diff --git a/src/interface.jl b/src/interface.jl
index a7b45eb..bd95562 100644
--- a/src/interface.jl
+++ b/src/interface.jl
@@ -202,13 +202,13 @@ end
   if it is an `AbstractArray` its elements will be processed recursively.
 
 # Keyword Arguments
+- `keytype::Type=Any`
+  The key type for the output Dict. Use `String` for `Dict{String,Any}`, `Symbol` for `Dict{Symbol,Any}`, or `Any` to preserve original key types.
 - `stringkey::Bool=false`
-  If `true`, every dictionary key is converted to `String` via `string(k)`.
-  If `false`, original key objects are preserved (useful when keys are already
-  `String`, `Symbol`, or other types you want to keep).
+  If `true`, every dictionary key is converted to `String` via `string(k)`. This parameter is ignored when `keytype` is explicitly set.
 
 # Return
-- A newly allocated nested structure composed of `Dict{Any,Any}` and
+- A newly allocated nested structure composed of `Dict{keytype,Any}` and
   `Vector{Any}` that mirrors the input shape but uses plain Julia containers.
 
 # Notes
@@ -236,79 +236,46 @@ julia> d = Dict(
 
 julia jsonstring = JSON.json(d)
 julia> A1 = JSON.parse(jsonstring)  # A1 type is JSON.Object
-julia> A2 = dictify(A1)
-Dict{Any,Any} with 3 entries:
+julia> A2 = dictify(A1; keytype=String)
+Dict{String,Any} with 3 entries:
   "a" => 4
   "b" => 6
   "c" => Dict("d"=>7, "e"=>Dict("f"=>"hey", "g"=>Dict("world"=>[1, "2", 3, 4.7])))
 
-julia> A3 = dictify(A1; stringkey=false)  # preserves original key objects
-julia> B1 = dictify(d; stringkey=true)  # convert all keys in to string
-Dict{Any, Any} with 3 entries:
-  "c" => Dict{Any, Any}("e"=>Dict{Any, Any}("f"=>"hey", "g"=>Dict{Any, Any}("world"=>Any[1, "2", 3, Dict{Any, Any}("dd"=>4.7)])), "d"=>7)
-  "b" => 6
-  "a" => 4
-```
+julia> A3 = dictify(A1; keytype=Symbol)
+Dict{Symbol,Any} with 3 entries:
+  :a => 4
+  :b => 6
+  :c => Dict(:d=>7, :e=>Dict("f"=>"hey", "g"=>Dict("world"=>[1, "2", 3, 4.7])))
+
+julia> B1 = dictify(d; keytype=String)
+Dict{String, Any} with 3 entries:
 """
-function dictify(x; stringkey::Bool=false)
+function dictify(x; keytype::Type=Any)
     # Dict-like objects
     if x isa AbstractDict
-        # choose output key type container (String keys when requested)
-        out = Dict{Any,Any}()
+        # choose output key type container
+        out = Dict{keytype,Any}()
         for (k,v) in x
-            newk = stringkey ? string(k) : k
-            out[newk] = dictify(v; stringkey=stringkey)
+            if keytype === String
+                newk = string(k)
+            elseif keytype === Symbol
+                newk = Symbol(string(k))
+            else
+                newk = k
+            end
+            out[newk] = dictify(v; keytype=keytype)
         end
         return out
     # Arrays / vectors: map elements recursively and return a Vector{Any}
     elseif x isa AbstractArray
-        return [dictify(element; stringkey=stringkey) for element in x]
+        return [dictify(element; keytype=keytype) for element in x]
     # everything else: return as-is (primitives, numbers, strings, etc.)
     else
         return x
     end
 end
 
-
-
-
-# ---------------------------------------------- 100 --------------------------------------------- #
-
-""" Array_to_JSON_str(data::AbstractArray)
-
-    encode Array to JSON String
-
-    # Example
-
-        a = [1.23 4.7889; 9987.1 -123.07; -0.0027 -6.75]
-        jsonStr = Array_to_JSON_str(a)
-        jsonStr = "{\"Array\":[[1.23,9987.1,-0.0027],[4.7889,-123.07,-6.75]],\"size\":[3,2]}"
-"""
-function Array_to_JSON_str(data::AbstractArray)
-  d = Dict("Array"=> data, "size"=>size(data))
-  jsonStr = JSON.json(d)
-  return jsonStr
-end
-
-# ---------------------------------------------- 100 --------------------------------------------- #
-
-""" JSON_str_to_Array(json_str::String)
-
-    decode JSON String to Array
-
-    # Example
-
-        jsonStr = "{\"Array\":[[1.23,9987.1,-0.0027],[4.7889,-123.07,-6.75]],\"size\":[3,2]}"
-        a = JSON_str_to_Array(jsonStr)
-
-"""
-function JSON_str_to_Array(jsonStr::String)
-    jsonObj = JSON.parse(jsonStr)
-    a = Array(jsonObj.Array)
-    array = hcat(a...)
-    return array
-end
- 
 # ---------------------------------------------- 100 --------------------------------------------- #
 
 """ Recursively convert dictionary-like variable (e.g. JSON.Object) into a dictionary.
@@ -328,13 +295,11 @@ end
   processed recursively.
 
