Schematizer
Schematizer is a lightweight library for data marshalling/unmarshalling in Python.
It helps you:
- Validate input and output data
- Marshal primitive data into a form you would like to interact with
- Unmarshal native data so that it can be rendered to JSON, YAML, MsgPack, etc.
Examples
Simple.
>>> from schematizer.exceptions import BaseValidationError
>>> from schematizer.schemas.compound import Dict, List
>>> from schematizer.schemas.simple import Date, Str
>>> from schematizer.validators import Length
>>>
>>> album_schema = Dict({
... 'title': Str(),
... 'released_at': Date(),
... })
>>>
>>> artist_schema = Dict({
... 'name': Str(),
... 'albums': List(album_schema),
... })
>>>
>>> artist_schema.to_native({
... 'name': 'Burzum',
... 'albums': [
... {
... 'title': 'Filosofem',
... 'released_at': '1996-01-01',
... },
... ],
... })
{'name': 'Burzum', 'albums': [{'title': 'Filosofem', 'released_at': datetime.date(1996, 1, 1)}]}With invalid data.
>>> try:
... artist_schema.to_native({
... 'albums': [
... {'released_at': '19960101'},
... ],
... })
... except BaseValidationError as exc:
... exc.flatten()
...
[
SimpleValidationError('MISSING', path=['name'], extra=None),
SimpleValidationError('MISSING', path=['albums', 0, 'title'], extra=None),
SimpleValidationError('INVALID', path=['albums', 0, 'released_at'], extra={'message': "time data '19960101' does not match format '%Y-%m-%d'"}),
]Installation
$ pip install schematizer
Documentation
Coming soon...
