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+Metadata-Version: 1.1
+Name: voluptuous
+Version: 0.8.11
+Summary: Voluptuous is a Python data validation library
+Home-page: https://github.com/alecthomas/voluptuous
+Author: Alec Thomas
+Author-email: alec@swapoff.org
+License: BSD
+Download-URL: https://pypi.python.org/pypi/voluptuous
+Description: Voluptuous is a Python data validation library
+        ==============================================
+        
+        |Build Status| |Stories in Ready|
+        
+        Voluptuous, *despite* the name, is a Python data validation library. It
+        is primarily intended for validating data coming into Python as JSON,
+        YAML, etc.
+        
+        It has three goals:
+        
+        1. Simplicity.
+        2. Support for complex data structures.
+        3. Provide useful error messages.
+        
+        Contact
+        -------
+        
+        Voluptuous now has a mailing list! Send a mail to
+        ` <mailto:voluptuous@librelist.com>`__ to subscribe. Instructions will
+        follow.
+        
+        You can also contact me directly via `email <mailto:alec@swapoff.org>`__
+        or `Twitter <https://twitter.com/alecthomas>`__.
+        
+        To file a bug, create a `new
+        issue <https://github.com/alecthomas/voluptuous/issues/new>`__ on GitHub
+        with a short example of how to replicate the issue.
+        
+        Show me an example
+        ------------------
+        
+        Twitter's `user search
+        API <https://dev.twitter.com/docs/api/1/get/users/search>`__ accepts
+        query URLs like:
+        
+        ::
+        
+            $ curl 'http://api.twitter.com/1/users/search.json?q=python&per_page=20&page=1
+        
+        To validate this we might use a schema like:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Schema
+            >>> schema = Schema({
+            ...   'q': str,
+            ...   'per_page': int,
+            ...   'page': int,
+            ... })
+        
+        This schema very succinctly and roughly describes the data required by
+        the API, and will work fine. But it has a few problems. Firstly, it
+        doesn't fully express the constraints of the API. According to the API,
+        ``per_page`` should be restricted to at most 20, defaulting to 5, for
+        example. To describe the semantics of the API more accurately, our
+        schema will need to be more thoroughly defined:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Required, All, Length, Range
+            >>> schema = Schema({
+            ...   Required('q'): All(str, Length(min=1)),
+            ...   Required('per_page', default=5): All(int, Range(min=1, max=20)),
+            ...   'page': All(int, Range(min=0)),
+            ... })
+        
+        This schema fully enforces the interface defined in Twitter's
+        documentation, and goes a little further for completeness.
+        
+        "q" is required:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import MultipleInvalid, Invalid
+            >>> try:
+            ...   schema({})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "required key not provided @ data['q']"
+            True
+        
+        ...must be a string:
+        
+        .. code:: pycon
+        
+            >>> try:
+            ...   schema({'q': 123})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "expected str for dictionary value @ data['q']"
+            True
+        
+        ...and must be at least one character in length:
+        
+        .. code:: pycon
+        
+            >>> try:
+            ...   schema({'q': ''})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "length of value must be at least 1 for dictionary value @ data['q']"
+            True
+            >>> schema({'q': '#topic'}) == {'q': '#topic', 'per_page': 5}
+            True
+        
+        "per\_page" is a positive integer no greater than 20:
+        
+        .. code:: pycon
+        
+            >>> try:
+            ...   schema({'q': '#topic', 'per_page': 900})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "value must be at most 20 for dictionary value @ data['per_page']"
+            True
+            >>> try:
+            ...   schema({'q': '#topic', 'per_page': -10})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "value must be at least 1 for dictionary value @ data['per_page']"
+            True
+        
+        "page" is an integer >= 0:
+        
+        .. code:: pycon
+        
+            >>> try:
+            ...   schema({'q': '#topic', 'per_page': 'one'})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc)
+            "expected int for dictionary value @ data['per_page']"
+            >>> schema({'q': '#topic', 'page': 1}) == {'q': '#topic', 'page': 1, 'per_page': 5}
+            True
+        
+        Defining schemas
+        ----------------
+        
+        Schemas are nested data structures consisting of dictionaries, lists,
+        scalars and *validators*. Each node in the input schema is pattern
+        matched against corresponding nodes in the input data.
