ci: update linters configuration

Update linters configuration to match style guides:

- CSS
- ESLint
- Markdownlint
- yamllint

bugs: 353152994

Change-Id: I9a25d179e675e432ca19771521d227a34e8f8e6b
GitOrigin-RevId: 84c672da6768906ff3c75a020d7379307cf96c3f

.github/workflows/deploy-site.yml

@@ -20,7 +20,7 @@
 #
 
 name: Deploy documentation to GitHub Pages
-on:
+on: # yamllint disable-line rule:truthy
   push:
     branches: ["main"]
   #
@@ -59,7 +59,7 @@ jobs:
         uses: actions/upload-pages-artifact@v3
         if: github.ref == 'refs/heads/main'
         with:
-          path: 'docs/build/public'
+          path: "docs/build/public"
       - name: Deploy to GitHub Pages
         if: github.ref == 'refs/heads/main'
         uses: actions/deploy-pages@v4

projects/dataflow-gcs-to-alloydb/docs/index.md

@@ -27,4 +27,4 @@ Cloud Storage to AlloyDB or PostgreSQL server in Cloud SQL.
 ## Quickstart
 
 1.  [Configure](./configuration.md) the pipeline parameters.
-2.  [Build and run](./build_and_run_pipeline.md) the Dataflow Flex pipeline.
+1.  [Build and run](./build_and_run_pipeline.md) the Dataflow Flex pipeline.

projects/dataproc-trino-autoscaler/docs/demo.md

@@ -185,8 +185,8 @@ in this tutorial, you can delete the project:
 1.  In the Cloud Console, go to the
     [**Manage resources** page](https://console.cloud.google.com/iam-admin/projects).
 
-2.  In the project list, select the project that you want to delete and then
+1.  In the project list, select the project that you want to delete and then
     click **Delete**.
 
-3.  In the dialog, type the project ID and then click **Shut down** to delete
+1.  In the dialog, type the project ID and then click **Shut down** to delete
     the project.

projects/imagen-object-changer/README.md

@@ -15,12 +15,12 @@ The solution works as follows:
 1.  The user provides an object label such as ‘car’, the source image file, and
     a GenAI Imagen prompt such as ‘red plastic toy car’. In this case, to
     replace cars with toy cars
-2.  Query Vision API with the source image and object label
-3.  Present list of found labels
-4.  If the user’s label was found in the list of detected labels, generate a
+1.  Query Vision API with the source image and object label
+1.  Present list of found labels
+1.  If the user’s label was found in the list of detected labels, generate a
     mask image based on the bounding boxes for the objects
-5.  Query Imagen with the original image, mask image, and GenAI prompt
-6.  Save the resulting generated images
+1.  Query Imagen with the original image, mask image, and GenAI prompt
+1.  Save the resulting generated images
 
 ## Example
 
@@ -63,9 +63,9 @@ replace the background instead:
 1.  With your browser, navigate to the
     [Google Cloud Console](https://console.cloud.google.com/home/dashboard) and
     select the right Project
-2.  Use the Console to Enable the
+1.  Use the Console to Enable the
     [Cloud Vision API in the API Library](https://console.cloud.google.com/apis/library/vision.googleapis.com)
-3.  Check that you can access
+1.  Check that you can access
     [Generative AI Studio Vision](https://console.cloud.google.com/vertex-ai/generative/vision)
 
 ### Installing the Application
@@ -82,20 +82,20 @@ replace the background instead:
     isolated environment for this application and its imported modules. Please
     refer to the links in this step for more information on virtual environment
 
-2.  Open a terminal on your computer, and execute the following gcloud command
+1.  Open a terminal on your computer, and execute the following gcloud command
     to authenticate the application for Google Cloud Platform:
 
     ```shell
     gcloud auth application-default login
     ```
 
-3.  Install the Python dependencies with:
+1.  Install the Python dependencies with:
 
     ```shell
     pip3 install -r requirements.txt --require-hashes
     ```
 
-4.  Test that the application can start without errors, by executing the
+1.  Test that the application can start without errors, by executing the
     following:
 
