pytastic 0.2.2

A dependency-free JSON validation library using TypedDict and Annotated

Pytastic

No Magic. Just Python.

Pytastic is a lightweight validation layer that respects your standard Python type hints. If you know TypedDict and Annotated, you already know how to use Pytastic.

View Docs at Pytastic Documentation

Why?

• Zero Dependencies: Pure Python standard library.
• No Learning Curve: It's just standard Python typing.
• IDE Friendly: We use standard types, so your IDE autocompletion works out of the box.
• Fast: Code generation makes Pytastic faster than Pydantic for common use cases.

Performance

Benchmark results (100,000 validation iterations):

Library	Time (s)	Ops/sec	Relative
msgspec	0.0533	1,877,872	1.00x
Pytastic	0.1794	557,277	3.37x
Pydantic	0.2002	499,381	3.76x

Pytastic is faster than Pydantic i.e. Pure Python with zero dependencies!

Installation

pip install pytastic

Usage

from pytastic import Pytastic
from typing import TypedDict, Annotated, List, Literal

vx = Pytastic()

# 1. Define Schema
class User(TypedDict):
    username: Annotated[str, "min_len=3; regex=^[a-z_]+$"]
    age: Annotated[int, "min=18"]
    role: Literal["admin", "user"]

2. Usage Patterns

Option A: Typed (Recommended)

No registration required. Best for IDE autocompletion.

try:
    user = vx.validate(User, {"username": "tersoo", "age": 25, "role": "admin"})
    print(user)
except Exception as e:
    print(e)

Option B: Dynamic (Requires Registration)

Registration required. Best for quick scripts or cleaner syntax.

vx.register(User)

# Now you can use the class name directly on the validator instance
user = vx.User({"username": "tersoo", "age": 25, "role": "admin"})

3. JSON Schema

# Export standard JSON Schema
print(vx.schema(User))
# Output:
# {
#   "type": "object",
#   "properties": {
#     "username": { "type": "string", "minLength": 3 ... },
#     ...
#   }
# }

License

MIT