+        
+        Literals
+        ~~~~~~~~
+        
+        Literals in the schema are matched using normal equality checks:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema(1)
+            >>> schema(1)
+            1
+            >>> schema = Schema('a string')
+            >>> schema('a string')
+            'a string'
+        
+        Types
+        ~~~~~
+        
+        Types in the schema are matched by checking if the corresponding value
+        is an instance of the type:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema(int)
+            >>> schema(1)
+            1
+            >>> try:
+            ...   schema('one')
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "expected int"
+            True
+        
+        URL's
+        ~~~~~
+        
+        URL's in the schema are matched by using ``urlparse`` library.
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Url
+            >>> schema = Schema(Url())
+            >>> schema('http://w3.org')
+            'http://w3.org'
+            >>> try:
+            ...   schema('one')
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "expected a URL"
+            True
+        
+        Lists
+        ~~~~~
+        
+        Lists in the schema are treated as a set of valid values. Each element
+        in the schema list is compared to each value in the input data:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema([1, 'a', 'string'])
+            >>> schema([1])
+            [1]
+            >>> schema([1, 1, 1])
+            [1, 1, 1]
+            >>> schema(['a', 1, 'string', 1, 'string'])
+            ['a', 1, 'string', 1, 'string']
+        
+        Validation functions
+        ~~~~~~~~~~~~~~~~~~~~
+        
+        Validators are simple callables that raise an ``Invalid`` exception when
+        they encounter invalid data. The criteria for determining validity is
+        entirely up to the implementation; it may check that a value is a valid
+        username with ``pwd.getpwnam()``, it may check that a value is of a
+        specific type, and so on.
+        
+        The simplest kind of validator is a Python function that raises
+        ValueError when its argument is invalid. Conveniently, many builtin
+        Python functions have this property. Here's an example of a date
+        validator:
+        
+        .. code:: pycon
+        
+            >>> from datetime import datetime
+            >>> def Date(fmt='%Y-%m-%d'):
+            ...   return lambda v: datetime.strptime(v, fmt)
+        
+        .. code:: pycon
+        
+            >>> schema = Schema(Date())
+            >>> schema('2013-03-03')
+            datetime.datetime(2013, 3, 3, 0, 0)
+            >>> try:
+            ...   schema('2013-03')
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "not a valid value"
+            True
+        
+        In addition to simply determining if a value is valid, validators may
+        mutate the value into a valid form. An example of this is the
+        ``Coerce(type)`` function, which returns a function that coerces its
+        argument to the given type:
+        
+        .. code:: python
+        
+            def Coerce(type, msg=None):
+                """Coerce a value to a type.
+        
+                If the type constructor throws a ValueError, the value will be marked as
+                Invalid.
+                """
+                def f(v):
+                    try:
+                        return type(v)
+                    except ValueError:
+                        raise Invalid(msg or ('expected %s' % type.__name__))
+                return f
+        
+        This example also shows a common idiom where an optional human-readable
+        message can be provided. This can vastly improve the usefulness of the
+        resulting error messages.
