Response marshalling

Flask-RESTX provides an easy way to control what data you actually render in your response or expect as an input payload. With the fields module, you can use whatever objects (ORM models/custom classes/etc.) you want in your resource. fields also lets you format and filter the response so you don’t have to worry about exposing internal data structures.

It’s also very clear when looking at your code what data will be rendered and how it will be formatted.

Basic Usage

You can define a dict or OrderedDict of fields whose keys are names of attributes or keys on the object to render, and whose values are a class that will format & return the value for that field. This example has three fields: two are String and one is a DateTime, formatted as an ISO 8601 datetime string (RFC 822 is supported as well):

from flask_restx import Resource, fields

model = api.model('Model', {
    'name': fields.String,
    'address': fields.String,
    'date_updated': fields.DateTime(dt_format='rfc822'),
})

@api.route('/todo')
class Todo(Resource):
    @api.marshal_with(model, envelope='resource')
    def get(self, **kwargs):
        return db_get_todo()  # Some function that queries the db

This example assumes that you have a custom database object (todo) that has attributes name, address, and date_updated. Any additional attributes on the object are considered private and won’t be rendered in the output. An optional envelope keyword argument is specified to wrap the resulting output.

The decorator marshal_with() is what actually takes your data object and applies the field filtering. The marshalling can work on single objects, dicts, or lists of objects.

Note

marshal_with() is a convenience decorator, that is functionally equivalent to:

class Todo(Resource):
    def get(self, **kwargs):
        return marshal(db_get_todo(), model), 200

The @api.marshal_with decorator add the swagger documentation ability.

This explicit expression can be used to return HTTP status codes other than 200 along with a successful response (see abort() for errors).

Renaming Attributes

Often times your public facing field name is different from your internal field name. To configure this mapping, use the attribute keyword argument.

model = {
    'name': fields.String(attribute='private_name'),
    'address': fields.String,
}

A lambda (or any callable) can also be specified as the attribute

model = {
    'name': fields.String(attribute=lambda x: x._private_name),
    'address': fields.String,
}

Nested properties can also be accessed with attribute:

model = {
    'name': fields.String(attribute='people_list.0.person_dictionary.name'),
    'address': fields.String,
}

Default Values

If for some reason your data object doesn’t have an attribute in your fields list, you can specify a default value to return instead of None.

model = {
    'name': fields.String(default='Anonymous User'),
    'address': fields.String,
}

Custom Fields & Multiple Values

Sometimes you have your own custom formatting needs. You can subclass the fields.Raw class and implement the format function. This is especially useful when an attribute stores multiple pieces of information. e.g. a bit-field whose individual bits represent distinct values. You can use fields to multiplex a single attribute to multiple output values.

This example assumes that bit 1 in the flags attribute signifies a “Normal” or “Urgent” item, and bit 2 signifies “Read” or “Unread”. These items might be easy to store in a bitfield, but for a human readable output it’s nice to convert them to separate string fields.

class UrgentItem(fields.Raw):
    def format(self, value):
        return "Urgent" if value & 0x01 else "Normal"

class UnreadItem(fields.Raw):
    def format(self, value):
        return "Unread" if value & 0x02 else "Read"

model = {
    'name': fields.String,
    'priority': UrgentItem(attribute='flags'),
    'status': UnreadItem(attribute='flags'),
}

Url & Other Concrete Fields

Flask-RESTX includes a special field, fields.Url, that synthesizes a uri for the resource that’s being requested. This is also a good example of how to add data to your response that’s not actually present on your data object.

class RandomNumber(fields.Raw):
    def output(self, key, obj):
        return random.random()

model = {
    'name': fields.String,
    # todo_resource is the endpoint name when you called api.route()
    'uri': fields.Url('todo_resource'),
    'random': RandomNumber,
}

By default fields.Url returns a relative uri. To generate an absolute uri that includes the scheme, hostname and port, pass the keyword argument absolute=True in the field declaration. To override the default scheme, pass the scheme keyword argument:

model = {
    'uri': fields.Url('todo_resource', absolute=True),
    'https_uri': fields.Url('todo_resource', absolute=True, scheme='https')
}

Complex Structures

You can have a flat structure that marshal() will transform to a nested structure:

>>> from flask_restx import fields, marshal
>>> import json
>>>
>>> resource_fields = {'name': fields.String}
>>> resource_fields['address'] = {}
>>> resource_fields['address']['line 1'] = fields.String(attribute='addr1')
>>> resource_fields['address']['line 2'] = fields.String(attribute='addr2')
>>> resource_fields['address']['city'] = fields.String
>>> resource_fields['address']['state'] = fields.String
>>> resource_fields['address']['zip'] = fields.String
>>> data = {'name': 'bob', 'addr1': '123 fake street', 'addr2': '', 'city': 'New York', 'state': 'NY', 'zip': '10468'}
>>> json.dumps(marshal(data, resource_fields))
'{"name": "bob", "address": {"line 1": "123 fake street", "line 2": "", "state": "NY", "zip": "10468", "city": "New York"}}'

Note

The address field doesn’t actually exist on the data object, but any of the sub-fields can access attributes directly from the object as if they were not nested.

