[Redis OM .NET](https://github.com/redis/redis-om-dotnet) | [Redis OM Node.js](https://github.com/redis/redis-om-node) | [Redis OM Spring](https://github.com/redis/redis-om-spring) | **Redis OM Python**
Installation is simple with `pip`, Poetry, or Pipenv.
```sh
# With pip
$ pip install redis-om
# Or, using Poetry
$ poetry add redis-om
```
## 🏁 Getting started
### Starting Redis
Before writing any code you'll need a Redis instance with the appropriate Redis modules! The quickest way to get this is with Docker:
```sh
docker run -p 6379:6379 -p 8001:8001 redis/redis-stack
```
This launches the [redis-stack](https://redis.io/docs/stack/) an extension of Redis that adds all manner of modern data structures to Redis. You'll also notice that if you open up http://localhost:8001 you'll have access to the redis-insight GUI, a GUI you can use to visualize and work with your data in Redis.
This validation ensures that fields like `first_name`, which the `Customer` model marked as a `str`, are always strings. **But every Redis OM model is also a Pydantic model**, so you can use Pydantic validators like `EmailStr`, `Pattern`, and many more for complex validations!
For example, because we used the `EmailStr` type for the `email` field, we'll get a validation error if we try to create a `Customer` with an invalid email address:
**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!
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, or you're using [Redis Enterprise][redis-enterprise-url].
**TIP**: *Wait, what's a Redis module?* If you aren't familiar with Redis modules, review the [So, How Do You Get RediSearch and RedisJSON?](#-so-how-do-you-get-redisearch-and-redisjson) section of this README.
Redis OM comes with a rich query language that allows you to query Redis with Python expressions.
To show how this works, we'll make a small change to the `Customer` model we defined earlier. We'll add `Field(index=True)` to tell Redis OM that we want to index the `last_name` and `age` fields:
Querying with this index features a rich expression syntax inspired by the Django ORM, SQLAlchemy, and Peewee. We think you'll enjoy it!
**Note:** Indexing only works for data stored in Redis logical database 0. If you are using a different database number when connecting to Redis, you can expect the code to raise a `MigrationError` when you run the migrator.
Sometimes you'll need to run a Redis command directly. Redis OM supports this through the `db` method on your model's class. This returns a connected Redis client instance which exposes a function named for each Redis command. For example, let's perform some basic set operations:
```python
from redis_om import HashModel
class Demo(HashModel):
some_field: str
redis_conn = Demo.db()
redis_conn.sadd("myset", "a", "b", "c", "d")
# Prints False
print(redis_conn.sismember("myset", "e"))
# Prints True
print(redis_conn.sismember("myset", "b"))
```
The parameters expected by each command function are those documented on the command's page on [redis.io](https://redis.io/commands/).
If you don't want to get a Redis connection from a model class, you can also use `get_redis_connection`:
Hit us up on the [Redis Discord Server](http://discord.gg/redis) or [open an issue on GitHub](https://github.com/redis-developer/redis-om-python/issues/new).
Some advanced features of Redis OM rely on core features from two source available Redis modules: [RediSearch][redisearch-url] and [RedisJSON][redis-json-url].
**Bug reports** are especially helpful at this stage of the project. [You can open a bug report on GitHub](https://github.com/redis/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/redis-om-python/issues/new) to get started.
