JSON & Data Converter
Paste, load, or drop your data to validate, format, and translate instantly between JSON, XML, CSV, YAML, and Markdown. Spot formatting errors instantly with line-by-line syntax diagnostics.
Saved & Recent Translations (Local)
JSON & Data Converter Guide & FAQs
Structured Data Formats: JSON, XML, YAML, and CSV
Data serialization is the process of converting complex data structures into format strings that can be stored or transmitted across networks. JSON (JavaScript Object Notation) is the dominant format for web APIs due to its lightweight syntax and native integration with JavaScript. It relies on key-value pairs and strict formatting, such as double quotes around keys and no trailing commas.
YAML (YAML Ain't Markup Language) is often preferred for configuration files because of its clean, human-readable structure, relying on indentation instead of brackets and braces. XML (eXtensible Markup Language) is a legacy, tag-based structured format widely used in enterprise and document-based services. CSV (Comma-Separated Values) is a flat, two-dimensional format representing tabular data, ideal for spreadsheets and database imports.
Transforming Structured Formats
This utility enables you to copy, paste, validate, and convert structures client-side. By converting nested objects (JSON/YAML/XML) into flat arrays (CSV) or vice-versa, you can easily bridge the gap between developer configurations and business spreadsheets securely.
Frequently Asked Questions
Why does my JSON fail validation?
Common causes of JSON validation failures include using single quotes instead of double quotes, missing commas between object properties, trailing commas at the end of lists, or unescaped control characters in strings.
What is the main benefit of YAML over JSON?
YAML is significantly easier for humans to read and write. It eliminates structural syntax markers like curly braces, brackets, and quotes, using white space indentation to represent structure, making it ideal for config files.
How does CSV handle fields containing commas?
If a field in a CSV file contains a comma, the entire field must be enclosed in double quotes (e.g., "Smith, John"). The parser will treat the comma inside quotes as literal text rather than a column delimiter.