List Field

You can also unmarshal fields as lists

>>> from flask_restx import fields, marshal
>>> import json
>>>
>>> resource_fields = {'name': fields.String, 'first_names': fields.List(fields.String)}
>>> data = {'name': 'Bougnazal', 'first_names' : ['Emile', 'Raoul']}
>>> json.dumps(marshal(data, resource_fields))
>>> '{"first_names": ["Emile", "Raoul"], "name": "Bougnazal"}'

Wildcard Field

If you don’t know the name(s) of the field(s) you want to unmarshall, you can use Wildcard

>>> from flask_restx import fields, marshal
>>> import json
>>>
>>> wild = fields.Wildcard(fields.String)
>>> wildcard_fields = {'*': wild}
>>> data = {'John': 12, 'bob': 42, 'Jane': '68'}
>>> json.dumps(marshal(data, wildcard_fields))
>>> '{"Jane": "68", "bob": "42", "John": "12"}'

The name you give to your Wildcard acts as a real glob as shown bellow

>>> from flask_restx import fields, marshal
>>> import json
>>>
>>> wild = fields.Wildcard(fields.String)
>>> wildcard_fields = {'j*': wild}
>>> data = {'John': 12, 'bob': 42, 'Jane': '68'}
>>> json.dumps(marshal(data, wildcard_fields))
>>> '{"Jane": "68", "John": "12"}'

Note

It is important you define your Wildcard outside your model (ie. you cannot use it like this: res_fields = {'*': fields.Wildcard(fields.String)}) because it has to be stateful to keep a track of what fields it has already treated.

Note

The glob is not a regex, it can only treat simple wildcards like ‘*’ or ‘?’.

In order to avoid unexpected behavior, when mixing Wildcard with other fields, you may want to use an OrderedDict and use the Wildcard as the last field

>>> from flask_restx import fields, marshal
>>> import json
>>>
>>> wild = fields.Wildcard(fields.Integer)
>>> # you can use it in api.model like this:
>>> # some_fields = api.model('MyModel', {'zoro': fields.String, '*': wild})
>>>
>>> data = {'John': 12, 'bob': 42, 'Jane': '68', 'zoro': 72}
>>> json.dumps(marshal(data, mod))
>>> '{"zoro": "72", "Jane": 68, "bob": 42, "John": 12}'

Nested Field

While nesting fields using dicts can turn a flat data object into a nested response, you can use Nested to unmarshal nested data structures and render them appropriately.

>>> from flask_restx import fields, marshal
>>> import json
>>>
>>> address_fields = {}
>>> address_fields['line 1'] = fields.String(attribute='addr1')
>>> address_fields['line 2'] = fields.String(attribute='addr2')
>>> address_fields['city'] = fields.String(attribute='city')
>>> address_fields['state'] = fields.String(attribute='state')
>>> address_fields['zip'] = fields.String(attribute='zip')
>>>
>>> resource_fields = {}
>>> resource_fields['name'] = fields.String
>>> resource_fields['billing_address'] = fields.Nested(address_fields)
>>> resource_fields['shipping_address'] = fields.Nested(address_fields)
>>> address1 = {'addr1': '123 fake street', 'city': 'New York', 'state': 'NY', 'zip': '10468'}
>>> address2 = {'addr1': '555 nowhere', 'city': 'New York', 'state': 'NY', 'zip': '10468'}
>>> data = {'name': 'bob', 'billing_address': address1, 'shipping_address': address2}
>>>
>>> json.dumps(marshal(data, resource_fields))
'{"billing_address": {"line 1": "123 fake street", "line 2": null, "state": "NY", "zip": "10468", "city": "New York"}, "name": "bob", "shipping_address": {"line 1": "555 nowhere", "line 2": null, "state": "NY", "zip": "10468", "city": "New York"}}'

This example uses two Nested fields. The Nested constructor takes a dict of fields to render as sub-fields.input. The important difference between the Nested constructor and nested dicts (previous example), is the context for attributes. In this example, billing_address is a complex object that has its own fields and the context passed to the nested field is the sub-object instead of the original data object. In other words: data.billing_address.addr1 is in scope here, whereas in the previous example data.addr1 was the location attribute. Remember: Nested and List objects create a new scope for attributes.

