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[julia/en] fix for #1483
This commit is contained in:
Keith Miyake
parent
e867dfd7b6
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@ -114,12 +114,12 @@ println("I'm Julia. Nice to meet you!") # => I'm Julia. Nice to meet you!
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####################################################
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# You don't declare variables before assigning to them.
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some_var = 5 # => 5
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some_var # => 5
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someVar = 5 # => 5
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someVar # => 5
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# Accessing a previously unassigned variable is an error
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try
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some_other_var # => ERROR: UndefVarError: some_other_var not defined
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someOtherVar # => ERROR: UndefVarError: someOtherVar not defined
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catch e
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println(e)
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end
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@ -286,62 +286,62 @@ d # => 5
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e # => 4
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# Dictionaries store mappings
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empty_dict = Dict() # => Dict{Any,Any} with 0 entries
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emptyDict = Dict() # => Dict{Any,Any} with 0 entries
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# You can create a dictionary using a literal
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filled_dict = Dict("one" => 1, "two" => 2, "three" => 3)
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filledDict = Dict("one" => 1, "two" => 2, "three" => 3)
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# => Dict{String,Int64} with 3 entries:
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# => "two" => 2, "one" => 1, "three" => 3
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# Look up values with []
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filled_dict["one"] # => 1
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filledDict["one"] # => 1
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# Get all keys
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keys(filled_dict)
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keys(filledDict)
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# => Base.KeySet for a Dict{String,Int64} with 3 entries. Keys:
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# => "two", "one", "three"
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# Note - dictionary keys are not sorted or in the order you inserted them.
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# Get all values
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values(filled_dict)
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values(filledDict)
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# => Base.ValueIterator for a Dict{String,Int64} with 3 entries. Values:
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# => 2, 1, 3
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# Note - Same as above regarding key ordering.
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# Check for existence of keys in a dictionary with in, haskey
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in(("one" => 1), filled_dict) # => true
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in(("two" => 3), filled_dict) # => false
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haskey(filled_dict, "one") # => true
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haskey(filled_dict, 1) # => false
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in(("one" => 1), filledDict) # => true
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in(("two" => 3), filledDict) # => false
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haskey(filledDict, "one") # => true
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haskey(filledDict, 1) # => false
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# Trying to look up a non-existent key will raise an error
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try
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filled_dict["four"] # => ERROR: KeyError: key "four" not found
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filledDict["four"] # => ERROR: KeyError: key "four" not found
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catch e
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println(e)
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end
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# Use the get method to avoid that error by providing a default value
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# get(dictionary, key, default_value)
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get(filled_dict, "one", 4) # => 1
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get(filled_dict, "four", 4) # => 4
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# get(dictionary, key, defaultValue)
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get(filledDict, "one", 4) # => 1
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get(filledDict, "four", 4) # => 4
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# Use Sets to represent collections of unordered, unique values
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empty_set = Set() # => Set(Any[])
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emptySet = Set() # => Set(Any[])
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# Initialize a set with values
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filled_set = Set([1, 2, 2, 3, 4]) # => Set([4, 2, 3, 1])
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filledSet = Set([1, 2, 2, 3, 4]) # => Set([4, 2, 3, 1])
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# Add more values to a set
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push!(filled_set, 5) # => Set([4, 2, 3, 5, 1])
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push!(filledSet, 5) # => Set([4, 2, 3, 5, 1])
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# Check if the values are in the set
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in(2, filled_set) # => true
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in(10, filled_set) # => false
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in(2, filledSet) # => true
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in(10, filledSet) # => false
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# There are functions for set intersection, union, and difference.
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other_set = Set([3, 4, 5, 6]) # => Set([4, 3, 5, 6])
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intersect(filled_set, other_set) # => Set([4, 3, 5])
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union(filled_set, other_set) # => Set([4, 2, 3, 5, 6, 1])
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otherSet = Set([3, 4, 5, 6]) # => Set([4, 3, 5, 6])
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intersect(filledSet, otherSet) # => Set([4, 3, 5])
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union(filledSet, otherSet) # => Set([4, 2, 3, 5, 6, 1])
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setdiff(Set([1,2,3,4]), Set([2,3,5])) # => Set([4, 1])
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####################################################
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@ -349,15 +349,15 @@ setdiff(Set([1,2,3,4]), Set([2,3,5])) # => Set([4, 1])
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####################################################
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# Let's make a variable
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some_var = 5
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someVar = 5
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# Here is an if statement. Indentation is not meaningful in Julia.
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if some_var > 10
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println("some_var is totally bigger than 10.")
