Epoxy is a magical tool for rapid development of GraphQL types, schemas, resolvers, mutations quickly & pragmatically.
- Minimal Boilerplate: You can create a GraphQL schema and execute it in less than 5 lines of code.
- Definition Ordering: It doesn't matter. Define your objects in any order you want. Epoxy will take care of the rest.
- Quick: Once you create your schema, epoxy doesn't get in the way. Your resolvers will be called directly by
graphql-corewith no additional indirection.
Epoxy is available on pypi under the package name graphql-epoxy, you can get it by running:
pip install graphql-epoxy
Defining a GraphQL Schema using Epoxy is as simple as creating a TypeRegistry and using it to create types for you.
from epoxy import TypeRegistry R = TypeRegistry() class Character(R.Interface): id = R.ID name = R.String friends = R.Character.List class Human(R.Implements.Character): home_planet = R.String.NonNull class Query(R.ObjectType): human = R.Human foo = R.Foo # This is defined below! Ordering doesn't matter! def resolve_human(self, obj, args, info): """This will be used as the description of the field Query.human.""" return Human(id=5, name='Bob', friends=[Human(id=6, name='Bill')]
You can even have epoxy learn about your already defined Python enums.
class MoodStatus(enums.Enum): HAPPY = 1 SAD = 2 MELANCHOLY = 3 R(MoodStatus)
And then use it in an ObjectType:
class Foo(R.ObjectType): mood = R.MoodStatus # or mood = R.Field(R.MoodStatus, description="Describing the mood of Foo, is sometimes pretty hard.") def resolve_mood(self, *args): return MoodStatus.HAPPY.value
Schema is a GraphQLSchema object. You can now use it with graphql:
schema = R.schema(R.Query) result = graphql(schema, ''' { human { id name homePlanet friends { name homePlanet } } } ''')
The schema is now defined as:
enum MoodStatus { HAPPY SAD MELANCHOLY } interface Character { id: ID name: String friends: [Character] } type Human implements Character { id: ID name: String friends: [Character] homePlanet: String! } type Foo { mood: MoodStatus } type Query { human: Human foo: Foo }
Notice that epoxy converted snake_cased fields to camelCase in the GraphQL Schema.
You can bring your own objects, (like a Django or SQLAlchemy model), or you can use the class you just created:
me = Human(id=2, name='Jake', home_planet='Earth', friends=[Human(id=3, name='Syrus', home_planet='Earth')]) print(me) # <Human id=2, name='Jake', home_planet='Earth', friends=[<Human id=3, name='Syrus', home_planet='Earth', friends=[]>]]> print(me.name) # Jake
Epoxy will automatically resolve the runtime types of your objects if class that you created from R.ObjectType, but
if you want to bring your own Human (i.e. a model.Model from Django), just tell Epoxy about it! And if you don't want
to, you can just override the is_type_of function inside Human to something more to your liking.
from django.db import models from my_app.graphql import R @R.Human.CanBe class RealHumanBean(models.Model): """ And a real hero. """ name = models.CharField(name=Name) # Or if you don't want to use the decorator: R.Human.CanBe(Human)
Epoxy also supports defining mutations. Making a Mutation a Relay mutation is as simple as changing R.Mutation to
Relay.Mutation.
class AddFriend(R.Mutation): class Input: human_to_add = R.ID.NonNull class Output: new_friends_list = R.Human.List @R.resolve_with_args def resolve(self, obj, human_to_add): obj.add_friend(human_to_add) return self.Output(new_friends_list=obj.friends) schema = R.schema(R.Query, R.Mutations)
You can then execute the query:
mutation AddFriend { addFriend(input: {humanToAdd: 6}) { newFriendsList { id name homePlanet } } }
class DateTime(R.Scalar): @staticmethod def serialize(dt): return dt.isoformat() @staticmethod def parse_literal(node): if isinstance(node, ast.StringValue): return datetime.datetime.strptime(node.value, "%Y-%m-%dT%H:%M:%S.%f") @staticmethod def parse_value(value): return datetime.datetime.strptime(value, "%Y-%m-%dT%H:%M:%S.%f")
class SimpleInput(R.InputType): a = R.Int b = R.Int some_underscore = R.String some_from_field = R.String(default_value='Hello World')
from enum import Enum @R class MyEnum(Enum): FOO = 1 BAR = 2 BAZ = 3
Use the force, check out how we've defined the schema for the starwars tests, and compare them to the reference implementation's schema.
At this point, Epoxy has rudimentary relay support. Enable support for Relay by mixing in the RelayMixin using
TypeResolver.Mixin.
from epoxy.contrib.relay import RelayMixin from epoxy.contrib.relay.data_source.memory import InMemoryDataSource # Epoxy provides an "in memory" data source, that implements `epoxy.contrib.relay.data_source.BaseDataSource`, # which can be used to easily create a mock data source. In practice, you'd implement your own data source. data_source = InMemoryDataSource() R = TypeRegistry() Relay = R.Mixin(RelayMixin, data_source)
Once RelayMixin has been mixed into the Registry, things can subclass Node automatically!
class Pet(R.Implements[Relay.Node]): name = R.String
Connections can be defined upon any object type. Here we'll make a Query root node that provides a connection
to a list of pets & a node field to resolve an indivudal node.
class Query(R.ObjectType): pets = Relay.Connection('Pet', R.Pet) # The duplicate 'Pet' definition is just temporary and will be removed. node = Relay.NodeField
class SimpleAddition(Relay.Mutation): class Input: a = R.Int b = R.Int class Output: sum = R.Int def execute(self, obj, input, info): return self.Output(sum=input.a + input.b)
Let's add some pets to the data_source and query them!
# Schema has to be defined so that all thunks are resolved before we can use `Pet` as a container. Schema = R.Schema(R.Query) pet_names = ["Max", "Buddy", "Charlie", "Jack", "Cooper", "Rocky"] for i, pet_name in enumerate(pet_names, 1): data_source.add(Pet(id=i, name=pet_name))
result = graphql(Schema, ''' { pets(first: 5) { edges { node { id name } cursor } pageInfo { hasPreviousPage hasNextPage startCursor endCursor } } node(id: "UGV0OjU=") { id ... on Pet { name } } } ''')