In MongoDB, the concept of embedded documents allows you to nest one document within another. This is useful when you have a document that contains a set of related data that you don’t want to store separately.

MongoEngine, a Python Object-Document Mapper (ODM), provides support for working with embedded documents. With MongoEngine, you can define EmbeddedDocument classes that can be used to organize and structure your data within MongoDB.

Defining an EmbeddedDocument

To define an embedded document with MongoEngine, you need to create a class that subclasses mongoengine.EmbeddedDocument. Below is an example of how to create an embedded document class representing a user’s address:

import mongoengine

class Address(mongoengine.EmbeddedDocument):
    street = mongoengine.StringField()
    city = mongoengine.StringField()
    state = mongoengine.StringField()
    zip_code = mongoengine.StringField()

In this example, the Address class is defined as an embedded document by subclassing mongoengine.EmbeddedDocument. The class has fields such as street, city, state, and zip_code which represent different properties of an address.

Using Embedded Documents

Once you have defined an embedded document, you can use it within another document by declaring it as a field with the EmbeddedDocumentField type. In the example below, we define a User document that has an embedded Address:

import mongoengine

class User(mongoengine.Document):
    name = mongoengine.StringField()
    address = mongoengine.EmbeddedDocumentField(Address)

The User class defines a name field of type StringField and an address field of type EmbeddedDocumentField that references the Address embedded document.

Accessing Embedded Document Fields

To access the fields of an embedded document, you can use dot notation on the field within the parent document. In the example below, we create a User instance and access its embedded Address fields:

user = User()
user.name = "John Doe"
user.address = Address(street="123 Main St", city="New York", state="NY", zip_code="10001")

print(user.name)
print(user.address.street)
print(user.address.city)
print(user.address.state)
print(user.address.zip_code)

In this example, we create a User instance, set its name field, and initialize the address field with an Address instance. We then print out the different fields of the embedded Address document using dot notation.

Conclusion

MongoEngine’s support for embedded documents allows you to create more complex and structured data models within MongoDB. By defining embedded document classes and using them within your main documents, you can organize related data and improve the efficiency of your queries.