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elseif some_var < 10 # This elseif clause is optional.
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println("some_var is smaller than 10.")
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if someVar > 10
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println("someVar is totally bigger than 10.")
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elseif someVar < 10 # This elseif clause is optional.
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println("someVar is smaller than 10.")
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else # The else clause is optional too.
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println("some_var is indeed 10.")
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println("someVar is indeed 10.")
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end
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# => prints "some var is smaller than 10"
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@ -434,8 +434,8 @@ add(5, 6)
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# => 11
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# Compact assignment of functions
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f_add(x, y) = x + y # => f_add (generic function with 1 method)
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f_add(3, 4) # => 7
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fAdd(x, y) = x + y # => fAdd (generic function with 1 method)
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fAdd(3, 4) # => 7
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# Function can also return multiple values as tuple
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fn(x, y) = x + y, x - y # => fn (generic function with 1 method)
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@ -478,67 +478,67 @@ catch e
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end
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# You can define functions that take keyword arguments
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function keyword_args(;k1=4, name2="hello") # note the ;
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function keywordArgs(;k1=4, name2="hello") # note the ;
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return Dict("k1" => k1, "name2" => name2)
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end
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# => keyword_args (generic function with 1 method)
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# => keywordArgs (generic function with 1 method)
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keyword_args(name2="ness") # => ["name2"=>"ness", "k1"=>4]
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keyword_args(k1="mine") # => ["name2"=>"hello", "k1"=>"mine"]
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keyword_args() # => ["name2"=>"hello", "k1"=>4]
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keywordArgs(name2="ness") # => ["name2"=>"ness", "k1"=>4]
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keywordArgs(k1="mine") # => ["name2"=>"hello", "k1"=>"mine"]
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keywordArgs() # => ["name2"=>"hello", "k1"=>4]
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# You can combine all kinds of arguments in the same function
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function all_the_args(normal_arg, optional_positional_arg=2; keyword_arg="foo")
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println("normal arg: $normal_arg")
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println("optional arg: $optional_positional_arg")
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println("keyword arg: $keyword_arg")
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function allTheArgs(normalArg, optionalPositionalArg=2; keywordArg="foo")
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println("normal arg: $normalArg")
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println("optional arg: $optionalPositionalArg")
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println("keyword arg: $keywordArg")
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end
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# => all_the_args (generic function with 2 methods)
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# => allTheArgs (generic function with 2 methods)
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all_the_args(1, 3, keyword_arg=4)
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allAheArgs(1, 3, keywordArg=4)
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# => normal arg: 1
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# => optional arg: 3
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# => keyword arg: 4
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# Julia has first class functions
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function create_adder(x)
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function createAdder(x)
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adder = function (y)
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return x + y
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end
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return adder
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end
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# => create_adder (generic function with 1 method)
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# => createAdder (generic function with 1 method)
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# This is "stabby lambda syntax" for creating anonymous functions
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(x -> x > 2)(3) # => true
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# This function is identical to create_adder implementation above.
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function create_adder(x)
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# This function is identical to createAdder implementation above.
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function createAdder(x)
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y -> x + y
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end
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# => create_adder (generic function with 1 method)
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# => createAdder (generic function with 1 method)
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# You can also name the internal function, if you want
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function create_adder(x)
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function createAdder(x)
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function adder(y)
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x + y
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end
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adder
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end
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# => create_adder (generic function with 1 method)
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# => createAdder (generic function with 1 method)
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add_10 = create_adder(10) # => (::getfield(Main, Symbol("#adder#11")){Int64})
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add10 = createAdder(10) # => (::getfield(Main, Symbol("#adder#11")){Int64})
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# (generic function with 1 method)
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add_10(3) # => 13
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add10(3) # => 13
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# There are built-in higher order functions
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map(add_10, [1,2,3]) # => [11, 12, 13]
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map(add10, [1,2,3]) # => [11, 12, 13]
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filter(x -> x > 5, [3, 4, 5, 6, 7]) # => [6, 7]
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# We can use list comprehensions
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[add_10(i) for i = [1, 2, 3]] # => [11, 12, 13]
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[add_10(i) for i in [1, 2, 3]] # => [11, 12, 13]
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[add10(i) for i = [1, 2, 3]] # => [11, 12, 13]
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[add10(i) for i in [1, 2, 3]] # => [11, 12, 13]
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[x for x in [3, 4, 5, 6, 7] if x > 5] # => [6, 7]
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####################################################
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@ -616,7 +616,7 @@ supertype(SubString) # => AbstractString
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# <: is the subtyping operator
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struct Lion <: Cat # Lion is a subtype of Cat
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mane_color
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maneColor
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roar::AbstractString
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end
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@ -627,7 +627,7 @@ Lion(roar::AbstractString) = Lion("green", roar)
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# This is an outer constructor because it's outside the type definition
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struct Panther <: Cat # Panther is also a subtype of Cat
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eye_color
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eyeColor
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Panther() = new("green")
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# Panthers will only have this constructor, and no default constructor.
