Drop JSON2 dependancy

Author: Affie

Project.toml

@@ -9,7 +9,6 @@ Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
-JSON2 = "2535ab7d-5cd8-5a07-80ac-9b1792aadce3"
 JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 ManifoldsBase = "3362f125-f0bb-47a3-aa74-596ffd7ef2fb"
@@ -32,7 +31,6 @@ Distributions = "0.23, 0.24, 0.25"
 DocStringExtensions = "0.8, 0.9"
 GraphPlot = "0.5.0"
 Graphs = "1.4"
-JSON2 = "0.3"
 JSON3 = "1"
 ManifoldsBase = "0.12, 0.13, 0.14"
 OrderedCollections = "1.4"

docs/src/variable_factor_serialization.md

@@ -36,7 +36,7 @@ upFactor = unpackFactor(dfg, pFactor, IncrementalInference)
 # to make it useable. Please add an issue if this poses a problem or causes issues.
 ```
 
-As a more complex example, we can use JSON2 to stringify the data and write it to a folder of files as FileDFG does:
+As a more complex example, we can use JSON3 to stringify the data and write it to a folder of files as FileDFG does:
 
 ```julia
 using DistributedFactorGraphs
@@ -50,19 +50,19 @@ x0 = addVariable!(dfg, :x0, Pose2)
 # Add at a fixed location PriorPose2 to pin :x0 to a starting location (10,10, pi/4)
 prior = addFactor!(dfg, [:x0], PriorPose2( MvNormal([10; 10; 1.0/8.0], Matrix(Diagonal([0.1;0.1;0.05].^2))) ) )
 
-# Slightly fancier example: We can use JSON2, we can serialize to a string
+# Slightly fancier example: We can use JSON3, we can serialize to a string
 varFolder = "/tmp"
 for v in getVariables(dfg)
     vPacked = packVariable(dfg, v)
     io = open("$varFolder/$(v.label).json", "w")
-    JSON2.write(io, vPacked)
+    JSON3.write(io, vPacked)
     close(io)
 end
 # Factors
 for f in getFactors(dfg)
     fPacked = packFactor(dfg, f)
     io = open("$folder/factors/$(f.label).json", "w")
-    JSON2.write(io, fPacked)
+    JSON3.write(io, fPacked)
     close(io)
 end
 ```

src/DistributedFactorGraphs.jl

@@ -22,7 +22,6 @@ using Dates
 using TimeZones
 using Distributions
 using Reexport
-import JSON2 # only for unpacking factorData via NamedTuples, TODO drop dependency
 using JSON3
 using StructTypes
 using LinearAlgebra

src/services/Serialization.jl

@@ -234,7 +234,7 @@ function packFactor(dfg::AbstractDFG, f::DFGFactor)
     return props
 end
 
-function reconstFactorData() end
+function reconstFactorData end
 
 function decodePackedType(dfg::AbstractDFG, varOrder::AbstractVector{Symbol}, ::Type{T}, packeddata::GenericFunctionNodeData{PT}) where {T<:FactorOperationalMemory, PT}
     #
@@ -248,24 +248,11 @@ function decodePackedType(dfg::AbstractDFG, varOrder::AbstractVector{Symbol}, ::
     return factordata
 end
 
-# TODO: REFACTOR THIS AS A JSON3 STRUCT DESERIALIZER.
 function fncStringToData(packtype::Type{<:AbstractPackedFactor}, data::String)
 
-    # Convert string to Named Tuples for kwargs
-    # packed_ = JSON3.read(data, GenericFunctionNodeData{packtype})
-    fncData = JSON3.read(data) #, NamedTuple) # Dict{String,Any})
-
-
-    # data isa AbstractString ? JSON2.read(data) : data
-    # JSON3.generate_type(packed.fnc)
-    # JSON3.generate_type(fncData["fnc"])
-    
-    # TODO use kwdef constructors instead,
-    # @info "user factor" fncData["fnc"]
-    restring = JSON3.write(fncData["fnc"])
-    # @show restring
-    # packT = JSON3.read(restring, packtype)
-    packT = packtype(;JSON2.read(restring)...)
+    # Read string as JSON object to use as kwargs
+    fncData = JSON3.read(data)
+    packT = packtype(;fncData.fnc...)
 
     packed = GenericFunctionNodeData{packtype}(
         fncData["eliminated"],
@@ -281,7 +268,7 @@ function fncStringToData(packtype::Type{<:AbstractPackedFactor}, data::String)
     )
     return packed
 end
-fncStringToData(packtype::Type{<:AbstractPackedFactor}, data::NamedTuple) = error("Who is calling deserialize factor with NamedTuple, likely JSON2 somewhere")
+fncStringToData(packtype::Type{<:AbstractPackedFactor}, data::NamedTuple) = error("Who is calling deserialize factor with NamedTuple, likely JSON3 somewhere")
 
 fncStringToData(::Type{T}, data::PackedFunctionNodeData{T}) where {T <: AbstractPackedFactor} = data
 function fncStringToData(fncType::String, data::PackedFunctionNodeData{T}) where {T <: AbstractPackedFactor}

test/runtests.jl

@@ -58,7 +58,7 @@ end
 end
 
 
-if get(ENV, "IIF_TEST", "") == "true"
+if get(ENV, "IIF_TEST", "true") == "true"
 
     # Switch to our upstream test branch.
     Pkg.add(PackageSpec(name="IncrementalInference", rev="upstream/dfg_integration_test"))