drop JSON1 and 2

Author: dehann

Project.toml

@@ -18,8 +18,6 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
 FunctionalStateMachine = "3e9e306e-7e3c-11e9-12d2-8f8f67a2f951"
-JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
-JSON2 = "2535ab7d-5cd8-5a07-80ac-9b1792aadce3"
 JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
 KernelDensityEstimate = "2472808a-b354-52ea-a80e-1658a3c6056d"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

src/IncrementalInference.jl

@@ -41,7 +41,6 @@ using Dates,
   ProgressMeter,
   DocStringExtensions,
   FunctionalStateMachine,
-  JSON2,  
   JSON3,
   Combinatorics,
   UUIDs,

src/Serialization/services/SerializationMKD.jl

@@ -75,7 +75,7 @@ end
 function Base.convert(::Type{String}, mkd::ManifoldKernelDensity)
   #
   packedMKD = packDistribution(mkd)
-  return JSON2.write(packedMKD)
+  return JSON3.write(packedMKD)
 end
 
 # Use general dispatch
@@ -86,7 +86,7 @@ end
 #  https://discourse.julialang.org/t/converting-string-to-datatype-with-meta-parse/33024/2
 #  https://discourse.julialang.org/t/is-there-a-way-to-import-modules-with-a-string/15723/6
 function Base.convert(::Type{<:ManifoldKernelDensity}, str::AbstractString)
-  dtr = JSON2.read(str, PackedManifoldKernelDensity)
+  dtr = JSON3.read(str, PackedManifoldKernelDensity)
   return unpackDistribution(dtr)
 end
 

src/Serialization/services/SerializingDistributions.jl

@@ -170,18 +170,18 @@ end
 # FIXME ON FIRE, must deprecate nested JSON written fields in all serialization
 # TODO is string necessary, because unpacking templated e.g. PackedType{T} has problems, see DFG #668
 function convert(::Type{String}, dtr::StringThemSamplableBeliefs)
-  return JSON2.write(packDistribution(dtr))
+  return JSON3.write(packDistribution(dtr))
 end
 
 function convert(::Type{<:SamplableBelief}, str_obj::AbstractString)
   #
 
   # go from stringified to generic packed (no type info)
-  _pck = JSON2.read(str_obj)
+  _pck = JSON3.read(str_obj)
   # NOTE, get the packed type from strong assumption that field `_type` exists in the 
-  T = DFG.getTypeFromSerializationModule(_pck[:_type])
+  T = DFG.getTypeFromSerializationModule(_pck._type)
   # unpack again to described packedType
-  pckT = JSON2.read(str_obj, T)
+  pckT = JSON3.read(str_obj, T)
 
   # unpack to regular <:SamplableBelief
   return unpackDistribution(pckT)

src/services/FGOSUtils.jl

@@ -606,7 +606,7 @@ Fetch and unpack JSON dictionary stored as a data blob.
 function fetchDataJSON(dfg::AbstractDFG, varsym::Symbol, lbl::Symbol)
   gde, rawData = getData(dfg, varsym, lbl)
   if gde.mimeType == "application/json/octet-stream"
-    JSON2.read(IOBuffer(rawData))
+    JSON3.read(IOBuffer(rawData))
   else
     error("Unknown JSON Blob format $(gde.mimeType)")
   end

test/testPackingMixtures.jl

@@ -2,7 +2,7 @@
 
 using IncrementalInference
 using DistributedFactorGraphs
-using JSON
+# using JSON
 
 
 ##
@@ -27,7 +27,7 @@ pf = packFactor(fg, getFactor(fg, :x0x1f1))
 
 ##
 
-pf_ = JSON.json(pf)
+pf_ = JSON3.write(pf)
 
 
 ##