     ```shell

projects/imagen-voice-captioning/README.md

@@ -10,13 +10,13 @@ and [Text-to-Speech AI](https://cloud.google.com/text-to-speech).
 The solution works as follows:
 
 1.  The user runs the application and selects a connected camera as the input
-2.  The applications shows a live view of the camera
-3.  The user triggers captioning
-4.  The camera’s image is sent to Imagen image captioning, which returns a
+1.  The applications shows a live view of the camera
+1.  The user triggers captioning
+1.  The camera’s image is sent to Imagen image captioning, which returns a
     textual description of the scene
-5.  The text is sent to Text-to-Speech AI, which returns an audio file
+1.  The text is sent to Text-to-Speech AI, which returns an audio file
     containing the caption synthesized as speech
-6.  The application plays back the audio, describing the scene verbally
+1.  The application plays back the audio, describing the scene verbally
 
 ## Example
 
@@ -46,11 +46,11 @@ in a grassy field behind a fence_”
 1.  With your browser, navigate to the
     [Google Cloud Console](https://console.cloud.google.com/home/dashboard) and
     select the right Project
-2.  Use the Console to Enable the
+1.  Use the Console to Enable the
     [Cloud Vision Text to Speech API](https://console.cloud.google.com/apis/library/texttospeech.googleapis.com)
-3.  Use the Console to Enable the
+1.  Use the Console to Enable the
     [Cloud Vision API in the API Library](https://console.cloud.google.com/apis/library/vision.googleapis.com)
-4.  Check that you can access
+1.  Check that you can access
     [Generative AI Studio Vision](https://console.cloud.google.com/vertex-ai/generative/vision)
 
 ### Creating the Service Account and Key
@@ -59,8 +59,8 @@ in a grassy field behind a fence_”
     to:
 
     1.  create a new service account in your GCP Project
-    2.  create and download a JSON key for it
-    3.  Bind the Cloud Storage object viewer role to it
+    1.  create and download a JSON key for it
+    1.  Bind the Cloud Storage object viewer role to it
 
     This service account will be used to access Cloud Vision API. Execute the
     following, replacing `[your-gcp-project]` with your project ID:
@@ -81,7 +81,7 @@ in a grassy field behind a fence_”
     gcloud services enable vision.googleapis.com
     ```
 
-2.  The service account key was downloaded as a file called `credentials.json`
+1.  The service account key was downloaded as a file called `credentials.json`
     in your current working directory. Note the location of the file, as you
     will need it later.
 
@@ -101,20 +101,20 @@ in a grassy field behind a fence_”
     isolated environment for this application and its imported modules. Please
     refer to the links in this step for more information on virtual environment
 
-2.  Install the Python dependencies with:
+1.  Install the Python dependencies with:
 
     ```shell
     pip3 install -r requirements.txt
     ```
 
-3.  Copy the service account key credentials.json that you downloaded earlier to
+1.  Copy the service account key credentials.json that you downloaded earlier to
     this same directory with e.g:
 
     ```shell
     cp ~/credentials.json .
     ```
 
-4.  Test that the application can start without errors, by executing the
+1.  Test that the application can start without errors, by executing the
     following:
 
     ```shell
@@ -139,21 +139,21 @@ in a grassy field behind a fence_”
 
 1.  Connect a camera such as a USB webcam to your computer. Test that the camera
     works on your computer
-2.  Start the application and provide the following parameter values:
+1.  Start the application and provide the following parameter values:
 
     1.  `--input`: <the device number of the connected cameras>. Start with 0
         and increase the number until you see the correct camera’s output on the
         screen
-    2.  `--credentials`: <path to the credentials.json you prepared earlier>
-    3.  `--project_id`: <your GCP project ID>
+    1.  `--credentials`: <path to the credentials.json you prepared earlier>
+    1.  `--project_id`: <your GCP project ID>
 
     Example command:
 
     ```shell
     python3 imagen-voice-captioning.py --input 1 --credentials credentials.json --project_id myproject
     ```
 
-3.  If successful, the application will output the following on the console:
+1.  If successful, the application will output the following on the console:
 
     ```text
     {'input': '1', 'credentials': 'credentials.json', 'project_id': 'myproject''}
@@ -164,10 +164,10 @@ in a grassy field behind a fence_”
 
     And open a window where it displays the camera’s live view on your desktop.
 
