aws-cdk.aws-appsync1.204.0
Published
The CDK Construct Library for AWS::AppSync
pip install aws-cdk-aws-appsync
Package Downloads
Authors
Requires Python
~=3.7
Dependencies
- aws-cdk.aws-certificatemanager
(==1.204.0)
- aws-cdk.aws-cognito
(==1.204.0)
- aws-cdk.aws-dynamodb
(==1.204.0)
- aws-cdk.aws-ec2
(==1.204.0)
- aws-cdk.aws-elasticsearch
(==1.204.0)
- aws-cdk.aws-iam
(==1.204.0)
- aws-cdk.aws-lambda
(==1.204.0)
- aws-cdk.aws-opensearchservice
(==1.204.0)
- aws-cdk.aws-rds
(==1.204.0)
- aws-cdk.aws-s3-assets
(==1.204.0)
- aws-cdk.aws-secretsmanager
(==1.204.0)
- aws-cdk.core
(==1.204.0)
- constructs
(<4.0.0,>=3.3.69)
- jsii
(<2.0.0,>=1.84.0)
- publication
(>=0.0.3)
- typeguard
(~=2.13.3)
AWS AppSync Construct Library
---AWS CDK v1 has reached End-of-Support on 2023-06-01. This package is no longer being updated, and users should migrate to AWS CDK v2.
For more information on how to migrate, see the Migrating to AWS CDK v2 guide.
The @aws-cdk/aws-appsync
package contains constructs for building flexible
APIs that use GraphQL.
import aws_cdk.aws_appsync as appsync
Example
DynamoDB
Example of a GraphQL API with AWS_IAM
authorization resolving into a DynamoDb
backend data source.
GraphQL schema file schema.graphql
:
type demo {
id: String!
version: String!
}
type Query {
getDemos: [ demo! ]
}
input DemoInput {
version: String!
}
type Mutation {
addDemo(input: DemoInput!): demo
}
CDK stack file app-stack.ts
:
api = appsync.GraphqlApi(self, "Api",
name="demo",
schema=appsync.Schema.from_asset(path.join(__dirname, "schema.graphql")),
authorization_config=appsync.AuthorizationConfig(
default_authorization=appsync.AuthorizationMode(
authorization_type=appsync.AuthorizationType.IAM
)
),
xray_enabled=True
)
demo_table = dynamodb.Table(self, "DemoTable",
partition_key=dynamodb.Attribute(
name="id",
type=dynamodb.AttributeType.STRING
)
)
demo_dS = api.add_dynamo_db_data_source("demoDataSource", demo_table)
# Resolver for the Query "getDemos" that scans the DynamoDb table and returns the entire list.
demo_dS.create_resolver(
type_name="Query",
field_name="getDemos",
request_mapping_template=appsync.MappingTemplate.dynamo_db_scan_table(),
response_mapping_template=appsync.MappingTemplate.dynamo_db_result_list()
)
# Resolver for the Mutation "addDemo" that puts the item into the DynamoDb table.
demo_dS.create_resolver(
type_name="Mutation",
field_name="addDemo",
request_mapping_template=appsync.MappingTemplate.dynamo_db_put_item(
appsync.PrimaryKey.partition("id").auto(),
appsync.Values.projecting("input")),
response_mapping_template=appsync.MappingTemplate.dynamo_db_result_item()
)
Aurora Serverless
AppSync provides a data source for executing SQL commands against Amazon Aurora Serverless clusters. You can use AppSync resolvers to execute SQL statements against the Data API with GraphQL queries, mutations, and subscriptions.
