From 4fc18a84270795a0c8277490277e5e959ea86cb6 Mon Sep 17 00:00:00 2001
From: Alex <7764119+AVaksman@users.noreply.github.com>
Date: Thu, 2 Apr 2020 13:58:44 -0400
Subject: [PATCH] feat!: drop node8 support (#405)

---
 cloud-language/snippets/analyze.v1.js         |  80 +++----
 .../automl/automlNaturalLanguageDataset.js    | 132 ++++++------
 .../automl/automlNaturalLanguageModel.js      | 204 +++++++++---------
 .../automl/automlNaturalLanguagePredict.js    |  52 ++---
 .../snippets/test/analyze.v1.test.js          |   6 +-
 .../test/automlNaturalLanguage.test.js        |   4 +-
 6 files changed, 239 insertions(+), 239 deletions(-)

diff --git a/cloud-language/snippets/analyze.v1.js b/cloud-language/snippets/analyze.v1.js
index afe9882f0e..162f190880 100644
--- a/cloud-language/snippets/analyze.v1.js
+++ b/cloud-language/snippets/analyze.v1.js
@@ -39,7 +39,7 @@ async function analyzeSentimentOfText(text) {
   const [result] = await client.analyzeSentiment({document});
 
   const sentiment = result.documentSentiment;
-  console.log(`Document sentiment:`);
+  console.log('Document sentiment:');
   console.log(`  Score: ${sentiment.score}`);
   console.log(`  Magnitude: ${sentiment.magnitude}`);
 
@@ -77,7 +77,7 @@ async function analyzeSentimentInFile(bucketName, fileName) {
   const [result] = await client.analyzeSentiment({document});
 
   const sentiment = result.documentSentiment;
-  console.log(`Document sentiment:`);
+  console.log('Document sentiment:');
   console.log(`  Score: ${sentiment.score}`);
   console.log(`  Magnitude: ${sentiment.magnitude}`);
 
@@ -189,7 +189,7 @@ async function analyzeSyntaxOfText(text) {
   console.log('Tokens:');
   syntax.tokens.forEach(part => {
     console.log(`${part.partOfSpeech.tag}: ${part.text.content}`);
-    console.log(`Morphology:`, part.partOfSpeech);
+    console.log('Morphology:', part.partOfSpeech);
   });
   // [END language_syntax_text]
 }
@@ -223,7 +223,7 @@ async function analyzeSyntaxInFile(bucketName, fileName) {
   console.log('Parts of speech:');
   syntax.tokens.forEach(part => {
     console.log(`${part.partOfSpeech.tag}: ${part.text.content}`);
-    console.log(`Morphology:`, part.partOfSpeech);
+    console.log('Morphology:', part.partOfSpeech);
   });
   // [END language_syntax_gcs]
 }
@@ -251,7 +251,7 @@ async function analyzeEntitySentimentOfText(text) {
   const [result] = await client.analyzeEntitySentiment({document});
   const entities = result.entities;
 
-  console.log(`Entities and sentiments:`);
+  console.log('Entities and sentiments:');
   entities.forEach(entity => {
     console.log(`  Name: ${entity.name}`);
     console.log(`  Type: ${entity.type}`);
@@ -285,7 +285,7 @@ async function analyzeEntitySentimentInFile(bucketName, fileName) {
   const [result] = await client.analyzeEntitySentiment({document});
   const entities = result.entities;
 
-  console.log(`Entities and sentiments:`);
+  console.log('Entities and sentiments:');
   entities.forEach(entity => {
     console.log(`  Name: ${entity.name}`);
     console.log(`  Type: ${entity.type}`);
@@ -353,98 +353,98 @@ async function classifyTextInFile(bucketName, fileName) {
   // [END language_classify_gcs]
 }
 
