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Python Dict ↔ JSON

Python logs and notebooks often print {'name': 'Alice'}. That is not valid JSON, so parse fails.

Dict → JSON handles common single quotes and True/False/None. The other direction yields a more Python-like literal.

No arbitrary Python is executed — text-level conversion only. Repr with expressions or custom classes needs a hand edit.

Conversion stays local. Debug data does not need to be saved to a file and uploaded.

Why it does not eval

Logs can contain user input. This page only replaces and parses literals so your text is never executed.

How this differs from To code

This page converts literals. For dataclass / TypedDict / type definitions, use To code and pick Python.

How to use it

  1. Copy a dict or JSON from a log or notebook.
  2. Choose Dict → JSON or JSON → Dict.
  3. Confirm True / False / None mapped to JSON.
  4. Format the JSON side; use To code if you need types.
  5. Edit datetime(...) or object-address repr into literals first.

When to use it

  • Turn a Django / Flask log dict into testable JSON.
  • Give a frontend teammate standard JSON instead of a Python print.
  • Turn a JSON fixture back into a readable dict for pytest.
  • If Repair cannot revive it, try it as a Python literal first.

Keep in mind

  • Function calls, comprehensions, and custom classes are not supported.
  • Tuples may become arrays. Check the meaning after convert.
  • Nothing is uploaded.

FAQ

Can True / None convert?

Common booleans and nulls map to JSON. Custom objects do not.

Is it safe?

It does not eval your text. It only does literal replacement and parse.

Can it generate a dataclass?

This page only converts literals. For type definitions, use To code and pick Python.

Is it uploaded?

No.

Are single quotes required?

Python dicts often use single quotes. Double-quoted JSON belongs on Format — you don't need this page first.

Can a set convert?

Sets are not standard JSON. Conversion may fail or become a list. Don't rely on it.

When should I use JSON Repair instead?

Use this page for obvious Python prints. Use Repair for broken JSON.

Are decimals and big integers accurate?

They follow JSON number rules. Spot-check very large integers.

Related tools

JSON to code JSON Format JSON ↔ YAML Back to the Workbench →