cdk-appsync-transformer 2.0.0a0
cdk-appsync-transformer
License: Apache-2.0
Requires Python: >=3.6

# AppSync Transformer Construct for AWS CDK

![build](https://github.com/kcwinner/cdk-appsync-transformer/workflows/Build/badge.svg)
[![codecov](https://codecov.io/gh/kcwinner/cdk-appsync-transformer/branch/main/graph/badge.svg)](https://codecov.io/gh/kcwinner/cdk-appsync-transformer)
[![dependencies Status](https://david-dm.org/kcwinner/cdk-appsync-transformer/status.svg)](https://david-dm.org/kcwinner/cdk-appsync-transformer)
[![npm](https://img.shields.io/npm/dt/cdk-appsync-transformer)](https://www.npmjs.com/package/cdk-appsync-transformer)

[![npm version](https://badge.fury.io/js/cdk-appsync-transformer.svg)](https://badge.fury.io/js/cdk-appsync-transformer)
[![PyPI version](https://badge.fury.io/py/cdk-appsync-transformer.svg)](https://badge.fury.io/py/cdk-appsync-transformer)

## Notice

For CDK versions < 1.64.0 please use [aws-cdk-appsync-transformer](https://github.com/kcwinner/aws-cdk-appsync-transformer).

## Why This Package

In April 2020 I wrote a [blog post](https://www.trek10.com/blog/appsync-with-the-aws-cloud-development-kit) on using the AWS Cloud Development Kit with AppSync. I wrote my own transformer in order to emulate AWS Amplify's method of using GraphQL directives in order to template a lot of the Schema Definition Language.

This package is my attempt to convert all of that effort into a separate construct in order to clean up the process.

## How Do I Use It

### Example Usage

API With Default Values

```python
import { AppSyncTransformer } from 'cdk-appsync-transformer';
...
new AppSyncTransformer(this, "my-cool-api", {
    schemaPath: 'schema.graphql'
});
```

schema.graphql

```graphql
type Customer
  @model
  @auth(
    rules: [
      { allow: groups, groups: ["Admins"] }
      { allow: private, provider: iam, operations: [read, update] }
    ]
  ) {
  id: ID!
  firstName: String!
  lastName: String!
  active: Boolean!
  address: String!
}

type Product
  @model
  @auth(
    rules: [
      { allow: groups, groups: ["Admins"] }
      { allow: public, provider: iam, operations: [read] }
    ]
  ) {
  id: ID!
  name: String!
  description: String!
  price: String!
  active: Boolean!
  added: AWSDateTime!
  orders: [Order] @connection
}

type Order @model @key(fields: ["id", "productID"]) {
  id: ID!
  productID: ID!
  total: String!
  ordered: AWSDateTime!
}
```

### [Supported Amplify Directives](https://docs.amplify.aws/cli/graphql-transformer/directives)

Tested:

* [@model](https://docs.amplify.aws/cli/graphql-transformer/directives#model)
* [@auth](https://docs.amplify.aws/cli/graphql-transformer/directives#auth)
* [@connection](https://docs.amplify.aws/cli/graphql-transformer/directives#connection)
* [@key](https://docs.amplify.aws/cli/graphql-transformer/directives#key)
* [@function](https://docs.amplify.aws/cli/graphql-transformer/directives#function)

  * These work differently here than they do in Amplify - see [Functions](#functions) below

Experimental:

* [@versioned](https://docs.amplify.aws/cli/graphql-transformer/directives#versioned)
* [@http](https://docs.amplify.aws/cli/graphql-transformer/directives#http)
* [@ttl](https://github.com/flogy/graphql-ttl-transformer)

  * Community directive transformer

Not Yet Supported:

* [@searchable](https://docs.amplify.aws/cli/graphql-transformer/directives#searchable)
* [@predictions](https://docs.amplify.aws/cli/graphql-transformer/directives#predictions)

### Custom Transformers & Directives

*This is an advanced feature*

It is possible to add pre/post custom transformers that extend the Amplify ITransformer. To see a simple example please look at [mapped-transformer.ts](./test/mappedTransformer/mapped-transformer.ts) in the tests section.

This allows you to modify the data either before or after the [cdk-transformer](./src/transformer/cdk-transformer.ts) is run.

*Limitation:* Due to some limitations with `jsii` we are unable to export the ITransformer interface from `graphql-transformer-core` to ensure complete type safety. Instead, there is a validation method that will check for `name`, `directive` and `typeDefinitions` members in the transformers that are passed in.

```python
import { PreTransformer, PostTransformer } from "./customTransformers";
new AppSyncTransformer(this, "my-cool-api", {
  schemaPath: "schema.graphql",
  preCdkTransformers: [new PreTransformer()],
  postCdkTransformers: [new PostTransformer()],
});
```

#### Custom VTL Transformer

Can be used to create custom [NONE](https://docs.aws.amazon.com/appsync/latest/devguide/resolver-mapping-template-reference-none.html) datasource resolvers.This allows for custom or special logic to be used and added via a transformer.

