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convert-json-util

v1.0.8

Published

A utility for converting JSON data to various formats

Downloads

142

Readme

# Convert JSON Utility

## Description

`convert-json-util` is a versatile utility for converting JSON data into various formats such as CSV, YAML, XML, XLSX, and TXT. This tool is designed to make it easy to transform JSON data into different file types for use in data sharing, reporting, and more. It supports validation using both [Zod](https://github.com/colinhacks/zod) schemas and custom schemas, and also allows conversion without any validation if no schema is provided.

## Installation

To install the package, use npm:

```sh
npm install convert-json-util

Usage

Importing the Module

To use the convertJson function, import it from the package:

import { convertJson } from 'convert-json-util';
import { ZodSchema } from 'zod';

Function Signature

convertJson(jsonData: any, schema?: any, saveToFile?: boolean, fileName?: string, fileType?: 'csv' | 'yaml' | 'xml' | 'xlsx' | 'txt'): { success: boolean, fileData?: string | Buffer, errors?: string[] }

Parameters

  • jsonData: The JSON data to be converted. It can be an object or an array of objects.
  • schema (optional): The schema used to validate the JSON data. This can be a Zod schema, any custom schema with parse, safeParse, or validate methods, or it can be omitted entirely for conversion without validation.
  • saveToFile (optional): A boolean indicating whether to save the converted data to a file. Default is false.
  • fileName (optional): The name of the file to save the converted data. Default is "data".
  • fileType (optional): The type of file to convert the data to. Options are 'csv', 'yaml', 'xml', 'xlsx', and 'txt'. Default is 'txt'.

Return Value

The function returns an object with the following properties:

  • success: A boolean indicating whether the conversion was successful.
  • fileData (optional): The converted data as a string or Buffer. This is only present if success is true.

Examples

Example 1: Converting JSON to CSV with Zod schema and saving to a file

import { convertJson } from 'convert-json-util';
import { z } from 'zod';

// Define a Zod schema for the JSON data
const schema = z.object({
    name: z.string(),
    age: z.number(),
    email: z.string().email()
});

const jsonData = [
    { name: "John Doe", age: 30, email: "[email protected]" },
    { name: "Jane Doe", age: 25, email: "[email protected]" }
];

const result = convertJson(jsonData, schema, true, "users", "csv");
console.log(result);

Example 2: Converting JSON to YAML without saving to a file using a custom schema

import { convertJson } from 'convert-json-util';

// Define a custom schema for the JSON data
const customSchema = {
    validate: (data: any) => {
        const errors: string[] = [];
        if (typeof data.name !== 'string') {
            errors.push('Invalid type for name. Expected string.');
        }
        if (typeof data.age !== 'number') {
            errors.push('Invalid type for age. Expected number.');
        }
        const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
        if (typeof data.email !== 'string' || !emailRegex.test(data.email)) {
            errors.push('Invalid email format.');
        }
        if (errors.length > 0) {
            return { success: false, errors };
        }
        return { success: true, data };
    }
};

const jsonData = { name: "John Doe", age: 30, email: "[email protected]" };

const result = convertJson(jsonData, customSchema, false, "user", "yaml");
console.log(result);

Example 3: Converting JSON to TXT without any validation

import { convertJson } from 'convert-json-util';

const jsonData = { name: "John Doe", age: 30, email: "[email protected]" };

const result = convertJson(jsonData, null, false, "user", "txt");
console.log(result);

Handling Errors

If an error occurs during conversion, the function will:

  • Print the error message to the console using console.error.
  • Throw an error to stop further execution, allowing it to be caught and handled by the calling code.

Supported File Types

  • CSV: Comma-separated values, useful for spreadsheets and data analysis.
  • YAML: A human-readable data serialization format.
  • XML: Extensible Markup Language, useful for structured data exchange.
  • XLSX: Excel spreadsheet format, useful for advanced data analysis and reporting.
  • TXT: Plain text format, useful for simple data storage and sharing.

License

This project is licensed under the MIT License. See the LICENSE file for details.