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Query Optimizer |
The query optimizer is a must-have extension for improved performance of your schema. What it does:
- Call QuerySet.select_related() on all selected foreign key relations by the query to avoid requiring an extra query to retrieve those
- Call QuerySet.prefetch_related() on all selected many-to-one/many-to-many relations by the query to avoid requiring an extra query to retrieve those.
- Call QuerySet.only() on all selected fields to reduce the database payload and only requesting what is actually being selected
- Call QuerySet.annotate() to support any passed annotations of Query Expressions.
Those are specially useful to avoid some common GraphQL pitfalls, like the famous n+1
issue.
The automatic optimization can be enabled by adding the DjangoOptimizerExtension
to your strawberry's schema config.
import strawberry
from strawberry_django.optimizer import DjangoOptimizerExtension
schema = strawberry.Schema(
Query,
extensions=[
# other extensions...
DjangoOptimizerExtension,
]
)
The optimizer will try to optimize all types automatically by introspecting it. Consider the following example:
class Artist(models.Model):
name = models.CharField()
class Album(models.Model):
name = models.CharField()
release_date = models.DateTimeField()
artist = models.ForeignKey("Artist", related_name="albums")
class Song(models.Model):
name = model.CharField()
duration = models.DecimalField()
album = models.ForeignKey("Album", related_name="songs")
from strawberry import auto
import strawberry_django
@strawberry_django.type(Artist)
class ArtistType:
name: auto
albums: list["AlbumType"]
albums_count: int = strawberry_django.field(annotate=Count("albums"))
@strawberry_django.type(Album)
class AlbumType:
name: auto
release_date: auto
artist: ArtistType
songs: list["SongType"]
@strawberry_django.type(Song)
class SongType:
name: auto
duration: auto
album_type: AlbumType
@strawberry.type
class Query:
artist: Artist = strawberry_django.field()
songs: list[SongType] = strawberry_django.field()
Querying for artist
and songs
like this:
query {
artist {
id
name
albums {
id
name
songs {
id
name
}
}
albumsCount
}
song {
id
album {
id
name
artist {
id
name
albums {
id
name
release_date
}
}
}
}
}
Would produce an ORM query like this:
# For "artist" query
Artist.objects.all().only("id", "name").prefetch_related(
Prefetch(
"albums",
queryset=Album.objects.all().only("id", "name").prefetch_related(
Prefetch(
"songs",
Song.objects.all().only("id", "name"),
)
)
),
).annotate(
albums_count=Count("albums")
)
# For "songs" query
Song.objects.all().only(
"id",
"album",
"album__id",
"album__name",
"album__release_date", # Note about this below
"album__artist",
"album__artist__id",
).select_related(
"album",
"album__artist",
).prefetch_related(
Prefetch(
"album__artist__albums",
Album.objects.all().only("id", "name", "release_date"),
)
)
Note
Even though album__release_date
field was not selected here, it got selected
in the prefetch query later. Since Django caches known objects, we have to select it here or
else it would trigger extra queries latter.
Sometimes you will have a custom resolver which cannot be automatically optimized by the extension. Take this for example:
class OrderItem(models.Model):
price = models.DecimalField()
quantity = models.IntegerField()
@property
def total(self) -> decimal.Decimal:
return self.price * self.quantity
from strawberry import auto
import strawberry_django
@strawberry_django.type(models.OrderItem)
class OrderItem:
price: auto
quantity: auto
total: auto
In this case, if only total
is requested it would trigger an extra query for
both price
and quantity
because both had their value retrievals
defered
by the optimizer.
A solution in this case would be to "tell the optimizer" how to optimize that field:
from strawberry import auto
import strawberry_django
@strawberry_django.type(models.OrderItem)
class OrderItem:
price: auto
quantity: auto
total: auto = strawberry_django.field(
only=["price", "quantity"],
)
Or if you are using a custom resolver:
import decimal
from strawberry import auto
import strawberry_django
@strawberry_django.type(models.OrderItem)
class OrderItem:
price: auto
quantity: auto
@strawberry_django.field(only=["price", "quantity"])
def total(self, root: models.OrderItem) -> decimal.Decimal:
return root.price * root.quantity # or root.total directly
The following options are accepted for optimizer hints:
only
: a list of fields in the same format as accepted by QuerySet.only()select_related
: a list of relations to join using QuerySet.select_related()prefetch_related
: a list of relations to prefetch using QuerySet.prefetch_related(). The options here are strings or a callable in the format ofCallable[[Info], Prefetch]
(e.g.prefetch_related=[lambda info: Prefetch(...)]
)annotate
: a dict of expressions to annotate using QuerySet.annotate(). The keys of this dict are strings, and each value is a Query Expression or a callable in the format ofCallable[[Info], BaseExpression]
(e.g.annotate={"total": lambda info: Sum(...)}
)
It is also possible to include type hints directly in the models' @property
to allow it to be resolved with auto
, while the GraphQL schema doesn't have
to worry about its internal logic.
