TOON for Python

The official Python implementation of TOON (Token-Oriented Object Notation): a compact, human-readable encoding of the JSON data model, designed to save tokens in LLM prompts. Keep working with dictionaries and lists in your code, and encode them as TOON only where a model reads them.

• Complete: implements TOON specification 4.2 and passes every official conformance fixture.
• Familiar: dumps, dump, loads, and load, like the json module, plus encode and decode, the names of the TypeScript reference implementation.
• Lossless: loads(dumps(data)) == data for every JSON-compatible value.
• Pure Python, no dependencies, fully typed, Python 3.10+.

Installation

pip install toon-format
# or
uv add toon-format

The module is toon_format. Install toon-format[pydantic] for the Pydantic integration.

Quick start

import toon_format

data = {
    "context": {"task": "Our favorite hikes together", "location": "Boulder"},
    "friends": ["ana", "luis", "sam"],
    "hikes": [
        {"id": 1, "name": "Blue Lake Trail", "distanceKm": 7.5, "wasSunny": True},
        {"id": 2, "name": "Ridge Overlook", "distanceKm": 9.2, "wasSunny": False},
    ],
}

text = toon_format.dumps(data)
print(text)

context:
  task: Our favorite hikes together
  location: Boulder
friends[3]: ana,luis,sam
hikes[2]{id,name,distanceKm,wasSunny}:
  1,Blue Lake Trail,7.5,true
  2,Ridge Overlook,9.2,false

assert toon_format.loads(text) == data

Keys of uniform arrays are written once, as a header, and each object becomes a row. With OpenAI's o200k_base tokenizer, this document takes 65 tokens, against 76 for compact JSON and 130 for indented JSON. The saving grows with the number of rows: 100 uniform records take 38% fewer tokens than compact JSON. Deeply nested or irregular data gains less.

Usage

Options

Encoding and decoding follow the json module, with the same keyword arguments where they apply:

toon_format.dumps(data, delimiter="\t")  # tabs often tokenize better than commas
toon_format.dumps(data, default=str)  # fallback for unsupported types
toon_format.loads(text, parse_float=Decimal)  # same hooks as json.loads
toon_format.loads(llm_output, strict=False)  # tolerate wrong counts and indentation

Errors

Invalid documents raise toon_format.ToonDecodeError, a ValueError that carries the 1-based line and the source line of the error:

try:
    toon_format.loads("a: 1\ntags[3]: a,b")
except toon_format.ToonDecodeError as exc:
    print(exc.line, exc.source)  # 2 tags[3]: a,b
    print(exc)  # line 2: Declared length 3 but found 2

encode and decode

encode and decode are the names used by the TypeScript reference implementation, @toon-format/toon, and by the other TOON implementations. Here they are aliases of dumps and loads, so code and examples carry over from one language to the other:

from toon_format import decode, encode

data = {
    "users": [
        {"id": 1, "name": "Ada", "role": "admin"},
        {"id": 2, "name": "Bob", "role": "user"},
    ]
}

print(encode(data))
# users[2]{id,name,role}:
#   1,Ada,admin
#   2,Bob,user

assert decode(encode(data)) == data

Options are keyword arguments in snake case, a spelling the specification allows (§13):

TypeScript	Python
encode(data)	encode(data)
encode(data, { indentSize: 4, delimiter: '\t' })	encode(data, indent_size=4, delimiter="\t")
decode(text)	decode(text)
decode(text, { strict: false })	decode(text, strict=False)

The streaming functions (encodeLines, decodeStream) and the replacer option have no Python counterpart.

Pydantic

With Pydantic, toon_format.dumps accepts any model, and ToonPydanticModel adds TOON counterparts of the JSON helpers:

from toon_format.pydantic import ToonPydanticModel


class User(ToonPydanticModel):
    name: str
    age: int


user = User.model_validate_toon("name: Ada\nage: 36")

Command line

This package has no command; use the official @toon-format/cli, which runs with Node.js and needs no installation:

npx @toon-format/cli data.json -o data.toon   # JSON to TOON
npx @toon-format/cli data.toon -o data.json   # TOON to JSON
npx @toon-format/cli data.json --stats        # token savings against JSON

Documentation

The full documentation is on Read the Docs: usage, the Python type mapping, the choices the specification leaves to implementations, and Pydantic.

Migrating from toon_format 0.9

The distribution and the module keep their names, and encode(value) and decode(text) keep working. Options are now keyword arguments instead of a dictionary, the token helpers and the toon command are gone, and the output follows specification 4.2. See the migration guide.

Contributing

See CONTRIBUTING.md. Project conventions for humans and coding agents are in AGENTS.md.

License

MIT