Features

Multi-driver support

Remember the @instance.register? That kicks in now!

The idea behind μMongo is to allow the same document definition to be used with different MongoDB drivers.

To achieve that the user only defines document templates. Templates which will be implemented when registered by an instance:

Basically an instance provides three types of information:

• The MongoDB driver to use
• The database to use
• The documents implemented

This way a template can be implemented by multiple instances, this can be useful for example to:

• Store the same documents in different databases
• Define an instance with an async driver for a web server and a synchronous one for shell interactions

But enough of theory, let's create our first instance!

>>> from umongo import Instance
>>> import pymongo
>>> con = pymongo.MongoClient()
>>> instance1 = Instance(con.db1)
>>> instance2 = Instance(con.db2)

Now we can define & register documents, then work with them:

>>> class Dog(Document):
...     pass

>>> Dog  # mark as a template in repr
<Template class '__main__.Dog'>

>>> Dog.is_template
True

>>> DogInstance1Impl = instance1.register(Dog)
>>> DogInstance1Impl  # mark as an implementation in repr
<Implementation class '__main__.Dog'>

>>> DogInstance1Impl.is_template
False

>>> DogInstance2Impl = instance2.register(Dog)
>>> DogInstance1Impl().commit()
>>> DogInstance1Impl.count_documents()
1

>>> DogInstance2Impl.count_documents()
0

Note

You can use instance.register as a decoration to replace the template with its implementation. This is especially useful if you only use a single instance:

>>> @instance.register
... class Dog(Document):
...     pass
>>> Dog().commit()

Note

Often in more complex applications you won't have your driver ready when defining your documents. In such cases you should use a special instance with lazy db loader depending on your driver:

>>> from umongo import TxMongoInstance
>>> instance = TxMongoInstance()
>>> @instance.register
... class Dog(Document):
...     pass
>>> # Don't try to use Dog (except for inheritance) now !
>>> db = create_txmongo_database()
>>> instance.init(db)
>>> # Now instance is ready
>>> yield Dog().commit()

For the moment all examples have been done with PyMongo, but things are pretty much the same with other drivers, just configure the instance and you're good to go:

>>> db = motor.motor_asyncio.AsyncIOMotorClient()['umongo_test']
>>> instance = Instance(db)
>>> @instance.register
... class Dog(Document):
...     name = fields.StrField(attribute='_id')
...     breed = fields.StrField(default="Mongrel")

Of course the way you'll be calling methods will differ:

>>> odwin = Dog(name='Odwin', breed='Labrador')
>>> yield from odwin.commit()
>>> dogs = yield from Dog.find()

Inheritance

Inheritance inside the same collection is achieve by adding a _cls field (accessible in the document as cls) in the document stored in MongoDB

>>> @instance.register
... class Parent(Document):
...     unique_in_parent = fields.IntField(unique=True)
...     class Meta:
...         allow_inheritance = True
>>> @instance.register
... class Child(Parent):
...     unique_in_child = fields.StrField(unique=True)
>>> child = Child(unique_in_parent=42, unique_in_child='forty_two')
>>> child.cls
'Child'

>>> child.dump()
{'cls': 'Child', 'unique_in_parent': 42, 'unique_in_child': 'forty_two'}

>>> Parent(unique_in_parent=22).dump()
{'unique_in_parent': 22}

>>> [x.document for x in Parent.opts.indexes]
[{'key': SON([('unique_in_parent', 1)]), 'name': 'unique_in_parent_1', 'sparse': True, 'unique': True}]

Warning

You must register a parent before its child inside a given instance.

Indexes

Warning

Indexes must be first submitted to MongoDB. To do so you should call :meth:umongo.Document.ensure_indexes once for each document

In fields, the unique attribute is implicitly handled by an index:

>>> @instance.register
... class WithUniqueEmail(Document):
...     email = fields.StrField(unique=True)
>>> [x.document for x in WithUniqueEmail.opts.indexes]
[{'key': SON([('email', 1)]), 'name': 'email_1', 'sparse': True, 'unique': True}]

>>> WithUniqueEmail.ensure_indexes()
>>> WithUniqueEmail().commit()
>>> WithUniqueEmail().commit()
[...]
ValidationError: {'email': 'Field value must be unique'}

Note

The index params also depend of the required, and null field attributes

For more custom indexes, the Meta.indexes attribute should be used:

>>> @instance.register
... class CustomIndexes(Document):
...     name = fields.StrField()
...     age = fields.Int()
...     class Meta:
...         indexes = ('#name', 'age', ('-age', 'name'))
>>> [x.document for x in CustomIndexes.opts.indexes]
[{'key': SON([('name', 'hashed')]), 'name': 'name_hashed'},
 {'key': SON([('age', 1), ]), 'name': 'age_1'},
 {'key': SON([('age', -1), ('name', 1)]), 'name': 'age_-1_name_1'}

