Installation • Features • Usage • Roadmap • Contributing

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The modern Python3.8+ out-of-the-box reactive cache solution

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Installation

Installation is as simple as:

pip install dory-cache

View the current documentation here

Usage

Dory's configuration is quite simple. On your project initialization just call the setup function as follows

from dory.setup import setup

setup(
    host=REDIS_HOST,
    port=REDIS_PORT,
    user=REDIS_USER,
    password=REDIS_PASSWORD
)

Features

Bloats

Bloats responds to the need of having a simpler approach on designing reactive cache on your system. They make cache configuration and management easy.

For example, let's pretend that we have a model called Product which can be either serialized or edited. So, to improve the Product serialization performance we cache the Product serialization view (GET /product/).

from dory.cache import cache
from dory.utils import F

@api.get('/product/<product_id>')
@cache(key=F('product_id'), timeout=timedelta(hours=1))
def get_product(request, product_id):
    """
    Serialize a Product
    """
    ...

Now everything works faster and as expected, but we did not contemplate that since the Product can be edited (PUT /product/), we could have cached an outdated version of the Product, so we need a way to force the cache to refresh itself. This is where Bloats come in handy!

Instead of caching the view with a generic cache decorator, decouple the cache configuration on a Bloat

from dory.bloats import Bloat, Field

class Product(Bloat):
    """
    Product's bloat
    """
    product_id: int = Field(...)
    
    class Options:
        timeout: timedelta = timedelta(hours=1)
        enabled: bool = True

from dory.bloats.utils import F, cache

@api.get('/product/<product_id>')
@cache(Product(product_id=F('product_id')))
def get_product(request, product_id):
    """
    Serialize a Product
    """
    ...

And now, when a Product is edited, you can force the view to refresh the cache using the Bloat as a middle-man.

from dory.bloats.utils import F, destroy

@api.put('/product/<product_id>')
@destroy(Product(product_id=F('product_id')))
def edit_product(request, product_id):
    """
    Edit a Product
    """
    ...

Now your cache will always be in sync and it'll be configured in a cleaner way! 🔥

Cache utils

Dory simplifies several cache utilities with an out-of-the-box interface. For example, a decorator to cache views comfortably:

from dory.cache import cache
from dory.utils import F

@api.get('/foo')
@cache(key=F('foo_id'), timeout=timedelta(hours=1))
def foo(request, foo_id):
    """
    Render a Foo
    """
    ...

Django signals

The Django signals will permit the Bloats to expire themselves when a post_save signal from the Bloat's Django designated model signal is sent.

from dory import bloats
from .api import models

class Product(bloats.Bloat):
    """
    Product's bloat
    """
    ...

    class Meta:
        django_model = models.Product

from dory.utils import F

@api.get('/product/<product_id>')
@cache(Product(product_id=F('product_id')))
def get_product(request, product_id):
    """
    Serialize a Product
    """
    ...

Roadmap

• Bloats 🐡 (See Bloats)
• Cache utils (See Cache utils)
  • Cache decorator
  • Ratelimit
• Django signals (See Django signals)
• Bloats v2
  • The v2 of the Bloats will implement the method .set(), capable not only to deprecate the current Bloat version, but to fill it it again. The design is still a WIP.
• Support more cache engines

Contributing

Suggestions and contributions are extremely welcome! ❤️
Just open an issue or a PR, and I'll respond as soon as I can.