Installation: julia> Pkg.add("JSON")
import JSON
# JSON.parse - string or stream to Julia data structures
s = "{\"a_number\" : 5.0, \"an_array\" : [\"string\", 9]}"
j = JSON.parse(s)
# Dict{AbstractString,Any} with 2 entries:
# "an_array" => {"string",9}
# "a_number" => 5.0
# JSON.json - Julia data structures to a string
JSON.json([2,3])
# "[2,3]"
JSON.json(j)
# "{\"an_array\":[\"string\",9],\"a_number\":5.0}"JSON.print(io::IO, s::AbstractString)
JSON.print(io::IO, s::Union{Integer, AbstractFloat})
JSON.print(io::IO, n::Void)
JSON.print(io::IO, b::Bool)
JSON.print(io::IO, a::Associative)
JSON.print(io::IO, v::AbstractVector)
JSON.print{T, N}(io::IO, v::Array{T, N})Writes a compact (no extra whitespace or identation) JSON representation to the supplied IO.
json(a::Any)Returns a compact JSON representation as an AbstractString.
JSON.parse(s::AbstractString; dicttype=Dict)
JSON.parse(io::IO; dicttype=Dict)
JSON.parsefile(filename::AbstractString; dicttype=Dict, use_mmap=true)Parses a JSON AbstractString or IO stream into a nested Array or Dict.
The dicttype indicates the dictionary type (<: Associative) that
JSON objects are parsed to. It defaults to Dict (the built-in Julia
dictionary), but a different type can be passed to, for example,
provide a desired ordering. For example, if you import DataStructures
(assuming the DataStructures
package is
installed), you can pass dicttype=DataStructures.OrderedDict to
maintain the insertion order of the items in the object.
JSON.lower(p::Point2D) = [p.x, p.y]Define a custom serialization rule for a particular data type. Must return a
value that can be directly serialized; see help for more details. Note that
JSON._print is deprecated and will eventually been discontinued.