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====== 学习Julia：一个Demo涵盖绝大部分语法 ======

Source: https://learnxinyminutes.com/



===== 英文版 =====

<code 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

# Julia (unlike Python for instance) has integer under/overflow
10^19      # => -8446744073709551616
# use bigint or floating point to avoid this
big(10)^19 # => 10000000000000000000
1e19       # => 1.0e19
10.0^19    # => 1.0e19

# 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, like in Python but unlike many other languages
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, so strings like "π" or "☃" are not directly equivalent
# to an array of single characters.
# Only if they contain only ASCII characters can they be safely indexed.
ascii("This is a string")[1]    # => 'T'
# => 'T': ASCII/Unicode U+0054 (category Lu: Letter, uppercase)
# Beware, Julia indexes everything from 1 (like MATLAB), not 0 (like most languages).
# Otherwise, iterating over strings is recommended (map, for loops, etc).

# String can be compared lexicographically, in dictionnary order:
"good" > "bye"   # => true
"good" == "good" # => true
"1 + 2 = 3" == "1 + 2 = $(1 + 2)" # => true

# $(..) can be used for string interpolation:
"2 + 2 = $(2 + 2)" # => "2 + 2 = 4"
# You can put any Julia expression inside the parentheses.

# Printing is easy
println("I'm Julia. Nice to meet you!")  # => I'm Julia. Nice to meet you!

# Another way to format strings is the printf macro from the stdlib Printf.
using Printf   # this is how you load (or import) a module
@printf "%d is less than %f\n" 4.5 5.3   # => 5 is less than 5.300000


####################################################
## 2. Variables and Collections
####################################################

# You don't declare variables before assigning to them.
someVar = 5  # => 5
someVar      # => 5

# Accessing a previously unassigned variable is an error
try
    someOtherVar  # => ERROR: UndefVarError: someOtherVar 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
# here ☃ is a Unicode 'snowman' characters, see http://emojipedia.org/%E2%98%83%EF%B8%8F if it displays wrongly here
☃ = 8  # => 8
# These are especially handy for mathematical notation, like the constant π
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 Array{Int64,1}

# 1-dimensional array literals can be written with comma-separated values.
b = [4, 5, 6] # => 3-element Array{Int64,1}: [4, 5, 6]
b = [4; 5; 6] # => 3-element Array{Int64,1}: [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] # => 2×2 Array{Int64,2}: [1 2; 3 4]

# Arrays of a particular type
b = Int8[4, 5, 6] # => 3-element Array{Int8,1}: [4, 5, 6]

# Add stuff to the end of a list with push! and append!
# By convention, the exclamation mark '!' is appended to names of functions
# that modify their arguments
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
b # => [4,5]

# Let's put it back
push!(b, 6)  # => [4,5,6]
b # => [4,5,6]

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 
a # => [2,4,3,4,5,6]
pushfirst!(a, 7)  # => [7,2,4,3,4,5,6]
a # => [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 Array{Int64,1}: [5,4,6]
sort(arr)      # => [4,5,6]
arr            # => [5,4,6]
sort!(arr)     # => [4,5,6]
arr            # => [4,5,6]

# Looking out of bounds is a BoundsError
try
    a[0] 
    # => ERROR: BoundsError: attempt to access 7-element Array{Int64,1} at 
    # index [0]
    # => Stacktrace:
    # =>  [1] getindex(::Array{Int64,1}, ::Int64) at .\array.jl:731
    # =>  [2] top-level scope at none:0
    # =>  [3] ...
    # => in expression starting at ...\LearnJulia.jl:180
    a[end + 1] 
    # => ERROR: BoundsError: attempt to access 7-element Array{Int64,1} at 
    # index [8]
    # => Stacktrace:
    # =>  [1] getindex(::Array{Int64,1}, ::Int64) at .\array.jl:731
    # =>  [2] top-level scope at none:0
    # =>  [3] ...
    # => in expression starting at ...\LearnJulia.jl:188
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 Array{Int64,1}: [1,2,3,4,5]
a2 = [1:5]  # => 1-element Array{UnitRange{Int64},1}: [1:5]

# 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 # => [3,5]

# Concatenate lists with append!
b = [1,2,3]
append!(a, b) # => [1, 2, 3, 4, 5, 1, 2, 3]
a # => [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)
typeof(tup) # => Tuple{Int64,Int64,Int64}
tup[1] # => 1
try
    tup[1] = 3  
    # => ERROR: MethodError: no method matching 
    # setindex!(::Tuple{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  # => 1
b  # => 2
c  # => 3

# Tuples are created even if you leave out the parentheses
d, e, f = 4, 5, 6  # => (4,5,6)
d  # => 4
e  # => 5
f  # => 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  # => 5
e  # => 4

