This release is a pre-release and may not be stable for production use.
msgspec-toon
msgspec-toon is a native TOON 4.1 codec for Python. It decodes TOON text
directly into msgspec.Struct objects. It does not build an intermediate
dict and list tree.
Use it when tabular data must fit in a language model context window, but the application still needs typed Python objects and fast in-process conversion.
This is a beta release. The project passes the pinned TOON 4.1.1 corpus, but it does not yet support every type that
msgspec.jsonsupports.
Install
Install the public beta from PyPI:
uv add msgspec-toon
The package requires Python 3.13 or newer. Its only runtime dependency is the
exact pin msgspec==0.21.1. Benchmark codecs and tokenizers are optional
development dependencies. They are not installed with the library.
Decode TOON into a Struct
import msgspec
import msgspec_toon as toon
class Metadata(msgspec.Struct, frozen=True):
alias: str
region: str
class Worker(msgspec.Struct, frozen=True):
pid: int
provider: str
metadata: Metadata
class Document(msgspec.Struct, frozen=True):
workers: list[Worker]
wire = b"""workers[2]{pid,provider,metadata{alias,region}}:
9007199254740993,claude,worker-a,west
80916,claude,worker-b,east"""
decoder = toon.Decoder(Document)
document = decoder.decode(wire)
assert isinstance(document, Document)
assert document.workers[0].pid == 9007199254740993
assert toon.encode(document) == wire
The parser uses the target type while it reads the input. It constructs the final Struct objects directly. The G2 allocation proof records zero temporary built-in dictionaries and lists for this path.
Read and write TOON files
The codec accepts bytes, bytearray, memoryview, or str. Encoding returns
bytes, so normal Python file APIs work without an adapter.
from pathlib import Path
import msgspec_toon as toon
source = Path("workers.toon")
target = Path("workers-copy.toon")
decoder = toon.Decoder(Document)
encoder = toon.Encoder()
value = decoder.decode(source.read_bytes())
target.write_bytes(encoder.encode(value))
The conversion itself does not open files, sockets, or subprocesses. Your application controls all I/O.
Use untyped values
Omit type when you need normal Python dictionaries and lists:
value = toon.decode(b"name: ada\nactive: true")
wire = toon.encode(value)
The public surface follows msgspec.json where support exists:
encodeanddecode- reusable
EncoderandDecoder enc_hookanddec_hook- strict decoding by default
- msgspec-compatible encode, decode, and validation errors
TOON wire options are explicit:
toon.encode(value, delimiter="\t", indent=1)
toon.decode(wire, indent_size=1)
Why not wrap another TOON codec?
A wrapper must first convert a Struct into built-in containers. Typed decode
must parse a built-in tree and then call msgspec.convert. Those extra trees
can cost more than the codec work.
| Project | Format target | Typed msgspec path | Integration model |
|---|---|---|---|
| msgspec-toon | TOON 4.1.1 corpus | Direct Struct encode and decode | Native, in process |
toon-rust |
TOON 3.0 | No Python msgspec path | Rust library and CLI |
toons 0.7.0 |
Earlier TOON grammar | Built-in tree | Python Rust extension |
python-toon 0.1.3 |
Earlier TOON grammar | to_builtins / convert |
Pure Python and CLI |
TOON 4 nested field groups are important. They let a uniform nested record use one tabular header:
workers[2]{pid,provider,metadata{alias,region}}:
20324,claude,worker-a,west
80916,claude,worker-b,east
Older encoders can fall back to a larger entry form for the same data.
Tokens and speed
The generated benchmark report publishes both axes:
- Direct encode, decode, and total time for each measured codec.
- Absolute token counts, including compact JSON, under tiktoken
o200k_base.
The report crosses four payload shapes with four record counts. Canonical TOON uses more tokens than compact JSON for the measured irregular shapes.
All timing rows come from one session and one release build. The estimator is
the mean across ten independent worker processes. It never reports the minimum.
The raw evidence is in conformance/report.json.
Conformance and safety
- All 538 pinned TOON 4.1.1 fixtures pass in both directions.
- Typed decode creates no intermediate built-in container tree.
- Integers keep Python precision and do not route through
float. - Errors contain coordinates and static messages, never input payload text.
- Malformed input must return an error. It must not panic or terminate Python.
- Canonical output is byte-locked by tests.
The generated support matrix in conformance/report.json lists supported,
rejected, and not-yet-supported msgspec features. Unsupported behavior fails
clearly. It does not silently return a different value.
Optional msgspec Struct fast path
The stock package reads Struct fields through msgspec's public Python
attributes. This is the compatible path for msgspec==0.21.1.
The repository also contains a versioned Struct-access capsule proposal for msgspec. You can build the same codec against that patch in an isolated environment:
make fastpath-build
make fastpath-check
make fastpath-bench
.venv-fastpath/bin/python
This workflow fetches a hash-pinned msgspec commit, applies the preserved patch,
and builds both release wheels. It does not modify the normal .venv. The build
fails unless the capsule path is active. Published wheels do not depend on the
unreleased API.
Develop and reproduce
Use uv for all Python environment work:
uv sync --locked # library and developer tools
make build # release extension in .venv
make check # Rust and Python checks
uv run python conformance/run.py # pinned 538-fixture corpus
make g2 # allocation proof in a separate build
uv sync --group bench --locked # opt in to benchmark packages
make bench # same-run codec and typed ladders
make public-report # raw JSON, R charts, and BENCHMARKS.md
make public-report uses the host Rscript, ggplot2, jsonlite, and
scales. It does not install R or add R packages to the Python environment.
License
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