-4.  To caption the camera view, select the camera display window and press
+1.  To caption the camera view, select the camera display window and press
     <SPACE>
 
-5.  If successful, the application will output:
+1.  If successful, the application will output:
 
     ```text
     Querying Imagen captioning...OK

projects/sa-tools/common/java-common/README.md

@@ -17,7 +17,7 @@ This folder contains reusable Java components:
     includeBuild("path/to/common/java-common")
     ```
 
-2.  Use appropriate module in your `build.gradle`: Example to use utils and
+1.  Use appropriate module in your `build.gradle`: Example to use utils and
     testing module:
 
     ```groovy

projects/sa-tools/common/ui-tests/src/CommonFunctions.test.js

@@ -14,7 +14,7 @@
  * limitations under the License.
  */
 
-import { describe, expect, it } from 'vitest';
+import {describe, expect, it} from 'vitest';
 import * as common from './Common/CommonFunctions';
 
 const commonFunctionsTestSuite = () => {

projects/sa-tools/common/ui-tests/src/SaToolsDate.test.js

@@ -14,8 +14,8 @@
  * limitations under the License.
  */
 
-import { describe, expect, it } from 'vitest';
-import { SaToolsDate } from './Common/SaToolsDate';
+import {describe, expect, it} from 'vitest';
+import {SaToolsDate} from './Common/SaToolsDate';
 
 const satoolsDateTestSuite = () => {
   it(`Given N number of substracted minutes should return new Date object of
@@ -42,7 +42,7 @@ const satoolsDateTestSuite = () => {
     ago`, () => {
     const testDate = new SaToolsDate(new Date('2022-12-01 11:00:00'));
     expect(testDate.formattedDateDiff(new Date('2022-12-01 10:00:00'))).toBe(
-      '1 hour(s) ago'
+        '1 hour(s) ago',
     );
   });
 
@@ -106,7 +106,7 @@ const satoolsDateTestSuite = () => {
   it(`Given a datetime in 50 mins ago should return 50 minute(s) ago`, () => {
     const testDate = new SaToolsDate(new Date('2022-12-01 10:10:00'));
     expect(
-      testDate.formattedDateDiffFrom(new Date('2022-12-01 11:00:00'))
+        testDate.formattedDateDiffFrom(new Date('2022-12-01 11:00:00')),
     ).toBe('50 minute(s) ago');
   });
 

projects/sa-tools/common/ui-tests/src/StringSet.test.js

@@ -14,8 +14,8 @@
  * limitations under the License.
  */
 
-import { describe, expect, it } from 'vitest';
-import { StringSet } from './Common/StringSet';
+import {describe, expect, it} from 'vitest';
+import {StringSet} from './Common/StringSet';
 
 /**
  * Assert StringSet equality to an array.

projects/sa-tools/common/ui-tests/vite.config.js

@@ -14,7 +14,7 @@
  * limitations under the License.
  */
 
-import { defineConfig } from 'vite';
+import {defineConfig} from 'vite';
 
 export default defineConfig({
   plugins: [],

projects/sa-tools/common/ui/SaToolsDate.js

@@ -122,4 +122,4 @@ class SaToolsDate {
   }
 }
 
-export { SaToolsDate };
+export {SaToolsDate};

projects/sa-tools/common/ui/StringSet.js

@@ -117,4 +117,4 @@ class StringSet {
   }
 }
 
-export { StringSet };
+export {StringSet};

projects/sa-tools/perf-benchmark/README.md

@@ -5,13 +5,13 @@ Consists of 3 modules:
 1.  API Server: Java SpringBoot based server providing RESTful API for creating,
     monitoring and cancelling BenchmarkJobs using the Benchmark Runner.
 
-2.  Benchmark Runner: Templated launch scripts on fork of Google's Perfkit
+1.  Benchmark Runner: Templated launch scripts on fork of Google's Perfkit
     benchmark maintained by @prakhargautam at
     <https://github.com/prakhag2/PerfKitBenchmarker> The runner executes a
     parameterized Cloud Build jobs with job specific parameters passed as input
     and writes the results to Google BigQuery table.
 