-require(`yargs`)
+require('yargs')
   .demand(1)
   .command(
-    `sentiment-text <text>`,
-    `Detects sentiment of a string.`,
+    'sentiment-text <text>',
+    'Detects sentiment of a string.',
     {},
     opts => analyzeSentimentOfText(opts.text)
   )
   .command(
-    `sentiment-file <bucketName> <fileName>`,
-    `Detects sentiment in a file in Google Cloud Storage.`,
+    'sentiment-file <bucketName> <fileName>',
+    'Detects sentiment in a file in Google Cloud Storage.',
     {},
     opts => analyzeSentimentInFile(opts.bucketName, opts.fileName)
   )
-  .command(`entities-text <text>`, `Detects entities in a string.`, {}, opts =>
+  .command('entities-text <text>', 'Detects entities in a string.', {}, opts =>
     analyzeEntitiesOfText(opts.text)
   )
   .command(
-    `entities-file <bucketName> <fileName>`,
-    `Detects entities in a file in Google Cloud Storage.`,
+    'entities-file <bucketName> <fileName>',
+    'Detects entities in a file in Google Cloud Storage.',
     {},
     opts => analyzeEntitiesInFile(opts.bucketName, opts.fileName)
   )
-  .command(`syntax-text <text>`, `Detects syntax of a string.`, {}, opts =>
+  .command('syntax-text <text>', 'Detects syntax of a string.', {}, opts =>
     analyzeSyntaxOfText(opts.text)
   )
   .command(
-    `syntax-file <bucketName> <fileName>`,
-    `Detects syntax in a file in Google Cloud Storage.`,
+    'syntax-file <bucketName> <fileName>',
+    'Detects syntax in a file in Google Cloud Storage.',
     {},
     opts => analyzeSyntaxInFile(opts.bucketName, opts.fileName)
   )
   .command(
-    `entity-sentiment-text <text>`,
-    `Detects sentiment of the entities in a string.`,
+    'entity-sentiment-text <text>',
+    'Detects sentiment of the entities in a string.',
     {},
     opts => analyzeEntitySentimentOfText(opts.text)
   )
   .command(
-    `entity-sentiment-file <bucketName> <fileName>`,
-    `Detects sentiment of the entities in a file in Google Cloud Storage.`,
+    'entity-sentiment-file <bucketName> <fileName>',
+    'Detects sentiment of the entities in a file in Google Cloud Storage.',
     {},
     opts => analyzeEntitySentimentInFile(opts.bucketName, opts.fileName)
   )
-  .command(`classify-text <text>`, `Classifies text of a string.`, {}, opts =>
+  .command('classify-text <text>', 'Classifies text of a string.', {}, opts =>
     classifyTextOfText(opts.text)
   )
   .command(
-    `classify-file <bucketName> <fileName>`,
-    `Classifies text in a file in Google Cloud Storage.`,
+    'classify-file <bucketName> <fileName>',
+    'Classifies text in a file in Google Cloud Storage.',
     {},
     opts => classifyTextInFile(opts.bucketName, opts.fileName)
   )
   .example(
-    `node $0 sentiment-text "President Obama is speaking at the White House."`
+    'node $0 sentiment-text "President Obama is speaking at the White House."'
   )
   .example(
-    `node $0 sentiment-file my-bucket file.txt`,
-    `Detects sentiment in gs://my-bucket/file.txt`
+    'node $0 sentiment-file my-bucket file.txt',
+    'Detects sentiment in gs://my-bucket/file.txt'
   )
   .example(
-    `node $0 entities-text "President Obama is speaking at the White House."`
+    'node $0 entities-text "President Obama is speaking at the White House."'
   )
   .example(
-    `node $0 entities-file my-bucket file.txt`,
-    `Detects entities in gs://my-bucket/file.txt`
+    'node $0 entities-file my-bucket file.txt',
+    'Detects entities in gs://my-bucket/file.txt'
   )
   .example(
-    `node $0 syntax-text "President Obama is speaking at the White House."`
+    'node $0 syntax-text "President Obama is speaking at the White House."'
   )
   .example(
-    `node $0 syntax-file my-bucket file.txt`,
-    `Detects syntax in gs://my-bucket/file.txt`
+    'node $0 syntax-file my-bucket file.txt',
+    'Detects syntax in gs://my-bucket/file.txt'
   )
   .example(
-    `node $0 entity-sentiment-text "President Obama is speaking at the White House."`
+    'node $0 entity-sentiment-text "President Obama is speaking at the White House."'
   )
   .example(
-    `node $0 entity-sentiment-file my-bucket file.txt`,
-    `Detects sentiment of entities in gs://my-bucket/file.txt`
+    'node $0 entity-sentiment-file my-bucket file.txt',
+    'Detects sentiment of entities in gs://my-bucket/file.txt'
   )
   .example(
-    `node $0 classify-text "Android is a mobile operating system developed by Google, based on the Linux kernel and designed primarily for touchscreen mobile devices such as smartphones and tablets."`
+    'node $0 classify-text "Android is a mobile operating system developed by Google, based on the Linux kernel and designed primarily for touchscreen mobile devices such as smartphones and tablets."'
   )
   .example(
-    `node $0 classify-file my-bucket android_text.txt`,
-    `Detects syntax in gs://my-bucket/android_text.txt`
+    'node $0 classify-file my-bucket android_text.txt',
+    'Detects syntax in gs://my-bucket/android_text.txt'
   )
   .wrap(120)
   .recommendCommands()
   .epilogue(
-    `For more information, see https://cloud.google.com/natural-language/docs`
+    'For more information, see https://cloud.google.com/natural-language/docs'
   )
   .help()
   .strict().argv;
diff --git a/cloud-language/snippets/automl/automlNaturalLanguageDataset.js b/cloud-language/snippets/automl/automlNaturalLanguageDataset.js
index 9ddedc7b7e..c6c584a07d 100755
--- a/cloud-language/snippets/automl/automlNaturalLanguageDataset.js
+++ b/cloud-language/snippets/automl/automlNaturalLanguageDataset.js
@@ -29,7 +29,7 @@ async function createDataset(
   multilabel
 ) {
   // [START automl_language_createDataset]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -45,9 +45,9 @@ async function createDataset(
   const projectLocation = client.locationPath(projectId, computeRegion);
 
   // Classification type is assigned based on multilabel value.
-  let classificationType = `MULTICLASS`;
+  let classificationType = 'MULTICLASS';
   if (multilabel) {
-    classificationType = `MULTILABEL`;
+    classificationType = 'MULTILABEL';
   }
 
   // Set dataset name and metadata.
@@ -65,14 +65,14 @@ async function createDataset(
   });
   // Display the dataset information.
   console.log(`Dataset name: ${dataset.name}`);
-  console.log(`Dataset id: ${dataset.name.split(`/`).pop(-1)}`);
+  console.log(`Dataset id: ${dataset.name.split('/').pop(-1)}`);
   console.log(`Dataset display name: ${dataset.displayName}`);
   console.log(`Dataset example count: ${dataset.exampleCount}`);
-  console.log(`Text classification type:`);
+  console.log('Text classification type:');
   console.log(
     `\t ${dataset.textClassificationDatasetMetadata.classificationType}`
   );
-  console.log(`Dataset create time:`);
+  console.log('Dataset create time:');
   console.log(`\tseconds: ${dataset.createTime.seconds}`);
   console.log(`\tnanos: ${dataset.createTime.nanos}`);
   // [END automl_language_createDataset]
@@ -80,7 +80,7 @@ async function createDataset(
 