+        
+        Dictionaries
+        ~~~~~~~~~~~~
+        
+        Each key-value pair in a schema dictionary is validated against each
+        key-value pair in the corresponding data dictionary:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema({1: 'one', 2: 'two'})
+            >>> schema({1: 'one'})
+            {1: 'one'}
+        
+        Extra dictionary keys
+        ^^^^^^^^^^^^^^^^^^^^^
+        
+        By default any additional keys in the data, not in the schema will
+        trigger exceptions:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema({2: 3})
+            >>> try:
+            ...   schema({1: 2, 2: 3})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "extra keys not allowed @ data[1]"
+            True
+        
+        This behaviour can be altered on a per-schema basis. To allow additional
+        keys use ``Schema(..., extra=ALLOW_EXTRA)``:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import ALLOW_EXTRA
+            >>> schema = Schema({2: 3}, extra=ALLOW_EXTRA)
+            >>> schema({1: 2, 2: 3})
+            {1: 2, 2: 3}
+        
+        To remove additional keys use ``Schema(..., extra=REMOVE_EXTRA)``:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import REMOVE_EXTRA
+            >>> schema = Schema({2: 3}, extra=REMOVE_EXTRA)
+            >>> schema({1: 2, 2: 3})
+            {2: 3}
+        
+        It can also be overridden per-dictionary by using the catch-all marker
+        token ``extra`` as a key:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Extra
+            >>> schema = Schema({1: {Extra: object}})
+            >>> schema({1: {'foo': 'bar'}})
+            {1: {'foo': 'bar'}}
+        
+        Required dictionary keys
+        ^^^^^^^^^^^^^^^^^^^^^^^^
+        
+        By default, keys in the schema are not required to be in the data:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema({1: 2, 3: 4})
+            >>> schema({3: 4})
+            {3: 4}
+        
+        Similarly to how extra\_ keys work, this behaviour can be overridden
+        per-schema:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema({1: 2, 3: 4}, required=True)
+            >>> try:
+            ...   schema({3: 4})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "required key not provided @ data[1]"
+            True
+        
+        And per-key, with the marker token ``Required(key)``:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema({Required(1): 2, 3: 4})
+            >>> try:
+            ...   schema({3: 4})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "required key not provided @ data[1]"
+            True
+            >>> schema({1: 2})
+            {1: 2}
+        
+        Optional dictionary keys
+        ^^^^^^^^^^^^^^^^^^^^^^^^
+        
+        If a schema has ``required=True``, keys may be individually marked as
+        optional using the marker token ``Optional(key)``:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Optional
+            >>> schema = Schema({1: 2, Optional(3): 4}, required=True)
+            >>> try:
+            ...   schema({})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "required key not provided @ data[1]"
+            True
+            >>> schema({1: 2})
+            {1: 2}
+            >>> try:
+            ...   schema({1: 2, 4: 5})
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "extra keys not allowed @ data[4]"
+            True
+        
+        .. code:: pycon
+        
+            >>> schema({1: 2, 3: 4})
+            {1: 2, 3: 4}
+        
+        Recursive schema
+        ~~~~~~~~~~~~~~~~
+        
+        There is no syntax to have a recursive schema. The best way to do it is
+        to have a wrapper like this:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Schema, Any
+            >>> def s2(v):
+            ...     return s1(v)
+            ...
+            >>> s1 = Schema({"key": Any(s2, "value")})
+            >>> s1({"key": {"key": "value"}})
+            {'key': {'key': 'value'}}
+        
+        Extending an existing Schema
+        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+        
+        Often it comes handy to have a base ``Schema`` that is extended with
+        more requirements. In that case you can use ``Schema.extend`` to create
+        a new ``Schema``:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Schema
+            >>> person = Schema({'name': str})
+            >>> person_with_age = person.extend({'age': int})
+            >>> sorted(list(person_with_age.schema.keys()))
+            ['age', 'name']
+        
+        The original ``Schema`` remains unchanged.
+        
+        Objects
+        ~~~~~~~
+        
+        Each key-value pair in a schema dictionary is validated against each
+        attribute-value pair in the corresponding object:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Object
+            >>> class Structure(object):
+            ...     def __init__(self, q=None):
+            ...         self.q = q
+            ...     def __repr__(self):
+            ...         return '<Structure(q={0.q!r})>'.format(self)
+            ...
+            >>> schema = Schema(Object({'q': 'one'}, cls=Structure))
+            >>> schema(Structure(q='one'))
+            <Structure(q='one')>
+        
+        Allow None values
+        ~~~~~~~~~~~~~~~~~
+        
+        To allow value to be None as well, use Any:
+        
+        .. code:: pycon
+        
+            >>> from voluptuous import Any
+        
+            >>> schema = Schema(Any(None, int))
+            >>> schema(None)
+            >>> schema(5)
+            5
+        
+        Error reporting
+        ---------------
+        
+        Validators must throw an ``Invalid`` exception if invalid data is passed
+        to them. All other exceptions are treated as errors in the validator and
+        will not be caught.
+        
+        Each ``Invalid`` exception has an associated ``path`` attribute
+        representing the path in the data structure to our currently validating
+        value, as well as an ``error_message`` attribute that contains the
+        message of the original exception. This is especially useful when you
+        want to catch ``Invalid`` exceptions and give some feedback to the user,
+        for instance in the context of an HTTP API.
