JSON TO CSV / CSV TO JSON

// JSON to CSV in Modern JavaScript
function jsonToCsv(jsonArray) {
  if (!jsonArray || !jsonArray.length) return '';
  const headers = Object.keys(jsonArray[0]);
  const csvRows = [
    headers.join(','), // Header Row
    ...jsonArray.map(row => 
      headers.map(fieldName => {
        const val = row[fieldName] ?? '';
        const str = typeof val === 'object' ? JSON.stringify(val) : String(val);
        return str.includes(',') || str.includes('\n') || str.includes('"')
          ? `"${str.replace(/"/g, '""')}"`
          : str;
      }).join(',')
    )
  ];
  return csvRows.join('\n');
}

import pandas as pd
import json

# 1. JSON to CSV with Flattening
with open("data.json", "r", encoding="utf-8") as f:
    raw_data = json.load(f)
df = pd.json_normalize(raw_data) # Automatic Nested Flattening
df.to_csv("output.csv", index=False, encoding="utf-8-sig")

# 2. CSV to JSON
df_csv = pd.read_csv("output.csv")
json_result = df_csv.to_json(orient="records", force_ascii=False, indent=2)
print(json_result)

# JSON to CSV using jq CLI tool
cat users.json | jq -r '(.[0] | keys_unsorted) as $keys | $keys, map([.[$keys[]]])[] | @csv' > users.csv

# CSV to JSON using csvkit CLI tool
csvjson users.csv | jq '.' > users.json

package main

import (
	"encoding/csv"
	"encoding/json"
	"os"
)

type User struct {
	ID   string `json:"id"`
	Name string `json:"name"`
}

func main() {
	file, _ := os.Create("output.csv")
	defer file.Close()
	writer := csv.NewWriter(file)
	defer writer.Flush()

	writer.Write([]string{"id", "name"})
	writer.Write([]string{"101", "Alpha Project"})
}