Models¶

The models module contains the booby highest level abstraction: the Model.

To define a model you should subclass the Model class and add a list of fields as attributes. And then you could instantiate your Model and work with these objects.

Something like this:

class Repo(Model):
     name = fields.String()
     owner = fields.Embedded(User)

booby = Repo(
    name='Booby',
    owner={
        'login': 'jaimegildesagredo',
        'name': 'Jaime Gil de Sagredo'
    })

print booby.to_json()
'{"owner": {"login": "jaimegildesagredo", "name": "Jaime Gil de Sagredo"}, "name": "Booby"}'

class models.Model(**kwargs)¶

The Model class. All Booby models should subclass this.

By default the Model’s __init__() takes a list of keyword arguments to initialize the fields values. If any of these keys is not a field then raises errors.FieldError. Of course you can overwrite the Model’s __init__() to get a custom behavior.

You can get or set Model fields values in two different ways: through object attributes or dict-like items:

>>> booby.name is booby['name']
True
>>> booby['name'] = 'booby'
>>> booby['foo'] = 'bar'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
errors.FieldError: foo

Parameters:	**kwargs – Keyword arguments with the fields values to initialize the model.

is_valid¶

This property will be True if there are not validation errors in this model fields. If there are any error then will be False.

This property wraps the Model.validate() method to be used in a boolean context.

to_json(*args, **kwargs)¶

This method returns the model as a json string. It receives the same arguments as the builtin json.dump() function.

To build a json representation of this model this method iterates over the object to build a dict and then serializes it as json.

update(*args, **kwargs)¶: This method updates the model fields values with the given dict. The model can be updated passing a dict object or keyword arguments, like the Python’s builtin dict.update().

validate()¶

This method validates the entire model. That is, validates all the fields within this model.

If some field validation fails, then this method raises the same exception that the field.validate() method had raised.

validation_errors¶: Generator of field name and validation error string pairs for each validation error on this model fields.