Cerberus Usage
==============

Basic Usage
-----------
You define a validation schema and pass it to an instance of the
:class:`~cerberus.Validator` class:

.. doctest::

    >>> schema = {'name': {'type': 'string'}}
    >>> v = Validator(schema)

Then you simply invoke the :meth:`~cerberus.Validator.validate` to validate
a dictionary against the schema. If validation succeeds, ``True`` is returned:

.. testsetup::

    schema = {'name': {'type': 'string'}}
    v = Validator(schema)
    document = {'name': 'john doe'}

.. doctest::

    >>> document = {'name': 'john doe'}
    >>> v.validate(document)
    True

Alternatively, you can pass both the dictionary and the schema to the
:meth:`~cerberus.Validator.validate` method:

.. doctest::

    >>> v = Validator()
    >>> v.validate(document, schema)
    True

Which can be handy if your schema is changing through the life of the
instance.

Details about validation schemas are covered in :doc:`schemas`.
See :doc:`validation-rules` and :doc:`normalization-rules` for an extensive
documentation of all supported rules.

Unlike other validation tools, Cerberus will not halt and raise an exception on
the first validation issue. The whole document will always be processed, and
``False`` will be returned if validation failed.  You can then access the
:attr:`~cerberus.Validator.errors` property to obtain a list of issues. See
:doc:`Errors & Error Handling <errors>` for different output options.

.. doctest::

    >>> schema = {'name': {'type': 'string'}, 'age': {'type': 'integer', 'min': 10}}
    >>> document = {'name': 'Little Joe', 'age': 5}
    >>> v.validate(document, schema)
    False
    >>> v.errors
    {'age': ['min value is 10']}

A :exc:`~cerberus.DocumentError` is raised when the document is not a mapping.

The Validator class and its instances are callable, allowing for the following
shorthand syntax:

.. doctest::

    >>> document = {'name': 'john doe'}
    >>> v(document)
    True

.. versionadded:: 0.4.1


.. _allowing-the-unknown:

Allowing the Unknown
--------------------
By default only keys defined in the schema are allowed:

.. doctest::

    >>> schema = {'name': {'type': 'string', 'maxlength': 10}}
    >>> v.validate({'name': 'john', 'sex': 'M'}, schema)
    False
    >>> v.errors
    {'sex': ['unknown field']}

However, you can allow unknown document keys pairs by either setting
``allow_unknown`` to ``True``:

.. doctest::

    >>> v.schema = {}
    >>> v.allow_unknown = True
    >>> v.validate({'name': 'john', 'sex': 'M'})
    True

Or you can set ``allow_unknown`` to a validation schema, in which case
unknown fields will be validated against it:

.. doctest::

    >>> v.schema = {}
    >>> v.allow_unknown = {'type': 'string'}
    >>> v.validate({'an_unknown_field': 'john'})
    True
    >>> v.validate({'an_unknown_field': 1})
    False
    >>> v.errors
    {'an_unknown_field': ['must be of string type']}

``allow_unknown`` can also be set at initialization:

.. doctest::

    >>> v = Validator({}, allow_unknown=True)
    >>> v.validate({'name': 'john', 'sex': 'M'})
    True
    >>> v.allow_unknown = False
    >>> v.validate({'name': 'john', 'sex': 'M'})
    False

``allow_unknown`` can also be set as rule to configure a validator for a nested
mapping that is checked against the :ref:`schema <schema_dict-rule>` rule:

.. doctest::

    >>> v = Validator()
    >>> v.allow_unknown
    False

    >>> schema = {
    ...   'name': {'type': 'string'},
    ...   'a_dict': {
    ...     'type': 'dict',
    ...     'allow_unknown': True,  # this overrides the behaviour for
    ...     'schema': {             # the validation of this definition
    ...       'address': {'type': 'string'}
    ...     }
    ...   }
    ... }

    >>> v.validate({'name': 'john',
    ...             'a_dict': {'an_unknown_field': 'is allowed'}},
    ...            schema)
    True

    >>> # this fails as allow_unknown is still False for the parent document.
    >>> v.validate({'name': 'john',
    ...             'an_unknown_field': 'is not allowed',
    ...             'a_dict':{'an_unknown_field': 'is allowed'}},
    ...            schema)
    False

    >>> v.errors
    {'an_unknown_field': ['unknown field']}

.. versionchanged:: 0.9
   ``allow_unknown`` can also be set for nested dict fields.

.. versionchanged:: 0.8
   ``allow_unknown`` can also be set to a validation schema.


.. _requiring-all:

Requiring all
-------------

By default any keys defined in the schema are not required.
However, you can require all document keys pairs by setting
``require_all`` to ``True`` at validator initialization (``v = Validator(…, require_all=True)``)
or change it latter via attribute access (``v.require_all = True``).
``require_all`` can also be set :ref:`as rule <require_all>` to configure a
validator for a subdocument that is checked against the
:ref:`schema <schema_dict-rule>` rule:

.. doctest::

    >>> v = Validator()
    >>> v.require_all
    False

    >>> schema = {
    ...   'name': {'type': 'string'},
    ...   'a_dict': {
    ...     'type': 'dict',
    ...     'require_all': True,
    ...     'schema': {
    ...       'address': {'type': 'string'}
    ...     }
    ...   }
    ... }

    >>> v.validate({'name': 'foo', 'a_dict': {}}, schema)
    False
    >>> v.errors
    {'a_dict': [{'address': ['required field']}]}

    >>> v.validate({'a_dict': {'address': 'foobar'}}, schema)
    True

.. versionadded:: 1.3

Fetching Processed Documents
----------------------------

The normalization and coercion are performed on the copy of the original
document and the result document is available via ``document``-property.

.. doctest::

   >>> v.schema = {'amount': {'type': 'integer', 'coerce': int}}
   >>> v.validate({'amount': '1'})
   True
   >>> v.document
   {'amount': 1}

Beside the ``document``-property a ``Validator``-instance has shorthand methods
to process a document and fetch its processed result.

`validated` Method
~~~~~~~~~~~~~~~~~~
There's a wrapper-method :meth:`~cerberus.Validator.validated` that returns the
validated document. If the document didn't validate :obj:`None` is returned,
unless you call the method with the keyword argument ``always_return_document``
set to ``True``.
It can be useful for flows like this:

.. testsetup::

    documents = ()

.. testcode::

    v = Validator(schema)
    valid_documents = [x for x in [v.validated(y) for y in documents]
                       if x is not None]

If a coercion callable or method raises an exception then the exception will
be caught and the validation with fail.

.. versionadded:: 0.9

`normalized` Method
~~~~~~~~~~~~~~~~~~~
Similarly, the :meth:`~cerberus.Validator.normalized` method returns a
normalized copy of a document without validating it:

.. doctest::

    >>> schema = {'amount': {'coerce': int}}
    >>> document = {'model': 'consumerism', 'amount': '1'}
    >>> normalized_document = v.normalized(document, schema)
    >>> type(normalized_document['amount'])
    <class 'int'>

.. versionadded:: 1.0


Warnings
--------

Warnings, such as about deprecations or likely causes of trouble, are issued
through the Python standard library's :mod:`warnings` module. The logging
module can be configured to catch these :func:`logging.captureWarnings`.