# Dictionaries store mappings
emptyDict = Dict()  # => Dict{Any,Any} with 0 entries

# You can create a dictionary using a literal
filledDict = Dict("one" => 1, "two" => 2, "three" => 3)
# => Dict{String,Int64} with 3 entries:
# =>  "two" => 2, "one" => 1, "three" => 3

# Look up values with []
filledDict["one"]  # => 1

# Get all keys
keys(filledDict)
# => 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(filledDict)
# => Base.ValueIterator for a 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), filledDict)  # => true
in(("two" => 3), filledDict)  # => false
haskey(filledDict, "one")     # => true
haskey(filledDict, 1)         # => false

# Trying to look up a non-existent key will raise an error
try
    filledDict["four"]  # => ERROR: 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, defaultValue)
get(filledDict, "one", 4)   # => 1
get(filledDict, "four", 4)  # => 4

# Use Sets to represent collections of unordered, unique values
emptySet = Set()  # => Set(Any[])
# Initialize a set with values
filledSet = Set([1, 2, 2, 3, 4])  # => Set([4, 2, 3, 1])

# Add more values to a set
push!(filledSet, 5)  # => Set([4, 2, 3, 5, 1])

# Check if the values are in the set
in(2, filledSet)   # => true
in(10, filledSet)  # => false

# There are functions for set intersection, union, and difference.
otherSet = Set([3, 4, 5, 6])         # => Set([4, 3, 5, 6])
intersect(filledSet, otherSet)      # => Set([4, 3, 5])
union(filledSet, otherSet)          # => 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
someVar = 5

# Here is an if statement. Indentation is not meaningful in Julia.
if someVar > 10
    println("someVar is totally bigger than 10.")
elseif someVar < 10    # This elseif clause is optional.
    println("someVar is smaller than 10.")
else                    # The else clause is optional too.
    println("someVar 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.
    # In this special case, no need for parenthesis: $animal and $(animal) give the same
end
# => 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
# => 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
# => mouse is a mammal
# => cat is a mammal
# => dog is a mammal

for (k, v) in Dict("dog" => "mammal", "cat" => "mammal", "mouse" => "mammal")
    println("$k is a $v")
end
# => mouse is a mammal
# => cat is a mammal
# => dog is a mammal

# While loops loop while a condition is true
let x = 0
    while x < 4
        println(x)
        x += 1  # Shorthand for in place increment: x = x + 1
    end
end
# => 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)
# => x is 5 and y is 6
# => 11

# Compact assignment of functions
f_add(x, y) = x + y  # => f_add (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 (generic function with 1 method)
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 (generic function with 3 methods)

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: MethodError: no method matching defaults(::Char)
    defaults()  # => ERROR: MethodError: no method matching 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 (generic function with 1 method)

keyword_args(name2="ness")  # => ["name2"=>"ness", "k1"=>4]
keyword_args(k1="mine")     # => ["name2"=>"hello", "k1"=>"mine"]
keyword_args()              # => ["name2"=>"hello", "k1"=>4]

# You can combine all kinds of arguments in the same function
function all_the_args(normalArg, optionalPositionalArg=2; keywordArg="foo")
    println("normal arg: $normalArg")
    println("optional arg: $optionalPositionalArg")
    println("keyword arg: $keywordArg")
end
# => all_the_args (generic function with 2 methods)

all_the_args(1, 3, keywordArg=4)
# => 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
# => create_adder (generic function with 1 method)

# 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
# => create_adder (generic function with 1 method)

# You can also name the internal function, if you want
function create_adder(x)
    function adder(y)
        x + y
    end
    adder
end
# => create_adder (generic function with 1 method)

add_10 = create_adder(10) # => (::getfield(Main, Symbol("#adder#11")){Int64}) 
                          # (generic function with 1 method)
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.
# For example, Number is an abstract type
subtypes(Number)  # => 2-element Array{Any,1}:
                  # =>  Complex
                  # =>  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
    maneColor
    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
    eyeColor
    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)  # => "rawwwr"
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 (generic function with 1 method)

pet_cat(Lion("42")) # => The cat says 42
try
    pet_cat(tigger) # => ERROR: MethodError: no method matching 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())  # => The orange tiger wins!
fight(tigger, Lion("ROAR")) # => The orange tiger wins!

