TypeID Python
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-utilsfor 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
1 maintainer
Metadata
1 maintainer
Release files for typeid-python 0.3.11
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Source distribution (sdist)
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