# Build a data source for AppSync to access the database.
# api: appsync.GraphqlApi
# Create username and password secret for DB Cluster
secret = rds.DatabaseSecret(self, "AuroraSecret",
username="clusteradmin"
)
# The VPC to place the cluster in
vpc = ec2.Vpc(self, "AuroraVpc")
# Create the serverless cluster, provide all values needed to customise the database.
cluster = rds.ServerlessCluster(self, "AuroraCluster",
engine=rds.DatabaseClusterEngine.AURORA_MYSQL,
vpc=vpc,
credentials={"username": "clusteradmin"},
cluster_identifier="db-endpoint-test",
default_database_name="demos"
)
rds_dS = api.add_rds_data_source("rds", cluster, secret, "demos")
# Set up a resolver for an RDS query.
rds_dS.create_resolver(
type_name="Query",
field_name="getDemosRds",
request_mapping_template=appsync.MappingTemplate.from_string("""
{
"version": "2018-05-29",
"statements": [
"SELECT * FROM demos"
]
}
"""),
response_mapping_template=appsync.MappingTemplate.from_string("""
$utils.toJson($utils.rds.toJsonObject($ctx.result)[0])
""")
)
# Set up a resolver for an RDS mutation.
rds_dS.create_resolver(
type_name="Mutation",
field_name="addDemoRds",
request_mapping_template=appsync.MappingTemplate.from_string("""
{
"version": "2018-05-29",
"statements": [
"INSERT INTO demos VALUES (:id, :version)",
"SELECT * WHERE id = :id"
],
"variableMap": {
":id": $util.toJson($util.autoId()),
":version": $util.toJson($ctx.args.version)
}
}
"""),
response_mapping_template=appsync.MappingTemplate.from_string("""
$utils.toJson($utils.rds.toJsonObject($ctx.result)[1][0])
""")
)
HTTP Endpoints
GraphQL schema file schema.graphql
:
type job {
id: String!
version: String!
}
input DemoInput {
version: String!
}
type Mutation {
callStepFunction(input: DemoInput!): job
}
GraphQL request mapping template request.vtl
:
{
"version": "2018-05-29",
"method": "POST",
"resourcePath": "/",
"params": {
"headers": {
"content-type": "application/x-amz-json-1.0",
"x-amz-target":"AWSStepFunctions.StartExecution"
},
"body": {
"stateMachineArn": "<your step functions arn>",
"input": "{ \"id\": \"$context.arguments.id\" }"
}
}
}
GraphQL response mapping template response.vtl
:
{
"id": "${context.result.id}"
}
CDK stack file app-stack.ts
:
api = appsync.GraphqlApi(self, "api",
name="api",
schema=appsync.Schema.from_asset(path.join(__dirname, "schema.graphql"))
)
http_ds = api.add_http_data_source("ds", "https://states.amazonaws.com",
name="httpDsWithStepF",
description="from appsync to StepFunctions Workflow",
authorization_config=appsync.AwsIamConfig(
signing_region="us-east-1",
signing_service_name="states"
)
)
http_ds.create_resolver(
type_name="Mutation",
field_name="callStepFunction",
request_mapping_template=appsync.MappingTemplate.from_file("request.vtl"),
response_mapping_template=appsync.MappingTemplate.from_file("response.vtl")
)
Amazon OpenSearch Service
AppSync has builtin support for Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) from domains that are provisioned through your AWS account. You can use AppSync resolvers to perform GraphQL operations such as queries, mutations, and subscriptions.
import aws_cdk.aws_opensearchservice as opensearch
# api: appsync.GraphqlApi
user = iam.User(self, "User")
domain = opensearch.Domain(self, "Domain",
version=opensearch.EngineVersion.OPENSEARCH_1_2,
removal_policy=RemovalPolicy.DESTROY,
fine_grained_access_control=opensearch.AdvancedSecurityOptions(master_user_arn=user.user_arn),
encryption_at_rest=opensearch.EncryptionAtRestOptions(enabled=True),
node_to_node_encryption=True,
enforce_https=True
)
ds = api.add_open_search_data_source("ds", domain)
ds.create_resolver(
type_name="Query",
field_name="getTests",
request_mapping_template=appsync.MappingTemplate.from_string(JSON.stringify({
"version": "2017-02-28",
"operation": "GET",
"path": "/id/post/_search",
"params": {
"headers": {},
"query_string": {},
"body": {"from": 0, "size": 50}
}
})),
response_mapping_template=appsync.MappingTemplate.from_string("""[
#foreach($entry in $context.result.hits.hits)
#if( $velocityCount > 1 ) , #end
$utils.toJson($entry.get("_source"))
#end
]""")
)
Custom Domain Names
For many use cases you may want to associate a custom domain name with your GraphQL API. This can be done during the API creation.