# Let's change the behavior when the Cat is specifically a Lion
fight(t::Tiger, l::Lion) = println("The $(l.maneColor)-maned lion wins!")
# => fight (generic function with 2 methods)

fight(tigger, Panther())  # => The orange tiger wins!
fight(tigger, Lion("ROAR")) # => 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())  # => The victorious cat says grrr
try
    fight(Panther(), Lion("RAWR"))  
    # => ERROR: MethodError: no method matching fight(::Panther, ::Lion)
    # => Closest candidates are:
    # =>   fight(::Tiger, ::Lion) at ...
    # =>   fight(::Tiger, ::Cat) at ...
    # =>   fight(::Lion, ::Cat) at ...
    # => ...
catch e
    println(e)
end

# Also let the cat go first
fight(c::Cat, l::Lion) = println("The cat beats the Lion")
# => fight (generic function with 4 methods)

# This warning is because it's unclear which fight will be called in:
try
    fight(Lion("RAR"), Lion("brown", "rarrr"))
    # => ERROR: MethodError: fight(::Lion, ::Lion) is ambiguous. Candidates:
    # =>   fight(c::Cat, l::Lion) in Main at ...
    # =>   fight(l::Lion, c::Cat) in Main at ...
    # => Possible fix, define
    # =>   fight(::Lion, ::Lion)
    # => ...
catch e
    println(e)
end
# The result may be different in other versions of Julia

fight(l::Lion, l2::Lion) = println("The lions come to a tie") 
# => fight (generic function with 5 methods)
fight(Lion("RAR"), Lion("brown", "rarrr"))  # => 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,), syntax = :intel)
    #         .text
    # ; Function square_area {
    # ; Location: REPL[116]:1       # Prologue
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: int.jl:54
    #         imul    ecx, ecx      # Square l and store the result in ECX
    # ;}
    #         mov     eax, ecx
    #         pop     rbp           # Restore old base pointer
    #         ret                   # Result will still be in EAX
    #         nop     dword ptr [rax + rax]
    # ;}

code_native(square_area, (Float32,), syntax = :intel)
    #         .text
    # ; Function square_area {
    # ; Location: REPL[116]:1
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: float.jl:398
    #         vmulss  xmm0, xmm0, xmm0  # Scalar single precision multiply (AVX)
    # ;}
    #         pop     rbp
    #         ret
    #         nop     word ptr [rax + rax]
    # ;}

code_native(square_area, (Float64,), syntax = :intel)
    #         .text
    # ; Function square_area {
    # ; Location: REPL[116]:1
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm0, xmm0, xmm0  # Scalar double precision multiply (AVX)
    # ;}
    #         pop     rbp
    #         ret
    #         nop     word ptr [rax + rax]
    # ;}

# 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,), syntax = :intel)
    #         .text
    # ; Function circle_area {
    # ; Location: REPL[121]:1
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: operators.jl:502
    # ; Function *; {
    # ; Location: promotion.jl:314
    # ; Function promote; {
    # ; Location: promotion.jl:284
    # ; Function _promote; {
    # ; Location: promotion.jl:261
    # ; Function convert; {
    # ; Location: number.jl:7
    # ; Function Type; {
    # ; Location: float.jl:60
    #         vcvtsi2sd       xmm0, xmm0, ecx     # Load integer (r) from memory
    #         movabs  rax, 497710928              # Load pi
    # ;}}}}}
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm1, xmm0, qword ptr [rax] # pi * r
    #         vmulsd  xmm0, xmm1, xmm0            # (pi * r) * r
    # ;}}
    #         pop     rbp
    #         ret
    #         nop     dword ptr [rax]
    # ;}

code_native(circle_area, (Float64,), syntax = :intel)
    #         .text
    # ; Function circle_area {
    # ; Location: REPL[121]:1
    #         push    rbp
    #         mov     rbp, rsp
    #         movabs  rax, 497711048
    # ; Function *; {
    # ; Location: operators.jl:502
    # ; Function *; {
    # ; Location: promotion.jl:314
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm1, xmm0, qword ptr [rax]
    # ;}}}
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm0, xmm1, xmm0
    # ;}
    #         pop     rbp
    #         ret
    #         nop     dword ptr [rax + rax]
    # ;}
</code>




===== 中文版 =====

<code julia>
# 单行注释只需要一个井号「#」
#= 多行注释
   只需要以「#=」开始「=#」结束
   还可以嵌套.
=#

####################################################
## 1. 原始类型与操作符
####################################################

# Julia 中一切皆为表达式

# 这是一些基本数字类型
typeof(3)       # => Int64
typeof(3.2)     # => Float64
typeof(2 + 1im) # => Complex{Int64}
typeof(2 // 3)  # => Rational{Int64}

# 支持所有的普通中缀操作符
1 + 1      # => 2
8 - 1      # => 7
10 * 2     # => 20
35 / 5     # => 7.0
10 / 2     # => 5.0  # 整数除法总是返回浮点数
div(5, 2)  # => 2    # 使用 div 可以获得整除的结果
5 \ 35     # => 7.0
2^2        # => 4    # 幂运算，不是异或 (xor)
12 % 10    # => 2

# 用括号提高优先级
(1 + 3) * 2 # => 8

# 位操作符
~2         # => -3 # 按位非 (not)
3 & 5      # => 1  # 按位与 (and)
2 | 4      # => 6  # 按位或 (or)
xor(2, 4)  # => 6  # 按位异或 (xor)
2 >>> 1    # => 1  # 逻辑右移
2 >> 1     # => 1  # 算术右移
2 << 1     # => 4  # 逻辑/算术左移

