# graphene-django-optimizer
[](https://travis-ci.com/github/tfoxy/graphene-django-optimizer)
[](https://codecov.io/gh/tfoxy/graphene-django-optimizer)
[](https://pypi.org/project/graphene-django-optimizer/)
Optimize queries executed by [graphene-django](https://github.com/graphql-python/graphene-django) automatically, using [`select_related`](https://docs.djangoproject.com/en/2.0/ref/models/querysets/#select-related), [`prefetch_related`](https://docs.djangoproject.com/en/2.0/ref/models/querysets/#prefetch-related) and [`only`](https://docs.djangoproject.com/en/2.0/ref/models/querysets/#only) methods of Django QuerySet.
## Install
```bash
pip install graphene-django-optimizer
```
_Note: If you are using Graphene V2, please install version `0.8`. v0.9 and forward will support only Graphene V3_
## Usage
Having the following schema based on [the tutorial of graphene-django](http://docs.graphene-python.org/projects/django/en/latest/tutorial-plain/#hello-graphql-schema-and-object-types) (notice the use of `gql_optimizer`)
```py
# cookbook/ingredients/schema.py
import graphene
from graphene_django.types import DjangoObjectType
import graphene_django_optimizer as gql_optimizer
from cookbook.ingredients.models import Category, Ingredient
class CategoryType(DjangoObjectType):
class Meta:
model = Category
class IngredientType(DjangoObjectType):
class Meta:
model = Ingredient
class Query(graphene.ObjectType):
all_categories = graphene.List(CategoryType)
all_ingredients = graphene.List(IngredientType)
def resolve_all_categories(root, info):
return gql_optimizer.query(Category.objects.all(), info)
def resolve_all_ingredients(root, info):
return gql_optimizer.query(Ingredient.objects.all(), info)
```
We will show some graphql queries and the queryset that will be executed.
Fetching all the ingredients with the related category:
```graphql
{
allIngredients {
id
name
category {
id
name
}
}
}
```
```py
# optimized queryset:
ingredients = (
Ingredient.objects
.select_related('category')
.only('id', 'name', 'category__id', 'category__name')
)
```
Fetching all the categories with the related ingredients:
```graphql
{
allCategories {
id
name
ingredients {
id
name
}
}
}
```
```py
# optimized queryset:
categories = (
Category.objects
.only('id', 'name')
.prefetch_related(Prefetch(
'ingredients',
queryset=Ingredient.objects.only('id', 'name'),
))
)
```
## Advanced usage
Sometimes we need to have a custom resolver function. In those cases, the field can't be auto optimized.
So we need to use `gql_optimizer.resolver_hints` decorator to indicate the optimizations.
If the resolver returns a model field, we can use the `model_field` argument:
```py
import graphene
import graphene_django_optimizer as gql_optimizer
class ItemType(gql_optimizer.OptimizedDjangoObjectType):
product = graphene.Field('ProductType')
@gql_optimizer.resolver_hints(
model_field='product',
)
def resolve_product(root, info):
# check if user have permission for seeing the product
if info.context.user.is_anonymous():
return None
return root.product
```
This will automatically optimize any subfield of `product`.
Now, if the resolver uses related fields, you can use the `select_related` argument:
```py
import graphene
import graphene_django_optimizer as gql_optimizer
class ItemType(gql_optimizer.OptimizedDjangoObjectType):
name = graphene.String()
@gql_optimizer.resolver_hints(
select_related=('product', 'shipping'),
only=('product__name', 'shipping__name'),
)
def resolve_name(root, info):
return '{} {}'.format(root.product.name, root.shipping.name)
```
Notice the usage of the type `OptimizedDjangoObjectType`, which enables
optimization of any single node queries.
Finally, if your field has an argument for filtering results,
you can use the `prefetch_related` argument with a function
that returns a `Prefetch` instance as the value.
```py
from django.db.models import Prefetch
import graphene
import graphene_django_optimizer as gql_optimizer
class CartType(gql_optimizer.OptimizedDjangoObjectType):
items = graphene.List(
'ItemType',
product_id=graphene.ID(),
)
@gql_optimizer.resolver_hints(
prefetch_related=lambda info, product_id: Prefetch(
'items',
queryset=gql_optimizer.query(Item.objects.filter(product_id=product_id), info),
to_attr='gql_product_id_' + product_id,
),
)
def resolve_items(root, info, product_id):
return getattr(root, 'gql_product_id_' + product_id)
```
With these hints, any field can be optimized.
### Optimize with non model fields
Sometimes we need to have a custom non model fields. In those cases, the optimizer would not optimize with the Django `.only()` method.