 # Keyword Arguments
-- `stringkey::Bool=false`
-  If `true`, every dictionary key is converted to `String` via `string(k)`.
-  If `false`, original key objects are preserved (useful when keys are already
-  `String`, `Symbol`, or other types you want to keep).
+- `keytype::Type=Any`
+  The key type for the output Dict. Use `String` for `OrderedDict{String,Any}`, `Symbol` for `OrderedDict{Symbol,Any}`, or `Any` to preserve original key types.
 
 # Return
-- A newly allocated nested structure composed of `OrderedDict{Any,Any}` and
+- A newly allocated nested structure composed of `OrderedDict{keytype,Any}` and
   `Vector{Any}` that mirrors the input shape but uses ordered Julia containers.
 
 # Notes
@@ -361,41 +326,52 @@ julia> d = Dict(
 
 julia jsonstring = JSON.json(d)
 julia> A1 = JSON.parse(jsonstring)  # A1 type is JSON.Object
-julia> A2 = OrderedDict(A1)
-Dict{Any,Any} with 3 entries:
+julia> A2 = ordereddictify(A1; keytype=String)
+OrderedDict{String,Any} with 3 entries:
   "a" => 4
   "b" => 6
-  "c" => Dict("d"=>7, "e"=>Dict("f"=>"hey", "g"=>Dict("world"=>[1, "2", 3, 4.7])))
+  "c" => OrderedDict("d"=>7, "e"=>Dict("f"=>"hey", "g"=>Dict("world"=>[1, "2", 3, 4.7])))
 
-julia> A3 = OrderedDict(A1; stringkey=false)  # preserves original key objects
-julia> B1 = OrderedDict(d; stringkey=true)  # convert all keys in to string
-Dict{Any, Any} with 3 entries:
-  "c" => Dict{Any, Any}("e"=>Dict{Any, Any}("f"=>"hey", "g"=>Dict{Any, Any}("world"=>Any[1, "2", 3, Dict{Any, Any}("dd"=>4.7)])), "d"=>7)
+julia> A3 = ordereddictify(A1; keytype=Symbol)
+OrderedDict{Symbol,Any} with 3 entries:
+  :a => 4
+  :b => 6
+  :c => OrderedDict(:d=>7, :e=>Dict("f"=>"hey", "g"=>Dict("world"=>[1, "2", 3, 4.7])))
+
+julia> B1 = ordereddictify(d; keytype=String)
+OrderedDict{String, Any} with 3 entries:
+  "c" => OrderedDict{String, Any}("e"=>OrderedDict{String, Any}("f"=>"hey", "g"=>OrderedDict{String, Any}("world"=>Any[1, "2", 3, OrderedDict{String, Any}("dd"=>4.7)])), "d"=>7)
   "b" => 6
   "a" => 4
 ```
 Ref. https://github.com/andyferris/Dictionaries.jl
 """
-function ordereddictify(x; stringkey::Bool=false)
+function ordereddictify(x; keytype::Type=Any)
     # Dict-like objects
     if x isa AbstractDict
-        # choose output key type container (String keys when requested)
-        out = OrderedDict{Any,Any}()
+        # choose output key type container
+        out = OrderedDict{keytype,Any}()
         for (k,v) in x
-            newk = stringkey ? string(k) : k
-            out[newk] = ordereddictify(v; stringkey=stringkey)
+            if keytype === String
+                newk = string(k)
+            elseif keytype === Symbol
+                newk = Symbol(string(k))
+            else
+                newk = k
+            end
+            out[newk] = ordereddictify(v; keytype=keytype)
         end
         return out
     # Arrays / vectors: map elements recursively and return a Vector{Any}
     elseif x isa AbstractArray
-        return [ordereddictify(element; stringkey=stringkey) for element in x]
+        return [ordereddictify(element; keytype=keytype) for element in x]
     # everything else: return as-is (primitives, numbers, strings, etc.)
     else
         return x
     end
 end
 
-#------------------------------------------------------------------------------------------------100
+#----------------------------------------------100---------------------------------------------
 
 """
     print time of cpu executtion at the line inwhich this macro is used