 async function listDatasets(projectId, computeRegion, filter) {
   // [START automl_language_listDatasets]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -100,27 +100,27 @@ async function listDatasets(projectId, computeRegion, filter) {
     filter: filter,
   });
   // Display the dataset information.
-  console.log(`List of datasets:`);
+  console.log('List of datasets:');
   datasets.forEach(dataset => {
     console.log(`Dataset name: ${dataset.name}`);
-    console.log(`Dataset id: ${dataset.name.split(`/`).pop(-1)}`);
+    console.log(`Dataset id: ${dataset.name.split('/').pop(-1)}`);
     console.log(`Dataset display name: ${dataset.displayName}`);
     console.log(`Dataset example count: ${dataset.exampleCount}`);
-    console.log(`Text classification type:`);
+    console.log('Text classification type:');
     console.log(
       `\t ${dataset.textClassificationDatasetMetadata.classificationType}`
     );
-    console.log(`Dataset create time: `);
+    console.log('Dataset create time: ');
     console.log(`\tseconds: ${dataset.createTime.seconds}`);
     console.log(`\tnanos: ${dataset.createTime.nanos}`);
-    console.log(`\n`);
+    console.log('\n');
   });
   // [END automl_language_listDatasets]
 }
 
 async function getDataset(projectId, computeRegion, datasetId) {
   // [START automl_language_getDataset]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -138,13 +138,13 @@ async function getDataset(projectId, computeRegion, datasetId) {
   const [dataset] = await client.getDataset({name: datasetFullId});
   // Display the dataset information.
   console.log(`Dataset name: ${dataset.name}`);
-  console.log(`Dataset id: ${dataset.name.split(`/`).pop(-1)}`);
+  console.log(`Dataset id: ${dataset.name.split('/').pop(-1)}`);
   console.log(`Dataset display name: ${dataset.displayName}`);
   console.log(`Dataset example count: ${dataset.exampleCount}`);
   console.log(
     `Text classification type: ${dataset.textClassificationDatasetMetadata.classificationType}`
   );
-  console.log(`Dataset create time: `);
+  console.log('Dataset create time: ');
   console.log(`\tseconds: ${dataset.createTime.seconds}`);
   console.log(`\tnanos: ${dataset.createTime.nanos}`);
   // [END automl_language_getDataset]
@@ -152,7 +152,7 @@ async function getDataset(projectId, computeRegion, datasetId) {
 
 async function importData(projectId, computeRegion, datasetId, path) {
   // [START automl_language_importDataset]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -168,7 +168,7 @@ async function importData(projectId, computeRegion, datasetId, path) {
   const datasetFullId = client.datasetPath(projectId, computeRegion, datasetId);
 
   // Get the multiple Google Cloud Storage URIs.
-  const inputUris = path.split(`,`);
+  const inputUris = path.split(',');
   const inputConfig = {
     gcsSource: {
       inputUris: inputUris,
@@ -180,17 +180,17 @@ async function importData(projectId, computeRegion, datasetId, path) {
     name: datasetFullId,
     inputConfig: inputConfig,
   });
-  console.log(`Processing import...`);
+  console.log('Processing import...');
   const response = await operation.promise();
   // The final result of the operation.
-  if (response[2].done === true) console.log(`Data imported.`);
+  if (response[2].done === true) console.log('Data imported.');
 
   // [END automl_language_importDataset]
 }
 
 async function exportData(projectId, computeRegion, datasetId, outputUri) {
   // [START automl_language_exportDataset]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -217,16 +217,16 @@ async function exportData(projectId, computeRegion, datasetId, outputUri) {
     name: datasetFullId,
     outputConfig: outputConfig,
   });
-  console.log(`Processing export...`);
+  console.log('Processing export...');
   const response = await operation.promise();
   // The final result of the operation.
-  if (response[2].done === true) console.log(`Data exported.`);
+  if (response[2].done === true) console.log('Data exported.');
   // [END automl_language_exportDataset]
 }
 
 async function deleteDataset(projectId, computeRegion, datasetId) {
   // [START automl_language_deleteDataset]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -244,72 +244,72 @@ async function deleteDataset(projectId, computeRegion, datasetId) {
   const [operation] = await client.deleteDataset({name: datasetFullId});
   const response = await operation.promise();
   // The final result of the operation.
-  if (response[2].done === true) console.log(`Dataset deleted.`);
+  if (response[2].done === true) console.log('Dataset deleted.');
   // [END automl_language_deleteDataset]
 }
 
