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schematics 1.1.1

Structured Data for Humans

Python Data Structures for Humans™.

For more information, please see our documentation:


Schematics is a Python library to combine types into structures, validate them, and transform the shapes of your data based on simple descriptions.

The internals are similar to ORM type systems, but there is no database layer in Schematics. Instead, we believe that building a database layer is made significantly easier when Schematics handles everything but writing the query.

Further, it can be used for a range of tasks where having a database involved may not make sense.

Some common use cases:


This is a simple Model.

>>> from schematics.models import Model
>>> from schematics.types import StringType, URLType
>>> class Person(Model):
...     name = StringType(required=True)
...     website = URLType()
>>> person = Person({'name': u'Joe Strummer',
...                  'website': ''})
u'Joe Strummer'

Serializing the data to JSON.

>>> import json
>>> json.dumps(person.to_primitive())
{"name": "Joe Strummer", "website": ""}

Let’s try validating without a name value, since it’s required.

>>> person = Person()
>>> = ''
>>> person.validate()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "schematics/", line 231, in validate
    raise ModelValidationError(e.messages)
schematics.exceptions.ModelValidationError: {'name': [u'This field is required.']}

Add the field and validation passes:

>>> person = Person()
>>> = 'Amon Tobin'
>>> = ''
>>> person.validate()

Testing & Coverage support

Run coverage and check the missing statements.

$ `coverage run --source schematics -m py.test && coverage report`
File Type Py Version Uploaded on Size
schematics-1.1.1.tar.gz (md5) Source 2015-11-04 58KB
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