Redis OM

Objecting mapping, and more, for Redis.

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Redis OM Python makes it easy to model Redis data in your Python applications.

Redis OM Python | Redis OM Node.js | Redis OM Spring | Redis OM .NET

Table of contents

• 💡 Why Redis OM?
• Starting Redis
• 📇 Modeling your domain (and indexing it!)
• 🔎 Querying
• Why this is important
• So how do you get RediSearch and RedisJSON?
• Why Redis OM?
• Getting started
• Installation
• Documentation
• Troubleshooting
• Contributing
• License

💡 Why Redis OM?

Redis OM provides high-level abstractions for using Redis in Python, making it easy to model and query your Redis domain objects.

This preview release contains the following features:

• Declarative object mapping for Redis objects
• Declarative secondary-index generation
• Fluent APIs for querying Redis

🏁 Getting started

Object Mapping

With Redis OM, you get powerful data modeling, extensible data validation with Pydantic, and rich query expressions.

Check out this example of how we'd model customer data with Redis OM. First, we're going to create a Customer model:

import datetime
from typing import Optional

from pydantic import EmailStr

from redis_om.model import (
    HashModel,
)


class Customer(HashModel):
    first_name: str
    last_name: str
    email: EmailStr
    join_date: datetime.date
    age: int
    bio: Optional[str]

NOTE: Redis OM uses Python type annotations for data validation. See the Data Validation section of this README for more details.

Now that we have a Customer model, let's use it to save customer data to Redis.

First, we create a new Customer object:

andrew = Customer(
    first_name="Andrew",
    last_name="Brookins",
    email="andrew.brookins@example.com",
    join_date=datetime.date.today(),
    age=38,
    bio="Python developer, works at Redis, Inc."
)

The model generates a globally unique primary key automatically without needing to talk to Redis.

print(andrew.pk)
'01FJM6PH661HCNNRC884H6K30C'

We can save the model to Redis by calling save():

andrew.save()

To retrieve this customer with its primary key, we use Customer.get():

other_andrew = Customer.get('01FJM6PH661HCNNRC884H6K30C')

Now let's see how Redis OM makes data validation a snap, thanks to Pydantic.

Data Validation

When you create a model with Redis OM, you define fields and give them type annotations. As a refresher, take a look at the Customer model we already built:

class Customer(HashModel):
    first_name: str
    last_name: str
    email: EmailStr
    join_date: datetime.date
    age: int
    bio: Optional[str]

Redis OM uses Pydantic behind the scenes to validate data at runtime, based on the model's type annotations.

This validation works for basic cases, like ensuring that first_name is always a string. But every Redis OM model is also a Pydantic model, so you can use existing Pydantic validators like EmailStr, Pattern, and many more for complex validation!

A Demo

Let's see what happens if we try to instantiate our Customer class with an invalid email address.

# We'll get a validation error if we try to use an invalid email address!
Customer(
    first_name="Andrew",
    last_name="Brookins",
    email="Not an email address!",
    join_date=datetime.date.today(),
    age=38,
    bio="Python developer, works at Redis, Inc."
)
# Traceback:
# pydantic.error_wrappers.ValidationError: 1 validation error for Customer
# email
#   value is not a valid email address (type=value_error.email)

# We'll also get a validation error if we try to save a model
# instance with an invalid email.
andrew = Customer(
    first_name="Andrew",
    last_name="Brookins",
    email="andrew.brookins@example.com",
    join_date=datetime.date.today(),
    age=38,
    bio="Python developer, works at Redis, Inc."
)

# Sometime later...
andrew.email = "Not valid"
andrew.save()

# Traceback:
# pydantic.error_wrappers.ValidationError: 1 validation error for Customer
# email
#   value is not a valid email address (type=value_error.email)

Data modeling, validation, and persisting to Redis all work regardless of how you run Redis.

However, Redis OM will take your Python applications to the next level if you're using the RediSearch and RedisJSON modules in your Redis deployment. Next, we'll talk about the rich query expressions and embedded models that Redis OM gives you with those Redis modules.

TIP: Wait, what's a Redis module? If you aren't familiar with Redis modules, review the RediSearch and RedisJSON section of this README.

Querying

Querying uses a rich expression syntax inspired by the Django ORM, SQLAlchemy, and Peewee.

The example code defines Address and Customer models for use with a Redis database with the RedisJSON module installed.

With these two classes defined, you can now:

• Validate data based on the model's type annotations using Pydantic
• Persist model instances to Redis as JSON
• Instantiate model instances from Redis by primary key (a client-generated ULID)
• Query on any indexed fields in the models

import datetime
from typing import Optional

from redis_om.model import (
    EmbeddedJsonModel,
    JsonModel,
    Field,
)

class Address(EmbeddedJsonModel):
    address_line_1: str
    address_line_2: Optional[str]
    city: str = Field(index=True)
    state: str = Field(index=True)
    country: str
    postal_code: str = Field(index=True)


class Customer(JsonModel):
    first_name: str = Field(index=True)
    last_name: str = Field(index=True)
    email: str = Field(index=True)
    join_date: datetime.date
    age: int = Field(index=True)
    bio: Optional[str] = Field(index=True, full_text_search=True,
                               default="")

    # Creates an embedded model.
    address: Address

Here are a few example queries that use the models we defined earlier:

# Find all customers with the last name "Brookins"
Customer.find(Customer.last_name == "Brookins").all()

# Find all customers that do NOT have the last name "Brookins"
Customer.find(Customer.last_name != "Brookins").all()
 
# Find all customers whose last name is "Brookins" OR whose age is 
# 100 AND whose last name is "Smith"
Customer.find((Customer.last_name == "Brookins") | (
    Customer.age == 100
) & (Customer.last_name == "Smith")).all()

# Find all customers who live in San Antonio, TX
Customer.find(Customer.address.city == "San Antonio",
              Customer.address.state == "TX")

Ready to learn more? Read the getting started guide or check out how to add Redis OM to your FastAPI project.

💻 Installation

Installation is simple with pip, Poetry, or Pipenv.

# With pip
$ pip install redis-om

# Or, using Poetry
$ poetry add redis-om

📚 Documentation

Documentation is available here.

⛏️ Troubleshooting

If you run into trouble or have any questions, we're here to help!

First, check the FAQ. If you don't find the answer there, hit us up on the Redis Discord Server.

✨ RediSearch and RedisJSON

Some advanced features of Redis OM rely on core features from two source available Redis modules: RediSearch and RedisJSON.

To learn more, read our documentation.

❤️ Contributing

We'd love your contributions!

Bug reports are especially helpful at this stage of the project. You can open a bug report on GitHub.

You can also contribute documentation -- or just let us know if something needs more detail. Open an issue on GitHub to get started.

License

Redis OM uses the BSD 3-Clause license.