Note

Meta.indexes should use the names of the fields as they appear in database (i.g. given a field nick = StrField(attribute='nk'), you refer to it in Meta.indexes as nk)

Indexes can be passed as:

• a string with an optional direction prefix (i.g. "my_field")
• a list of string with optional direction prefix for compound indexes (i.g. ["field1", "-field2"])
• a :class:pymongo.IndexModel object
• a dict used to instantiate an :class:pymongo.IndexModel for custom configuration (i.g. {'key': ['field1', 'field2'], 'expireAfterSeconds': 42})

Allowed direction prefix are: - + for ascending - - for descending - $ for text - # for hashed

Note

If no direction prefix is passed, ascending is assumed

In case of a field defined in a child document, its index is automatically compounded with the _cls

>>> @instance.register
... class Parent(Document):
...     unique_in_parent = fields.IntField(unique=True)
...     class Meta:
...         allow_inheritance = True
>>> @instance.register
... class Child(Parent):
...     unique_in_child = fields.StrField(unique=True)
...     class Meta:
...         indexes = ['#unique_in_parent']
>>> [x.document for x in Child.opts.indexes]
[{'name': 'unique_in_parent_1', 'sparse': True, 'unique': True, 'key': SON([('unique_in_parent', 1)])},
{'name': 'unique_in_parent_hashed__cls_1', 'key': SON([('unique_in_parent', 'hashed'), ('_cls', 1)])},
{'name': '_cls_1', 'key': SON([('_cls', 1)])},
{'name': 'unique_in_child_1__cls_1', 'sparse': True, 'unique': True, 'key': SON([('unique_in_child', 1), ('_cls', 1)])}]

I18n

μMongo provides a simple way to work with i18n (internationalization) through the :func:umongo.set_gettext, for example to use python's default gettext:

from umongo import set_gettext
from gettext import gettext
set_gettext(gettext)

This way each error message will be passed to the custom gettext function in order for it to return the localized version of it.

See examples/flask for a working example of i18n with flask-babel.

Note

To set up i18n inside your app, you should start with messages.pot which is a translation template of all the messages used in μMongo (and its dependency marshmallow).

Marshmallow integration

Under the hood, μMongo heavily uses marshmallow for all of its data validation work.

However an ODM has some special needs (i.g. handling required fields through MongoDB's unique indexes) that force it to extend marshmallow's base types.

In short, you should not try to use marshmallow base types (:class:marshmallow.Schema, :class:marshmallow.fields.Field or :class:marshmallow.validate.Validator for instance) in a μMongo document but instead use their μMongo equivalents (respectively :class:umongo.abstract.BaseSchema, :class:umongo.abstract.BaseField and :class:umongo.abstract.BaseValidator).

Now let's go back to the Base concepts, the schema contains a little... simplification !

According to it, the client and OO worlds are made of the same data, but only in a different form (serialized vs object oriented). However pretty often the API you want to provide doesn't strictly follow your datamodel (e.g. you don't want to display or allow modification of the passwords in your /users route)

Let's go back to our Dog document, in real life you can rename your dog but not change it breed. So in our user API we should have a schema that enforce this !

>>> DogMaSchema = Dog.schema.as_marshmallow_schema()

As you can imagine, as_marshmallow_schema converts the original μMongo schema into a pure marshmallow schema. This way we can now customize it by subclassing it:

>>> class PatchDogSchema(DogMaSchema):
...     class Meta:
...         fields = ('name', )
>>> patch_dog_schema = PatchDogSchema()
>>> patch_dog_schema.load({'name': 'Scruffy', 'breed': 'Golden retriever'}).errors
{'_schema': ['Unknown field name breed.']}

>>> ret = patch_dog_schema.load({'name': 'Scruffy'})
>>> ret.errors
{}

>>> ret.data
{'name': 'Scruffy'}

Finally we can integrate the validated data into OO world:

>>> my_dog.update(ret.data)
>>> my_dog.name
'Scruffy'

Note

When instantiating a custom marshmallow schema, you can usestrict=True to make the schema raise a ValidationError instead of returning an error dict. This allows for better integration with μMongo's own error handling:

try:
    data, _ = patch_dog_schema.load(payload)
    my_dog.update(data)
    my_dog.commit()
except (ValidationError, UMongoError) as e:
    # error handling

This works great when you want to add special behavior depending of the situation. For more simple use cases we could use the marshmallow pre/post processors.