-require(`yargs`)
+require('yargs')
   .demand(1)
   .options({
     computeRegion: {
-      alias: `c`,
-      type: `string`,
+      alias: 'c',
+      type: 'string',
       default: process.env.REGION_NAME,
       requiresArg: true,
-      description: `region name e.g. "us-central1"`,
+      description: 'region name e.g. "us-central1"',
     },
     datasetName: {
-      alias: `n`,
-      type: `string`,
-      default: `testDataSet`,
+      alias: 'n',
+      type: 'string',
+      default: 'testDataSet',
       requiresArg: true,
-      description: `Name of the Dataset`,
+      description: 'Name of the Dataset',
     },
     datasetId: {
-      alias: `i`,
-      type: `string`,
+      alias: 'i',
+      type: 'string',
       requiresArg: true,
-      description: `Id of the dataset`,
+      description: 'Id of the dataset',
     },
     filter: {
-      alias: `f`,
-      default: `text_classification_dataset_metadata:*`,
-      type: `string`,
+      alias: 'f',
+      default: 'text_classification_dataset_metadata:*',
+      type: 'string',
       requiresArg: false,
-      description: `filter expression`,
+      description: 'filter expression',
     },
     multilabel: {
-      alias: `m`,
-      type: `string`,
+      alias: 'm',
+      type: 'string',
       default: false,
       requiresArg: true,
       description:
-        `Type of the classification problem, ` +
-        `False - MULTICLASS, True - MULTILABEL.`,
+        'Type of the classification problem, ' +
+        'False - MULTICLASS, True - MULTILABEL.',
     },
     outputUri: {
-      alias: `o`,
-      type: `string`,
+      alias: 'o',
+      type: 'string',
       requiresArg: true,
-      description: `URI (or local path) to export dataset`,
+      description: 'URI (or local path) to export dataset',
     },
     path: {
-      alias: `p`,
-      type: `string`,
+      alias: 'p',
+      type: 'string',
       global: true,
-      default: `gs://nodejs-docs-samples-vcm/flowerTraindataMini.csv`,
+      default: 'gs://nodejs-docs-samples-vcm/flowerTraindataMini.csv',
       requiresArg: true,
-      description: `URI or local path to input .csv, or array of .csv paths`,
+      description: 'URI or local path to input .csv, or array of .csv paths',
     },
     projectId: {
-      alias: `z`,
-      type: `number`,
+      alias: 'z',
+      type: 'number',
       default: process.env.GCLOUD_PROJECT,
       requiresArg: true,
-      description: `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`,
+      description: 'The GCLOUD_PROJECT string, e.g. "my-gcloud-project"',
     },
   })
-  .command(`create-dataset`, `creates a new Dataset`, {}, opts =>
+  .command('create-dataset', 'creates a new Dataset', {}, opts =>
     createDataset(
       opts.projectId,
       opts.computeRegion,
@@ -317,21 +317,21 @@ require(`yargs`)
       opts.multilabel
     )
   )
-  .command(`list-datasets`, `list all Datasets`, {}, opts =>
+  .command('list-datasets', 'list all Datasets', {}, opts =>
     listDatasets(opts.projectId, opts.computeRegion, opts.filter)
   )
-  .command(`get-dataset`, `Get a Dataset`, {}, opts =>
+  .command('get-dataset', 'Get a Dataset', {}, opts =>
     getDataset(opts.projectId, opts.computeRegion, opts.datasetId)
   )
-  .command(`delete-dataset`, `Delete a dataset`, {}, opts =>
+  .command('delete-dataset', 'Delete a dataset', {}, opts =>
     deleteDataset(opts.projectId, opts.computeRegion, opts.datasetId)
   )
-  .command(`import-data`, `Import labeled items into dataset`, {}, opts =>
+  .command('import-data', 'Import labeled items into dataset', {}, opts =>
     importData(opts.projectId, opts.computeRegion, opts.datasetId, opts.path)
   )
   .command(
-    `export-data`,
-    `Export a dataset to a Google Cloud Storage Bucket`,
+    'export-data',
+    'Export a dataset to a Google Cloud Storage Bucket',
     {},
     opts =>
       exportData(
@@ -341,15 +341,15 @@ require(`yargs`)
         opts.outputUri
       )
   )
-  .example(`node $0 create-dataset -n "newDataSet"`)
-  .example(`node $0 list-datasets -f "imageClassificationDatasetMetadata:*"`)
-  .example(`node $0 get-dataset -i "DATASETID"`)
-  .example(`node $0 delete-dataset -i "DATASETID"`)
+  .example('node $0 create-dataset -n "newDataSet"')
+  .example('node $0 list-datasets -f "imageClassificationDatasetMetadata:*"')
+  .example('node $0 get-dataset -i "DATASETID"')
+  .example('node $0 delete-dataset -i "DATASETID"')
   .example(
-    `node $0 import-data -i "dataSetId" -p "gs://myproject/mytraindata.csv"`
+    'node $0 import-data -i "dataSetId" -p "gs://myproject/mytraindata.csv"'
   )
   .example(
-    `node $0 export-data -i "dataSetId" -o "gs://myproject/outputdestination.csv"`
+    'node $0 export-data -i "dataSetId" -o "gs://myproject/outputdestination.csv"'
   )
   .wrap(120)
   .recommendCommands()
diff --git a/cloud-language/snippets/automl/automlNaturalLanguageModel.js b/cloud-language/snippets/automl/automlNaturalLanguageModel.js
index f75d57c06e..6702dc3840 100755
--- a/cloud-language/snippets/automl/automlNaturalLanguageModel.js
+++ b/cloud-language/snippets/automl/automlNaturalLanguageModel.js
@@ -24,7 +24,7 @@
 
 async function createModel(projectId, computeRegion, datasetId, modelName) {
   // [START automl_language_createModel]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -52,21 +52,21 @@ async function createModel(projectId, computeRegion, datasetId, modelName) {
     model: myModel,
   });
   console.log(`Training operation name: ${initialApiResponse.name}`);
-  console.log(`Training started...`);
+  console.log('Training started...');
   const [model] = await operation.promise();
   // Retrieve deployment state.
-  let deploymentState = ``;
+  let deploymentState = '';
   if (model.deploymentState === 1) {
-    deploymentState = `deployed`;
+    deploymentState = 'deployed';
   } else if (model.deploymentState === 2) {
-    deploymentState = `undeployed`;
+    deploymentState = 'undeployed';
   }
 
