Fixed nothing to NULL MySQL problem with workround trhough missing.

src/manifestIO.jl

@@ -316,7 +316,6 @@ This will insert each row of `df` into the `geographical_features` table in the
 function custom_load(conn::MySQL.Connection, table_name::String, df::DataFrame)
     # Preprocess DataFrame to ensure data integrity
     preprocess_dataframe!(df)
-    println(df)
     
     col_names = join(["`$(name)`" for name in names(df)], ", ")
     placeholders = join(["?" for _ in 1:length(names(df))], ", ")
@@ -324,8 +323,8 @@ function custom_load(conn::MySQL.Connection, table_name::String, df::DataFrame)
     prepared_stmt = DBInterface.prepare(conn, insert_stmt)
     
     for row in eachrow(df)
-        # Convert row to Tuple, directly handling `nothing` (for NULL handling in SQL)
-        values = Tuple([x === nothing ? nothing : x for x in row])
+        # Convert row to Tuple, directly handling `missing` (for NULL handling in SQL)
+        values = Tuple([x === missing ? missing : x for x in row])
         DBInterface.execute(prepared_stmt, values)
     end
 end
@@ -369,7 +368,7 @@ function preprocess_dataframe!(df::DataFrame)
         col_type = eltype(df[!, col])
 
         # Convert missing values to nothing for SQL NULL compatibility
-        df[!, col] = map(x -> ismissing(x) ? nothing : x, df[!, col])
+        df[!, col] = map(x -> ismissing(x) ? missing : x, df[!, col])
 
         # Clamp numeric values if range is defined for the column type
         if haskey(SQL_RANGES, col_type)
@@ -379,7 +378,7 @@ function preprocess_dataframe!(df::DataFrame)
 
         # Replace NaN and Inf with nothing in numeric columns
         if col_type <: AbstractFloat
-            df[!, col] = map(x -> isfinite(x) ? x : nothing, df[!, col])
+            df[!, col] = map(x -> isfinite(x) ? x : missing, df[!, col])
         end
     end
 end