import aws_cdk.aws_certificatemanager as acm
import aws_cdk.aws_route53 as route53
# hosted zone and route53 features
# hosted_zone_id: str
zone_name = "example.com"
my_domain_name = "api.example.com"
certificate = acm.Certificate(self, "cert", domain_name=my_domain_name)
api = appsync.GraphqlApi(self, "api",
name="myApi",
domain_name=appsync.DomainOptions(
certificate=certificate,
domain_name=my_domain_name
)
)
# hosted zone for adding appsync domain
zone = route53.HostedZone.from_hosted_zone_attributes(self, "HostedZone",
hosted_zone_id=hosted_zone_id,
zone_name=zone_name
)
# create a cname to the appsync domain. will map to something like xxxx.cloudfront.net
route53.CnameRecord(self, "CnameApiRecord",
record_name="api",
zone=zone,
domain_name=my_domain_name
)
Schema
Every GraphQL Api needs a schema to define the Api. CDK offers appsync.Schema
for static convenience methods for various types of schema declaration: code-first
or schema-first.
Code-First
When declaring your GraphQL Api, CDK defaults to a code-first approach if the
schema
property is not configured.
api = appsync.GraphqlApi(self, "api", name="myApi")
CDK will declare a Schema
class that will give your Api access functions to
define your schema code-first: addType
, addToSchema
, etc.
You can also declare your Schema
class outside of your CDK stack, to define
your schema externally.
schema = appsync.Schema()
schema.add_type(appsync.ObjectType("demo",
definition={"id": appsync.GraphqlType.id()}
))
api = appsync.GraphqlApi(self, "api",
name="myApi",
schema=schema
)
See the code-first schema section for more details.
Schema-First
You can define your GraphQL Schema from a file on disk. For convenience, use
the appsync.Schema.fromAsset
to specify the file representing your schema.
api = appsync.GraphqlApi(self, "api",
name="myApi",
schema=appsync.Schema.from_asset(path.join(__dirname, "schema.graphl"))
)
Imports
Any GraphQL Api that has been created outside the stack can be imported from
another stack into your CDK app. Utilizing the fromXxx
function, you have
the ability to add data sources and resolvers through a IGraphqlApi
interface.
# api: appsync.GraphqlApi
# table: dynamodb.Table
imported_api = appsync.GraphqlApi.from_graphql_api_attributes(self, "IApi",
graphql_api_id=api.api_id,
graphql_api_arn=api.arn
)
imported_api.add_dynamo_db_data_source("TableDataSource", table)
If you don't specify graphqlArn
in fromXxxAttributes
, CDK will autogenerate
the expected arn
for the imported api, given the apiId
. For creating data
sources and resolvers, an apiId
is sufficient.
Authorization
There are multiple authorization types available for GraphQL API to cater to different access use cases. They are:
- API Keys (
AuthorizationType.API_KEY
) - Amazon Cognito User Pools (
AuthorizationType.USER_POOL
) - OpenID Connect (
AuthorizationType.OPENID_CONNECT
) - AWS Identity and Access Management (
AuthorizationType.AWS_IAM
) - AWS Lambda (
AuthorizationType.AWS_LAMBDA
)
These types can be used simultaneously in a single API, allowing different types of clients to access data. When you specify an authorization type, you can also specify the corresponding authorization mode to finish defining your authorization. For example, this is a GraphQL API with AWS Lambda Authorization.
import aws_cdk.aws_lambda as lambda_
# auth_function: lambda.Function
appsync.GraphqlApi(self, "api",
name="api",
schema=appsync.Schema.from_asset(path.join(__dirname, "appsync.test.graphql")),
authorization_config=appsync.AuthorizationConfig(
default_authorization=appsync.AuthorizationMode(
authorization_type=appsync.AuthorizationType.LAMBDA,
lambda_authorizer_config=appsync.LambdaAuthorizerConfig(
handler=auth_function
)
)
)
)
Permissions
When using AWS_IAM
as the authorization type for GraphQL API, an IAM Role
with correct permissions must be used for access to API.