So if we still want to optimize with the `.only()` method, we need to use `disable_abort_only` option:
```py
class IngredientType(gql_optimizer.OptimizedDjangoObjectType):
calculated_calories = graphene.String()
class Meta:
model = Ingredient
def resolve_calculated_calories(root, info):
return get_calories_for_ingredient(root.id)
class Query(object):
all_ingredients = graphene.List(IngredientType)
def resolve_all_ingredients(root, info):
return gql_optimizer.query(Ingredient.objects.all(), info, disable_abort_only=True)
```
## Contributing
See [CONTRIBUTING.md](./CONTRIBUTING.md)
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"description": "# graphene-django-optimizer\n\n[](https://travis-ci.com/github/tfoxy/graphene-django-optimizer)\n[](https://codecov.io/gh/tfoxy/graphene-django-optimizer)\n[](https://pypi.org/project/graphene-django-optimizer/)\n\n\n\nOptimize queries executed by [graphene-django](https://github.com/graphql-python/graphene-django) automatically, using [`select_related`](https://docs.djangoproject.com/en/2.0/ref/models/querysets/#select-related), [`prefetch_related`](https://docs.djangoproject.com/en/2.0/ref/models/querysets/#prefetch-related) and [`only`](https://docs.djangoproject.com/en/2.0/ref/models/querysets/#only) methods of Django QuerySet.\n\n## Install\n\n```bash\npip install graphene-django-optimizer\n```\n\n_Note: If you are using Graphene V2, please install version `0.8`. v0.9 and forward will support only Graphene V3_\n\n## Usage\n\nHaving the following schema based on [the tutorial of graphene-django](http://docs.graphene-python.org/projects/django/en/latest/tutorial-plain/#hello-graphql-schema-and-object-types) (notice the use of `gql_optimizer`)\n\n```py\n# cookbook/ingredients/schema.py\nimport graphene\n\nfrom graphene_django.types import DjangoObjectType\nimport graphene_django_optimizer as gql_optimizer\n\nfrom cookbook.ingredients.models import Category, Ingredient\n\n\nclass CategoryType(DjangoObjectType):\n class Meta:\n model = Category\n\n\nclass IngredientType(DjangoObjectType):\n class Meta:\n model = Ingredient\n\n\nclass Query(graphene.ObjectType):\n all_categories = graphene.List(CategoryType)\n all_ingredients = graphene.List(IngredientType)\n\n def resolve_all_categories(root, info):\n return gql_optimizer.query(Category.objects.all(), info)\n\n def resolve_all_ingredients(root, info):\n return gql_optimizer.query(Ingredient.objects.all(), info)\n```\n\nWe will show some graphql queries and the queryset that will be executed.\n\nFetching all the ingredients with the related category:\n\n```graphql\n{\n allIngredients {\n id\n name\n category {\n id\n name\n }\n }\n}\n```\n\n```py\n# optimized queryset:\ningredients = (\n Ingredient.objects\n .select_related('category')\n .only('id', 'name', 'category__id', 'category__name')\n)\n```\n\nFetching all the categories with the related ingredients:\n\n```graphql\n{\n allCategories {\n id\n name\n ingredients {\n id\n name\n }\n }\n}\n```\n\n```py\n# optimized queryset:\ncategories = (\n Category.objects\n .only('id', 'name')\n .prefetch_related(Prefetch(\n 'ingredients',\n queryset=Ingredient.objects.only('id', 'name'),\n ))\n)\n```\n\n## Advanced usage\n\nSometimes we need to have a custom resolver function. In those cases, the field can't be auto optimized.\nSo we need to use `gql_optimizer.resolver_hints` decorator to indicate the optimizations.\n\nIf the resolver returns a model field, we can use the `model_field` argument:\n\n```py\nimport graphene\nimport graphene_django_optimizer as gql_optimizer\n\n\nclass ItemType(gql_optimizer.OptimizedDjangoObjectType):\n product = graphene.Field('ProductType')\n\n @gql_optimizer.resolver_hints(\n model_field='product',\n )\n def resolve_product(root, info):\n # check if user have permission for seeing the product\n if info.context.user.is_anonymous():\n return None\n return root.product\n```\n\nThis will automatically optimize any subfield of `product`.\n\nNow, if the resolver uses related fields, you can use the `select_related` argument:\n\n```py\nimport graphene\nimport graphene_django_optimizer as gql_optimizer\n\n\nclass ItemType(gql_optimizer.OptimizedDjangoObjectType):\n name = graphene.String()\n\n @gql_optimizer.resolver_hints(\n select_related=('product', 'shipping'),\n only=('product__name', 'shipping__name'),\n )\n def resolve_name(root, info):\n return '{} {}'.format(root.product.name, root.shipping.name)\n```\n\nNotice the usage of the type `OptimizedDjangoObjectType`, which enables\noptimization of any single node queries.\n\nFinally, if your field has an argument for filtering results,\nyou can use the `prefetch_related` argument with a function\nthat returns a `Prefetch` instance as the value.\n\n```py\nfrom django.db.models import Prefetch\nimport graphene\nimport graphene_django_optimizer as gql_optimizer\n\n\nclass CartType(gql_optimizer.OptimizedDjangoObjectType):\n items = graphene.List(\n 'ItemType',\n product_id=graphene.ID(),\n )\n\n @gql_optimizer.resolver_hints(\n prefetch_related=lambda info, product_id: Prefetch(\n 'items',\n queryset=gql_optimizer.query(Item.objects.filter(product_id=product_id), info),\n to_attr='gql_product_id_' + product_id,\n ),\n )\n def resolve_items(root, info, product_id):\n return getattr(root, 'gql_product_id_' + product_id)\n```\n\nWith these hints, any field can be optimized.\n\n### Optimize with non model fields\n\nSometimes we need to have a custom non model fields. 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