Indexes

Indexes play a crucial role in optimizing database performance, and PyODMongo provides you with flexible options for defining and managing them. This section will guide you on how to create indexes using PyODMongo.

Simple Index Creation

The simplest way to create indexes in PyODMongo is by using the Field, specifying which field should be indexed.

from pyodmongo import DbModel, Field
from typing import ClassVar


class Product(DbModel):
    name: str = Field(index=True)
    code: str = Field(index=True, unique=True)
    description: str = Field(text_index=True, default_language="english")
    price: float
    product_type: str
    is_available: bool
    _collection: ClassVar = "products"

• index: bool: When set to True, this Field will result in the creation of an index in the MongoDB collection using the same name as the field.
• unique: bool: When set to True, this Field enforces uniqueness for the indexed values in the MongoDB collection. In other words, no two documents in the collection can have the same value for this field.
• text_index: bool: Setting this Field to True indicates that the field should be included in the text indexes of the MongoDB collection. Text indexes are used for full-text search functionality.
• default_language: str: The default language that MongoDb will set in collection text index. You can check more detail in Text Search Languages.

Advanced Index Creation

However, if you need to create more specific or complex indexes, you can utilize the IndexModel from PyMongo. To do this, define a class-level attribute _indexes as a list of IndexModel instances. You can find detailed information about creating indexes with PyMongo in their official documentation.

Here's an example of how to create custom indexes in PyODMongo:

from pyodmongo import DbModel
from pymongo import IndexModel, ASCENDING, DESCENDING
from typing import ClassVar


class Product(DbModel):
    name: str
    code: str
    description: str
    price: float
    product_type: str
    is_available: bool
    _collection: ClassVar = "products"
    _indexes: ClassVar = [
        IndexModel([("name", ASCENDING), ("price", DESCENDING)], name="name_and_price"),
        IndexModel([("product_type", DESCENDING)], name="product_type"),
    ]

In this example, we define two custom indexes for the Product model using IndexModel. The first index is a compound index on the name field in ascending order and the price field in descending order, named 'name_and_price'. The second index is on the product_type field in descending order, named 'product_type'.

PyODMongo supports creating any index structure by following the PyMongo index structure guidelines. This flexibility allows you to optimize your database performance according to your specific requirements.