When configuring permissions, you can specify specific resources to only be
accessible by IAM
authorization. For example, if you want to only allow mutability
for IAM
authorized access you would configure the following.
In schema.graphql
:
type Mutation {
updateExample(...): ...
@aws_iam
}
In IAM
:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"appsync:GraphQL"
],
"Resource": [
"arn:aws:appsync:REGION:ACCOUNT_ID:apis/GRAPHQL_ID/types/Mutation/fields/updateExample"
]
}
]
}
See documentation for more details.
To make this easier, CDK provides grant
API.
Use the grant
function for more granular authorization.
# api: appsync.GraphqlApi
role = iam.Role(self, "Role",
assumed_by=iam.ServicePrincipal("lambda.amazonaws.com")
)
api.grant(role, appsync.IamResource.custom("types/Mutation/fields/updateExample"), "appsync:GraphQL")
IamResource
In order to use the grant
functions, you need to use the class IamResource
.
IamResource.custom(...arns)
permits custom ARNs and requires an argument.IamResouce.ofType(type, ...fields)
permits ARNs for types and their fields.IamResource.all()
permits ALL resources.
Generic Permissions
Alternatively, you can use more generic grant
functions to accomplish the same usage.
These include:
- grantMutation (use to grant access to Mutation fields)
- grantQuery (use to grant access to Query fields)
- grantSubscription (use to grant access to Subscription fields)
# api: appsync.GraphqlApi
# role: iam.Role
# For generic types
api.grant_mutation(role, "updateExample")
# For custom types and granular design
api.grant(role, appsync.IamResource.of_type("Mutation", "updateExample"), "appsync:GraphQL")
Pipeline Resolvers and AppSync Functions
AppSync Functions are local functions that perform certain operations onto a backend data source. Developers can compose operations (Functions) and execute them in sequence with Pipeline Resolvers.
# api: appsync.GraphqlApi
appsync_function = appsync.AppsyncFunction(self, "function",
name="appsync_function",
api=api,
data_source=api.add_none_data_source("none"),
request_mapping_template=appsync.MappingTemplate.from_file("request.vtl"),
response_mapping_template=appsync.MappingTemplate.from_file("response.vtl")
)
AppSync Functions are used in tandem with pipeline resolvers to compose multiple operations.
# api: appsync.GraphqlApi
# appsync_function: appsync.AppsyncFunction
pipeline_resolver = appsync.Resolver(self, "pipeline",
api=api,
data_source=api.add_none_data_source("none"),
type_name="typeName",
field_name="fieldName",
request_mapping_template=appsync.MappingTemplate.from_file("beforeRequest.vtl"),
pipeline_config=[appsync_function],
response_mapping_template=appsync.MappingTemplate.from_file("afterResponse.vtl")
)
Learn more about Pipeline Resolvers and AppSync Functions here.
Code-First Schema
CDK offers the ability to generate your schema in a code-first approach. A code-first approach offers a developer workflow with:
- modularity: organizing schema type definitions into different files
- reusability: simplifying down boilerplate/repetitive code
- consistency: resolvers and schema definition will always be synced
The code-first approach allows for dynamic schema generation. You can generate your schema based on variables and templates to reduce code duplication.
Code-First Example
To showcase the code-first approach. Let's try to model the following schema segment.
interface Node {
id: String
}
type Query {
allFilms(after: String, first: Int, before: String, last: Int): FilmConnection
}
type FilmNode implements Node {
filmName: String
}
type FilmConnection {
edges: [FilmEdge]
films: [Film]
totalCount: Int
}
type FilmEdge {
node: Film
cursor: String
}
Above we see a schema that allows for generating paginated responses. For example,
we can query allFilms(first: 100)
since FilmConnection
acts as an intermediary
for holding FilmEdges
we can write a resolver to return the first 100 films.
