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Relay library for graphql-core

Project description

Relay Library for GraphQL Python

GraphQL-relay-py is the Relay library for GraphQL-core.

It allows the easy creation of Relay-compliant servers using GraphQL-core.

GraphQL-Relay-Py is a Python port of graphql-relay-js, while GraphQL-Core is a Python port of GraphQL.js, the reference implementation of GraphQL for JavaScript.

Since version 3, GraphQL-Relay-Py and GraphQL-Core support Python 3.6 and above only. For older versions of Python, you can use version 2 of these libraries.

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Getting Started

A basic understanding of GraphQL and of the GraphQL Python implementation is needed to provide context for this library.

An overview of GraphQL in general is available in the README for the Specification for GraphQL.

This library is designed to work with the the GraphQL-Core Python reference implementation of a GraphQL server.

An overview of the functionality that a Relay-compliant GraphQL server should provide is in the GraphQL Relay Specification on the Relay website. That overview describes a simple set of examples that exist as tests in this repository. A good way to get started with this repository is to walk through that documentation and the corresponding tests in this library together.

Using Relay Library for GraphQL Python (graphql-core)

Install Relay Library for GraphQL Python

pip install graphql-core
pip install graphql-relay

When building a schema for GraphQL, the provided library functions can be used to simplify the creation of Relay patterns.


Helper functions are provided for both building the GraphQL types for connections and for implementing the resolver method for fields returning those types.

  • connection_args returns the arguments that fields should provide when they return a connection type.

  • connection_definitions returns a connection_type and its associated edgeType, given a name and a node type.

  • connection_from_array is a helper method that takes an array and the arguments from connection_args, does pagination and filtering, and returns an object in the shape expected by a connection_type's resolver function.

  • cursor_for_object_in_connection is a helper method that takes an array and a member object, and returns a cursor for use in the mutation payload.

An example usage of these methods from the test schema:

ship_edge, ship_connection = connection_definitions('Ship', shipType)

factionType = GraphQLObjectType(
    description='A faction in the Star Wars saga',
    fields=lambda: {
        'id': global_id_field('Faction'),
        'name': GraphQLField(
            description='The name of the faction.',
        'ships': GraphQLField(
            description='The ships used by the faction.',
            resolve=lambda faction, _info, **args: connection_from_array(
                [getShip(ship) for ship in faction.ships], args),

This shows adding a ships field to the Faction object that is a connection. It uses connection_definitions('Ship', shipType) to create the connection type, adds connection_args as arguments on this function, and then implements the resolver function by passing the array of ships and the arguments to connection_from_array.

Object Identification

Helper functions are provided for both building the GraphQL types for nodes and for implementing global IDs around local IDs.

  • node_definitions returns the Node interface that objects can implement, and returns the node root field to include on the query type. To implement this, it takes a function to resolve an ID to an object, and to determine the type of a given object.
  • to_global_id takes a type name and an ID specific to that type name, and returns a "global ID" that is unique among all types.
  • from_global_id takes the "global ID" created by to_global_id, and returns the type name and ID used to create it.
  • global_id_field creates the configuration for an id field on a node.
  • plural_identifying_root_field creates a field that accepts a list of non-ID identifiers (like a username) and maps then to their corresponding objects.

An example usage of these methods from the test schema:

def get_node(global_id, _info):
    type_, id_ = from_global_id(global_id)
    if type_ == 'Faction':
        return getFaction(id_)
    elif type_ == 'Ship':
        return getShip(id_)
        return None

def get_node_type(obj, _info, _type):
    if isinstance(obj, Faction):
        return factionType
        return shipType

node_interface, node_field = node_definitions(get_node, get_node_type)

factionType = GraphQLObjectType(
    name= 'Faction',
    description= 'A faction in the Star Wars saga',
    fields= lambda: {
        'id': global_id_field('Faction'),
    interfaces= [node_interface]

queryType = GraphQLObjectType(
    name= 'Query',
    fields= lambda: {
        'node': node_field

This uses node_definitions to construct the Node interface and the node field; it uses from_global_id to resolve the IDs passed in in the implementation of the function mapping ID to object. It then uses the global_id_field method to create the id field on Faction, which also ensures implements the node_interface. Finally, it adds the node field to the query type, using the node_field returned by node_definitions.


A helper function is provided for building mutations with single inputs and client mutation IDs.

  • mutation_with_client_mutation_id takes a name, input fields, output fields, and a mutation method to map from the input fields to the output fields, performing the mutation along the way. It then creates and returns a field configuration that can be used as a top-level field on the mutation type.

An example usage of these methods from the test schema:

class IntroduceShipMutation:
    def __init__(self, shipId, factionId, clientMutationId=None):
        self.shipId = shipId
        self.factionId = factionId
        self.clientMutationId = clientMutationId

def mutate_and_get_payload(_info, shipName, factionId):
    newShip = createShip(shipName, factionId)
    return IntroduceShipMutation(, factionId=factionId)

shipMutation = mutation_with_client_mutation_id(
        'shipName': GraphQLInputField(
        'factionId': GraphQLInputField(
        'ship': GraphQLField(
            resolve=lambda payload, _info: getShip(payload.shipId)
        'faction': GraphQLField(
            resolve=lambda payload, _info: getFaction(payload.factionId)

mutationType = GraphQLObjectType(
    fields=lambda: {
        'introduceShip': shipMutation

This code creates a mutation named IntroduceShip, which takes a faction ID and a ship name as input. It outputs the Faction and the Ship in question. mutate_and_get_payload then gets each input field as keyword parameter, performs the mutation by constructing the new ship, then returns an object that will be resolved by the output fields.

Our mutation type then creates the introduceShip field using the return value of mutation_with_client_mutation_id.


After cloning this repository from GitHub, we recommend using Poetry to create a test environment. With poetry installed, you do this with the following command:

poetry install

You can then run the complete test suite like this:

poetry run pytest

In order to run only a part of the tests with increased verbosity, you can add pytest options, like this:

poetry run pytest tests/node -vv

In order to check the code style with flake8, use this:

poetry run flake8

Use the tox command to run the test suite with different Python versions and perform all additional source code checks. You can also restrict tox to an individual environment, like this:

poetry run tox -e py37

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