1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286
|
=================
Schema Validation
=================
.. currentmodule:: jsonschema
The Basics
----------
The simplest way to validate an instance under a given schema is to use the
:func:`validate` function.
.. autofunction:: validate
.. [#] For information on creating JSON schemas to validate
your data, there is a good introduction to JSON Schema
fundamentals underway at `Understanding JSON Schema
<http://spacetelescope.github.io/understanding-json-schema/>`_
The Validator Interface
-----------------------
:mod:`jsonschema` defines an (informal) interface that all validator
classes should adhere to.
.. class:: IValidator(schema, types=(), resolver=None, format_checker=None)
:argument dict schema: the schema that the validator object
will validate with. It is assumed to be valid, and providing
an invalid schema can lead to undefined behavior. See
:meth:`IValidator.check_schema` to validate a schema first.
:argument types: Override or extend the list of known types when
validating the :validator:`type` property. Should map strings (type
names) to class objects that will be checked via :func:`isinstance`.
See :ref:`validating-types` for details.
:type types: dict or iterable of 2-tuples
:argument resolver: an instance of :class:`RefResolver` that will be
used to resolve :validator:`$ref` properties (JSON references). If
unprovided, one will be created.
:argument format_checker: an instance of :class:`FormatChecker`
whose :meth:`~conforms` method will be called to check and see if
instances conform to each :validator:`format` property present
in the schema. If unprovided, no validation will be done for
:validator:`format`.
.. attribute:: DEFAULT_TYPES
The default mapping of JSON types to Python types used when validating
:validator:`type` properties in JSON schemas.
.. attribute:: META_SCHEMA
An object representing the validator's meta schema (the schema that
describes valid schemas in the given version).
.. attribute:: VALIDATORS
A mapping of validator names (:class:`str`\s) to functions
that validate the validator property with that name. For more
information see :ref:`creating-validators`.
.. attribute:: schema
The schema that was passed in when initializing the object.
.. classmethod:: check_schema(schema)
Validate the given schema against the validator's :attr:`META_SCHEMA`.
:raises: :exc:`SchemaError` if the schema is invalid
.. method:: is_type(instance, type)
Check if the instance is of the given (JSON Schema) type.
:type type: str
:rtype: bool
:raises: :exc:`UnknownType` if ``type`` is not a known type.
.. method:: is_valid(instance)
Check if the instance is valid under the current :attr:`schema`.
:rtype: bool
>>> schema = {"maxItems" : 2}
>>> Draft3Validator(schema).is_valid([2, 3, 4])
False
.. method:: iter_errors(instance)
Lazily yield each of the validation errors in the given instance.
:rtype: an iterable of :exc:`ValidationError`\s
>>> schema = {
... "type" : "array",
... "items" : {"enum" : [1, 2, 3]},
... "maxItems" : 2,
... }
>>> v = Draft3Validator(schema)
>>> for error in sorted(v.iter_errors([2, 3, 4]), key=str):
... print(error.message)
4 is not one of [1, 2, 3]
[2, 3, 4] is too long
.. method:: validate(instance)
Check if the instance is valid under the current :attr:`schema`.
:raises: :exc:`ValidationError` if the instance is invalid
>>> schema = {"maxItems" : 2}
>>> Draft3Validator(schema).validate([2, 3, 4])
Traceback (most recent call last):
...
ValidationError: [2, 3, 4] is too long
All of the :ref:`versioned validators <versioned-validators>` that
are included with :mod:`jsonschema` adhere to the interface, and
implementors of validator classes that extend or complement the
ones included should adhere to it as well. For more information see
:ref:`creating-validators`.
.. _validating-types:
Validating With Additional Types
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Occasionally it can be useful to provide additional or alternate types when
validating the JSON Schema's :validator:`type` property. Validators allow this
by taking a ``types`` argument on construction that specifies additional types,
or which can be used to specify a different set of Python types to map to a
given JSON type.
