $v") end # prints: # dog is a mammal # cat is a mammal # mouse is a mammal # While loops loop while a condition is true let x = 0 while x < 4 println(x) x += 1 # Shorthand for x = x + 1 end end # prints: # 0 # 1 # 2 # 3 # Handle exceptions with a try/catch block try error("help") catch e println("caught it $e") end # => caught it ErrorException("help") #################################################### ## 4. Functions #################################################### # The keyword 'function' creates new functions #function name(arglist) # body... #end function add(x, y) println("x is $x and y is $y") # Functions return the value of their last statement x + y end add(5, 6) # => 11 after printing out "x is 5 and y is 6" # Compact assignment of functions f_add(x, y) = x + y # => "f (generic function with 1 method)" f_add(3, 4) # => 7 # Function can also return multiple values as tuple fn(x, y) = x + y, x - y fn(3, 4) # => (7, -1) # You can define functions that take a variable number of # positional arguments function varargs(args...) return args # use the keyword return to return anywhere in the function end # => varargs (generic function with 1 method) varargs(1, 2, 3) # => (1,2,3) # The ... is called a splat. # We just used it in a function definition. # It can also be used in a function call, # where it will splat an Array or Tuple's contents into the argument list. add([5,6]...) # this is equivalent to add(5,6) x = (5, 6) # => (5,6) add(x...) # this is equivalent to add(5,6) # You can define functions with optional positional arguments function defaults(a, b, x=5, y=6) return "$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 Dict("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","k1"=>4] # You can combine all kinds of arguments in the same function 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 # This is "stabby lambda syntax" for creating anonymous functions (x -> x > 2)(3) # => true # This function is identical to create_adder implementation above. 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 # 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 [add_10(i) for i = [1, 2, 3]] # => [11, 12, 13] [add_10(i) for i in [1, 2, 3]] # => [11, 12, 13] [x for x in [3, 4, 5, 6, 7] if x > 5] # => [6, 7] #################################################### ## 5. Types #################################################### # Julia has a type system. # Every value has a type; variables do not have types themselves. # You can use the `typeof` function to get the type of a value. typeof(5) # => Int64 # Types are first-class values typeof(Int64) # => DataType typeof(DataType) # => DataType # DataType is the type that represents types, including itself. # Types are used for documentation, optimizations, and dispatch. # They are not statically checked. # Users can define types # They are like records or structs in other languages. # New types are defined using the `struct` keyword. # struct Name # field::OptionalType # ... # end struct Tiger taillength::Float64 coatcolor # not including a type annotation is the same as `::Any` end # The default constructor's arguments are the properties # of the type, in the order they are listed in the definition tigger = Tiger(3.5, "orange") # => Tiger(3.5,"orange") # The type doubles as the constructor function for values of that type sherekhan = typeof(tigger)(5.6, "fire") # => Tiger(5.6,"fire") # These struct-style types are called concrete types # They can be instantiated, but cannot have subtypes. # The other kind of types is abstract types. # abstract Name abstract type Cat end # just a name and point in the type hierarchy # Abstract types cannot be instantiated, but can have subtypes. using InteractiveUtils # defines the subtype and supertype function # For example, Number is an abstract type subtypes(Number) # => 2-element Array{Any,1}: # Complex{T<:Real} # Real subtypes(Cat) # => 0-element Array{Any,1} # AbstractString, as the name implies, is also an abstract type subtypes(AbstractString) # 4-element Array{Any,1}: # String # SubString # SubstitutionString # Test.GenericString # Every type has a super type; use the `supertype` function to get it. typeof(5) # => Int64 supertype(Int64) # => Signed supertype(Signed) # => Integer supertype(Integer) # => Real supertype(Real) # => Number supertype(Number) # => Any supertype(supertype(Signed)) # => Real supertype(Any) # => Any # All of these type, except for Int64, are abstract. typeof("fire") # => String supertype(String) # => AbstractString # Likewise here with String supertype(SubString) # => AbstractString # <: is the subtyping operator struct Lion <: Cat # Lion is a subtype of Cat mane_color roar::AbstractString end # You can define more constructors for your type # Just define a function of the same name as the type # and call an existing constructor to get a value of the correct type Lion(roar::AbstractString) = Lion("green", roar) # This is an outer constructor because it's outside the type definition struct 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 # Using inner constructors, like Panther does, gives you control # over how values of the type can be created. # When possible, you should use outer constructors rather than inner ones. #################################################### ## 6. Multiple-Dispatch #################################################### # In Julia, all named functions are generic functions # This means that they are built up from many small methods # Each constructor for Lion is a method of the generic function Lion. # For a non-constructor example, let's make a function meow: # Definitions for Lion, Panther, Tiger function meow(animal::Lion) animal.roar # access type properties using dot notation end function meow(animal::Panther) "grrr" end function meow(animal::Tiger) "rawwwr" end # Testing the meow function meow(tigger) # => "rawwr" meow(Lion("brown", "ROAAR")) # => "ROAAR" meow(Panther()) # => "grrr" # Review the local type hierarchy Tiger <: Cat # => false Lion <: Cat # => true Panther <: Cat # => true # Defining a function that takes Cats function pet_cat(cat::Cat) println("The cat says $(meow(cat))") end pet_cat(Lion("42")) # => prints "The cat says 42" try pet_cat(tigger) # => ERROR: no method pet_cat(Tiger,) catch e println(e) end # In OO languages, single dispatch is common; # this means that the method is picked based on the type of the first argument. # In Julia, all of the argument types contribute to selecting the best method. # Let's define a function with more arguments, so we can see the difference function fight(t::Tiger, c::Cat) println("The $(t.coatcolor) tiger wins!") end # => fight (generic function with 1 method) fight(tigger, Panther()) # => prints The orange tiger wins! fight(tigger, Lion("ROAR")) # => prints The orange tiger wins! # Let's change the behavior when the Cat is specifically a Lion fight(t::Tiger, l::Lion) = println("The $(l.mane_color)-maned lion wins!") # => fight (generic function with 2 methods) fight(tigger, Panther()) # => prints The orange tiger wins! fight(tigger, Lion("ROAR")) # => prints The green-maned lion wins! # We don't need a Tiger in order to fight fight(l::Lion, c::Cat) = println("The victorious cat says $(meow(c))") # => fight (generic function with 3 methods) fight(Lion("balooga!"), Panther()) # => prints The victorious cat says grrr try fight(Panther(), Lion("RAWR")) catch e println(e) # => MethodError(fight, (Panther("green"), Lion("green", "RAWR")), # 0x000000000000557b) end # Also let the cat go first fight(c::Cat, l::Lion) = println("The cat beats the Lion") # This warning is because it's unclear which fight will be called in: try fight(Lion("RAR"), Lion("brown", "rarrr")) # => prints The victorious cat says rarrr catch e println(e) # => MethodError(fight, (Lion("green", "RAR"), Lion("brown", "rarrr")), # 0x000000000000557c) end # The result may be different in other versions of Julia fight(l::Lion, l2::Lion) = println("The lions come to a tie") fight(Lion("RAR"), Lion("brown", "rarrr")) # => prints The lions come to a tie # Under the hood # You can take a look at the llvm and the assembly code generated. square_area(l) = l * l # square_area (generic function with 1 method) square_area(5) # => 25 # What happens when we feed square_area an integer? code_native(square_area, (Int32,)) # .section __TEXT,__text,regular,pure_instructions # Filename: none # Source line: 1 # Prologue # push RBP # mov RBP, RSP # Source line: 1 # movsxd RAX, EDI # Fetch l from memory? # imul RAX, RAX # Square l and store the result in RAX # pop RBP # Restore old base pointer # ret # Result will still be in RAX code_native(square_area, (Float32,)) # .section __TEXT,__text,regular,pure_instructions # Filename: none # Source line: 1 # push RBP # mov RBP, RSP # Source line: 1 # vmulss XMM0, XMM0, XMM0 # Scalar single precision multiply (AVX) # pop RBP # ret code_native(square_area, (Float64,)) # .section __TEXT,__text,regular,pure_instructions # Filename: none # Source line: 1 # push RBP # mov RBP, RSP # Source line: 1 # vmulsd XMM0, XMM0, XMM0 # Scalar double precision multiply (AVX) # pop RBP # ret # # Note that julia will use floating point instructions if any of the # arguments are floats. # Let's calculate the area of a circle circle_area(r) = pi * r * r # circle_area (generic function with 1 method) circle_area(5) # 78.53981633974483 code_native(circle_area, (Int32,)) # .section __TEXT,__text,regular,pure_instructions # Filename: none # Source line: 1 # push RBP # mov RBP, RSP # Source line: 1 # vcvtsi2sd XMM0, XMM0, EDI # Load integer (r) from memory # movabs RAX, 4593140240 # Load pi # vmulsd XMM1, XMM0, QWORD PTR [RAX] # pi * r # vmulsd XMM0, XMM0, XMM1 # (pi * r) * r # pop RBP # ret # code_native(circle_area, (Float64,)) # .section __TEXT,__text,regular,pure_instructions # Filename: none # Source line: 1 # push RBP # mov RBP, RSP # movabs RAX, 4593140496 # Source line: 1 # vmulsd XMM1, XMM0, QWORD PTR [RAX] # vmulsd XMM0, XMM1, XMM0 # pop RBP # ret # ``` ## Further Reading You can get a lot more detail from the [Julia Documentation](https://docs.julialang.org/) The best place to get help with Julia is the (very friendly) [Discourse forum](https://discourse.julialang.org/).