Dataplex Universal Catalog client libraries

This page shows how to get started with the Cloud Client Libraries for the Dataplex API. Client libraries make it easier to access Google Cloud APIs from a supported language. Although you can use Google Cloud APIs directly by making raw requests to the server, client libraries provide simplifications that significantly reduce the amount of code you need to write.

Read more about the Cloud Client Libraries and the older Google API Client Libraries in Client libraries explained .

Install the client library

C#

Install-Package Google.Cloud.Dataplex.V1

For more information, see Setting Up a C# Development Environment .

Go

go get cloud.google.com/go/dataplex/apiv1

For more information, see Setting Up a Go Development Environment .

Java

If you are using Maven , add the following to your pom.xml file:

<dependency>  
<groupId>com.google.cloud</groupId>  
<artifactId>google-cloud-dataplex</artifactId>  
<version> DATAPLEX_LIBRARY_VERSION 
</version>
</dependency>

If you are using Gradle , add the following to your dependencies:

compile group: 'com.google.cloud', name: 'google-cloud-dataplex', version: ' DATAPLEX_LIBRARY_VERSION 
'

For more information, see Setting Up a Java Development Environment .

Node.js

npm install @google-cloud/dataplex

For more information, see Setting Up a Node.js Development Environment .

PHP

composer require google/cloud-dataplex

For more information, see Using PHP on Google Cloud .

Python

pip install --upgrade google-cloud-dataplex

For more information, see Setting Up a Python Development Environment .

Ruby

gem install google-cloud-dataplex

For more information, see Setting Up a Ruby Development Environment .

Set up authentication

To authenticate calls to Google Cloud APIs, client libraries support Application Default Credentials (ADC) ; the libraries look for credentials in a set of defined locations and use those credentials to authenticate requests to the API. With ADC, you can make credentials available to your application in a variety of environments, such as local development or production, without needing to modify your application code.

For production environments, the way you set up ADC depends on the service and context. For more information, see Set up Application Default Credentials .

For a local development environment, you can set up ADC with the credentials that are associated with your Google Account:

Install the Google Cloud CLI. After installation, initialize the Google Cloud CLI by running the following command:
```
gcloud  
init
```
If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity .
If you're using a local shell, then create local authentication credentials for your user account:
```
gcloud  
auth  
application-default  
login
```
You don't need to do this if you're using Cloud Shell.

If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity .

A sign-in screen appears. After you sign in, your credentials are stored in the local credential file used by ADC .

Use the client library

The following example shows how to use the client library.

Java

  import 
  
 com.google.cloud.dataplex.v1. AspectType 
 
 ; 
 import 
  
 com.google.cloud.dataplex.v1. CatalogServiceClient 
 
 ; 
 import 
  
 com.google.cloud.dataplex.v1. LocationName 
 
 ; 
 import 
  
 java.util.List 
 ; 
 public 
  
 class 
 CreateAspectType 
  
 { 
  
 public 
  
 static 
  
 void 
  
 main 
 ( 
 String 
 [] 
  
 args 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 // TODO(developer): Replace these variables before running the sample. 
  
 String 
  
 projectId 
  
 = 
  
 "MY_PROJECT_ID" 
 ; 
  
 // Available locations: https://cloud.google.com/dataplex/docs/locations 
  
 String 
  
 location 
  
 = 
  
 "MY_LOCATION" 
 ; 
  
 String 
  
 aspectTypeId 
  
 = 
  
 "MY_ASPECT_TYPE_ID" 
 ; 
  
  AspectType 
 
 . 
  MetadataTemplate 
 
  
 aspectField 
  
 = 
  
  AspectType 
 
 . 
 MetadataTemplate 
 . 
 newBuilder 
 () 
  
 // The name must follow regex ^(([a-zA-Z]{1})([\\w\\-_]{0,62}))$ 
  
 // That means name must only contain alphanumeric character or dashes or underscores, 
  
 // start with an alphabet, and must be less than 63 characters. 
  