By default when the sub-object is None, an object with default values for the nested fields will be generated instead of null. This can be modified by passing the allow_null parameter, see the Nested constructor for more details.

Use Nested with List to marshal lists of more complex objects:

user_fields = api.model('User', {
    'id': fields.Integer,
    'name': fields.String,
})

user_list_fields = api.model('UserList', {
    'users': fields.List(fields.Nested(user_fields)),
})

The api.model() factory

The model() factory allows you to instantiate and register models to your API or Namespace.

my_fields = api.model('MyModel', {
    'name': fields.String,
    'age': fields.Integer(min=0)
})

# Equivalent to
my_fields = Model('MyModel', {
    'name': fields.String,
    'age': fields.Integer(min=0)
})
api.models[my_fields.name] = my_fields

Duplicating with clone

The Model.clone() method allows you to instantiate an augmented model. It saves you duplicating all fields.

parent = Model('Parent', {
    'name': fields.String
})

child = parent.clone('Child', {
    'age': fields.Integer
})

The Api/Namespace.clone also register it on the API.

parent = api.model('Parent', {
    'name': fields.String
})

child = api.clone('Child', parent, {
    'age': fields.Integer
})

Polymorphism with api.inherit

The Model.inherit() method allows to extend a model in the “Swagger way” and to start handling polymorphism.

parent = api.model('Parent', {
    'name': fields.String,
    'class': fields.String(discriminator=True)
})

child = api.inherit('Child', parent, {
    'extra': fields.String
})

The Api/Namespace.clone will register both the parent and the child in the Swagger models definitions.

parent = Model('Parent', {
    'name': fields.String,
    'class': fields.String(discriminator=True)
})

child = parent.inherit('Child', {
    'extra': fields.String
})

The class field in this example will be populated with the serialized model name only if the property does not exists in the serialized object.

The Polymorph field allows you to specify a mapping between Python classes and fields specifications.

mapping = {
    Child1: child1_fields,
    Child2: child2_fields,
}

fields = api.model('Thing', {
    owner: fields.Polymorph(mapping)
})

Custom fields

Custom output fields let you perform your own output formatting without having to modify your internal objects directly. All you have to do is subclass Raw and implement the format() method:

class AllCapsString(fields.Raw):
    def format(self, value):
        return value.upper()


# example usage
fields = {
    'name': fields.String,
    'all_caps_name': AllCapsString(attribute='name'),
}

You can also use the __schema_format__, __schema_type__ and __schema_example__ to specify the produced types and examples:

class MyIntField(fields.Integer):
    __schema_format__ = 'int64'

class MySpecialField(fields.Raw):
    __schema_type__ = 'some-type'
    __schema_format__ = 'some-format'

class MyVerySpecialField(fields.Raw):
    __schema_example__ = 'hello, world'

Skip fields which value is None

You can skip those fields which values is None instead of marshaling those fields with JSON value, null. This feature is useful to reduce the size of response when you have a lots of fields which value may be None, but which fields are None are unpredictable.

Let consider the following example with an optional skip_none keyword argument be set to True.

>>> from flask_restx import Model, fields, marshal_with
>>> import json
>>> model = Model('Model', {
...     'name': fields.String,
...     'address_1': fields.String,
...     'address_2': fields.String
... })
>>> @marshal_with(model, skip_none=True)
... def get():
...     return {'name': 'John', 'address_1': None}
...
>>> get()
OrderedDict([('name', 'John')])

You can see that address_1 and address_2 are skipped by marshal_with(). address_1 be skipped because value is None. address_2 be skipped because the dictionary return by get() have no key, address_2.

Skip none in Nested fields

If your module use fields.Nested, you need to pass skip_none=True keyword argument to fields.Nested.

>>> from flask_restx import Model, fields, marshal_with
>>> import json
>>> model = Model('Model', {
...     'name': fields.String,
...     'location': fields.Nested(location_model, skip_none=True)
... })

Define model using JSON Schema

You can define models using JSON Schema (Draft v4).

address = api.schema_model('Address', {
    'properties': {
        'road': {
            'type': 'string'
        },
    },
    'type': 'object'
})

person = api.schema_model('Person', {
    'required': ['address'],
    'properties': {
        'name': {
            'type': 'string'
        },
        'age': {
            'type': 'integer'
        },
        'birthdate': {
            'type': 'string',
            'format': 'date-time'
        },
        'address': {
            '$ref': '#/definitions/Address',
        }
    },
    'type': 'object'
})