:mod:`jsonschema` tries to strike a balance between performance in the common
case and generality. For instance, JSON Schema defines a ``number`` type, which
can be validated with a schema such as ``{"type" : "number"}``. By default,
this will accept instances of Python :class:`numbers.Number`. This includes in
particular :class:`int`\s and :class:`float`\s, along with
:class:`decimal.Decimal` objects, :class:`complex` numbers etc. For
``integer`` and ``object``, however, rather than checking for
:class:`numbers.Integral` and :class:`collections.abc.Mapping`,
:mod:`jsonschema` simply checks for :class:`int` and :class:`dict`, since the
more general instance checks can introduce significant slowdown, especially
given how common validating these types are.
If you *do* want the generality, or just want to add a few specific additional
types as being acceptible for a validator object, :class:`IValidator`\s have a
``types`` argument that can be used to provide additional or new types.
.. code-block:: python
class MyInteger(object):
...
Draft3Validator(
schema={"type" : "number"},
types={"number" : (numbers.Number, MyInteger)},
)
The list of default Python types for each JSON type is available on each
validator object in the :attr:`IValidator.DEFAULT_TYPES` attribute. Note
that you need to specify all types to match if you override one of the
existing JSON types, so you may want to access the set of default types
when specifying your additional type.
.. _versioned-validators:
Versioned Validators
--------------------
:mod:`jsonschema` ships with validator classes for various versions of
the JSON Schema specification. For details on the methods and attributes
that each validator class provides see the :class:`IValidator` interface,
which each included validator class implements.
.. autoclass:: Draft3Validator
.. autoclass:: Draft4Validator
For example, if you wanted to validate a schema you created against the
Draft 4 meta-schema, you could use:
.. code-block:: python
from jsonschema import Draft4Validator
schema = {
"$schema": "http://json-schema.org/schema#",
"type": "object",
"properties": {
"name": {"type": "string"},
"email": {"type": "string"},
},
"required": ["email"]
}
Draft4Validator.check_schema(schema)
Validating Formats
------------------
JSON Schema defines the :validator:`format` property which can be used to check
if primitive types (``string``\s, ``number``\s, ``boolean``\s) conform to
well-defined formats. By default, no validation is enforced, but optionally,
validation can be enabled by hooking in a format-checking object into an
:class:`IValidator`.
.. doctest::
>>> validate("localhost", {"format" : "hostname"})
>>> validate(
... "-12", {"format" : "hostname"}, format_checker=FormatChecker(),
... )
Traceback (most recent call last):
...
ValidationError: "-12" is not a "hostname"
.. autoclass:: FormatChecker
:members:
:exclude-members: cls_checks
.. attribute:: checkers
A mapping of currently known formats to tuple of functions that
validate them and errors that should be caught. New checkers can be
added and removed either per-instance or globally for all checkers
using the :meth:`FormatChecker.checks` or
:meth:`FormatChecker.cls_checks` decorators respectively.
.. classmethod:: cls_checks(format, raises=())
Register a decorated function as *globally* validating a new format.
Any instance created after this function is called will pick up the
supplied checker.
:argument str format: the format that the decorated function will check
:argument Exception raises: the exception(s) raised by the decorated
function when an invalid instance is found. The exception object
will be accessible as the :attr:`ValidationError.cause` attribute
of the resulting validation error.
There are a number of default checkers that :class:`FormatChecker`\s know how
to validate. Their names can be viewed by inspecting the
:attr:`FormatChecker.checkers` attribute. Certain checkers will only be
available if an appropriate package is available for use. The available
checkers, along with their requirement (if any,) are listed below.
========== ====================
Checker Notes
========== ====================
hostname
ipv4
ipv6 OS must have :func:`socket.inet_pton` function
email
uri requires rfc3987_
date-time requires strict-rfc3339_ [#]_
date
time
regex
color requires webcolors_
========== ====================
.. [#] For backwards compatibility, isodate_ is also supported, but it will
allow any `ISO 8601 <http://en.wikipedia.org/wiki/ISO_8601>`_ date-time,
not just `RFC 3339 <http://www.ietf.org/rfc/rfc3339.txt>`_ as mandated by
the JSON Schema specification.
.. _isodate: http://pypi.python.org/pypi/isodate/
.. _rfc3987: http://pypi.python.org/pypi/rfc3987/
.. _strict-rfc3339: http://pypi.python.org/pypi/strict-rfc3339/
.. _webcolors: http://pypi.python.org/pypi/webcolors/
|