Example:

```graphql
type Thing {
  fooBar: String
}

type Query {
  listThingCustom: Thing
    @custom(request: "test/custom-resolvers/Test/request.vtl", response: "test/custom-resolvers/Test/response.vtl")
}
```

The above will generate a `Query.listThingCustom` request and response resolver.
You can customize the location of custom resolvers using the `customVtlTransformerRootDirectory` property.

### Overriding generated vtl

*This is an advanced feature*

You can override generated request and response mapping templates using the `overrideResolver` convenience method.

```python
const appsyncTransformer = new AppSyncTransformer(this, "my-cool-api", {
  schemaPath: "schema.graphql",
});

// You can override the just the request, just the response, or BOTH
appsyncTransformer.overrideResolver({
  typeName: 'Query',
  fieldName: 'listThings',
  requestMappingTemplateFile: path.join(process.cwd(), 'custom-resolvers', 'Things', 'request.vtl'),
  responseMappingTemplateFile: path.join(process.cwd(), 'custom-resolvers', 'Things', 'response.vtl'),
});
```

### Authentication

User Pool Authentication

```python
const userPool = new UserPool(this, 'my-cool-user-pool', {
    ...
})
...
const userPoolClient = new UserPoolClient(this, `${id}-client`, {
    userPool: this.userPool,
    ...
})
...
new AppSyncTransformer(this, "my-cool-api", {
    schemaPath: 'schema.graphql',
    authorizationConfig: {
        defaultAuthorization: {
            authorizationType: AuthorizationType.USER_POOL,
            userPoolConfig: {
                userPool: userPool,
                appIdClientRegex: userPoolClient.userPoolClientId,
                defaultAction: UserPoolDefaultAction.ALLOW
            }
        }
    }
});
```

#### IAM

##### Unauth Role

You can grant access to the `public` policies generated from the `@auth` transformer by using `appsyncTransformer.grantPublic(...)`. In the example below you can see we give public iam read access for the Product type. This will generate permissions for `listProducts`, `getProduct` and `Product` (to get all the fields). We then attach it to our `publicRole` using the grantPublic method.

Example:

```graphql
type Product
    @model
    @auth(rules: [
        { allow: groups, groups: ["Admins"] },
        { allow: public, provider: iam, operations: [read] }
    ])
    @key(name: "productsByName", fields: ["name", "added"], queryField: "productsByName") {
        id: ID!
        name: String!
        description: String!
        price: String!
        active: Boolean!
        added: AWSDateTime!
        orders: [Order] @connection
}
```

```python
const identityPool = new CfnIdentityPool(stack, 'test-identity-pool', {
    identityPoolName: 'test-identity-pool',
    cognitoIdentityProviders: [
      {
        clientId: userPoolClient.userPoolClientId,
        providerName: `cognito-idp.${stack.region}.amazonaws.com/${userPool.userPoolId}`,
      },
    ],
    allowUnauthenticatedIdentities: true,
  });

const publicRole = new Role(stack, 'public-role', {
  assumedBy: new WebIdentityPrincipal('cognito-identity.amazonaws.com')
    .withConditions({
      'StringEquals': { 'cognito-identity.amazonaws.com:aud': `${identityPool.ref}` },
      'ForAnyValue:StringLike': { 'cognito-identity.amazonaws.com:amr': 'unauthenticated' },
    }),
});

appSyncTransformer.grantPublic(publicRole);
```

##### Auth Role

You can grant access to the `private` policies generated from the `@auth` transformer by using `appsyncTransformer.grantPrivate(...)`. In the example below you can see we give private iam read and update access for the Customer type. This will generate permissions for `listCustomers`, `getCustomer`, `updateCustomer` and `Customer` (to get all the fields). We then attach it to our `privateFunction` using the grantPrivate method. *You could also use an identity pool as in the unauth example above, I just wanted to show a varied range of use*

```graphql
type Customer
    @model
    @auth(rules: [
        { allow: groups, groups: ["Admins"] },
        { allow: private, provider: iam, operations: [read, update] }
    ]) {
        id: ID!
        firstName: String!
        lastName: String!
        active: Boolean!
        address: String!
}
```

```python
const privateFunction = new Function(stack, 'test-function', {
  runtime: Runtime.NODEJS_12_X,
  code: Code.fromInline('export function handler() { }'),
  handler: 'handler',
});

appSyncTransformer.grantPrivate(privateFunction);
```

### Functions

#### Directive Example

```graphql
type Query {
  listUsers: UserConnection @function(name: "myFunction")
  getUser(id: ID!): User @function(name: "myFunction")
}
```

There are two ways to add functions as data sources (and their resolvers)

#### Construct Convenience Method

```python
const myFunction = new Function(...);

// first argument is the name in the @function directive
appsyncTransformer.addLambdaDataSourceAndResolvers('myFunction', 'unique-id', myFunction, {
  name: 'lambdaDatasourceName'
})
```

`addLambdaDataSourceAndResolvers` does the same thing as the manual version below. However, if you want to customize mapping templates you will have to bypass this and set up the data source and resolvers yourself

