JSON CSV XML YAML Converter
What Are Data Serialization Formats
Data serialization formats are standardized ways to represent structured information as text or binary sequences that can be stored in files, transmitted over networks, and reconstructed by software on the receiving end. They solve a fundamental problem in computing: how to move data between programs, systems, and platforms that may be written in different programming languages and running on different operating systems.
The four most common text-based serialization formats in use today are JSON, CSV, XML, and YAML. Each was created to address specific needs and has evolved its own ecosystem of tools, libraries, and best practices. Understanding these formats is essential for anyone working with data, whether you are a software developer, data analyst, system administrator, or technical writer.
The key distinction between these formats lies in the trade-offs they make between human readability, machine parseability, expressiveness, and verbosity. JSON strikes a balance between all four. CSV sacrifices expressiveness for simplicity. XML prioritizes expressiveness and validation at the cost of verbosity. YAML maximizes human readability but introduces complexity in its whitespace-sensitive parsing.
JSON Explained (RFC 8259)
JSON (JavaScript Object Notation) was formalized by Douglas Crockford in the early 2000s and standardized as RFC 8259 by the IETF. Despite its JavaScript origins, JSON is language-independent and supported by virtually every programming language through native or third-party libraries.
A JSON document is built from two structures: objects (unordered sets of key-value pairs enclosed in curly braces) and arrays (ordered lists of values enclosed in square brackets). Values can be strings (double-quoted), numbers, booleans (true or false), null, objects, or arrays. This recursive structure allows JSON to represent arbitrarily complex nested data.
JSON's strict syntax rules — no trailing commas, no comments, no single quotes, no undefined — make it unambiguous to parse. This strictness is a feature: it eliminates the compatibility issues that plague looser formats. The trade-off is that JSON can feel rigid when used for configuration files where comments are helpful. This limitation led to the creation of formats like JSON5 and JSONC that extend JSON with developer-friendly features.
CSV Format (RFC 4180)
CSV is arguably the most widely used data format in the world. Every spreadsheet application, database management system, and data analysis tool can import and export CSV. The format dates back to the early days of computing, with implementations predating the personal computer era.
RFC 4180 established common rules for CSV: fields are separated by commas, records are separated by line breaks (CRLF), and fields containing commas, double quotes, or line breaks must be enclosed in double quotes. Double quotes within quoted fields are escaped by doubling them (for example, the value She said "hello" becomes "She said ""hello""").
Despite its simplicity, CSV has notable limitations. There is no standard way to represent nested or hierarchical data. Data types are ambiguous — the string "123" and the number 123 look identical. Character encoding is unspecified. These limitations mean that converting from richer formats like JSON or XML to CSV inevitably involves flattening and loss of structure.
XML Structure
XML (Extensible Markup Language) was published as a W3C Recommendation in 1998. It was designed to be both human-readable and machine-readable, with a self-describing structure where element names convey meaning. XML documents consist of elements (with opening and closing tags), attributes (key-value pairs within opening tags), text content, and processing instructions.
XML's greatest strengths are its support for namespaces (avoiding name collisions when combining documents), schemas (XSD for defining and validating document structure), and transformation languages (XSLT for converting XML to other formats). These features make XML the format of choice for complex enterprise integrations, document standards (XHTML, SVG, MathML), and protocols (SOAP).
The main criticism of XML is its verbosity. A simple key-value pair like {"name": "John"} in JSON requires <name>John</name> in XML — significantly more characters. For large datasets, this verbosity translates to increased file sizes and network transfer times.
YAML Configuration Files
YAML was first released in 2001 and has become the de facto standard for configuration files in the DevOps ecosystem. YAML's design philosophy prioritizes human readability over machine efficiency. Indentation defines structure, colons separate keys from values, and dashes denote list items.
YAML supports all the data types JSON does plus additional features like comments (prefixed with #), multi-line strings (using | for literal blocks or > for folded blocks), and anchors/aliases for reusing data within a document. YAML also supports multiple documents in a single file, separated by triple dashes (---).
The most common use cases for YAML include Docker Compose files, Kubernetes manifests, GitHub Actions workflows, Ansible playbooks, and application configuration files. YAML's readability makes it ideal for files that are frequently read and edited by humans, while JSON is preferred for machine-to-machine data exchange.
When to Use Each Format
Choosing the right format depends on your specific requirements. Use JSON for API responses, web application data exchange, and programmatic configuration where strict parsing is needed. Use CSV for tabular data that will be imported into spreadsheets or databases, or when you need the smallest possible file size for flat data. Use XML when you need schema validation, namespaces, or compatibility with enterprise systems and legacy integrations. Use YAML for human-edited configuration files, especially in DevOps pipelines and container orchestration.
Consider data complexity as a key factor. Flat, tabular data maps naturally to CSV. Simple key-value structures work well in any format. Deeply nested hierarchical data is best represented in JSON, XML, or YAML. If you need to include metadata alongside data (like XML attributes), XML or YAML may be the better choice.
Converting Between Formats
Converting between serialization formats requires understanding the structural differences and potential data loss at each step. JSON to CSV conversion requires flattening nested objects and arrays into a two-dimensional table. This converter uses dot notation to represent nested paths (for example, user.address.city), which preserves the hierarchy in a flat structure that can be reconstructed later.
JSON to XML conversion maps objects to elements and primitive values to text content. Arrays are handled by repeating the parent element name. Attributes can be represented using a special @ prefix convention. XML to JSON conversion reverses this process but must handle the richer XML data model (attributes, mixed content, namespaces) that has no direct JSON equivalent.
JSON to YAML conversion is the most straightforward since YAML is a superset of JSON. Every valid JSON document is also valid YAML. The conversion primarily reformats the syntax — replacing braces with indentation and removing quotes from keys — improving readability without changing the data structure.
Frequently Asked Questions
Can I convert nested JSON to CSV?
Yes. The converter flattens nested JSON objects using dot notation. For example, {"user": {"name": "John"}} becomes a CSV column header user.name with value John. Arrays are serialized as JSON strings within CSV cells.
Is my data sent to a server?
No. All conversion happens entirely in your browser using JavaScript. No data is transmitted to any server. You can verify this by disconnecting from the internet and confirming the tool still works.
What CSV delimiters are supported?
The converter supports comma, tab, and semicolon delimiters. You can select the delimiter from the options dropdown before converting. Tab-delimited output is sometimes called TSV (Tab-Separated Values).
Does the converter handle large files?
The converter works well with files up to several megabytes. Very large files may slow down depending on your browser and device. For files larger than 10 MB, consider using a command-line tool like jq or csvkit.
What YAML features are supported?
The converter supports key-value pairs, nested objects via indentation, arrays with dash syntax, strings, numbers, booleans, and null values. Advanced features like anchors, aliases, and multi-line strings are supported for output but not parsed on input.
Can I convert XML with attributes?
XML attributes are converted to special keys prefixed with @ when converting to JSON or YAML. For example, <item id="1"> becomes {"@id": "1"}. When converting back to XML, keys starting with @ are restored as attributes.
What is the difference between pretty print and minify?
Pretty print adds indentation and line breaks for readability. Minify removes all unnecessary whitespace to reduce file size, useful for production deployments where bandwidth matters.