# 可以用函数 bitstring 查看二进制数。
bitstring(12345)
# => "0000000000000000000000000000000000000000000000000011000000111001"
bitstring(12345.0)
# => "0100000011001000000111001000000000000000000000000000000000000000"

# 布尔值是原始类型
true
false

# 布尔操作符
!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

# 链式比较
1 < 2 < 3 # => true
2 < 3 < 2 # => false

# 字符串可以由「"」创建
"This is a string."

# 字符字面量可用「'」创建
'a'

# 字符串使用 UTF-8 编码
# 可以像取数组取值一样用 index 取出对应字符
ascii("This is a string")[1]
# => 'T': ASCII/Unicode U+0054 (category Lu: Letter, uppercase) 
# Julia 的 index 从 1 开始 :(
# 但只有在字符串仅由 ASCII 字符构成时，字符串才能够被安全的引索
# 因此建议使用遍历器 (map, for loops, 等)

# $ 可用于字符插值:
"2 + 2 = $(2 + 2)" # => "2 + 2 = 4"
# 可以将任何 Julia 表达式放入括号。

# 另一种输出格式化字符串的方法是使用标准库 Printf 中的 Printf 宏
using Printf
@printf "%d is less than %f\n" 4.5 5.3  # => 5 is less than 5.300000

# 打印字符串很容易
println("I'm Julia. Nice to meet you!") # => I'm Julia. Nice to meet you!

# 字符串可以按字典序进行比较
"good" > "bye" # => true
"good" == "good" # => true
"1 + 2 = 3" == "1 + 2 = $(1 + 2)" # => true

####################################################
## 2. 变量与集合
####################################################

# 给变量赋值就是声明变量
some_var = 5 # => 5
some_var # => 5

# 访问未声明变量会抛出异常
try
    some_other_var # => ERROR: UndefVarError: some_other_var not defined
catch e
    println(e)
end

# 变量名必须以下划线或字母开头
# 之后任何字母，数字，下划线，叹号都是合法的。
SomeOtherVar123! = 6 # => 6

# 甚至可以用 unicode 字符
☃ = 8 # => 8
# 用数学符号非常方便
2 * π # => 6.283185307179586

# 注意 Julia 的命名规约:
#
# * 名称可以用下划线「_」分割。
#   不过一般不推荐使用下划线，除非不用变量名就会变得难于理解
#
# * 类型名以大写字母开头，单词以 CamelCase 方式连接，无下划线。
#
# * 函数与宏的名字小写，无下划线。
#
# * 会改变输入的函数名末位为「!」。
#   这类函数有时被称为 mutating functions 或 in-place functions.

# 数组存储一列值，index 从 1 开始
a = Int64[]  # => 0-element Array{Int64,1}

# 一维数组可以以逗号分隔值的方式声明
b = [4, 5, 6]  # => 3-element Array{Int64,1}: [4, 5, 6]
b = [4; 5; 6]  # => 3-element Array{Int64,1}: [4, 5, 6]
b[1]    # => 4
b[end]  # => 6

# 二维数组以分号分隔维度
matrix = [1 2; 3 4]  # => 2×2 Array{Int64,2}: [1 2; 3 4]

# 指定数组的类型
b = Int8[4, 5, 6]  # => 3-element Array{Int8,1}: [4, 5, 6]

# 使用 push! 和 append! 往数组末尾添加元素
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]

# 用 pop 弹出尾部的元素
pop!(b)  # => 6
b # => [4,5]

# 再放回去
push!(b, 6)  # => [4,5,6]
b # => [4,5,6]

a[1] # => 1 #  永远记住 Julia 的引索从 1 开始！而不是 0！

# 用 end 可以直接取到最后索引。它可以用在任何索引表达式中
a[end] # => 6

# 数组还支持 popfirst! 和 pushfirst!
popfirst!(a)  # => 1 
a # => [2,4,3,4,5,6]
pushfirst!(a, 7)  # => [7,2,4,3,4,5,6]
a # => [7,2,4,3,4,5,6]

# 以叹号结尾的函数名表示它会改变参数的值
arr = [5,4,6]  # => 3-element Array{Int64,1}: [5,4,6]
sort(arr)   # => [4,5,6]
arr         # => [5,4,6]
sort!(arr)  # => [4,5,6]
arr         # => [4,5,6]

# 数组越界会抛出 BoundsError
try
    a[0] 
    # => ERROR: BoundsError: attempt to access 7-element Array{Int64,1} at 
    # index [0]
    # => Stacktrace:
    # =>  [1] getindex(::Array{Int64,1}, ::Int64) at .\array.jl:731
    # =>  [2] top-level scope at none:0
    # =>  [3] ...
    # => in expression starting at ...\LearnJulia.jl:203
    a[end + 1] 
    # => ERROR: BoundsError: attempt to access 7-element Array{Int64,1} at 
    # index [8]
    # => Stacktrace:
    # =>  [1] getindex(::Array{Int64,1}, ::Int64) at .\array.jl:731
    # =>  [2] top-level scope at none:0
    # =>  [3] ...
    # => in expression starting at ...\LearnJulia.jl:211
catch e
    println(e)
end