 . 
 setName 
 ( 
 "name_of_the_field" 
 ) 
  
 // Metadata Template is recursive structure, 
  
 // primitive types such as "string" or "integer" indicate leaf node, 
  
 // complex types such as "record" or "array" would require nested Metadata Template 
  
 . 
 setType 
 ( 
 "string" 
 ) 
  
 . 
 setIndex 
 ( 
 1 
 ) 
  
 . 
  setAnnotations 
 
 ( 
  
  AspectType 
 
 . 
 MetadataTemplate 
 . 
 Annotations 
 . 
 newBuilder 
 () 
  
 . 
 setDescription 
 ( 
 "description of the field" 
 ) 
  
 . 
 build 
 ()) 
  
 . 
  setConstraints 
 
 ( 
  
  AspectType 
 
 . 
 MetadataTemplate 
 . 
 Constraints 
 . 
 newBuilder 
 () 
  
 // Specifies if field will be required in Aspect Type. 
  
 . 
  setRequired 
 
 ( 
 true 
 ) 
  
 . 
 build 
 ()) 
  
 . 
 build 
 (); 
  
 List<AspectType 
 . 
  MetadataTemplate 
 
>  
 aspectFields 
  
 = 
  
 List 
 . 
 of 
 ( 
 aspectField 
 ); 
  
  AspectType 
 
  
 createdAspectType 
  
 = 
  
 createAspectType 
 ( 
 projectId 
 , 
  
 location 
 , 
  
 aspectTypeId 
 , 
  
 aspectFields 
 ); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Successfully created aspect type: " 
  
 + 
  
 createdAspectType 
 . 
  getName 
 
 ()); 
  
 } 
  
 // Method to create Aspect Type located in projectId, location and with aspectTypeId and 
  
 // aspectFields specifying schema of the Aspect Type 
  
 public 
  
 static 
  
  AspectType 
 
  
 createAspectType 
 ( 
  
 String 
  
 projectId 
 , 
  
 String 
  
 location 
 , 
  
 String 
  
 aspectTypeId 
 , 
  
 List<AspectType 
 . 
  MetadataTemplate 
 
>  
 aspectFields 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 // Initialize client that will be used to send requests. This client only needs to be created 
  
 // once, and can be reused for multiple requests. 
  
 try 
  
 ( 
  CatalogServiceClient 
 
  
 client 
  
 = 
  
  CatalogServiceClient 
 
 . 
 create 
 ()) 
  
 { 
  
  LocationName 
 
  
 locationName 
  
 = 
  
  LocationName 
 
 . 
 of 
 ( 
 projectId 
 , 
  
 location 
 ); 
  
  AspectType 
 
  
 aspectType 
  
 = 
  
  AspectType 
 
 . 
 newBuilder 
 () 
  
 . 
 setDescription 
 ( 
 "description of the aspect type" 
 ) 
  
 . 
  setMetadataTemplate 
 
 ( 
  
  AspectType 
 
 . 
 MetadataTemplate 
 . 
 newBuilder 
 () 
  
 // The name must follow regex ^(([a-zA-Z]{1})([\\w\\-_]{0,62}))$ 
  
 // That means name must only contain alphanumeric character or dashes or 
  
 // underscores, start with an alphabet, and must be less than 63 characters. 
  
 . 
 setName 
 ( 
 "name_of_the_template" 
 ) 
  
 . 
 setType 
 ( 
 "record" 
 ) 
  
 // Aspect Type fields, that themselves are Metadata Templates 
  
 . 
  addAllRecordFields 
 
 ( 
 aspectFields 
 ) 
  
 . 
 build 
 ()) 
  
 . 
 build 
 (); 
  
 return 
  
 client 
 . 
  createAspectTypeAsync 
 
 ( 
 locationName 
 , 
  
 aspectType 
 , 
  
 aspectTypeId 
 ). 
 get 
 (); 
  
 } 
  
 } 
 }

Python

  from 
  
 typing 
  
 import 
 List 
 from 
  
 google.cloud 
  
 import 
  dataplex_v1 
 
 # Method to create Aspect Type located in project_id, location and with aspect_type_id and 
 # aspect_fields specifying schema of the Aspect Type 
 def 
  
 create_aspect_type 
 ( 
 project_id 
 : 
 str 
 , 
 location 
 : 
 str 
 , 
 aspect_type_id 
 : 
 str 
 , 
 aspect_fields 
 : 
 List 
 [ 
  dataplex_v1 
 
 . 
  AspectType 
 
 . 
  MetadataTemplate 
 
 ], 
 ) 
 - 
> dataplex_v1 
 . 
 AspectType 
 : 
  
 """Method to create Aspect Type located in project_id, location and with aspect_type_id and 
 aspect_fields specifying schema of the Aspect Type""" 
 # Initialize client that will be used to send requests across threads. This 
 # client only needs to be created once, and can be reused for multiple requests. 
 # After completing all of your requests, call the "__exit__()" method to safely 
 # clean up any remaining background resources. Alternatively, use the client as 
 # a context manager. 
 with 
  dataplex_v1 
 
