dictify 2.0.1

Python `dict` and `json` verification for humankind :)

Dictify : Document oriented schema / validation.

{dictify} is a python library for Document Oriented schema and validation with simple syntax, suitable for handling Python Dict, JSON.

Get it

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.. code-block::

pip install dictify

Schema Definition

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For general usage with nested data structure, use Model and Field classes to define schemas as example below:

.. code-block:: python

from dictify import Model, Field

class User(Model):
    name = Field(required=True).instance(str).match('[a-zA-Z0-9 ._-]+$')  # [1]
    email = Field(required=True).instance(str).match('.+@.+')  # [1]

class Note(Model):
    title = Field(required=True).instance(str)
    content = Field().instance(str)
    user = Field(required=True).instance(User)

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[1] Field validation can be chained.

Data Assignment and Validation

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After schema definition, we can use it by creating Model instance with required data.

.. code-block:: python

user = User({'name': 'user-1', 'email': '[e-mail]'})
note = Note({'title': 'Title-1', 'user': user})

Furthur data modification will be validated.

.. code-block:: python

note['title'] = 'Title-2'  # pass validation.
note['title'] = 0  # Raise Model.Error, require `str` instance.
note['user']['name'] = 0  # Raise Model.Error, require `str` instance.

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**Note :** Use ``try..except`` to catch errors if needed.

Use like Python dict()

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dictify.Model is a subclass of dict which is validated by defined schema.

.. code-block:: python

user.update({'name': 'user-2'})

note.update({
    'title': 'Title-3',
    'content': 'Content-1',
    'user': user
})

# Code below will raise `Model.Error`.
note.update({'title': 0, 'user': 0})

Convert data to dict() or JSON

---

.. code-block:: python

import json

note_dict = dict(note)
note_json = json.dumps(note)

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**Note :** For converting to JSON, all data must be instance of ``str``, ``int``,
``bool``, ``dict``, ``list``, ``dictify.Model``, ``dictify.ListOf`` or **None** which are **JSON** compatible.