-3.  Daily Perfkit benchmarks runner cron-based runner for standard shapes.
+1.  Daily Perfkit benchmarks runner cron-based runner for standard shapes.
 
 ## Prerequisites
 
@@ -130,25 +130,25 @@ generated and open it in the browser:
     gcloud firestore databases create --type=datastore-mode --project "${PROJECT_ID}" --location "nam5"
     ```
 
-2.  If facing this error: "Unable to Sign-In using Google Sign-In. An Error has
+1.  If facing this error: "Unable to Sign-In using Google Sign-In. An Error has
     occured. Only accounts from the organization can access this site." Make
     sure the Authorized Domains section under OAuth Screen
     <https://console.cloud.google.com/apis/credentials/consent/edit?project=><replace_with_PROJECT_ID>
     having domain name of user's Identiy Platform, ex: example.com Which means
     <[email protected]> login will be allowed.
 
-3.  If facing this error: "Storage object. Permission 'storage.objects.get'
+1.  If facing this error: "Storage object. Permission 'storage.objects.get'
     denied on resource (or it may not exist)., forbidden" or "denied: Permission
     "artifactregistry.repositories.uploadArtifacts" denied on resource" Make
     sure that <project_number>@cloudbuild.gserviceaccount.com exist, and having
     Artifact Registry Writer and Storage Object Creator permissions.
 
-4.  If facing this error: "message":"Failed to open popup
+1.  If facing this error: "message":"Failed to open popup
     window","stack":"Error: Failed to open popup window\n at new ..." Make sure
     the allow pop-up from the Cloud Run's URL domain is allowed from Browser's
     address bar.
 
-5.  Error: Members belonging to the external domain cannot be added as domain
+1.  Error: Members belonging to the external domain cannot be added as domain
     restricted sharing is enforced by the organization policy Depending on
     organization policy being used, some organization will have
     constraints/iam.allowedPolicyMemberDomains to be restricted to be on the
@@ -165,13 +165,13 @@ generated and open it in the browser:
     gcloud beta emulators datastore start --no-store-on-disk &
     ```
 
-2.  Set Environment variables
+1.  Set Environment variables
 
     ```shell
     $(gcloud beta emulators datastore env-init)
     ```
 
-3.  Run Local server
+1.  Run Local server
 
     ```shell
     cd api/

projects/sa-tools/perf-benchmark/ui/vite.config.js

@@ -14,7 +14,7 @@
  * limitations under the License.
  */
 /* eslint-disable comma-dangle, semi */
-import { defineConfig } from 'vite';
+import {defineConfig} from 'vite';
 import react from '@vitejs/plugin-react';
 
 export default defineConfig({

projects/sa-tools/performance-testing/README.md

@@ -42,7 +42,7 @@ The deployment approach is by deploying two copies of pt-admin component:
 
 1.  To the target GCP Project. Create a new GCP Project, or use an existing GCP
     Project where the deployer user having permissions as Owner or Editor.
-2.  To run pt-admin container locally (hosting the UI and part of the backend)
+1.  To run pt-admin container locally (hosting the UI and part of the backend)
 
 The less pre-requisite dependencies to run this setup is by doing it from the
 Cloud Shell. Make sure there's enough disk space to run the commands below.

projects/sa-tools/performance-testing/pt-operator/README.md

@@ -22,13 +22,13 @@ cluster-info` shows).
     kubectl apply -f config/samples/
     ```
 
-2.  Build and push your image to the location specified by `IMG`:
+1.  Build and push your image to the location specified by `IMG`:
 
     ```sh
     make docker-build docker-push IMG=<some-registry>/pt-operator:tag
     ```
 
-3.  Deploy the controller to the cluster with the image specified by `IMG`:
+1.  Deploy the controller to the cluster with the image specified by `IMG`:
 
     ```sh
     make deploy IMG=<some-registry>/pt-operator:tag
@@ -68,7 +68,7 @@ the desired state is reached on the cluster.
     make install
     ```
 
-2.  Run your controller (this will run in the foreground, so switch to a new
+1.  Run your controller (this will run in the foreground, so switch to a new
     terminal if you want to leave it running):
 
     ```sh