# 报错时错误会指出出错的文件位置以及行号，标准库也一样
# 你可以在 Julia 安装目录下的 share/julia 文件夹里找到这些标准库

# 可以用 range 初始化数组
a = [1:5;]  # => 5-element Array{Int64,1}: [1,2,3,4,5]
# 注意！分号不可省略
a2 = [1:5]  # => 1-element Array{UnitRange{Int64},1}: [1:5]

# 可以切割数组
a[1:3] # => [1, 2, 3]
a[2:end] # => [2, 3, 4, 5]

# 用 splice! 切割原数组
arr = [3,4,5]
splice!(arr, 2) # => 4 
arr # => [3,5]

# 用 append! 连接数组
b = [1,2,3]
append!(a, b) # => [1, 2, 3, 4, 5, 1, 2, 3]
a # => [1, 2, 3, 4, 5, 1, 2, 3]

# 检查元素是否在数组中
in(1, a) # => true

# 用 length 获得数组长度
length(a) # => 8

# 元组(Tuples)是不可变的
tup = (1, 2, 3)  # => (1,2,3)
typeof(tup) # => Tuple{Int64,Int64,Int64}
tup[1] # => 1
try
    tup[1] = 3  
    # => ERROR: MethodError: no method matching 
    # setindex!(::Tuple{Int64,Int64,Int64}, ::Int64, ::Int64)
catch e
    println(e)
end

# 大多数组的函数同样支持元组
length(tup) # => 3
tup[1:2]    # => (1,2)
in(2, tup)  # => true

# 可以将元组的元素解包赋给变量
a, b, c = (1, 2, 3)  # => (1,2,3)  
a # => 1
b # => 2
c # => 3

# 不用括号也可以
d, e, f = 4, 5, 6  # => (4,5,6)
d # => 4
e # => 5
f # => 6

# 单元素 tuple 不等于其元素值
(1,) == 1 # => false
(1) == 1  # => true

# 交换值
e, d = d, e  # => (5,4) 
d # => 5
e # => 4


# 字典用于储存映射(mappings)（键值对）
empty_dict = Dict()  # => Dict{Any,Any} with 0 entries

# 也可以用字面量创建字典
filled_dict = Dict("one" => 1, "two" => 2, "three" => 3)
# => Dict{String,Int64} with 3 entries:
# =>  "two" => 2, "one" => 1, "three" => 3

# 用 [] 获得键值
filled_dict["one"] # => 1

# 获得所有键
keys(filled_dict)
# => Base.KeySet for a Dict{String,Int64} with 3 entries. Keys:
# =>  "two", "one", "three"
# 注意，键的顺序不是插入时的顺序

# 获得所有值
values(filled_dict)
# => Base.ValueIterator for a Dict{String,Int64} with 3 entries. Values: 
# =>  2, 1, 3
# 注意，值的顺序也一样

# 用 in 检查键值是否已存在，用 haskey 检查键是否存在
in(("one" => 1), filled_dict)  # => true
in(("two" => 3), filled_dict)  # => false
haskey(filled_dict, "one")     # => true
haskey(filled_dict, 1)         # => false

# 获取不存在的键的值会抛出异常
try
    filled_dict["four"]  # => ERROR: KeyError: key "four" not found
catch e
    println(e)
end

# 使用 get 可以提供默认值来避免异常
# get(dictionary,key,default_value)
get(filled_dict, "one", 4)   # => 1
get(filled_dict, "four", 4)  # => 4

# Set 表示无序不可重复的值的集合
empty_set = Set()  # => Set(Any[])
# 初始化一个带初值的 Set
filled_set = Set([1, 2, 2, 3, 4])  # => Set([4, 2, 3, 1])

# 新增值
push!(filled_set, 5)  # => Set([4, 2, 3, 5, 1])

# 检查 Set 中是否存在某值
in(2, filled_set)   # => true
in(10, filled_set)  # => false

# 交集，并集，差集
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. 控制语句
####################################################

# 声明一个变量
some_var = 5

# 这是一个 if 语句块，其中的缩进不是必须的
if some_var > 10
    println("some_var is totally bigger than 10.")
elseif some_var < 10    # elseif 是可选的
    println("some_var is smaller than 10.")
else                    # else 也是可选的
    println("some_var is indeed 10.")
end
# => some_var is smaller than 10.


