List models

import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/bigquery"
	"google.golang.org/api/iterator"
)

// listModels demonstrates iterating through the collection of ML models in a dataset
// and printing a basic identifier of the model.
func listModels(w io.Writer, projectID, datasetID string) error {
	// projectID := "my-project-id"
	// datasetID := "mydataset"
	ctx := context.Background()

	client, err := bigquery.NewClient(ctx, projectID)
	if err != nil {
		return fmt.Errorf("bigquery.NewClient: %w", err)
	}
	defer client.Close()

	fmt.Fprintf(w, "Models contained in dataset %q\n", datasetID)
	it := client.Dataset(datasetID).Models(ctx)
	for {
		m, err := it.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			return err
		}
		fmt.Fprintf(w, "Model: %s\n", m.FullyQualifiedName())
	}
	return nil
}

import com.google.api.gax.paging.Page;
import com.google.cloud.bigquery.BigQuery;
import com.google.cloud.bigquery.BigQuery.ModelListOption;
import com.google.cloud.bigquery.BigQueryException;
import com.google.cloud.bigquery.BigQueryOptions;
import com.google.cloud.bigquery.Model;

public class ListModels {

  public static void main(String[] args) {
    // TODO(developer): Replace these variables before running the sample.
    String datasetName = "MY_DATASET_NAME";
    listModels(datasetName);
  }

  public static void listModels(String datasetName) {
    try {
      // Initialize client that will be used to send requests. This client only needs to be created
      // once, and can be reused for multiple requests.
      BigQuery bigquery = BigQueryOptions.getDefaultInstance().getService();

      Page<Model> models = bigquery.listModels(datasetName, ModelListOption.pageSize(100));
      if (models == null) {
        System.out.println("Dataset does not contain any models.");
        return;
      }
      models
          .iterateAll()
          .forEach(model -> System.out.printf("Success! Model ID: %s", model.getModelId()));
    } catch (BigQueryException e) {
      System.out.println("Models not listed in dataset due to error: \n" + e.toString());
    }
  }
}

// Import the Google Cloud client library
const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();

async function listModels() {
  // Lists all existing models in the dataset.

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const datasetId = "my_dataset";

  const dataset = bigquery.dataset(datasetId);

  dataset.getModels().then(data => {
    const models = data[0];
    console.log('Models:');
    models.forEach(model => console.log(model.metadata));
  });
}

from google.cloud import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# TODO(developer): Set dataset_id to the ID of the dataset that contains
#                  the models you are listing.
# dataset_id = 'your-project.your_dataset'

models = client.list_models(dataset_id)  # Make an API request.

print("Models contained in '{}':".format(dataset_id))
for model in models:
    full_model_id = "{}.{}.{}".format(
        model.project, model.dataset_id, model.model_id
    )
    friendly_name = model.friendly_name
    print("{}: friendly_name='{}'".format(full_model_id, friendly_name))