 . 
  CatalogServiceClient 
 
 () 
 as 
 client 
 : 
 # The resource name of the Aspect Type location 
 parent 
 = 
 f 
 "projects/ 
 { 
 project_id 
 } 
 /locations/ 
 { 
 location 
 } 
 " 
 aspect_type 
 = 
  dataplex_v1 
 
 . 
  AspectType 
 
 ( 
 description 
 = 
 "description of the aspect type" 
 , 
 metadata_template 
 = 
  dataplex_v1 
 
 . 
  AspectType 
 
 . 
  MetadataTemplate 
 
 ( 
 # The name must follow regex ^(([a-zA-Z]{1})([\\w\\-_]{0,62}))$ 
 # That means name must only contain alphanumeric character or dashes or underscores, 
 # start with an alphabet, and must be less than 63 characters. 
 name 
 = 
 "name_of_the_template" 
 , 
 type 
 = 
 "record" 
 , 
 # Aspect Type fields, that themselves are Metadata Templates. 
 record_fields 
 = 
 aspect_fields 
 , 
 ), 
 ) 
 create_operation 
 = 
 client 
 . 
 create_aspect_type 
 ( 
 parent 
 = 
 parent 
 , 
 aspect_type 
 = 
 aspect_type 
 , 
 aspect_type_id 
 = 
 aspect_type_id 
 ) 
 return 
 create_operation 
 . 
 result 
 ( 
 60 
 ) 
 if 
 __name__ 
 == 
 "__main__" 
 : 
 # TODO(developer): Replace these variables before running the sample. 
 project_id 
 = 
 "MY_PROJECT_ID" 
 # Available locations: https://cloud.google.com/dataplex/docs/locations 
 location 
 = 
 "MY_LOCATION" 
 aspect_type_id 
 = 
 "MY_ASPECT_TYPE_ID" 
 aspect_field 
 = 
  dataplex_v1 
 
 . 
  AspectType 
 
 . 
  MetadataTemplate 
 
 ( 
 # The name must follow regex ^(([a-zA-Z]{1})([\\w\\-_]{0,62}))$ 
 # That means name must only contain alphanumeric character or dashes or underscores, 
 # start with an alphabet, and must be less than 63 characters. 
 name 
 = 
 "name_of_the_field" 
 , 
 # Metadata Template is recursive structure, 
 # primitive types such as "string" or "integer" indicate leaf node, 
 # complex types such as "record" or "array" would require nested Metadata Template 
 type 
 = 
 "string" 
 , 
 index 
 = 
 1 
 , 
 annotations 
 = 
  dataplex_v1 
 
 . 
  AspectType 
 
 . 
  MetadataTemplate 
 
 . 
  Annotations 
 
 ( 
 description 
 = 
 "description of the field" 
 ), 
 constraints 
 = 
  dataplex_v1 
 
 . 
  AspectType 
 
 . 
  MetadataTemplate 
 
 . 
  Constraints 
 
 ( 
 # Specifies if field will be required in Aspect Type. 
 required 
 = 
 True 
 ), 
 ) 
 aspect_fields 
 = 
 [ 
 aspect_field 
 ] 
 created_aspect_type 
 = 
 create_aspect_type 
 ( 
 project_id 
 , 
 location 
 , 
 aspect_type_id 
 , 
 aspect_fields 
 ) 
 print 
 ( 
 f 
 "Successfully created aspect type: 
 { 
 created_aspect_type 
 . 
 name 
 } 
 " 
 )

Additional resources

C#

The following list contains links to more resources related to the client library for C#:

Go

The following list contains links to more resources related to the client library for Go:

Java

The following list contains links to more resources related to the client library for Java:

Node.js

The following list contains links to more resources related to the client library for Node.js:

PHP

The following list contains links to more resources related to the client library for PHP:

Python

The following list contains links to more resources related to the client library for Python:

Ruby

The following list contains links to more resources related to the client library for Ruby:

Dataplex Universal Catalog client libraries Stay organized with collections Save and categorize content based on your preferences.

Install the client library

C#

Go

Java

Node.js

PHP

Python

Ruby

Set up authentication

Use the client library

Java

Python

Additional resources

C#

Go

Java

Node.js

PHP

Python

Ruby

Dataplex Universal Catalog client libraries