In a separate file, we can declare our object types and related functions.
We will call this file object-types.ts
and we will have created it in a way that
allows us to generate other XxxConnection
and XxxEdges
in the future.
import aws_cdk.aws_appsync as appsync
pluralize = require("pluralize")
args = {
"after": appsync.GraphqlType.string(),
"first": appsync.GraphqlType.int(),
"before": appsync.GraphqlType.string(),
"last": appsync.GraphqlType.int()
}
Node = appsync.InterfaceType("Node",
definition={"id": appsync.GraphqlType.string()}
)
FilmNode = appsync.ObjectType("FilmNode",
interface_types=[Node],
definition={"film_name": appsync.GraphqlType.string()}
)
def generate_edge_and_connection(base):
edge = appsync.ObjectType(f"{base.name}Edge",
definition={"node": base.attribute(), "cursor": appsync.GraphqlType.string()}
)
connection = appsync.ObjectType(f"{base.name}Connection",
definition={
"edges": edge.attribute(is_list=True),
"pluralize(base.name)": base.attribute(is_list=True),
"total_count": appsync.GraphqlType.int()
}
)
return {"edge": edge, "connection": connection}
Finally, we will go to our cdk-stack
and combine everything together
to generate our schema.
# dummy_request: appsync.MappingTemplate
# dummy_response: appsync.MappingTemplate
api = appsync.GraphqlApi(self, "Api",
name="demo"
)
object_types = [Node, FilmNode]
film_connections = generate_edge_and_connection(FilmNode)
api.add_query("allFilms", appsync.ResolvableField(
return_type=film_connections.connection.attribute(),
args=args,
data_source=api.add_none_data_source("none"),
request_mapping_template=dummy_request,
response_mapping_template=dummy_response
))
api.add_type(Node)
api.add_type(FilmNode)
api.add_type(film_connections.edge)
api.add_type(film_connections.connection)
Notice how we can utilize the generateEdgeAndConnection
function to generate
Object Types. In the future, if we wanted to create more Object Types, we can simply
create the base Object Type (i.e. Film) and from there we can generate its respective
Connections
and Edges
.
Check out a more in-depth example here.
GraphQL Types
One of the benefits of GraphQL is its strongly typed nature. We define the types within an object, query, mutation, interface, etc. as GraphQL Types.
GraphQL Types are the building blocks of types, whether they are scalar, objects, interfaces, etc. GraphQL Types can be:
- Scalar Types: Id, Int, String, AWSDate, etc.
- Object Types: types that you generate (i.e.
demo
from the example above) - Interface Types: abstract types that define the base implementation of other Intermediate Types
More concretely, GraphQL Types are simply the types appended to variables.
Referencing the object type Demo
in the previous example, the GraphQL Types
is String!
and is applied to both the names id
and version
.
Directives
Directives
are attached to a field or type and affect the execution of queries,
mutations, and types. With AppSync, we use Directives
to configure authorization.
CDK provides static functions to add directives to your Schema.
-
Directive.iam()
sets a type or field's authorization to be validated throughIam
-
Directive.apiKey()
sets a type or field's authorization to be validated through aApi Key
-
Directive.oidc()
sets a type or field's authorization to be validated throughOpenID Connect
-
Directive.cognito(...groups: string[])
sets a type or field's authorization to be validated throughCognito User Pools
groups
the name of the cognito groups to give access
To learn more about authorization and directives, read these docs here.
Field and Resolvable Fields
While GraphqlType
is a base implementation for GraphQL fields, we have abstractions
on top of GraphqlType
that provide finer grain support.
Field
Field
extends GraphqlType
and will allow you to define arguments. Interface Types are not resolvable and this class will allow you to define arguments,
but not its resolvers.