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end
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@ -669,14 +669,14 @@ Lion <: Cat # => true
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Panther <: Cat # => true
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# Defining a function that takes Cats
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function pet_cat(cat::Cat)
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function petCat(cat::Cat)
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println("The cat says $(meow(cat))")
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end
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# => pet_cat (generic function with 1 method)
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# => petCat (generic function with 1 method)
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pet_cat(Lion("42")) # => The cat says 42
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petCat(Lion("42")) # => The cat says 42
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try
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pet_cat(tigger) # => ERROR: MethodError: no method matching pet_cat(::Tiger)
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petCat(tigger) # => ERROR: MethodError: no method matching petCat(::Tiger)
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catch e
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println(e)
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end
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@ -695,7 +695,7 @@ fight(tigger, Panther()) # => The orange tiger wins!
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fight(tigger, Lion("ROAR")) # => The orange tiger wins!
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# Let's change the behavior when the Cat is specifically a Lion
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fight(t::Tiger, l::Lion) = println("The $(l.mane_color)-maned lion wins!")
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fight(t::Tiger, l::Lion) = println("The $(l.maneColor)-maned lion wins!")
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# => fight (generic function with 2 methods)
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fight(tigger, Panther()) # => The orange tiger wins!
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@ -744,14 +744,14 @@ fight(Lion("RAR"), Lion("brown", "rarrr")) # => The lions come to a tie
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# Under the hood
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# You can take a look at the llvm and the assembly code generated.
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square_area(l) = l * l # square_area (generic function with 1 method)
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squareArea(l) = l * l # squareArea (generic function with 1 method)
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square_area(5) # => 25
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squareArea(5) # => 25
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# What happens when we feed square_area an integer?
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code_native(square_area, (Int32,), syntax = :intel)
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# What happens when we feed squareArea an integer?
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codeNative(squareArea, (Int32,), syntax = :intel)
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# .text
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# ; Function square_area {
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# ; Function squareArea {
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# ; Location: REPL[116]:1 # Prologue
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# push rbp
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# mov rbp, rsp
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@ -765,9 +765,9 @@ code_native(square_area, (Int32,), syntax = :intel)
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# nop dword ptr [rax + rax]
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# ;}
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code_native(square_area, (Float32,), syntax = :intel)
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codeNative(squareArea, (Float32,), syntax = :intel)
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# .text
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# ; Function square_area {
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# ; Function squareArea {
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# ; Location: REPL[116]:1
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# push rbp
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# mov rbp, rsp
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@ -780,9 +780,9 @@ code_native(square_area, (Float32,), syntax = :intel)
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# nop word ptr [rax + rax]
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# ;}
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code_native(square_area, (Float64,), syntax = :intel)
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codeNative(squareArea, (Float64,), syntax = :intel)
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# .text
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# ; Function square_area {
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# ; Function squareArea {
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# ; Location: REPL[116]:1
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# push rbp
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# mov rbp, rsp
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@ -798,12 +798,12 @@ code_native(square_area, (Float64,), syntax = :intel)
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# Note that julia will use floating point instructions if any of the
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# arguments are floats.
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# Let's calculate the area of a circle
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circle_area(r) = pi * r * r # circle_area (generic function with 1 method)
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circle_area(5) # 78.53981633974483
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circleArea(r) = pi * r * r # circleArea (generic function with 1 method)
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circleArea(5) # 78.53981633974483
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code_native(circle_area, (Int32,), syntax = :intel)
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codeNative(circleArea, (Int32,), syntax = :intel)
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# .text
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# ; Function circle_area {
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# ; Function circleArea {
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# ; Location: REPL[121]:1
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# push rbp
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# mov rbp, rsp
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@ -832,9 +832,9 @@ code_native(circle_area, (Int32,), syntax = :intel)
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# nop dword ptr [rax]
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# ;}
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code_native(circle_area, (Float64,), syntax = :intel)
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codeNative(circleArea, (Float64,), syntax = :intel)
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# .text
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# ; Function circle_area {
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# ; Function circleArea {
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# ; Location: REPL[121]:1
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# push rbp
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# mov rbp, rsp
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