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You can format and validate JSON without sending it to an online service: use VS Code, Python’s built-in JSON tools, or jq on your computer. A successful syntax check only proves that the document parses; checking that it has the fields and values an application expects requires a schema or the application’s own validation.

Choose a local workflow

Tool Best suited to Network consideration
VS Code Editing a project or configuration file and seeing errors while you work It can download HTTP/HTTPS schemas unless downloads are disabled or the schema is local.
Python’s standard-library JSON tools Formatting or checking a file from the command line, including in scripts Processes the local file; Python’s documentation cautions that untrusted input can consume substantial CPU and memory.
jq Quick syntax checks, pipelines, and automated workflows Processes local files or standard input.
Browser formatter A quick one-off task when the tool’s local-processing behavior is verified “No upload” depends on the implementation. Inspect network activity and avoid remote save or share features for sensitive data.

Format and check JSON in VS Code

  1. Open the .json file in VS Code and confirm the language mode is JSON if the consuming program expects strict JSON.

  2. Run Format Document: press Shift+Alt+F on Windows or Shift+Option+F on macOS.

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  3. Review the editor’s diagnostics. VS Code can check structure and values against an associated JSON Schema and show errors in the editor. Configure an appropriate schema through user or workspace settings, or a workspace schema file.

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Do not confuse VS Code’s JSONC mode with strict JSON. JSONC allows line or block comments and trailing commas for VS Code configuration files; those are not valid in strict JSON. If another program will read the file, use JSON mode and check it with a strict parser.

For an offline workflow, keep the schema on your computer or disable schema downloads with the json.schemaDownload.enable setting. Otherwise, the JSON extension can fetch HTTP/HTTPS schemas even though the file itself is open locally. See VS Code’s JSON documentation.

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Check a file with Python

Python’s standard-library json module can parse and pretty-print JSON. To check a file without writing formatted output, run:

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python -m json.tool file.json > /dev/null

A valid document produces no error; malformed input produces a parse error with location information. This command spelling is common and is referenced by the validator guide, but Python command-line details can differ by runtime version. The official documentation currently shown is for Python 3.14.8 and demonstrates the python -m json shell form. If a particular flag or invocation matters, check the help or documentation for the Python interpreter installed on your system.

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To create a pretty-printed copy rather than only test the input, redirect the output to a different file:

python -m json.tool file.json > formatted.json

Using a separate output file avoids replacing the input while the command is reading it. Consult the Python 3.14 JSON documentation for the module’s behavior and command-line options. Python warns that parsing untrusted input can use substantial CPU and memory, so limit the size of data you process.

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Check JSON with jq

For a local syntax check, run:

jq empty file.json

On valid input, jq emits no JSON value; invalid input produces an error and a nonzero exit status, making the command useful in scripts and CI. jq can read a local file or standard input. See the jq 1.8 manual for its command-line behavior.

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Use a browser formatter only after checking its data path

A browser-based formatter may process JSON locally, but a privacy statement or “no upload” label is a vendor’s claim, not an independent audit. For sensitive content, verify whether the page sends requests containing the JSON, and do not use save, history, or share-link features unless you understand how they handle the data.

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Some tools describe themselves as self-contained and usable offline. For example, jsonfmt.dev describes its toolkit as a self-contained HTML file that works offline and processes data locally. You can save a supported self-contained tool and use it offline; when the sensitivity warrants it, inspect the browser’s network activity as well. Loading a web page and its scripts initially still involves downloading them unless you already have a local copy.

Large documents can also strain browser memory or responsiveness. For multi-megabyte files, a local editor or command-line tool is often more practical than pasting into a page.

Know what each validation step proves

  • Formatting changes whitespace and indentation for readability. It does not prove the data is meaningful to an application.
  • Syntax validation checks whether the document follows JSON grammar, catching problems such as malformed quotes, commas, or brackets.
  • Schema validation checks parsed data against an explicit expected structure and constraints, such as required fields or value types. Use the schema intended for the application; the JSON Schema getting-started guide explains how schemas are constructed and used.
  • Application validation checks rules enforced by the program that consumes the JSON. A generic parser or schema check does not guarantee that every application-specific rule is satisfied.

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