JSON Viewerv1.0.0

Paste raw JSON text into the input area or load a .json file to parse and explore the data as a collapsible tree structure. Each object and array in the hierarchy renders as a toggleable node, allowing you to drill into deeply nested structures without losing context. Key names, string values, numeric values, boolean values, and null entries are displayed with semantic markup so each data type is distinguishable at a glance.

• Paste or type valid JSON into the Paste or type JSON below textarea. Alternatively, click Or load from a .json file to upload a local .json file from disk.
• Click View to parse the input and render the collapsible tree. If the JSON is invalid, an error notification appears indicating the parse error and approximate location.
• Click any object or array node label in the tree to toggle that branch open or closed. The Expand All and Collapse All buttons toggle every node at once for quick overview or detail inspection.
• Open Settings to configure the Indent Size (2, 4, or 8 spaces, or tab) used by the beautifier and the Default Collapse Depth that controls how many nesting levels are expanded on initial render.
• Click Beautify to reformat the raw input with consistent indentation. Click Minify to compress the JSON onto a single line with no whitespace, useful for copying into API requests or configuration fields.
• Click Copy Formatted to place the beautified version of the current JSON onto the clipboard.
• Type a term into the Filter keys or values search field to highlight matching keys and values throughout the tree. Branches containing matches remain visible while non-matching branches collapse, making it straightforward to locate specific data points in large documents.
• The Statistics section displays the total number of keys, the maximum nesting depth, the total number of values, and the byte size of the raw input, providing a quick structural summary.
• Click Reset to clear all input, output, search terms, and saved state, returning every field to its default value.

Structured JSON data appears throughout software development, data engineering, API integration, and configuration management. A dedicated viewer that renders collapsible trees, provides search, and reports structural statistics accelerates debugging and review workflows across many domains.

• API Development: Inspect response payloads from REST or GraphQL endpoints by pasting the raw JSON to verify field names, nesting structure, and data types before writing client-side parsing logic.
• Configuration Review: Load application configuration files (package.json, tsconfig.json, Terraform state) to explore settings hierarchies and confirm values without opening a code editor.
• Data Engineering: Examine exported dataset samples in JSON format to validate schema consistency, check for unexpected null values, and measure nesting depth before building ETL pipelines.
• Quality Assurance: Compare expected and actual JSON outputs during test runs by beautifying both with the same indent settings, making structural differences visible in a side-by-side diff.
• Education: Demonstrate JSON data structures to students by pasting example objects and arrays, expanding and collapsing branches to illustrate how nested data maps to programming language constructs like dictionaries and lists.
• Log Analysis: Parse structured log entries emitted in JSON Lines format one record at a time, using the search filter to locate specific request IDs, error codes, or timestamps within verbose payloads.
• Database Administration: Inspect BSON-exported MongoDB documents or CouchDB responses to verify document structure, embedded arrays, and reference fields without running additional queries.
• DevOps and Infrastructure: Review Kubernetes resource definitions, AWS CloudFormation outputs, or CI/CD pipeline artifacts stored as JSON to trace configuration values across multi-level nesting before applying changes to production environments.