How do you convert between Python objects and JSON?

Q: How do you convert between Python objects and JSON?

**Target Audience:** Beginners learning Python, and developers who want the edge cases an interviewer probes **Difficulty:** Easy **Python version:** Behaviour checked on CPython 3.11 (and in the page's Pyodide 3.11 runtime) > **How to read this doc:** Each idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact words an interviewer expects. Every output block in the **Verified** section was copied from a real run of the examples on this page. ## 1. Why This Even Matters — A Story First Imagine sending a piece of flat-pack furniture by post. You cannot post the assembled wardrobe, so you take it apart, pack the pieces in a box with a list of parts, and the person at the other end builds it again from the list. A Python object lives in your program's memory and cannot travel over a network or sit in a text file as it is. **JSON** is the flat-pack box: a plain-text format with a small, fixed set of piece types (objects, arrays, str

The problem

Question presented to candidate: "You get JSON from an API and need to send JSON back. How do you convert between JSON and Python objects, and what happens with types JSON does not have, like dates, sets or your own classes?"

What a strong answer should cover:

json.dumps / json.loads work with strings; json.dump / json.load work with file objects
The type mapping: object to dict, array to list, string to str, number to int or float, true/false to True/False, null to None
The round trip is lossy: tuples come back as lists, non-string dict keys become strings, and set, datetime, Decimal or custom classes raise TypeError unless you pass default=
Decoding custom types with object_hook (or parse_float=Decimal for exact numbers); for real APIs, a validation layer such as dataclasses or Pydantic
Useful options: indent, sort_keys, separators, ensure_ascii=False; errors arrive as json.JSONDecodeError, a ValueError
Gotchas: NaN/Infinity are emitted by default (not valid JSON; use allow_nan=False), and duplicate keys silently keep the last value

Clarifying questions expected:

Do the objects contain non-JSON types such as dates, decimals or sets?
Does the output need to be stable (sorted keys) or human-readable (indented)?

Code / implementation expected: Yes — dumps/loads plus a default= function for one custom type.

json
serialization

Try it yourself

Sketch your approach before you read the solution. That is what the interview tests.

Stuck? Get a hint.

A short nudge toward the approach. It will not give the answer away.

Solution

Target Audience: Beginners learning Python, and developers who want the edge cases an interviewer probes Difficulty: Easy Python version: Behaviour checked on CPython 3.11 (and in the page's Pyodide 3.11 runtime)

How to read this doc: Each idea is explained in plain language first, then tagged with 📌 Interview term: so you also learn the exact words an interviewer expects. Every output block in the Verified section was copied from a real run of the examples on this page.

1. Why This Even Matters — A Story First

Imagine sending a piece of flat-pack furniture by post. You cannot post the assembled wardrobe, so you take it apart, pack the pieces in a box with a list of parts, and the person at the other end builds it again from the list.

A Python object lives in your program's memory and cannot travel over a network or sit in a text file as it is. JSON is

The solution is hidden so you can try first

12 min read · 12 sections

Run the code

Edit the code and run it here. Each console line with an expected value becomes a test.

Pythondumps and loads: the type mapping, lossy round trips, formatting and errors

Practice

PythonCustom types with default= and object_hook, plus the NaN, Decimal and duplicate-key gotchas