   // Display the model information.
   console.log(`Model name: ${model.name}`);
-  console.log(`Model id: ${model.name.split(`/`).pop(-1)}`);
+  console.log(`Model id: ${model.name.split('/').pop(-1)}`);
   console.log(`Model display name: ${model.displayName}`);
-  console.log(`Model create time:`);
+  console.log('Model create time:');
   console.log(`\tseconds: ${model.createTime.seconds}`);
   console.log(`\tnanos: ${model.createTime.nanos}`);
   console.log(`Model deployment state: ${deploymentState}`);
@@ -75,7 +75,7 @@ async function createModel(projectId, computeRegion, datasetId, modelName) {
 
 async function getOperationStatus(operationFullId) {
   // [START automl_language_getOperationStatus]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -95,7 +95,7 @@ async function getOperationStatus(operationFullId) {
 
 async function listModels(projectId, computeRegion, filter) {
   // [START automl_language_listModels]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -110,21 +110,21 @@ async function listModels(projectId, computeRegion, filter) {
   const projectLocation = client.locationPath(projectId, computeRegion);
 
   // List all the models available in the region by applying filter.
-  if (filter === ``) filter = `textClassificationModelMetadata:*`;
+  if (filter === '') filter = 'textClassificationModelMetadata:*';
   const [models] = await client.listModels({
     parent: projectLocation,
     filter: filter,
   });
 
   // Display the model information.
-  console.log(`List of models:`);
+  console.log('List of models:');
   models.forEach(model => {
     console.log(`Model name: ${model.name}`);
-    console.log(`Model id: ${model.name.split(`/`).pop(-1)}`);
+    console.log(`Model id: ${model.name.split('/').pop(-1)}`);
     console.log(`Model display name: ${model.displayName}`);
     console.log(`Model dataset id: ${model.datasetId}`);
-    if (model.modelMetadata === `translationModelMetadata`) {
-      console.log(`Translation model metadata:`);
+    if (model.modelMetadata === 'translationModelMetadata') {
+      console.log('Translation model metadata:');
       console.log(`\tBase model: ${model.translationModelMetadata.baseModel}`);
       console.log(
         `\tSource language code: ${model.translationModelMetadata.sourceLanguageCode}`
@@ -132,12 +132,12 @@ async function listModels(projectId, computeRegion, filter) {
       console.log(
         `\tTarget language code: ${model.translationModelMetadata.targetLanguageCode}`
       );
-    } else if (model.modelMetadata === `textClassificationModelMetadata`) {
+    } else if (model.modelMetadata === 'textClassificationModelMetadata') {
       console.log(
         `Text classification model metadata: ${model.textClassificationModelMetadata}`
       );
-    } else if (model.modelMetadata === `imageClassificationModelMetadata`) {
-      console.log(`Image classification model metadata:`);
+    } else if (model.modelMetadata === 'imageClassificationModelMetadata') {
+      console.log('Image classification model metadata:');
       console.log(
         `\tBase model id: ${model.imageClassificationModelMetadata.baseModelId}`
       );
@@ -151,21 +151,21 @@ async function listModels(projectId, computeRegion, filter) {
         `\tStop reason: ${model.imageClassificationModelMetadata.stopReason}`
       );
     }
-    console.log(`Model create time:`);
+    console.log('Model create time:');
     console.log(`\tseconds: ${model.createTime.seconds}`);
     console.log(`\tnanos: ${model.createTime.nanos}`);
-    console.log(`Model update time:`);
+    console.log('Model update time:');
     console.log(`\tseconds: ${model.updateTime.seconds}`);
     console.log(`\tnanos: ${model.updateTime.nanos}`);
     console.log(`Model deployment state: ${model.deploymentState}`);
-    console.log(`\n`);
+    console.log('\n');
   });
   // [END automl_language_listModels]
 }
 
 async function getModel(projectId, computeRegion, modelId) {
   // [START automl_language_getModel]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -184,11 +184,11 @@ async function getModel(projectId, computeRegion, modelId) {
 
   // Display the model information.
   console.log(`Model name: ${model.name}`);
-  console.log(`Model id: ${model.name.split(`/`).pop(-1)}`);
+  console.log(`Model id: ${model.name.split('/').pop(-1)}`);
   console.log(`Model display name: ${model.displayName}`);
   console.log(`Model dataset id: ${model.datasetId}`);
-  if (model.modelMetadata === `translationModelMetadata`) {
-    console.log(`Translation model metadata:`);
+  if (model.modelMetadata === 'translationModelMetadata') {
+    console.log('Translation model metadata:');
     console.log(`\tBase model: ${model.translationModelMetadata.baseModel}`);
     console.log(
       `\tSource language code: ${model.translationModelMetadata.sourceLanguageCode}`
@@ -196,12 +196,12 @@ async function getModel(projectId, computeRegion, modelId) {
     console.log(
       `\tTarget language code: ${model.translationModelMetadata.targetLanguageCode}`
     );
-  } else if (model.modelMetadata === `textClassificationModelMetadata`) {
+  } else if (model.modelMetadata === 'textClassificationModelMetadata') {
     console.log(
       `Text classification model metadata: ${model.textClassificationModelMetadata}`
     );
-  } else if (model.modelMetadata === `imageClassificationModelMetadata`) {
-    console.log(`Image classification model metadata:`);
+  } else if (model.modelMetadata === 'imageClassificationModelMetadata') {
+    console.log('Image classification model metadata:');
     console.log(
       `\tBase model id: ${model.imageClassificationModelMetadata.baseModelId}`
     );
@@ -215,10 +215,10 @@ async function getModel(projectId, computeRegion, modelId) {
       `\tStop reason: ${model.imageClassificationModelMetadata.stopReason}`
     );
   }
-  console.log(`Model create time:`);
+  console.log('Model create time:');
   console.log(`\tseconds: ${model.createTime.seconds}`);
   console.log(`\tnanos: ${model.createTime.nanos}`);
-  console.log(`Model update time:`);
+  console.log('Model update time:');
   console.log(`\tseconds: ${model.updateTime.seconds}`);
   console.log(`\tnanos: ${model.updateTime.nanos}`);
   console.log(`Model deployment state: ${model.deploymentState}`);
@@ -232,8 +232,8 @@ async function listModelEvaluations(
   filter_
 ) {
   // [START automl_language_listModelEvaluations]
-  const automl = require(`@google-cloud/automl`);
-  const util = require(`util`);
+  const automl = require('@google-cloud/automl');
+  const util = require('util');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -253,7 +253,7 @@ async function listModelEvaluations(
     parent: modelFullId,
     filter: filter_,
   });
-  console.log(`List of model evaluations:`);
+  console.log('List of model evaluations:');
   elements.forEach(element => {
     console.log(util.inspect(element, false, null));
   });
@@ -268,8 +268,8 @@ async function getModelEvaluation(
   modelEvaluationId
 ) {
   // [START automl_language_getModelEvaluation]
-  const automl = require(`@google-cloud/automl`);
-  const util = require(`util`);
+  const automl = require('@google-cloud/automl');
+  const util = require('util');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -299,8 +299,8 @@ async function getModelEvaluation(
 
