datatype 0.4

Anonymous datatype validation

datatype - Anonymous datatype validation
========================================

Example:
--------


>>> from datatype.validation import failures

>>> datatype = {'foo': [{'bar': 'int'}]}
>>> bad_value = {'foo': [{'bar': 'baz'}], 'bif': 'pow!'}

>>> failures(datatype, bad_value)
['foo[0].bar: expected int, got str', 'unexpected property "bif"']


Wildcard dictionary keys:

>>> datatype = {'_any_': ['int']}
>>> good_value = {'foo': [1, 2, 3], 'bar': [3, 4, 5]}

>>> failures(datatype, good_value)
[]


Datatype Definitions
--------------------

Datatype definitions are represented with a small set of types that should be
built-in for *most* languages.

Required types for proper validation:

* int
* float
* string
* boolean
* dictionary (or anonymous object)
* list (or array)


Specification
-------------

DEFINITION = PRIMITIVE | LIST | DICTIONARY
PRIMITIVE = ["nullable "] + ("int" | "str" | "float" | "bool")
DICTIONARY = {DICTIONARY-KEY: DEFINITION}
DICTIONARY-KEY = (["optional "] + DICTIONARY-KEY-NAME) | "_any_"
DICTIONARY-KEY-NAME = [A-Za-z0-9_]+
LIST = [DEFINITION]


Definition Examples (in python):
--------------------------------

definition: "int"
example value: 5

definition: {"foo": "int"}
example value: {"foo": 5}

definition: [{"foo": ["bool"]}]
example value: [{"foo": [True, False]}, {"foo": [False, False]}]

definition: {"_any_": "int"}
example value: {"foo": 5, "bar": 7}


Copyright and License
---------------------

Copyright 2011 LearningStation, Inc.

Licensed under the BSD-3 License. You may obtain a copy of the License in the
LICENSE file.