update

src/interface.jl

@@ -6,7 +6,7 @@ export noNegative!, randomWithProb, randomChoiceWithProb, findIndex, limitvalue,
         matMul_3Dto4D_batchwise, isNotEqual, linearToCartesian, vectorMax,
         multiply_last, multiplyRandomElements, replaceElements, replaceElements!, isBetween,
         isLess, allTrue, getStringBetweenCharacters, JSON3read_stringKey, mkDictPath!, 
-        getDictPath, dataframeToCSV, dfToJSONRows
+        getDictPath
 
 using JSON3, DataStructures, Distributions, Random, Dates, UUIDs, MQTTClient, DataFrames, CSV
 using ..util, ..communication
@@ -1149,63 +1149,6 @@ function getDictPath(dict::Dict, keys::Vector)
 end
 
 
-""" Convert a dataframe into CSV.
-
-# Arguments
-  - `df::DataFrame`
-    A connection object to Postgres database
-    
-# Return
-  - `result::String`
-
-# Example
-```jldoctest
-julia> using DataFrames, GeneralUtils
-julia> df = DataFrame(A=1:3, B=5:7, fixed=1)
-julia> result = GeneralUtils.dataframeToCSV(df)
-```
-
-# Signature
-"""
-function dataframeToCSV(df::DataFrame)
-  # Create an IOBuffer to capture the output
-  io = IOBuffer()
-  CSV.write(io, df)
-  dfStr = String(take!(io))
-  return dfStr
-end
-
-""" Convert a DataFrame into a list of JSON rows.
-
-#  Arguments
-  - `df::DataFrame` 
-    The input DataFrame to be converted.
-
-#  Return
-  - `rows::Vector{Dict{String, Any}}` 
-    A vector of dictionaries, where each dictionary represents a row in JSON format.
-
-#  Example
-  ```jldoctest
-  julia> using DataFrame, JSON3
-  julia> df = DataFrame(A = [1, 2, 3], B = ["apple", "banana", "cherry"])
-  julia> json_rows = dfToJSONRows(df)
-  ```
-
-#  Signature
-"""
-function dfToJSONRows(df::DataFrame)
-  rows = []
-  for row in eachrow(df)
-      json_row = Dict{String, Any}()
-      for col in names(df)
-          json_row[col] = row[col]
-      end
-      push!(rows, json_row)
-  end
-  return rows
-end
-