 async function displayEvaluation(projectId, computeRegion, modelId, filter) {
   // [START automl_language_displayEvaluation]
-  const automl = require(`@google-cloud/automl`);
-  const math = require(`mathjs`);
+  const automl = require('@google-cloud/automl');
+  const math = require('mathjs');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -324,7 +324,7 @@ async function displayEvaluation(projectId, computeRegion, modelId, filter) {
     // There is evaluation for each class in a model and for overall model.
     // Get only the evaluation of overall model.
     if (!element.annotationSpecId) {
-      const modelEvaluationId = element.name.split(`/`).pop(-1);
+      const modelEvaluationId = element.name.split('/').pop(-1);
 
       // Resource name for the model evaluation.
       const modelEvaluationFullId = client.modelEvaluationPath(
@@ -348,31 +348,31 @@ async function displayEvaluation(projectId, computeRegion, modelId, filter) {
       confidenceMetricsEntries.forEach(confidenceMetricsEntry => {
         if (confidenceMetricsEntry.confidenceThreshold === 0.5) {
           console.log(
-            `Precision and recall are based on a score threshold of 0.5`
+            'Precision and recall are based on a score threshold of 0.5'
           );
           console.log(
-            `Model Precision: `,
-            math.round(confidenceMetricsEntry.precision * 100, 2) + `%`
+            'Model Precision: ',
+            math.round(confidenceMetricsEntry.precision * 100, 2) + '%'
           );
           console.log(
-            `Model Recall: `,
-            math.round(confidenceMetricsEntry.recall * 100, 2) + `%`
+            'Model Recall: ',
+            math.round(confidenceMetricsEntry.recall * 100, 2) + '%'
           );
           console.log(
-            `Model F1 score: `,
-            math.round(confidenceMetricsEntry.f1Score * 100, 2) + `%`
+            'Model F1 score: ',
+            math.round(confidenceMetricsEntry.f1Score * 100, 2) + '%'
           );
           console.log(
-            `Model Precision@1: `,
-            math.round(confidenceMetricsEntry.precisionAt1 * 100, 2) + `%`
+            'Model Precision@1: ',
+            math.round(confidenceMetricsEntry.precisionAt1 * 100, 2) + '%'
           );
           console.log(
-            `Model Recall@1: `,
-            math.round(confidenceMetricsEntry.recallAt1 * 100, 2) + `%`
+            'Model Recall@1: ',
+            math.round(confidenceMetricsEntry.recallAt1 * 100, 2) + '%'
           );
           console.log(
-            `Model F1 score@1: `,
-            math.round(confidenceMetricsEntry.f1ScoreAt1 * 100, 2) + `%`
+            'Model F1 score@1: ',
+            math.round(confidenceMetricsEntry.f1ScoreAt1 * 100, 2) + '%'
           );
         }
       });
@@ -383,7 +383,7 @@ async function displayEvaluation(projectId, computeRegion, modelId, filter) {
 
 async function deleteModel(projectId, computeRegion, modelId) {
   // [START automl_language_deleteModel]
-  const automl = require(`@google-cloud/automl`);
+  const automl = require('@google-cloud/automl');
 
   const client = new automl.v1beta1.AutoMlClient();
 
@@ -401,78 +401,78 @@ async function deleteModel(projectId, computeRegion, modelId) {
   const [operation] = client.deleteModel({name: modelFullId});
   const response = await operation.promise();
   // The final result of the operation.
-  if (response[2].done === true) console.log(`Model deleted.`);
+  if (response[2].done === true) console.log('Model deleted.');
 