#### Manually

Fields with the `@function` directive will be accessible via `appsyncTransformer.functionResolvers`. It will return a map like so:

```python
{
  'user-function': [
    { typeName: 'Query', fieldName: 'listUsers' },
    { typeName: 'Query', fieldName: 'getUser' },
    { typeName: 'Mutation', fieldName: 'createUser' },
    { typeName: 'Mutation', fieldName: 'updateUser' }
  ]
}
```

You can grab your function resolvers via the map and assign them your own function(s). Example might be something like:

```python
const userFunction = new Function(...);
const userFunctionDataSource = appsyncTransformer.appsyncAPI.addLambdaDataSource('some-id', userFunction);

const dataSourceMap = {
  'user-function': userFunctionDataSource
};

for (const [functionName, resolver] of Object.entries(appsyncTransformer.functionResolvers)) {
  const dataSource = dataSourceMap[functionName];
  new Resolver(this.nestedAppsyncStack, `${resolver.typeName}-${resolver.fieldName}-resolver`, {
    api: appsyncTransformer.appsyncAPI,
    typeName: resolver.typeName,
    fieldName: resolver.fieldName,
    dataSource: dataSource,
    requestMappingTemplate: resolver.defaultRequestMappingTemplate,
    responseMappingTemplate: resolver.defaultResponseMappingTemplate // This defaults to allow errors to return to the client instead of throwing
  });
}
```

### Table Name Map

Often you will need to access your table names in a lambda function or elsewhere. The cdk-appsync-transformer will return these values as a map of table names to cdk tokens. These tokens will be resolved at deploy time. They can be accessed via `appSyncTransformer.tableNameMap`.

```python
{
  CustomerTable: '${Token[TOKEN.1300]}',
  ProductTable: '${Token[TOKEN.1346]}',
  OrderTable: '${Token[TOKEN.1392]}',
  BlogTable: '${Token[TOKEN.1442]}',
  PostTable: '${Token[TOKEN.1492]}',
  CommentTable: '${Token[TOKEN.1546]}',
  UserTable: '${Token[TOKEN.1596]}'
}
```

### Table Map

You may need to access your dynamo table L2 constructs. These can be accessed via `appSyncTransformer.tableMap`.

### Custom Table Names

If you do not like autogenerated names for your Dynamo tables you can pass in props to specify them. Use the `tableKey` value derived from the `@model` directive. Example, if you have `type Foo @model` you would use `FooTable` as the key value.

```python
const appSyncTransformer = new AppSyncTransformer(stack, 'test-transformer', {
  schemaPath: testSchemaPath,
  tableNames: {
    CustomerTable: customerTableName,
    OrderTable: orderTableName
  },
});
```

### DynamoDB Streams

There are two ways to enable DynamoDB streams for a table. The first version is probably most preferred. You pass in the `@model` type name and the StreamViewType as properties when creating the AppSyncTransformer. This will also allow you to access the `tableStreamArn` property of the L2 table construct from the `tableMap`.

```python
const appSyncTransformer = new AppSyncTransformer(stack, 'test-transformer', {
  schemaPath: testSchemaPath,
  dynamoDbStreamConfig: {
    Order: StreamViewType.NEW_IMAGE,
    Blog: StreamViewType.NEW_AND_OLD_IMAGES
  }
});

const orderTable = appSyncTransformer.tableMap.OrderTable;
// Do something with the table stream arn - orderTable.tableStreamArn
```

A convenience method is also available. It returns the stream arn because the L2 Table construct does not seem to update with the value since we are updating the underlying CfnTable. Normally a Table construct must pass in the stream specification as a prop

```python
const streamArn = appSyncTransformer.addDynamoDBStream({
  modelTypeName: 'Order',
  streamViewType: StreamViewType.NEW_IMAGE,
});

// Do something with the streamArn
```

### DataStore Support

1. Pass `syncEnabled: true` to the `AppSyncTransformerProps`
2. Generate necessary exports (see [Code Generation](#code-generation) below)

### Cfn Outputs

* `appsyncGraphQLEndpointOutput` - the appsync graphql endpoint

### Code Generation

I've written some helpers to generate code similarly to how AWS Amplify generates statements and types. You can find the code [here](https://github.com/kcwinner/advocacy/tree/master/cdk-amplify-appsync-helpers).

## Versioning

I will *attempt* to align the major and minor version of this package with [AWS CDK], but always check the release descriptions for compatibility.

I currently support [![GitHub package.json dependency version (prod)](https://img.shields.io/github/package-json/dependency-version/kcwinner/cdk-appsync-transformer/aws-cdk-lib)](https://github.com/aws/aws-cdk)

## Contributing

See [CONTRIBUTING](CONTRIBUTING.md) for details

## License

Distributed under [Apache License, Version 2.0](LICENSE)

## References

* [aws cdk](https://aws.amazon.com/cdk)
* [amplify-cli](https://github.com/aws-amplify/amplify-cli)
* [Amplify Directives](https://docs.amplify.aws/cli/graphql-transformer/directives)

# Sponsors

## [Stedi](https://www.stedi.com/)