For example, if we want to create the following type:
type Node {
test(argument: string): String
}
The CDK code required would be:
field = appsync.Field(
return_type=appsync.GraphqlType.string(),
args={
"argument": appsync.GraphqlType.string()
}
)
type = appsync.InterfaceType("Node",
definition={"test": field}
)
Resolvable Fields
ResolvableField
extends Field
and will allow you to define arguments and its resolvers.
Object Types can have fields that resolve and perform operations on
your backend.
You can also create resolvable fields for object types.
type Info {
node(id: String): String
}
The CDK code required would be:
# api: appsync.GraphqlApi
# dummy_request: appsync.MappingTemplate
# dummy_response: appsync.MappingTemplate
info = appsync.ObjectType("Info",
definition={
"node": appsync.ResolvableField(
return_type=appsync.GraphqlType.string(),
args={
"id": appsync.GraphqlType.string()
},
data_source=api.add_none_data_source("none"),
request_mapping_template=dummy_request,
response_mapping_template=dummy_response
)
}
)
To nest resolvers, we can also create top level query types that call upon other types. Building off the previous example, if we want the following graphql type definition:
type Query {
get(argument: string): Info
}
The CDK code required would be:
# api: appsync.GraphqlApi
# dummy_request: appsync.MappingTemplate
# dummy_response: appsync.MappingTemplate
query = appsync.ObjectType("Query",
definition={
"get": appsync.ResolvableField(
return_type=appsync.GraphqlType.string(),
args={
"argument": appsync.GraphqlType.string()
},
data_source=api.add_none_data_source("none"),
request_mapping_template=dummy_request,
response_mapping_template=dummy_response
)
}
)
Learn more about fields and resolvers here.
Intermediate Types
Intermediate Types are defined by Graphql Types and Fields. They have a set of defined fields, where each field corresponds to another type in the system. Intermediate Types will be the meat of your GraphQL Schema as they are the types defined by you.
Intermediate Types include:
Interface Types
Interface Types are abstract types that define the implementation of other intermediate types. They are useful for eliminating duplication and can be used to generate Object Types with less work.
You can create Interface Types externally.
node = appsync.InterfaceType("Node",
definition={
"id": appsync.GraphqlType.string(is_required=True)
}
)
To learn more about Interface Types, read the docs here.
Object Types
Object Types are types that you declare. For example, in the code-first example
the demo
variable is an Object Type. Object Types are defined by
GraphQL Types and are only usable when linked to a GraphQL Api.
You can create Object Types in two ways:
-
Object Types can be created externally.
api = appsync.GraphqlApi(self, "Api", name="demo" ) demo = appsync.ObjectType("Demo", definition={ "id": appsync.GraphqlType.string(is_required=True), "version": appsync.GraphqlType.string(is_required=True) } ) api.add_type(demo)
This method allows for reusability and modularity, ideal for larger projects. For example, imagine moving all Object Type definition outside the stack.
object-types.ts
- a file for object type definitionsimport aws_cdk.aws_appsync as appsync demo = appsync.ObjectType("Demo", definition={ "id": appsync.GraphqlType.string(is_required=True), "version": appsync.GraphqlType.string(is_required=True) } )
cdk-stack.ts
- a file containing our cdk stack# api: appsync.GraphqlApi api.add_type(demo)
-
Object Types can be created externally from an Interface Type.
node = appsync.InterfaceType("Node", definition={ "id": appsync.GraphqlType.string(is_required=True) } ) demo = appsync.ObjectType("Demo", interface_types=[node], definition={ "version": appsync.GraphqlType.string(is_required=True) } )
This method allows for reusability and modularity, ideal for reducing code duplication.
To learn more about Object Types, read the docs here.
Enum Types
Enum Types are a special type of Intermediate Type. They restrict a particular set of allowed values for other Intermediate Types.
enum Episode {
NEWHOPE
EMPIRE
JEDI
}
This means that wherever we use the type Episode in our schema, we expect it to be exactly one of NEWHOPE, EMPIRE, or JEDI.