   // [END automl_language_deleteModel]
 }
 
-require(`yargs`)
+require('yargs')
   .demand(1)
   .options({
     computeRegion: {
-      alias: `c`,
-      type: `string`,
+      alias: 'c',
+      type: 'string',
       default: process.env.REGION_NAME,
       requiresArg: true,
-      description: `region name e.g. "us-central1"`,
+      description: 'region name e.g. "us-central1"',
     },
     datasetId: {
-      alias: `i`,
-      type: `string`,
+      alias: 'i',
+      type: 'string',
       requiresArg: true,
-      description: `Id of the dataset`,
+      description: 'Id of the dataset',
     },
     filter: {
-      alias: `f`,
-      default: ``,
-      type: `string`,
+      alias: 'f',
+      default: '',
+      type: 'string',
       requiresArg: true,
-      description: `Name of the Dataset to search for`,
+      description: 'Name of the Dataset to search for',
     },
     modelName: {
-      alias: `m`,
-      type: `string`,
+      alias: 'm',
+      type: 'string',
       default: false,
       requiresArg: true,
-      description: `Name of the model`,
+      description: 'Name of the model',
     },
     modelId: {
-      alias: `a`,
-      type: `string`,
-      default: ``,
+      alias: 'a',
+      type: 'string',
+      default: '',
       requiresArg: true,
-      description: `Id of the model`,
+      description: 'Id of the model',
     },
     modelEvaluationId: {
-      alias: `e`,
-      type: `string`,
-      default: ``,
+      alias: 'e',
+      type: 'string',
+      default: '',
       requiresArg: true,
-      description: `Id of the model evaluation`,
+      description: 'Id of the model evaluation',
     },
     operationFullId: {
-      alias: `o`,
-      type: `string`,
-      default: ``,
+      alias: 'o',
+      type: 'string',
+      default: '',
       requiresArg: true,
-      description: `Full name of an operation`,
+      description: 'Full name of an operation',
     },
     projectId: {
-      alias: `z`,
-      type: `number`,
+      alias: 'z',
+      type: 'number',
       default: process.env.GCLOUD_PROJECT,
       requiresArg: true,
-      description: `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`,
+      description: 'The GCLOUD_PROJECT string, e.g. "my-gcloud-project"',
     },
     trainBudget: {
-      alias: `t`,
-      type: `string`,
-      default: ``,
+      alias: 't',
+      type: 'string',
+      default: '',
       requiresArg: true,
-      description: `Budget for training the model`,
+      description: 'Budget for training the model',
     },
   })
-  .command(`create-model`, `creates a new Model`, {}, opts =>
+  .command('create-model', 'creates a new Model', {}, opts =>
     createModel(
       opts.projectId,
       opts.computeRegion,
@@ -482,18 +482,18 @@ require(`yargs`)
     )
   )
   .command(
-    `get-operation-status`,
-    `Gets status of current operation`,
+    'get-operation-status',
+    'Gets status of current operation',
     {},
     opts => getOperationStatus(opts.operationFullId)
   )
-  .command(`list-models`, `list all Models`, {}, opts =>
+  .command('list-models', 'list all Models', {}, opts =>
     listModels(opts.projectId, opts.computeRegion, opts.filter)
   )
-  .command(`get-model`, `Get a Model`, {}, opts =>
+  .command('get-model', 'Get a Model', {}, opts =>
     getModel(opts.projectId, opts.computeRegion, opts.modelId)
   )
-  .command(`list-model-evaluations`, `List model evaluations`, {}, opts =>
+  .command('list-model-evaluations', 'List model evaluations', {}, opts =>
     listModelEvaluations(
       opts.projectId,
       opts.computeRegion,
@@ -501,7 +501,7 @@ require(`yargs`)
       opts.filter
     )
   )
-  .command(`get-model-evaluation`, `Get model evaluation`, {}, opts =>
+  .command('get-model-evaluation', 'Get model evaluation', {}, opts =>
     getModelEvaluation(
       opts.projectId,
       opts.computeRegion,
@@ -509,7 +509,7 @@ require(`yargs`)
       opts.modelEvaluationId
     )
   )
-  .command(`display-evaluation`, `Display evaluation`, {}, opts =>
+  .command('display-evaluation', 'Display evaluation', {}, opts =>
     displayEvaluation(
       opts.projectId,
       opts.computeRegion,
@@ -517,17 +517,17 @@ require(`yargs`)
       opts.filter
     )
   )
-  .command(`delete-model`, `Delete a Model`, {}, opts =>
+  .command('delete-model', 'Delete a Model', {}, opts =>
     deleteModel(opts.projectId, opts.computeRegion, opts.modelId)
   )
-  .example(`node $0 create-model -i "DatasetID" -m "myModelName" -t "2"`)
-  .example(`node $0 get-operation-status -i "datasetId" -o "OperationFullID"`)
-  .example(`node $0 list-models -f "textClassificationModelMetadata:*"`)
-  .example(`node $0 get-model -a "ModelID"`)
-  .example(`node $0 list-model-evaluations -a "ModelID"`)
-  .example(`node $0 get-model-evaluation -a "ModelId" -e "ModelEvaluationID"`)
-  .example(`node $0 display-evaluation -a "ModelId"`)
-  .example(`node $0 delete-model -a "ModelID"`)
+  .example('node $0 create-model -i "DatasetID" -m "myModelName" -t "2"')
+  .example('node $0 get-operation-status -i "datasetId" -o "OperationFullID"')
+  .example('node $0 list-models -f "textClassificationModelMetadata:*"')
+  .example('node $0 get-model -a "ModelID"')
+  .example('node $0 list-model-evaluations -a "ModelID"')
+  .example('node $0 get-model-evaluation -a "ModelId" -e "ModelEvaluationID"')
+  .example('node $0 display-evaluation -a "ModelId"')
+  .example('node $0 delete-model -a "ModelID"')
   .wrap(120)
   .recommendCommands()
   .help()
diff --git a/cloud-language/snippets/automl/automlNaturalLanguagePredict.js b/cloud-language/snippets/automl/automlNaturalLanguagePredict.js
index 41cfc0a144..535899ec15 100755
--- a/cloud-language/snippets/automl/automlNaturalLanguagePredict.js
+++ b/cloud-language/snippets/automl/automlNaturalLanguagePredict.js
@@ -24,8 +24,8 @@
 
 async function predict(projectId, computeRegion, modelId, filePath) {
   // [START automl_language_predict]
-  const automl = require(`@google-cloud/automl`);
-  const fs = require(`fs`);
+  const automl = require('@google-cloud/automl');
+  const fs = require('fs');
 
   // Create client for prediction service.
   const client = new automl.v1beta1.PredictionServiceClient();
@@ -42,13 +42,13 @@ async function predict(projectId, computeRegion, modelId, filePath) {
   const modelFullId = client.modelPath(projectId, computeRegion, modelId);
 