# For 循环遍历
# 可迭代的类型包括：Range, Array, Set, Dict 和 AbstractString
for animal = ["dog", "cat", "mouse"]
    println("$animal is a mammal")
    # 你可以用 $ 将变量或表达式插入字符串中 
end
# => dog is a mammal
# => cat is a mammal
# => mouse is a mammal

# 你也可以不用「=」而使用「in」
for animal in ["dog", "cat", "mouse"]
    println("$animal is a mammal")
end
# => 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
# => mouse is a mammal
# => cat is a mammal
# => dog is a mammal
# 注意！这里的输出顺序和上面的不同

for (k, v) in Dict("dog" => "mammal", "cat" => "mammal", "mouse" => "mammal")
    println("$k is a $v")
end
# => mouse is a mammal
# => cat is a mammal
# => dog is a mammal

# While 循环
let x = 0
    while x < 4
        println(x)
        x += 1  # x = x + 1 的缩写
    end
end
# => 0
# => 1
# => 2
# => 3

# 用 try/catch 处理异常
try
    error("help")
catch e
    println("caught it $e")
end
# => caught it ErrorException("help")

####################################################
## 4. 函数
####################################################

# 关键字 function 用于定义函数
# function name(arglist)
#   body...
# end
function add(x, y)
    println("x is $x and y is $y")

    # 函数会返回最后一行的值
    x + y
end

add(5, 6)
# => x is 5 and y is 6
# => 11

# 更紧凑的定义函数
f_add(x, y) = x + y  # => f_add (generic function with 1 method)
f_add(3, 4)  # => 7

# 函数可以将多个值作为元组返回
fn(x, y) = x + y, x - y # => fn (generic function with 1 method)
fn(3, 4)  # => (7, -1)

# 还可以定义接收可变长参数的函数
function varargs(args...)
    return args
    # 使用 return 可以在函数内的任何地方返回
end
# => varargs (generic function with 1 method)

varargs(1,2,3) # => (1,2,3)

# 省略号「...」称为 splat
# 刚刚用在了函数定义中
# 在调用函数时也可以使用它，此时它会把数组或元组解包为参数列表
add([5,6]...)  # 等价于 add(5,6)

x = (5, 6)  # => (5,6)
add(x...)  # 等价于 add(5,6)

# 可定义带可选参数的函数
function defaults(a, b, x=5, y=6)
    return "$a $b and $x $y"
end
# => defaults (generic function with 3 methods)

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: MethodError: no method matching defaults(::Char)
    defaults()  # => ERROR: MethodError: no method matching defaults()
catch e
    println(e)
end

# 还可以定义带关键字参数的函数
function keyword_args(;k1=4, name2="hello")  # 注意分号 ';'
    return Dict("k1" => k1, "name2" => name2)
end
# => keyword_args (generic function with 1 method)

keyword_args(name2="ness")  # => ["name2"=>"ness", "k1"=>4]
keyword_args(k1="mine")     # => ["name2"=>"hello", "k1"=>"mine"]
keyword_args()              # => ["name2"=>"hello", "k1"=>4]

# 可以在一个函数中组合各种类型的参数
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 (generic function with 2 methods)

all_the_args(1, 3, keyword_arg=4)
# => normal arg: 1
# => optional arg: 3
# => keyword arg: 4

# Julia 有一等函数
function create_adder(x)
    adder = function (y)
        return x + y
    end
    return adder
end
# => create_adder (generic function with 1 method)

# 这是用 "stabby lambda syntax" 创建的匿名函数
(x -> x > 2)(3) # => true

# 这个函数和上面的 create_adder 是等价的
function create_adder(x)
    y -> x + y
end
# => create_adder (generic function with 1 method)

# 你也可以给内部函数起个名字
function create_adder(x)
    function adder(y)
        x + y
    end
    adder
end
# => create_adder (generic function with 1 method)

add_10 = create_adder(10) # => (::getfield(Main, Symbol("#adder#11")){Int64}) 
                          # (generic function with 1 method)
add_10(3)  # => 13

# 内置的高阶函数有
map(add_10, [1,2,3])  # => [11, 12, 13]
filter(x -> x > 5, [3, 4, 5, 6, 7])  # => [6, 7]

# 还可以使用 list comprehensions 让 map 更美观
[add_10(i) for i = [1, 2, 3]]   # => [11, 12, 13]
[add_10(i) for i in [1, 2, 3]]  # => [11, 12, 13]

####################################################
## 5.  类型
####################################################

# Julia 有类型系统
# 所有的值都有类型；但变量本身没有类型
# 你可以用 `typeof` 函数获得值的类型
typeof(5) # => Int64

# 类型是一等值
typeof(Int64)     # => DataType
typeof(DataType)  # => DataType
# DataType 是代表类型的类型，也代表他自己的类型

# 类型可用于文档化代码、执行优化以及多重派分(dispatch)
# Julia 并不只是静态的检查类型

# 用户还可以自定义类型
# 就跟其它语言的 record 或 struct 一样
# 用 `struct` 关键字定义新的类型

# struct Name
#   field::OptionalType
#   ...
# end
struct Tiger
    taillength::Float64
    coatcolor  # 不带类型标注相当于 `::Any`
end