For that this integration provides 2 decorators that can be used:
strawberry_django.model_property
: similar to@property
but accepts optimization hintsstrawberry_django.cached_model_property
: similar to@cached_property
but accepts optimization hints
The example in the previous section could be written using @model_property
like this:
from strawberry_django.descriptors import model_property
class OrderItem(models.Model):
price = models.DecimalField()
quantity = models.IntegerField()
@model_property(only=["price", "quantity"])
def total(self) -> decimal.Decimal:
return self.price * self.quantity
from strawberry import auto
import strawberry_django
@strawberry_django.type(models.OrderItem)
class OrderItem:
price: auto
quantity: auto
total: auto
total
now will be properly optimized since it points to a @model_property
decorated attribute, which contains the required information for optimizing it.
The optimizer has dedicated support for polymorphic queries, that is, fields which return an interface. The optimizer will handle optimizing any subtypes of the interface as necessary. This is supported on top level queries as well as relations between models. See the following sections for how this interacts with your models.
If you are already using the Django Polymorphic library, polymorphic queries work out of the box.
from django.db import models
from polymorphic.models import PolymorphicModel
class Project(PolymorphicModel):
topic = models.CharField(max_length=255)
class ResearchProject(Project):
supervisor = models.CharField(max_length=30)
class ArtProject(Project):
artist = models.CharField(max_length=30)
import strawberry
import strawberry_django
from . import models
@strawberry_django.interface(models.Project)
class ProjectType:
topic: strawberry.auto
@strawberry_django.type(models.ResearchProject)
class ResearchProjectType(ProjectType):
supervisor: strawberry.auto
@strawberry_django.type(models.ArtProject)
class ArtProjectType(ProjectType):
artist: strawberry.auto
@strawberry.type
class Query:
projects: list[ProjectType] = strawberry_django.field()
The projects
field will return either ResearchProjectType or ArtProjectType, matching on whether it is a
ResearchProject or ArtProject. The optimizer will make sure to only select those fields from subclasses which are
requested in the GraphQL query in the same way that it does normally.
Warning
The optimizer does not filter your QuerySet and Django will return
all instances of your model, regardless of whether their type exists in your GraphQL schema or not.
Make sure you have a corresponding type for every model subclass or add a get_queryset
method to your
GraphQL interface type to filter out unwanted subtypes.
Otherwise you might receive an error like
Abstract type 'ProjectType' must resolve to an Object type at runtime for field 'Query.projects'.
Models using InheritanceManager
from django-model-utils
are also supported.
from django.db import models
from model_utils.managers import InheritanceManager
class Project(models.Model):
topic = models.CharField(max_length=255)
objects = InheritanceManager()
class ResearchProject(Project):
supervisor = models.CharField(max_length=30)
class ArtProject(Project):
artist = models.CharField(max_length=30)
import strawberry
import strawberry_django
from . import models
@strawberry_django.interface(models.Project)
class ProjectType:
topic: strawberry.auto
@strawberry_django.type(models.ResearchProject)
class ResearchProjectType(ProjectType):
supervisor: strawberry.auto
@strawberry_django.type(models.ArtProject)
class ArtProjectType(ProjectType):
artist: strawberry.auto
@strawberry.type
class Query:
projects: list[ProjectType] = strawberry_django.field()
The projects
field will return either ResearchProjectType or ArtProjectType, matching on whether it is a
ResearchProject or ArtProject. The optimizer automatically calls select_subclasses
, passing in any subtypes present
in your schema.
Warning
The optimizer does not filter your QuerySet and Django will return
all instances of your model, regardless of whether their type exists in your GraphQL schema or not.
Make sure you have a corresponding type for every model subclass or add a get_queryset
method to your
GraphQL interface type to filter out unwanted subtypes.
Otherwise you might receive an error like
Abstract type 'ProjectType' must resolve to an Object type at runtime for field 'Query.projects'.
Note
If you have polymorphic relations (as in: a field that points to a model with subclasses), you need to make sure
the manager being used to look up the related model is an InheritanceManager
.
Strawberry Django uses the model's base manager
by default, which is different from the standard objects
.
Either change your base manager to also be an InheritanceManager
or set Strawberry Django to use the default
manager: DjangoOptimizerExtension(prefetch_custom_queryset=True)
.
The optimizer also supports polymorphism even if your models are not polymorphic.
resolve_type
in the GraphQL interface type is used to tell GraphQL the actual type that should be used.
from django.db import models
class Project(models.Model):
topic = models.CharField(max_length=255)
supervisor = models.CharField(max_length=30)
artist = models.CharField(max_length=30)
import strawberry
import strawberry_django
from . import models
@strawberry_django.interface(models.Project)
class ProjectType:
topic: strawberry.auto
@classmethod
def resolve_type(cls, value, info, parent_type) -> str:
if not isinstance(value, models.Project):
raise TypeError()
if value.artist:
return 'ArtProjectType'
if value.supervisor:
return 'ResearchProjectType'
raise TypeError()
@classmethod
def get_queryset(cls, qs, info):
return qs
@strawberry_django.type(models.ResearchProject)
class ResearchProjectType(ProjectType):
supervisor: strawberry.auto
@strawberry_django.type(models.ArtProject)
class ArtProjectType(ProjectType):
artist: strawberry.auto
@strawberry.type
class Query:
projects: list[ProjectType] = strawberry_django.field()
Warning
Make sure to add get_queryset
to your interface type, to force the optimizer to use
prefetch_related
, otherwise this technique will not work for relation fields.