dictify 4.0.0

Documents schema and data validation

Dictify

Schema and data validation for Python mappings and JSON-like documents.

dictify is a lightweight library for standalone field validation and mapping-shaped models with annotated fields.

• Python 3.12+
• Use Field(...) for defaults, required fields, and extra validators
• Use Python annotations to declare Model field types
• Access model data with either attributes or mapping syntax

Install

pip install dictify

Quick Example

from datetime import UTC, datetime
from typing import Annotated

from dictify import Field, Model


class Note(Model):
    title: str = Field(required=True).verify(
        lambda value: len(value) <= 300,
        "Title must be 300 characters or fewer",
    )
    content: str = Field()
    timestamp: Annotated[datetime, "creation time"] = Field(
        default=lambda: datetime.now(UTC)
    )


note = Note({"title": "Dictify", "content": "dictify is easy"})

note.content = "Updated content"
note["content"] = "Updated again"

# These raise Model.Error.
note.title = 0
note["title"] = 0

Strict Mode

Model is strict by default.

• strict=True rejects undeclared keys and undeclared public attributes
• strict=False stores undeclared keys and attributes as extra model data

note = Note({"title": "Dictify"}, strict=False)

note.category = "docs"
assert note["category"] == "docs"
assert dict(note)["category"] == "docs"

Native Conversion

Use explicit conversion when you need plain Python data.

import json

note_dict = dict(note)        # shallow dict conversion
note_native = note.dict()     # recursive dict/list conversion
note_json = json.dumps(note.dict())

Standalone Fields

Field.instance(...) still works well for standalone validation.

email = Field(required=True).instance(str).match(r".+@.+")
email.value = "[e-mail]"

Typing Status

The annotation-first model API is fully supported at runtime.

Static type checker support for declarations like email: str = Field(...) is still limited and may require cast(Any, Field(...)) depending on the checker and editor.

Documentation

• Docs: https://nitipit.github.io/dictify/
• Usage: https://nitipit.github.io/dictify/guide/usage/
• Field API: https://nitipit.github.io/dictify/guide/field-api/
• Validation Recipes: https://nitipit.github.io/dictify/guide/validation-recipes/
• Changelog: https://github.com/nitipit/dictify/blob/dev/CHANGELOG.md