   // Read the file content for prediction.
-  const snippet = fs.readFileSync(filePath, `utf8`);
+  const snippet = fs.readFileSync(filePath, 'utf8');
 
   // Set the payload by giving the content and type of the file.
   const payload = {
     textSnippet: {
       content: snippet,
-      mimeType: `text/plain`,
+      mimeType: 'text/plain',
     },
   };
 
@@ -59,7 +59,7 @@ async function predict(projectId, computeRegion, modelId, filePath) {
     payload: payload,
     params: {},
   });
-  console.log(`Prediction results:`);
+  console.log('Prediction results:');
   response[0].payload.forEach(result => {
     console.log(`Predicted class name: ${result.displayName}`);
     console.log(`Predicted class score: ${result.classification.score}`);
@@ -67,47 +67,47 @@ async function predict(projectId, computeRegion, modelId, filePath) {
   // [END automl_language_predict]
 }
 
-require(`yargs`)
+require('yargs')
   .demand(1)
   .options({
     computeRegion: {
-      alias: `c`,
-      type: `string`,
+      alias: 'c',
+      type: 'string',
       default: process.env.REGION_NAME,
       requiresArg: true,
-      description: `region name e.g. "us-central1"`,
+      description: 'region name e.g. "us-central1"',
     },
     filePath: {
-      alias: `f`,
-      default: `./resources/test.txt`,
-      type: `string`,
+      alias: 'f',
+      default: './resources/test.txt',
+      type: 'string',
       requiresArg: true,
-      description: `local text file path of the content to be classified`,
+      description: 'local text file path of the content to be classified',
     },
     modelId: {
-      alias: `i`,
-      type: `string`,
+      alias: 'i',
+      type: 'string',
       requiresArg: true,
-      description: `Id of the model which will be used for text classification`,
+      description: 'Id of the model which will be used for text classification',
     },
     projectId: {
-      alias: `z`,
-      type: `number`,
+      alias: 'z',
+      type: 'number',
       default: process.env.GCLOUD_PROJECT,
       requiresArg: true,
-      description: `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`,
+      description: 'The GCLOUD_PROJECT string, e.g. "my-gcloud-project"',
     },
     scoreThreshold: {
-      alias: `s`,
-      type: `string`,
-      default: `0.5`,
+      alias: 's',
+      type: 'string',
+      default: '0.5',
       requiresArg: true,
       description:
-        `A value from 0.0 to 1.0.  When the model makes predictions for an image it will` +
-        `only produce results that have at least this confidence score threshold.  Default is .5`,
+        'A value from 0.0 to 1.0.  When the model makes predictions for an image it will' +
+        'only produce results that have at least this confidence score threshold.  Default is .5',
     },
   })
-  .command(`predict`, `classify the content`, {}, opts =>
+  .command('predict', 'classify the content', {}, opts =>
     predict(
       opts.projectId,
       opts.computeRegion,
@@ -116,7 +116,7 @@ require(`yargs`)
       opts.scoreThreshold
     )
   )
-  .example(`node $0 predict -i "modelId" -f "./resources/test.txt" -s "0.5"`)
+  .example('node $0 predict -i "modelId" -f "./resources/test.txt" -s "0.5"')
   .wrap(120)
   .recommendCommands()
   .help()
diff --git a/cloud-language/snippets/test/analyze.v1.test.js b/cloud-language/snippets/test/analyze.v1.test.js
index 8e9404b060..4dc992f8ea 100644
--- a/cloud-language/snippets/test/analyze.v1.test.js
+++ b/cloud-language/snippets/test/analyze.v1.test.js
@@ -18,7 +18,7 @@ const fs = require('fs');
 const path = require('path');
 const {Storage} = require('@google-cloud/storage');
 const {assert} = require('chai');
-const {describe, it} = require('mocha');
+const {after, before, describe, it} = require('mocha');
 const cp = require('child_process');
 const uuid = require('uuid');
 
@@ -28,8 +28,8 @@ describe('analyze.v1', () => {
   const storage = new Storage();
   const cmd = 'node analyze.v1.js';
   const bucketName = `nodejs-docs-samples-test-${uuid.v4()}`;
-  const fileName = `text.txt`;
-  const fileName2 = `android_text.txt`;
+  const fileName = 'text.txt';
+  const fileName2 = 'android_text.txt';
   const localFilePath = path.join(__dirname, `../resources/${fileName}`);
   const localFilePath2 = path.join(__dirname, `../resources/${fileName2}`);
   const text = fs.readFileSync(localFilePath, 'utf-8');
diff --git a/cloud-language/snippets/test/automlNaturalLanguage.test.js b/cloud-language/snippets/test/automlNaturalLanguage.test.js
index 8f68970e2e..efc5daab67 100644
--- a/cloud-language/snippets/test/automlNaturalLanguage.test.js
+++ b/cloud-language/snippets/test/automlNaturalLanguage.test.js
@@ -93,7 +93,7 @@ describe.skip('automl', () => {
   });
 
   it('should display evaluation from prexisting model', async () => {
-    const donotdeleteModelId = `TCN4740161257642267869`;
+    const donotdeleteModelId = 'TCN4740161257642267869';
 
     // Confirm dataset exists
     let output = execSync(`${cmdDataset} list-datasets`);
@@ -112,7 +112,7 @@ describe.skip('automl', () => {
   });
 
   it('should run Prediction from prexisting model', async () => {
-    const donotdeleteModelId = `TCN4740161257642267869`;
+    const donotdeleteModelId = 'TCN4740161257642267869';
 
     // Confirm dataset exists
     let output = execSync(`${cmdDataset} list-datasets`);