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dory-cache-0.1.0
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-
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | dory-cache-0.1.0 |
| نام | dory-cache |
| نسخه کتابخانه | 0.1.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Sören Rifé |
| ایمیل نویسنده | sorenrife@gmail.com |
| آدرس صفحه اصلی | https://github.com/sorenrife/dory |
| آدرس اینترنتی | https://pypi.org/project/dory-cache/ |
| مجوز | MIT |
<img src="https://user-images.githubusercontent.com/55748056/172958283-fa9b17c3-16a5-49e7-9a12-3d33dc5b6f6d.png" width="300">
Dory
====
Dory is a **Python3.8+** out-of-the box smart cache library. It simplifies multiple cache features and brings [Bloats](#Bloats) to the table, a tool designed to make smarter your application cache.
| Badges
--- | ---
Build | [](https://github.com/sorenrife/dory/actions/workflows/test.yaml) [](https://github.com/sorenrife/dory/actions/workflows/deploy.yaml) [](https://codecov.io/gh/sorenrife/dory)
Docs | [](https://sorenrife.gitbook.io/dory/)
Package | [](https://pypi.python.org/pypi/dory-cache/) [](https://pypi.python.org/pypi/dory-cache/) [](https://github.com/psf/black)
Support | [](https://www.buymeacoffee.com/sorenrife)
## Table of content
- [Installation](#Installation)
- [Features](#Features)
- [Cache utils](#Cache-utils)
- [Bloats](#Bloats)
- [Usage](#Usage)
- [Examples](#Examples)
- [Roadmap](#Roadmap)
- [Contributing](#Contributing)
## Installation
Installation is as simple as:
```bash
pip install dory-cache
```
## Features
### Cache utils
**Dory** simplifies several cache utilities with an out-of-the-box interface. For example, a decorator to cache views comfortably:
```python
@api.get('/foo')
@dory.cache(key='foo', timeout=timedelta(hours=1))
def foo(request):
"""
Render a Foo
"""
...
```
More about it on the [docs](https://sorenrife.gitbook.io/dory/) 🔥
### Bloats
<p align="center">
<img src="https://user-images.githubusercontent.com/55748056/173080628-aafb7b87-67c4-4181-9619-01ee7a4126bc.png" width="300">
</p>
<p align="center"><i>Porcupinefish have the ability to inflate their bodies by swallowing water or air, thereby becoming rounder.</i></p>
<br>
`Bloats` responds to the necessity to have a solid and clean way to define cache usage and to permit an smart cache approach to your system.
The main idea behind it is that a `Bloat` has the ability to `inflate` -as a Porcupinefish does- meaning that has the ability to cache a `key/value` given a certain configuration.
Also, has the ability to `deflate` meaning exactly the contrary, that deletes the given `key/value` from the cache. Having a `Bloat` decoupled gives the application the ability to interact with the cache in a comfortable way around all the project.
For example, let's pretend that we have a model called `Product` wich can be either renderizer or edited.
```python
class Product(Model):
"""
Store information about a Product
"""
id: int = PrimaryKey()
name: str = Text()
description: str = Text()
```
So, to improve the `Product` performance we cache the `Product` serialization view *(GET /product)*.
```python
@api.get('/product/<id>')
@dory.cache(key=lambda request, id: "product:%s" % id, timeout=timedelta(hours=1))
def get_product(request, id) -> Response:
"""
Serialize a Product
"""
...
```
Now everything works faster and as expected, but we did not contemplate that since the `Product` can be edited *(POST /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 custom key, decouple the cache configuration on a `Bloat`:
```python
class Product(dory.Bloat):
"""
Product's bloat
"""
prefix: str = 'product'
key: str
timeout: timedelta = timedelta(hours=1)
enabled: bool = True
def __init__(product_id: int):
self.key = '%s' % product_id
```
```python
@api.get('/product/<id>')
@bloats.Product.cache(args=lambda request, id: dict(product_id=id))
def get_product(request, id) -> Response:
"""
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.
```python
@api.post('/product/<id>')
def edit_product(request, id):
"""
Edit a Product
"""
# edit the product
services.product.edit(request.body)
# clean up outdated cache
bloats.Product(product_id=id).deflate()
```
Now your cache will always be in sync and it'll be configured in a cleaner way! 🔥
## Roadmap
- [ ] **Cache utils** (See [Cache utils](#Cache-utils))
- [ ] **Cache decorator**
- [ ] **Ratelimit**
- [ ] **Bloats 🐡** (See [Bloats](#Bloats))
- [ ] **Django signals**
```python
class Product(models.Model, dory.django.BloatModel):
"""
Store information about a Product
"""
id: int
name: str = m.CharField(max_length=24)
description: str = m.TextField()
```
```python
@api.get('/product/<id>')
@bloats.Product.cache(args=lambda request, id: dict(product_id=id), deflate_on=models.Product.post_save)
def get_product(request, id):
"""
Serialize a Product
"""
...
```
- [ ] **Bloats v2**
- The v2 of the `Bloats` will implement the method `.reflate()`, capable not only to `deflate` the current `Bloat` but to `inflate` it again. The design is still a `WIP`.
## Contributing
Suggestions and contributions are extremely welcome! ❤️
Just open an issue or a PR, and I'll respond as soon as I can.
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl dory-cache-0.1.0:
pip install dory-cache-0.1.0.whl
نصب پکیج tar.gz dory-cache-0.1.0:
pip install dory-cache-0.1.0.tar.gz