schemes 0.1

Easy input validation and data manipulation.

Schemes is a library for validating and deserializing input obtained via JSON, XML, msgpack or other similar formats, and for preparing data for serialization for output to the same formats and/or for persistence (typically, but not exclusively, to a cache or a NoSQL data store).

Overview

In order to use Schemes, you need at first to define one or more schemas:

user_schema = Schema({'id': ReadOnly(Long()),
                      'username': String(min_length=3, max_length=16),
                      'fullname': Optional(String()),
                      'password': WriteOnly(String(min_length=8))})

You can then use the schema definition to create a document from input data:

try:
    user = user_schema.create(
        {'username': u'tawmas', 'password': u'supersecret'})
except ValidationError as error:
    print(error.reason)

All fields are implicitly treated as mandatory, unless marked with a modifier such as Optional, ReadOnly or Internal. If one or more validation errors occurr, Schemes will report all validation errors in a friendly dictionary structure.

You can update an existing document from new input data:

try:
    user = user_schema.patch(user, {'password': u'verysecure'})
except ValidationError as error:
    print(error.reason)

patch() accepts partial inputs, and it only overwrites the fields which are actually present in the input data.

Finally, you can leverage the schema to prepare a document for output:

representation = user_schema.emit(user)

This gives you a dictionary representation of your document suitable to be serialized. Non-public fields are omitted, and some field types are converted to a serialization friendly formats (for example, datetimes are emitted as RFC 3339 strings).

Early prerelease warning

Schemes is at an early prerelease stage. As such, the public interface may well change, and no documentation is available yet except for the Overview above.

Full documentation will be made available when the project reaches the beta stage. In the meanwhile, you can have a look at the tests, especially the integration tests in tests/integration.

Initial development is on Python 2.7. The code is expected, and periodically tested, to work on pypy, and it is expected to break on Python 3. Full support for pypy and Python 3.3+ are planned for a later alpha stage.

Features and roadmap

• Validation and conversion from a serialized format for document creation and update.

• Conversion to a serializable external representation.

• Conversion to a serializable internal representation (PLANNED).

• Coercion of raw data (e.g. from a database or a cache) without triggering full validation (PROVISIONAL IMPLEMENTATION).

• Easily extensible.

• Many field types supported out of the box:

  • booleans

  • integers

  • longs

  • floats

  • decimals (PLANNED)

  • unicode strings

  • encoded bytestrings (PLANNED)

  • datetimes

  • dates

  • lists

  • embedded schemas

• Many field modifiers supported out of the box: optional (with or without a default value), read-only (with optional automatic creation and update values), write-only, internal.

• Support custom rules on existing field types (PLANNED).

• Alternate declarative syntax (PLANNED).

• Versioned schemas with automatic upgrade and downgrade of documents (PLANNED).

Installing Schemes

You can install Schemes with pip:

pip install schemes

If you want to hack on Schemes or run the test suite, you will also need to install pytest, and optionally the pytest-cov extension. You can automatically install Schemes and its testing dependencies with pip:

pip install schemes[testing]

License

Schemes is an open source project by Tommaso R. Donnarumma, distributed under the MIT license. See the LICENSE file for details.

Schemes comes with an embedded copy of the python-rfc3339 library by LShift Ltd., which is also distributed under the MIT license.