redis-schematics 0.2.0

Installing

Using pip:

pip install redis_schamatics

Understanding Persistence layers

There are several ways to implement complex objects persitence on a key-value-set database such as redis. The best way to do it depends on your application constraints. We think that providing a good abstraction for your application is to allow you to choose which abstraction you want to use. Below you can find a comparison on different provided abstraction layers.

Currently we only support a SimpleRedisMixin and SimpleRedisModel, but you can use BaseRedisMixin to build your own persistance layers.

SimpleRedisMixin

Add Redis persistance to an object using a single hash approach. Each type correnspond to a single key on redis containing a hash set with every instance as an entry on the set which contains a serialized object.

You may use this Mixin when you have frequent match on primary key, set and all operations, hard memory contraints or wants a single key approach. You may not use this Mixin if you need performance on filter and get on non primary key operations.

HashRedisMixin

Add Redis persistance to an object using a single hash approach. Each type correnspond to a single key on redis containing a hash set with every instance as an entry on the set which contains a serialized object.

You may use this Mixin when you have frequent match on primary key, set and all operations, hard memory contraints or wants a single key approach. You may not use this Mixin if you need performance on filter and get on non primary key operations.

Quickstart

Creating models with persistence

Note: you should include a pk, but don’t bother setting it’s value manually. We can infer it from an id field or by setting a tuple of field names using __unique_together__.

from datetime import datetime, timedelta

from redis import StrictRedis
from redis_schematics import SimpleRedisMixin
from schematics import models, types


class IceCreamModel(models.Model, SimpleRedisMixin):
    pk = types.StringType()  # Just include a pk
    id = types.StringType()
    flavour = types.StringType()
    amount_kg = types.IntType()
    best_before = types.DateTimeType()

Setting on Redis

Saving is simple as set().

 vanilla = IceCreamModel(dict(
     id='vanilla',
     flavour='Sweet Vanilla',
     amount_kg=42,
     best_before=datetime.now() + timedelta(days=2),
 ))

chocolate = IceCreamModel(dict(
     id='chocolate',
     flavour='Delicious Chocolate',
     amount_kg=12,
     best_before=datetime.now() + timedelta(days=3),
 ))

 vanilla.set()
 chocolate.set()

Getting from Redis

There are two basic ways to get an element from Redis: by pk or by value. You can use the classmethods match_for_pk(pk) or match_for_values(**Kwargs) or just simply match(**kwargs) to let us choose which one. Notice that the performance from both methods is a lot different, so you may avoid matching for values on high performance environments. You may also use refresh to reload an object from storage if it has been modified.

IceCreamModel.match_for_pk('vanilla')
IceCreamModel.match_for_values(amount__gte=30)

IceCreamModel.match(id='vanilla')  # match on pk
IceCreamModel.match(best_before__gte=datetime.now())  # match on values

vanilla.refresh()

Fetching all and filtering

You can also use all() to deserialize all and filters. Notice that this invlolves deserializing all stored objects.

IceCreamModel.all()
IceCreamModel.filter(amount__gte=30)

Deleting and expiring

To remove objects, you can set __expire__ or use the delete() method. Notice that expires work differently on single key and multiple keys approaches.

class MyVolatileModel(models.Model, SimpleRedisMixin):
    __expire__ = 3600  # model expire (in seconds)
    pk = types.StringType()

vanilla.delete()

Roadmap

• Support a distributed Mixin with one key per field.

• Support a distributed Hash Mixin with one hash per field.

• Consistent set of unit tests.

• Support redis relationships between models.

• Support transaction aware methods.