tsrkit-types 0.2.1

Performant Python Typings library for type-safe binary serialization, JSON encoding, and data validation with zero dependencies

TSRKit Types

A high‑performance, strongly‑typed Python serialization library with built‑in JSON support. TSRKit Types provides a concise type system for integers, bytes, strings, bits, sequences, dictionaries, enums, and structs with deterministic, validated encoding.

Highlights

• Native C extension for performance‑critical encode/decode paths
• Deterministic binary encoding and JSON serialization
• Strong runtime validation with type‑safe containers
• Clean, small API designed for application‑level data modeling

Installation

Wheels (recommended)

pip install tsrkit-types

Build from source

pip install .

The native extension is required. Wheels are provided for macOS and Linux.

Quickstart

from tsrkit_types import Uint, U16, String, Bytes, Bits, TypedVector, Dictionary, structure

# Integers
value = Uint(1000)
encoded = value.encode()
decoded = Uint.decode(encoded)

# Fixed-width integer
port = U16(8080)

# Strings and bytes
name = String("alice")
blob = Bytes(b"payload")

# Bits
flags = Bits([True, False, True, True])

# Typed container
VecU16 = TypedVector[U16]
ports = VecU16([U16(80), U16(443)])

# Dictionary with typed keys/values
Config = Dictionary[String, U16]
config = Config({String("port"): U16(8080)})

# Structs
@structure
class Person:
    name: String
    age: U16

p = Person(name=String("bob"), age=U16(42))

# Binary + JSON
binary = p.encode()
json_data = p.to_json()

Type Overview

• Integers: Uint, U8, U16, U32, U64
• Strings: String
• Bytes: Bytes, Bytes16, Bytes32, Bytes64, Bytes128, Bytes256, Bytes512, Bytes1024, ByteArray
• Bits: Bits
• Sequences: Seq, Vector, Array, TypedVector, TypedArray, BoundedVector, TypedBoundedVector
• Dictionary: Dictionary
• Enums: Enum
• Structs: structure
• Choice/Option: Choice, Option

Encoding Notes

• Fixed‑width integers are little‑endian.
• Variable‑length integers use a compact prefix encoding optimized for smaller values.
• Dictionaries encode in sorted key order for determinism.

Benchmarks

See benchmark.md for current results and Python/stdlib baselines. Raw benchmark outputs are written to:

• benchmarks/out/bench_results.json
• benchmarks/out/bench_profiles.json

Development

Tests

uv run pytest

Linting

uv run ruff check .