Redis OM

<h1 align="center">Redis OM</h1>
<p align="center">
    <p align="center">
        Objecting mapping, and more, for Redis.
    </p>
</p>

---

[![Version][version-svg]][package-url]
[![License][license-image]][license-url]
[![Build Status][ci-svg]][ci-url]

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

**Redis OM Python** | [Redis OM Node.js][redis-om-js] | [Redis OM Spring][redis-om-spring] | [Redis OM .NET][redis-om-dotnet]

<details>
  <summary><strong>Table of contents</strong></summary>

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  - [💡 Why Redis OM?](#-why-redis-om)
  - [Starting Redis](#starting-redis)
  - [📇 Modeling your domain (and indexing it!)](#-modeling-your-domain-and-indexing-it)
  - [🔎 Querying](#-querying)
  - [Why this is important](#why-this-is-important)
  - [So how do you get RediSearch and RedisJSON?](#so-how-do-you-get-redisearch-and-redisjson)
  - [Why Redis OM?](#why)
  - [Getting started](#getting-started)
  - [Installation](#installation)
  - [Documentation](#documentation)
  - [Troubleshooting](#troubleshooting)
  - [Contributing](#contributing)
  - [License](#license)

<!-- END doctoc generated TOC please keep comment here to allow auto update -->

</details>

## 💡 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](pydantic-url), and rich query expressions.

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

```python
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:

```python
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.

```python
print(andrew.pk)
'01FJM6PH661HCNNRC884H6K30C'
```

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

```python
andrew.save()
```

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

```python
other_andrew = Customer.get('01FJM6PH661HCNNRC884H6K30C')
```

**Ready to learn more?** Check out the [getting started](docs/getting_started.md) guide.

Or, continue reading to see how Redis OM makes data validation a snap.

### Data Validation

Redis OM uses [Pydantic](pydantic-url) to validate data based on the type annotations you assign to fields in a model class.

This validation ensures that fields like `first_name`, which the `Customer` model marked as a `str`, are always string. **But every Redis OM model is also a Pydantic model**, so you can use Pydantic validators like `EmailStr`, `Pattern`, and many more for complex validation!

As an example, because we used the `EmailStr` validator, we'll get a validation error if we try to save a `Customer` with an invalid email address:

```python
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."
)
```

This code generates a validation error:

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

What's great about this is **any existing Pydantic validator should work** as a drop-in type annotation with a Redis OM model. You can also write arbitrarily complex custom validations!

To learn more, see the [documentation on data validation](docs/validation.md).


#### Rich Queries and Embedded Models

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

Next, we'll show you the **rich query expressions** and **embedded models** Redis OM provides when the [RediSearch](redisearch-url) and [RedisJSON](redis-json-url) modules are installed in your Redis deployment.

**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

Let's make a small change to the `Customer` model we defined earlier to let Redis OM know that we want to query using the `last_name` and `age` fields:

```python
class Customer(HashModel):
    first_name: str
    last_name: str = Field(index=True)
    email: EmailStr
    join_date: datetime.date
    age: int = Field(index=True)
    bio: Optional[str]
```

Now, if we use this model with a Redis deployment that has the [RediSearch module](redisearch-url) installed, we can run queries like the following:

```python
# 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()
```

These queries -- and more! -- are possible because **Redis OM manages indexes for you automatically**.

Querying with this index features a rich expression syntax inspired by the Django ORM, SQLAlchemy,  and Peewee. We think you'll enjoy it!

To see more example queries, see the [documentation on querying](docs/querying.md).

### Embedded Models

Redis OM can store and query **nested models** like any document database, with the speed and power you get from Redis. Let's see how this works.

In the next example, we'll define a new `Address` model and embed it within the `Customer` model.

```python
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
```

With these two models and a Redis deployment with the RedisJSON module installed, we can run queries like the following:

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

To learn more, read the [documentation on embedded models](docs/embedded.md).

## 💻 Installation

Installation is simple with `pip`, Poetry, or Pipenv.

```sh
# With pip
$ pip install redis-om

# Or, using Poetry
$ poetry add redis-om
```

## 📚 Documentation

The Redis OM documentation is available [here](docs/index.md).

## ⛏️ Troubleshooting

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

First, check the [FAQ](docs/faq.md). If you don't find the answer there,
hit us up on the [Redis Discord Server](http://discord.gg/redis).

## ✨ RediSearch and RedisJSON

Some advanced features of Redis OM rely on core features from two source available Redis modules: [RediSearch](redisearch-url) and [RedisJSON](redis-json-url).

You can run these modules in your self-hosted Redis deployment, or you can use Redis Enterprise, which includes both modules.

To learn more, read [our documentation](docs/redis_modules.md).

## ❤️ 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](https://github.com/redis-om/redis-om-python/issues/new).

You can also **contribute documentation** -- or just let us know if something needs more detail. [Open an issue on GitHub](https://github.com/redis-om/redis-om-python/issues/new) to get started.

## License

Redis OM uses the [BSD 3-Clause license][license-url].

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[package-url]: https://pypi.org/project/redis-om/
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[license-image]: http://img.shields.io/badge/license-BSD_3--Clause-green.svg?style=flat-square
[license-url]: LICENSE

<!-- Links -->

[redis-om-website]: https://developer.redis.com
[redis-om-js]: https://github.com/redis-om/redis-om-js
[redis-om-dotnet]: https://github.com/redis-om/redis-om-dotnet
[redis-om-spring]: https://github.com/redis-om/redis-om-spring
[redisearch-url]: https://oss.redis.com/redisearch/
[redis-json-url]: https://oss.redis.com/redisjson/
[pydantic-url]: https://github.com/samuelcolvin/pydantic
[ulid-url]: https://github.com/ulid/spec