The above GraphQL Enumeration Type can be expressed in CDK as the following:
# api: appsync.GraphqlApi
episode = appsync.EnumType("Episode",
definition=["NEWHOPE", "EMPIRE", "JEDI"
]
)
api.add_type(episode)
To learn more about Enum Types, read the docs here.
Input Types
Input Types are special types of Intermediate Types. They give users an easy way to pass complex objects for top level Mutation and Queries.
input Review {
stars: Int!
commentary: String
}
The above GraphQL Input Type can be expressed in CDK as the following:
# api: appsync.GraphqlApi
review = appsync.InputType("Review",
definition={
"stars": appsync.GraphqlType.int(is_required=True),
"commentary": appsync.GraphqlType.string()
}
)
api.add_type(review)
To learn more about Input Types, read the docs here.
Union Types
Union Types are a special type of Intermediate Type. They are similar to Interface Types, but they cannot specify any common fields between types.
Note: the fields of a union type need to be Object Types
. In other words, you
can't create a union type out of interfaces, other unions, or inputs.
union Search = Human | Droid | Starship
The above GraphQL Union Type encompasses the Object Types of Human, Droid and Starship. It can be expressed in CDK as the following:
# api: appsync.GraphqlApi
string = appsync.GraphqlType.string()
human = appsync.ObjectType("Human", definition={"name": string})
droid = appsync.ObjectType("Droid", definition={"name": string})
starship = appsync.ObjectType("Starship", definition={"name": string})
search = appsync.UnionType("Search",
definition=[human, droid, starship]
)
api.add_type(search)
To learn more about Union Types, read the docs here.
Query
Every schema requires a top level Query type. By default, the schema will look
for the Object Type
named Query
. The top level Query
is the only exposed
type that users can access to perform GET
operations on your Api.
To add fields for these queries, we can simply run the addQuery
function to add
to the schema's Query
type.
# api: appsync.GraphqlApi
# film_connection: appsync.InterfaceType
# dummy_request: appsync.MappingTemplate
# dummy_response: appsync.MappingTemplate
string = appsync.GraphqlType.string()
int = appsync.GraphqlType.int()
api.add_query("allFilms", appsync.ResolvableField(
return_type=film_connection.attribute(),
args={"after": string, "first": int, "before": string, "last": int},
data_source=api.add_none_data_source("none"),
request_mapping_template=dummy_request,
response_mapping_template=dummy_response
))
To learn more about top level operations, check out the docs here.
Mutation
Every schema can have a top level Mutation type. By default, the schema will look
for the ObjectType
named Mutation
. The top level Mutation
Type is the only exposed
type that users can access to perform mutable
operations on your Api.
To add fields for these mutations, we can simply run the addMutation
function to add
to the schema's Mutation
type.
# api: appsync.GraphqlApi
# film_node: appsync.ObjectType
# dummy_request: appsync.MappingTemplate
# dummy_response: appsync.MappingTemplate
string = appsync.GraphqlType.string()
int = appsync.GraphqlType.int()
api.add_mutation("addFilm", appsync.ResolvableField(
return_type=film_node.attribute(),
args={"name": string, "film_number": int},
data_source=api.add_none_data_source("none"),
request_mapping_template=dummy_request,
response_mapping_template=dummy_response
))
To learn more about top level operations, check out the docs here.
Subscription
Every schema can have a top level Subscription type. The top level Subscription
Type
is the only exposed type that users can access to invoke a response to a mutation. Subscriptions
notify users when a mutation specific mutation is called. This means you can make any data source
real time by specify a GraphQL Schema directive on a mutation.
Note: The AWS AppSync client SDK automatically handles subscription connection management.
To add fields for these subscriptions, we can simply run the addSubscription
function to add
to the schema's Subscription
type.
# api: appsync.GraphqlApi
# film: appsync.InterfaceType
api.add_subscription("addedFilm", appsync.Field(
return_type=film.attribute(),
args={"id": appsync.GraphqlType.id(is_required=True)},
directives=[appsync.Directive.subscribe("addFilm")]
))
To learn more about top level operations, check out the docs here.