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Python implementation of TypeIDs: type-safe, K-sortable, and globally unique identifiers inspired by Stripe IDs

Project description

TypeID Python

PyPI - Version PyPI - Python Version PyPI Downloads GitHub License

[!WARNING] main may contain unreleased changes. For stable usage, use the latest release tag.

A high-performance Python implementation of TypeIDs — type-safe, sortable identifiers based on UUIDv7.

TypeIDs are designed for modern systems where identifiers should be:

  • globally unique
  • sortable by creation time
  • safe to expose externally
  • easy to reason about in logs, APIs, and databases

This library provides a Python package with Rust acceleration.

Key features

  • ✅ UUIDv7-based, time-sortable identifiers
  • ✅ Schema-based ID explanations (JSON / YAML)
  • ✅ Fast generation & parsing (Rust-accelerated)
  • ✅ Multiple integrations (Pydantic, FastAPI, ...)
  • ✅ Type-safe prefixes (user_, order_, ...)
  • ✅ Human-readable and URL-safe
  • ✅ CLI tools (new, encode, decode, explain)
  • ✅ Fully offline, no external services

Performance

TypeID is optimized for real-world performance, not just correctness.

Benchmark summary (mean time)

Operation Before Rust Rust + optimizations
Generate 3.47 µs 0.70 µs
Parse 2.08 µs 1.30 µs
Workflow 5.52 µs 2.25 µs

Highlights

  • 🚀 ~5× faster generation
  • ~1.6× faster parsing
  • 🔁 ~2.5× faster end-to-end workflows

Benchmarks are:

  • reproducible
  • committed as raw JSON
  • runnable locally via bench/

See Docs: Performance for details.

Installation

Core

$ pip install typeid-python

Included:

  • Rust base32 encode/decode
  • uuid-utils for fast UUIDv7 generation

Other optional extras

$ pip install typeid-python[yaml]     # YAML schema support
$ pip install typeid-python[cli]      # CLI tools

Extras are strictly optional.

Usage

Basic

from typeid import TypeID

tid = TypeID(prefix="user")

assert tid.prefix == "user"
assert isinstance(tid.suffix, str)
assert str(tid).startswith("user_")

From string

from typeid import TypeID

tid = TypeID.from_string("user_01h45ytscbebyvny4gc8cr8ma2")
assert tid.prefix == "user"

From UUIDv7

from typeid import TypeID
from uuid_utils import uuid7

u = uuid7()
tid = TypeID.from_uuid(prefix="user", suffix=u)

assert tid.uuid.version == 7

Typed prefixes

from typing import Literal
from typeid import TypeID, typeid_factory

UserID = TypeID[Literal["user"]]
gen_user_id = typeid_factory("user")

user_id = gen_user_id()

CLI

$ pip install typeid-python[cli]

Generate:

$ typeid new -p user
user_01h2xcejqtf2nbrexx3vqjhp41

Decode:

$ typeid decode user_01h2xcejqtf2nbrexx3vqjhp41
uuid: 0188bac7-4afa-78aa-bc3b-bd1eef28d881

Encode:

$ typeid encode 0188bac7-4afa-78aa-bc3b-bd1eef28d881 --prefix user

Framework integrations

TypeID is framework-agnostic by design. Integrations are provided as optional adapters, installed explicitly and kept separate from the core.

Available integrations

  • Pydantic (v2) Native field type with validation and JSON Schema support.

    from typing import Literal
    from pydantic import BaseModel
    from typeid.integrations.pydantic import TypeIDField
    
    class User(BaseModel):
        id: TypeIDField[Literal["user"]]
    
  • FastAPI (Coming Soon 🚧)

  • SQLAlchemy (Coming Soon 🚧)

All integrations are opt-in via extras and never affect the core package.

typeid explain — understand any ID

$ typeid explain user_01h45ytscbebyvny4gc8cr8ma2

Outputs:

parsed:
  prefix: user
  uuid: 01890bf0-846f-7762-8605-5a3abb40e0e5
  created_at: 2025-03-12T10:41:23Z
  sortable: true

Works without schema, fully offline.

Schema-based explanations

Define meaning for prefixes using JSON or YAML.

Example (typeid.schema.json):

{
  "schema_version": 1,
  "types": {
    "user": {
      "name": "User",
      "owner_team": "identity-platform",
      "pii": true
    }
  }
}

Then:

$ typeid explain user_01h45ytscbebyvny4gc8cr8ma2

Read more here: "Docs: Explain".

Design principles

  • Non-breaking: stable APIs
  • Lazy evaluation: work is done only when needed
  • Explainability: identifiers carry meaning
  • Transparency: performance claims are backed by data

Think of TypeID as UUIDs + semantics + observability — without sacrificing speed

License

MIT

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