Included with Marrow Mongo are field types covering all core types supported by MongoDB. A class model is used to define new field types, with a large amount of functionality provided by the base Field class itself.

This base class is directly usable where the underlying field type is dynamic or not known prior to access.

The Field class is a subclass of Marrow Schema's Attribute and all field instances applicable to a given Document class or instance are accessible using the ordered dictionary __fields__.

from marrow.mongo import Document, Field

class Sample(Document):
    name = Field()

assert 'name' in Sample.__fields__

Name Mapping

In general, basic fields accept one positional parameter: the name of the field to store data against within MongoDB. In the following example any attempt to read or write to the field attriute of a MyDocument instance will instead retrieve data from the backing document using the key name. If no name is specified explicitly the name of the attribute the field is assigned to is used by default. The most frequent use of this is in mapping the _id field from MongoDB to a less cumbersome property name.

You can also pass this name using the name keyword argument. This may be required (if overriding the default name) for non-basic field types, and is required for complex types.

from marrow.mongo import Document

class MyDocument(Document):
    field = Field('name')

Default Values

There are a few attributes of a field that determine what happens when an attempt is made to access a value that currently does not exist in the backing document. If no default is provided and there is no value in the backing store for the field, any attempt to read the value of the field through attribute access will result in an AttributeError exception.


If a default value is provided, automatically assign it to the backing document when a new instance is constructed.



A single value to store, or a function called to generate a new value on first access (the default) or on instance construction (if assign is True).

No default.


If True, will store None. If False, will store non-None values, or not store. (The key will be missing from the backing store.)



This field must have a value assigned; None and an empty string are values.


Limiting Choice

Passing either an iterable of values, or a callback producing an iterable of values, as the choices argument allows you to restrict the acceptable values for the field. If static, this list will be included in the validation document. In this way you can emulate an enum or a set if applied to a field encapsulated in an Array.

The ability to restrict acceptable values this way is available to all types of field. Some, such as Number and its more specific subclasses, provide additional methods to restrict allowable values, such as ranges or minimums and maximums.

Field Exclusivity

Occasionally it may be useful to have two distinct fields where it is acceptable to have a value assigned to only one. We model this dependency through exclusion. By passing a set of field names as the exclusive argument you can define the fields that must not be set for the current field to be assignable.

Similar to this example, if you wish to define mutual exclusivity you must define both sides of the limitation. MyDocument declares that if link is set, mail can not be set, and likewise the reverse.

class MyDocument(Document):
    link = Field(exclusive={'mail'})
    mail = Field(exclusive={'link'})

Data Transformation

As we rely on Marrow Schema we make use of its transformation and validation APIs (and objects) to allow for customization of both data ingress and egress. By default Marrow Mongo attempts to ensure the value stored behind-the-scenes matches MongoDB and BSON datatype expectations to allow for conversion-free final use.

If one wanted to store Python Decimal objects within the database and wasn't running the latest MongoDB version which has direct support for this type, you could store them safely as strings. An easy way to accomplish this is to use Marrow Schema's Decimal transformer.

When attempting to retrieve the value, the string stored in the database will be converted to a Decimal object automatically. When assigning a Decimal value to the attribute it will be likewise converted back to a string for storage in MongoDB.

from marrow.schema.transform import decimal

class MyDocument(Document):
    field = Field(transformer=decimal)

Transformation in Field Subclasses

There is a shortcut for handling transformation (when using the default transfomer) in field subclasses, used extensively by the built-in field types. When subclassing Field you can simply define a to_native and/or to_foreign method.

These methods are passed the document the field is attached to, the name of the field, and the value being read or written. They must return either the same value, or some value after hypothetical transformation. The reason for the seeming duplication of the field information (which would otherwise be accessible via self) is to allow for the assignment of non-method functions, callable objects, or static methods.

class AwesomeField(Field):
    def to_native(self, doc, name, value):
        return value

    def to_foreign(self, doc, name, value):
        return str(value).upper()

Data Validation

By default no data validation is performed beyond the errors that may be raised during datatype transformation for a given Field subclass. Any field-level configuration for validation-like features effect the generation of the MongoDB-side validation document. You can make use of custom client-side valiation within your own models by utilizing Marrow Schema validation objects.

This example provides a username-based _id field.

from marrow.schema.validate.pattern import username

class MyDocument(Document):
    id = Field('_id', validator=username)


Subclasses of Document provide a __projection__ attribute containing the default set of fields to project based on field project predicates. Behaviour is somewhat complex; all fields excluding those marked for exclusion (False) are projected unless any are marked for explicit inclusion (True) in which case just those are. Fields whose predicates evaluate to None (the default) will only be included in the former case.

class MyDocument(Document):
    foo = Field()
    bar = Field(project=None)
    baz = Field(project=False)

MyDocument.__projection__ == {'foo': True, 'bar': True}

Read/Write Permissions

The shortcut methods is_readable(context=None) and is_writeable(context=None) are provided to evaluate the read and write predicates, which follow a pattern similar to projection. Literal True and False are allowed as constants to represent "always" and "never". These may alternatively be callbacks (or callable objects) which optionally take a context argument and return True or False, or an iterable of such objects which may also return None to abstain from voting in the access control list (ACL).

class MyDocument(Document):
    foo = Field(write=False) == False


Virtually identical to the read and write access permissions, the sort predicate follows the same rules and provides an is_sortable(context=None) evaluation method.

results matching ""

    No results matching ""