For example to simply customize the dump:

>>> from umongo import post_dump  # same as `from marshmallow import post_dump`
>>> @instance.register
... class Dog(Document):
...     name = fields.StrField(required=True)
...     breed = fields.StrField(default="Mongrel")
...     birthday = fields.DateTimeField()
...     @post_dump
...     def customize_dump(self, data):
...         data['name'] = data['name'].capitalize()
...         data['brief'] = "Hi ! My name is %s and I'm a %s" % (data['name'], data['breed'])"
...
>>> Dog(name='scruffy').dump()
{'name': 'Scruffy', 'breed': 'Mongrel', 'brief': "Hi ! My name is Scruffy and I'm a Mongrel"}

Now let's imagine we want to allow the per-breed creation of a massive number of ducks. The API would accept a really different format than our datamodel:

{
    'breeds': [
        {'name': 'Mandarin Duck', 'births': ['2016-08-29T00:00:00', '2016-08-31T00:00:00', ...]},
        {'name': 'Mallard', 'births': ['2016-08-27T00:00:00', ...]},
        ...
    ]
}

Now starting from the μMongo schema would not help, so we will create our schema from scratch... almost:

>>> MassiveBreedSchema(marshmallow.Schema):
...     name = Duck.schema.fields['breed'].as_marshmallow_field()
...     births = marshmallow.fields.List(
...         Duck.schema.fields['birthday'].as_marshmallow_field())
>>> MassiveDuckSchema(marshmallow.Schema):
...     breeds = marshmallow.fields.List(marshmallow.fields.Nested(MassiveBreedSchema))

Note

A custom marshmallow schema :class:umongo.marshmallow_bonus.SchemaFromUmongo can be used instead of regular :class:marshmallow.Schema to benefit from a tighter integration with μMongo (unknown field checking and field with missing value actually return the missing singleton instead of serializing it as None)

This time we directly convert μMongo schema's fields into their marshmallow equivalent with as_marshmallow_field. Now we can build our ducks easily:

try:
    data, _ =  MassiveDuckSchema(strict=True).load(payload)
    ducks = []
    for breed in data['breeds']:
        for birthday in breed['births']:
            duck = Duck(breed=breed['name']), birthday=birthday)
            duck.commit()
            ducks.append(duck)
except ValidationError as e:
    # Error handling
    ...

One final thought

A field's missing and default attributes are not handled the same in marshmallow and μMongo.

In marshmallow default contains the value to use during serialization (i.e. calling schema.dump(doc)) and missing the value for deserialization. where the field is

In μMongo however there is only a default attribute which will be used when creating (or loading from user world) a document where this field is missing. This is because you don't need to control how μMongo will store the document in mongo world.

So when you use as_marshmallow_field, the resulting marshmallow field's missing&default will by default both be inferred from μMongo's default field. You may want to overwrite this behavior by using marshmallow_missing/marshmallow_default attributes:

@instance.register
class Employee(Document):
    name = fields.StrField(default='John Doe')
    birthday = fields.DateTimeField(marshmallow_missing='2000-01-01T00:00:00Z')
    # You can use `missing` singleton to overwrite `default` field inference
    skill = fields.StrField(default='Dummy', marshmallow_default=missing)

ret = Employee.schema.as_marshmallow_schema()().load({})
assert ret.data == {'name': 'John Doe', 'birthday': datetime(2000, 1, 1, 0, 0, tzinfo=tzutc()), 'skill': 'Dummy'}
ret = Employee.schema.as_marshmallow_schema()().dump({})
assert ret.data == {'name': 'John Doe', 'birthday': '2000-01-01T00:00:00+00:00'}  # Note `skill` hasn't been serialized

Field validate & io_validate

Fields can be configured with special validators through the validate attribute:

from umongo import Document, fields, validate

@instance.register
class Employee(Document):
    name = fields.StrField(validate=[validate.Length(max=120), validate.Regexp(r"[a-zA-Z ']+")])
    age = fields.IntField(validate=validate.Range(min=18, max=65))
    email = fields.StrField(validate=validate.Email())
    type = fields.StrField(validate=validate.OneOf(['private', 'sergeant', 'general']))

Those validators will be enforced each time a field is modified:

>>> john = Employee(name='John Rambo')
>>> john.age = 99  # it's not his war anymore...
[...]
ValidationError: ['Must be between 18 and 65.']

Now sometimes you'll need for your validator to query your database (this is mainly done to validate a :class:umongo.data_objects.Reference). For this need you can use the io_validate attribute. This attribute should be passed a function (or a list of functions) that will do database access in accordance with the used mongodb driver.

For example with Motor-asyncio driver, io_validate's functions will be wrapped by :class:asyncio.coroutine and called with yield from.

from motor.motor_asyncio import AsyncIOMotorClient
db = AsyncIOMotorClient().test
instance = Instance(db)

@instance.register
class TrendyActivity(Document):
    name = fields.StrField()


@instance.register
class Job(Document):

    def _is_dream_job(field, value):
        if not (yield from TrendyActivity.find_one(name=value)):
            raise ValidationError("No way I'm doing this !")

    activity = fields.StrField(io_validate=_is_dream_job)


@asyncio.coroutine
def run():
    yield from TrendyActivity(name='Pythoning').commit()
    yield from Job(activity='Pythoning').commit()
    yield from Job(activity='Javascripting...').commit()
    # raises ValidationError: {'activity': ["No way I'm doing this !"]}

Warning

When converting to marshmallow with as_marshmallow_schema and as_marshmallow_fields, the io_validate attribute will not be preserved.