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# Querying
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Querying uses a rich expression syntax inspired by the Django ORM, SQLAlchemy, and Peewee.
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The example code defines `Address` and `Customer` models for use with a Redis database with the [RedisJSON](redis-json-url) module installed.
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With these two classes defined, you can now:
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* Validate data based on the model's type annotations using Pydantic
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* Persist model instances to Redis as JSON
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* Instantiate model instances from Redis by primary key (a client-generated [ULID](ulid-url))
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* Query on any indexed fields in the models
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```python
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import datetime
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from typing import Optional
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from redis_om.model import (
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EmbeddedJsonModel,
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JsonModel,
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Field,
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)
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class Address(EmbeddedJsonModel):
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address_line_1: str
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address_line_2: Optional[str]
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city: str = Field(index=True)
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state: str = Field(index=True)
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country: str
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postal_code: str = Field(index=True)
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class Customer(JsonModel):
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first_name: str = Field(index=True)
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last_name: str = Field(index=True)
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email: str = Field(index=True)
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join_date: datetime.date
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age: int = Field(index=True)
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bio: Optional[str] = Field(index=True, full_text_search=True,
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default="")
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# Creates an embedded model.
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address: Address
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```
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Here are a few example queries that use the models we defined earlier:
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```python
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# Find all customers with the last name "Brookins"
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Customer.find(Customer.last_name == "Brookins").all()
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# Find all customers that do NOT have the last name "Brookins"
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Customer.find(Customer.last_name != "Brookins").all()
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# Find all customers whose last name is "Brookins" OR whose age is
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# 100 AND whose last name is "Smith"
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Customer.find((Customer.last_name == "Brookins") | (
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Customer.age == 100
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) & (Customer.last_name == "Smith")).all()
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# Find all customers who live in San Antonio, TX
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Customer.find(Customer.address.city == "San Antonio",
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Customer.address.state == "TX")
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```
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