# 默认构造函数的参数是类型的属性，按类型定义中的顺序排列
tigger = Tiger(3.5, "orange")  # => Tiger(3.5, "orange")

# 用新类型作为构造函数还会创建一个类型
sherekhan = typeof(tigger)(5.6, "fire")  # => Tiger(5.6, "fire")

# 类似 struct 的类型被称为具体类型
# 它们可被实例化，但不能有子类型
# 另一种类型是抽象类型

# 抽象类型名
abstract type Cat end  # 仅仅是指向类型结构层次的一个名称

# 抽象类型不能被实例化，但可以有子类型
# 例如，Number 就是抽象类型
subtypes(Number)  # => 2-element Array{Any,1}:
                  # =>  Complex
                  # =>  Real
subtypes(Cat)  # => 0-element Array{Any,1}

# AbstractString，类如其名，也是一个抽象类型
subtypes(AbstractString)  # => 4-element Array{Any,1}:
                          # =>  String
                          # =>  SubString
                          # =>  SubstitutionString
                          # =>  Test.GenericString

# 所有的类型都有父类型。可以用函数 `supertype` 得到父类型
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
# 除了 Int64 外，其余的类型都是抽象类型
typeof("fire")      # => String
supertype(String)   # => AbstractString
supertype(AbstractString) # => Any
supertype(SubString)  # => AbstractString

# <: 是子类型化操作符
struct Lion <: Cat  # Lion 是 Cat 的子类型
    mane_color
    roar::AbstractString
end

# 可以继续为你的类型定义构造函数
# 只需要定义一个与类型同名的函数，并调用已有的构造函数得到正确的类型
Lion(roar::AbstractString) = Lion("green", roar)  # => Lion
# 这是一个外部构造函数，因为它在类型定义之外

struct Panther <: Cat # Panther 也是 Cat 的子类型
    eye_color
    Panther() = new("green")
    # Panthers 只有这个构造函数，没有默认构造函数
end
# 像 Panther 一样使用内置构造函数，让你可以控制如何构建类型的值
# 应该尽量使用外部构造函数，而不是内部构造函数

####################################################
## 6. 多分派
####################################################

# Julia 中所有的函数都是通用函数，或者叫做泛型函数(generic functions)
# 也就是说这些函数都是由许多小方法组合而成的
# Lion 的每一种构造函数都是通用函数 Lion 的一个方法

# 我们来看一个非构造函数的例子
# 首先，让我们定义一个函数 meow

# Lion, Panther, Tiger 的 meow 定义分别为
function meow(animal::Lion)
    animal.roar # 使用点记号「.」访问属性
end
# => meow (generic function with 1 method)

function meow(animal::Panther)
    "grrr"
end
# => meow (generic function with 2 methods)

function meow(animal::Tiger)
    "rawwwr"
end
# => meow (generic function with 3 methods)

# 试试 meow 函数
meow(tigger)  # => "rawwwr"
meow(Lion("brown", "ROAAR"))  # => "ROAAR"
meow(Panther()) # => "grrr"

# 回顾类型的层次结构
Tiger   <: Cat  # => false
Lion    <: Cat  # => true
Panther <: Cat  # => true

# 定义一个接收 Cat 类型的函数
function pet_cat(cat::Cat)
    println("The cat says $(meow(cat))")
end
# => pet_cat (generic function with 1 method)

pet_cat(Lion("42"))  # => The cat says 42
try
    pet_cat(tigger)  # => ERROR: MethodError: no method matching pet_cat(::Tiger)
catch e
    println(e)
end

# 在面向对象语言中，通常都是单分派
# 这意味着使用的方法取决于第一个参数的类型
# 而 Julia 中选择方法时会考虑到所有参数的类型

# 让我们定义一个有更多参数的函数，这样我们就能看出区别
function fight(t::Tiger, c::Cat)
    println("The $(t.coatcolor) tiger wins!")
end
# => fight (generic function with 1 method)

fight(tigger, Panther())  # => The orange tiger wins!
fight(tigger, Lion("ROAR")) # => fight(tigger, Lion("ROAR"))

# 让我们修改一下传入 Lion 类型时的行为
fight(t::Tiger, l::Lion) = println("The $(l.mane_color)-maned lion wins!")
# => fight (generic function with 2 methods)

fight(tigger, Panther())  # => The orange tiger wins!
fight(tigger, Lion("ROAR"))  # => The green-maned lion wins!

