A decorator which prefers a precalculated attribute over calling the decorated method.
Project description
Requirements
Python 3.6+
What is it?
fallback_property transforms a function into a property and uses the decorated function as fallback if no value was assigned to the property itself. A special descriptor (fallback_property.FallbackDescriptor) is used internally.
Django (or similar frameworks)
fallback_property is useful if you have a function that aggregates values from related objects, which could already be fetched using an annotated queryset. The decorator will favor the precalculated value over calling the actual method.
It is especially helpful, if you optimize your application and want to replace legacy or performance critical properties with precalulated values using .annotate().
How to use it?
Simply define a function and use the decorator fallback_property
from fallback_property import fallback_property class Foo: @fallback_property() def fallback_func(self): return 7
Arguments
The fallback_property() has two optional arguments.
- cached: bool = True
If the property is accessed multiple times, call the fallback function only once.
- logging: bool = False
Log a warning if there was a fallback to the decorated, original method.
Usage Example (Django)
Suppose we have the following models
from django.db import models class Pipeline(model.Model): @property def total_length(self): return sum(self.parts.values_list('length', flat=True)) class Parts(models.Model): length = models.PositiveIntegerField() pipeline = models.ForeignKey(Pipeline, related_name='parts')
Calling pipline.total_length will always trigger another query and is even more expensive when dealing with multiple objects. This can be optimized by using .annotate() and fallback_property()
from django.db import models, QuerySet from django.db.functions import Coalesce from django.db.models import Sum from fallback_property import fallback_property class PipelineQuerySet(QuerySet): def with_total_length(self): return self.annotate( total_length=Coalesce( Sum('parts__length', output_field=models.IntegerField()), 0, ) ) class Pipeline(model.Model): @fallback_property(logging=True) def total_length(self): return sum(self.parts.values_list('length', flat=True))
You can now access the total_length without triggering another query or get a warning, when the fallback function is used
pipeline = Pipeline.objects.with_total_length().first() print(pipeline.total_length)
Important: The annotated value and the property must have the same name.
Development
This project is using poetry to manage all dev dependencies.
Clone this repository and run
poetry install poetry run pip install django
to create a virtual environment with all dependencies.
You can now run the test suite using
poetry run pytest
This repository follows the angular commit conventions. You can register a pre-commit hook to validate your commit messages by using husky. The configurations are already in place if you have nodejs installed. Just run
npm install
and the pre-commit hook will be registered.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file fallback-property-0.2.0.tar.gz
.
File metadata
- Download URL: fallback-property-0.2.0.tar.gz
- Upload date:
- Size: 6.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.8.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d38ade19054561af1ff1a75d31039f5433dc69a6f0dab575f4325f6cf3309a9e |
|
MD5 | c7720246d53735c7d191e90c47cf7045 |
|
BLAKE2b-256 | ac6869bf9263c237af25f1c9a72a6f81e5faee98190820d96f5d3149b724f328 |
File details
Details for the file fallback_property-0.2.0-py3-none-any.whl
.
File metadata
- Download URL: fallback_property-0.2.0-py3-none-any.whl
- Upload date:
- Size: 5.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.8.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 81df40929c17b1d5520e1a168cf28c926240a17f51455a7144d78d4689bfe786 |
|
MD5 | 0bfbd3214d4fe3b644b4cf7ed877ce0a |
|
BLAKE2b-256 | bb862df9de9c7c44472c1afa9d47638e1da14cdbd1e018c7f9c27f614bd8c72d |