+        
+        .. code:: pycon
+        
+            >>> def validate_email(email):
+            ...     """Validate email."""
+            ...     if not "@" in email:
+            ...         raise Invalid("This email is invalid.")
+            ...     return email
+            >>> schema = Schema({"email": validate_email})
+            >>> exc = None
+            >>> try:
+            ...     schema({"email": "whatever"})
+            ... except MultipleInvalid as e:
+            ...     exc = e
+            >>> str(exc)
+            "This email is invalid. for dictionary value @ data['email']"
+            >>> exc.path
+            ['email']
+            >>> exc.msg
+            'This email is invalid.'
+            >>> exc.error_message
+            'This email is invalid.'
+        
+        The ``path`` attribute is used during error reporting, but also during
+        matching to determine whether an error should be reported to the user or
+        if the next match should be attempted. This is determined by comparing
+        the depth of the path where the check is, to the depth of the path where
+        the error occurred. If the error is more than one level deeper, it is
+        reported.
+        
+        The upshot of this is that *matching is depth-first and fail-fast*.
+        
+        To illustrate this, here is an example schema:
+        
+        .. code:: pycon
+        
+            >>> schema = Schema([[2, 3], 6])
+        
+        Each value in the top-level list is matched depth-first in-order. Given
+        input data of ``[[6]]``, the inner list will match the first element of
+        the schema, but the literal ``6`` will not match any of the elements of
+        that list. This error will be reported back to the user immediately. No
+        backtracking is attempted:
+        
+        .. code:: pycon
+        
+            >>> try:
+            ...   schema([[6]])
+            ...   raise AssertionError('MultipleInvalid not raised')
+            ... except MultipleInvalid as e:
+            ...   exc = e
+            >>> str(exc) == "not a valid value @ data[0][0]"
+            True
+        
+        If we pass the data ``[6]``, the ``6`` is not a list type and so will
+        not recurse into the first element of the schema. Matching will continue
+        on to the second element in the schema, and succeed:
+        
+        .. code:: pycon
+        
+            >>> schema([6])
+            [6]
+        
+        Running tests.
+        --------------
+        
+        Voluptuous is using nosetests:
+        
+        ::
+        
+            $ nosetests
+        
+        Why use Voluptuous over another validation library?
+        ---------------------------------------------------
+        
+        **Validators are simple callables**
+            No need to subclass anything, just use a function.
+        **Errors are simple exceptions.**
+            A validator can just ``raise Invalid(msg)`` and expect the user to
+            get useful messages.
+        **Schemas are basic Python data structures.**
+            Should your data be a dictionary of integer keys to strings?
+            ``{int: str}`` does what you expect. List of integers, floats or
+            strings? ``[int, float, str]``.
+        **Designed from the ground up for validating more than just forms.**
+            Nested data structures are treated in the same way as any other
+            type. Need a list of dictionaries? ``[{}]``
+        **Consistency.**
+            Types in the schema are checked as types. Values are compared as
+            values. Callables are called to validate. Simple.
+        
+        Other libraries and inspirations
+        --------------------------------
+        
+        Voluptuous is heavily inspired by
+        `Validino <http://code.google.com/p/validino/>`__, and to a lesser
+        extent, `jsonvalidator <http://code.google.com/p/jsonvalidator/>`__ and
+        `json\_schema <http://blog.sendapatch.se/category/json_schema.html>`__.
+        
+        I greatly prefer the light-weight style promoted by these libraries to
+        the complexity of libraries like FormEncode.
+        
+        .. |Build Status| image:: https://travis-ci.org/alecthomas/voluptuous.png
+           :target: https://travis-ci.org/alecthomas/voluptuous
+        .. |Stories in Ready| image:: https://badge.waffle.io/alecthomas/voluptuous.png?label=ready&title=Ready
+           :target: https://waffle.io/alecthomas/voluptuous
+        
+Platform: any
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 2
+Classifier: Programming Language :: Python :: 2.7
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.1
+Classifier: Programming Language :: Python :: 3.2
+Classifier: Programming Language :: Python :: 3.3
+Classifier: Programming Language :: Python :: 3.4