# 我们不需要一只老虎参与战斗
fight(l::Lion, c::Cat) = println("The victorious cat says $(meow(c))")
# => fight (generic function with 3 methods)

fight(Lion("balooga!"), Panther())  # => The victorious cat says grrr
try
    fight(Panther(), Lion("RAWR"))  
    # => ERROR: MethodError: no method matching fight(::Panther, ::Lion)
    # => Closest candidates are:
    # =>   fight(::Tiger, ::Lion) at ...
    # =>   fight(::Tiger, ::Cat) at ...
    # =>   fight(::Lion, ::Cat) at ...
    # => ...
catch e
    println(e)
end

# 试试把 Cat 放在前面
fight(c::Cat, l::Lion) = println("The cat beats the Lion")
# => fight (generic function with 4 methods)

# 由于无法判断该使用哪个 fight 方法，而产生了错误
try
    fight(Lion("RAR"), Lion("brown", "rarrr"))
    # => ERROR: MethodError: fight(::Lion, ::Lion) is ambiguous. Candidates:
    # =>   fight(c::Cat, l::Lion) in Main at ...
    # =>   fight(l::Lion, c::Cat) in Main at ...
    # => Possible fix, define
    # =>   fight(::Lion, ::Lion)
    # => ...
catch e
    println(e)
end
# 在不同版本的 Julia 中错误信息可能有所不同

fight(l::Lion, l2::Lion) = println("The lions come to a tie") 
# => fight (generic function with 5 methods)
fight(Lion("RAR"), Lion("brown", "rarrr"))  # => The lions come to a tie


# 深入编译器之后
# 你还可以看看 llvm 以及它生成的汇编代码

square_area(l) = l * l  # => square_area (generic function with 1 method)
square_area(5)  # => 25

# 当我们喂给 square_area 一个整数时会发生什么？
code_native(square_area, (Int32,), syntax = :intel)
    #         .text
    # ; Function square_area {
    # ; Location: REPL[116]:1       # 函数序言 (Prologue)
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: int.jl:54
    #         imul    ecx, ecx      # 求 l 的平方，并把结果放在 ECX 中
    # ;}
    #         mov     eax, ecx
    #         pop     rbp           # 还原旧的基址指针(base pointer)
    #         ret                   # 返回值放在 EAX 中
    #         nop     dword ptr [rax + rax]
    # ;}
# 使用 syntax 参数指定输出语法。默认为 AT&T 格式，这里指定为 Intel 格式

code_native(square_area, (Float32,), syntax = :intel)
    #         .text
    # ; Function square_area {
    # ; Location: REPL[116]:1
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: float.jl:398
    #         vmulss  xmm0, xmm0, xmm0  # 标量双精度乘法 (AVX)
    # ;}
    #         pop     rbp
    #         ret
    #         nop     word ptr [rax + rax]
    # ;}

code_native(square_area, (Float64,), syntax = :intel)
    #         .text
    # ; Function square_area {
    # ; Location: REPL[116]:1
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm0, xmm0, xmm0  # 标量双精度乘法 (AVX)
    # ;}
    #         pop     rbp
    #         ret
    #         nop     word ptr [rax + rax]
    # ;}

# 注意！只要参数中有浮点数，Julia 就会使用浮点指令
# 让我们计算一下圆的面积
circle_area(r) = pi * r * r # => circle_area (generic function with 1 method)
circle_area(5)  # => 78.53981633974483

code_native(circle_area, (Int32,), syntax = :intel)
    #         .text
    # ; Function circle_area {
    # ; Location: REPL[121]:1
    #         push    rbp
    #         mov     rbp, rsp
    # ; Function *; {
    # ; Location: operators.jl:502
    # ; Function *; {
    # ; Location: promotion.jl:314
    # ; Function promote; {
    # ; Location: promotion.jl:284
    # ; Function _promote; {
    # ; Location: promotion.jl:261
    # ; Function convert; {
    # ; Location: number.jl:7
    # ; Function Type; {
    # ; Location: float.jl:60
    #         vcvtsi2sd       xmm0, xmm0, ecx     # 从内存中读取整数 r
    #         movabs  rax, 497710928              # 读取 pi
    # ;}}}}}
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm1, xmm0, qword ptr [rax] # pi * r
    #         vmulsd  xmm0, xmm1, xmm0            # (pi * r) * r
    # ;}}
    #         pop     rbp
    #         ret
    #         nop     dword ptr [rax]
    # ;}

code_native(circle_area, (Float64,), syntax = :intel)
    #         .text
    # ; Function circle_area {
    # ; Location: REPL[121]:1
    #         push    rbp
    #         mov     rbp, rsp
    #         movabs  rax, 497711048
    # ; Function *; {
    # ; Location: operators.jl:502
    # ; Function *; {
    # ; Location: promotion.jl:314
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm1, xmm0, qword ptr [rax]
    # ;}}}
    # ; Function *; {
    # ; Location: float.jl:399
    #         vmulsd  xmm0, xmm1, xmm0
    # ;}
    #         pop     rbp
    #         ret
    #         nop     dword ptr [rax + rax]
    # ;}
</code>
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