Schematics
Python Data Structures for Humans™.
Install / Use
/learn @schematics/SchematicsREADME
========== Schematics
.. rubric:: Python Data Structures for Humans™.
.. image:: https://travis-ci.org/schematics/schematics.svg?branch=master :target: https://travis-ci.org/schematics/schematics :alt: Build Status
.. image:: https://coveralls.io/repos/github/schematics/schematics/badge.svg?branch=master :target: https://coveralls.io/github/schematics/schematics?branch=master :alt: Coverage
About
Project documentation: https://schematics.readthedocs.io/en/latest/
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 easily made when Schematics handles everything except for writing the query.
Schematics can be used for tasks where having a database involved is unusual.
Some common use cases:
- Design and document specific
data structures <https://schematics.readthedocs.io/en/latest/usage/models.html>_ Convert structures <https://schematics.readthedocs.io/en/latest/usage/exporting.html#converting-data>_ to and from different formats such as JSON or MsgPackValidate <https://schematics.readthedocs.io/en/latest/usage/validation.html>_ API inputsRemove fields based on access rights <https://schematics.readthedocs.io/en/latest/usage/exporting.html>_ of some data's recipient- Define message formats for communications protocols, like an RPC
- Custom
persistence layers <https://schematics.readthedocs.io/en/latest/usage/models.html#model-configuration>_
Example
This is a simple Model.
.. code:: python
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': 'http://soundcloud.com/joestrummer'}) person.name u'Joe Strummer'
Serializing the data to JSON.
.. code:: python
import json json.dumps(person.to_primitive()) {"name": "Joe Strummer", "website": "http://soundcloud.com/joestrummer"}
Let's try validating without a name value, since it's required.
.. code:: python
person = Person() person.website = 'http://www.amontobin.com/' person.validate() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "schematics/models.py", line 231, in validate raise DataError(e.messages) schematics.exceptions.DataError: {'name': ['This field is required.']}
Add the field and validation passes.
.. code:: python
person = Person() person.name = 'Amon Tobin' person.website = 'http://www.amontobin.com/' person.validate()
.. _coverage:
Testing & Coverage support
Run coverage and check the missing statements. ::
$ coverage run --source schematics -m py.test && coverage report
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