You can format and validate JSON without sending it to a website: use VS Code, Python’s built-in JSON tools, or jq on your device. A successful parse confirms that the document follows JSON syntax; it does not prove that the data has the fields or values a particular application requires. For sensitive content, also check whether any schema lookup or browser feature contacts a remote service.
Choose a local workflow
| Tool | Best for | What it checks | Network consideration |
|---|---|---|---|
| VS Code | Editing project files and seeing errors as you work | Formatting, syntax diagnostics, and optional JSON Schema feedback | Remote schema downloads can be controlled in settings. |
| Python | One-off files, scripts, and local checks | Parsing and pretty-printing with the standard-library JSON module | Processes local input; no website is required. |
| jq | Command-line checks, pipelines, and automation | Parsing and JSON transformations | Runs locally on files or standard input. |
| Browser formatter | Quick formatting when the page’s data handling has been verified | Depends on the tool | Confirm that the JSON is not sent over the network and avoid remote save or share features. |
Format and validate a JSON file in VS Code
- Open the
.jsonfile in VS Code. - Run Format Document: press
Shift+Alt+Fon Windows orShift+Option+Fon macOS. Review the file for syntax diagnostics. - If you need to check required properties, types, or allowed values, associate an appropriate JSON Schema through user or workspace settings, or a workspace schema file. VS Code can provide structural and value feedback for an associated schema: VS Code JSON editing documentation.
- Check the language mode. VS Code’s JSONC mode permits comments and trailing commas for configuration files; strict JSON does not. If another program will read the file as JSON, use JSON mode and confirm it with a strict parser.
For a workflow that must not make schema-related network requests, keep the schema local or disable HTTP/HTTPS schema downloads with the json.schemaDownload.enable setting. An otherwise local editing workflow may contact the network to retrieve a remote schema.
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Check JSON with Python
Python’s standard-library json module can parse and pretty-print JSON. To check a local file without writing formatted output, use:
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python -m json.tool file.json > /dev/nullOn systems where /dev/null is unavailable, direct the output to an appropriate null device or use the interpreter’s documented command-line behavior. A parse error identifies where the input failed; Python’s documentation demonstrates line, column, and character-offset details. The current documentation cited here is for Python 3.14.8: Python JSON documentation.
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Command-line spellings and options can vary with Python versions. The Python documentation shows the python -m json shell form, while python -m json.tool is also referenced by a validator guide. If flags or exact behavior matter, check python -m json.tool --help or the documentation for the interpreter installed on your machine.
Validate JSON with jq
For a local syntax check with jq, run:
jq empty file.jsonThe command parses the file without printing a transformed document. A valid file exits successfully; invalid input produces an error and a nonzero exit status. It can also read standard input, making it useful in scripts and pipelines. See the jq 1.8 manual for the tool’s JSON processing options.
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Understand what each kind of validation proves
- Formatting changes whitespace and indentation to make data easier to read. It does not establish that the data is meaningful or correct for an application.
- Syntax validation checks whether a parser can read the document as JSON. It catches problems such as malformed quotes, commas, or brackets.
- Schema validation checks parsed data against an explicit structure and constraints, such as expected properties and value types. The JSON Schema getting-started guide explains how schemas describe and validate data.
- Application validation means checking any further rules imposed by the program that consumes the file. A parser or schema check alone may not establish that the application will accept or correctly use the data.
Use browser formatters cautiously with sensitive data
A browser formatter may process text locally, but “local” is an implementation claim, not something to infer from a privacy statement alone. For example, jsonfmt.dev describes its toolkit as a self-contained HTML file that works offline: jsonfmt.dev. That description applies to that tool, not to browser formatters generally.
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- Before pasting sensitive JSON, inspect the tool’s stated data flow and, when warranted, the browser’s developer tools network panel to see whether requests include the content. A security guide describes this network-panel check: JSON Formatter security information.
- A web page and its scripts must be downloaded before they can run in the browser unless you already have a local copy. If the tool supports it, saving a self-contained page and then working offline can reduce reliance on a server; offline behavior alone is not a substitute for checking how the tool handles data.
- Do not use save, history, or share-link features for sensitive JSON unless you understand where the content goes. A shareable URL may expose data even if formatting itself happens locally.
Account for file size and offline requirements
- Large documents can strain browser memory or become slow to process. For multi-megabyte files, a local command-line tool may be more practical than pasting into a browser page.
- Python’s documentation warns that parsing untrusted input can consume substantial CPU and memory. Limit input size when checking files from untrusted sources.
- If the workflow must stay offline, use local software and local schemas. In VS Code, remote schema retrieval is a separate network consideration from editing the JSON file itself.
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