Guava VS JHipster

The first problem is at the level of Type System, given that a situation more correct would allow us to distinguish through the Collection Type which abstraction we are operating with, species if definable as mutable or immutable. The JCF was born at a time when great care was taken to offer immediate operational data structures, and with attention to performance, but with less attention to constructs or uses that are now seen as common. These concepts have been taken up by other infrastructures from which we certainly cannot fail to mention: Eclipse Collection, Guava Collections, and VAVR.

Even better is getting Gradle/Maven to correctly pull "plain" vs "Android" versions of the package instead of them just publishing the diverging code base as two repository packages.

https://github.com/google/guava/issues/2914

I'll admit I'm surprised to see that BOMs have been documented on maven.apache.org since mid-2008. It looks like Spring, for example, didn't adopt them until mid-2014. I don't know how widely they caught on in other areas. The first discussion of them in the context of Guava may have been in 2018, as I don't see mention of them in the various issues from 2011-2015 (#605, #1329, #1471, #1954.

And a quick peek at the source code for ImmutableList seems to confirm this (https://github.com/google/guava/blob/master/guava/src/com/google/common/collect/ImmutableList.java - it goes via a bunch of methods, but ends up using Arrays.copyOf(), which creates a fixed-size array).

The guava library of Java has some of these data structures implemented: https://github.com/google/guava/wiki/ImmutableCollectionsExplained , but implementations of the above book in many languages can be found on github (say, this one for Haskell: https://github.com/aistrate/Okasaki )

Java Mask: Java Mask is a library that offers various string masking techniques for sensitive data such as credit card numbers, email addresses, and more. You can find the library at: https://github.com/miguelfreitas93/java-mask DataMasker: DataMasker is a Java library specifically designed for masking sensitive data, including credit card numbers, using customizable masking patterns. Visit the GitHub repository for more information and usage examples: https://github.com/GDSSecurity/DataMasker Maskify: Maskify is a simple Java library that can be used to mask credit card numbers, Social Security numbers, and other sensitive information. You can find the library at: https://github.com/jonathancarvalhoalves/maskify CreditCardUtils: This is a lightweight Java library that provides utility methods for validating, formatting, and masking credit card numbers. Visit the GitHub repository for more information: https://github.com/malkusch/creditcardutils Google Guava: Google Guava is a popular set of Java libraries containing a wealth of utilities for working with strings, collections, and more. While not specifically designed for masking credit card information, you can use Guava's string manipulation methods to mask sensitive data: https://github.com/google/guava

I mean, I guess, technically? If you define it like that, then Microsoft has people working for them for free, as does Google, as does Apple, etc. It's not that weird, and you can try to twist it to be weird, but those of us in the software industry largely regard this as a good thing.

So we have https://github.com/google/guava/issues/4011

Ok, so let's implement our lazy initialization more smartly to avoid acquiring the lock every time and use old fashion but still working double-checked locking. I've found it implemented by Suppliers.memoize in guava library.

An easy way to get a pre-configured Keycloak instance is to use JHipster's jhipster-sample-app-oauth2 application. It gets updated with every JHipster release. You can clone it with the following command:

provider "auth0" { domain = "https://" debug = false } # Create a new Auth0 application for the JHipster app resource "auth0_client" "java_ms_client" { name = "JavaMicroservices" description = "Java Microservices Client Created Through Terraform" app_type = "regular_web" callbacks = ["http://localhost:8080/login/oauth2/code/oidc"] allowed_logout_urls = ["http://localhost:8080"] oidc_conformant = true jwt_configuration { alg = "RS256" } } # Configuring client_secret_post as an authentication method. resource "auth0_client_credentials" "java_ms_client_creds" { client_id = auth0_client.java_ms_client.id authentication_method = "client_secret_post" } # Create roles for the JHipster app resource "auth0_role" "admin" { name = "ROLE_ADMIN" description = "Administrator" } resource "auth0_role" "user" { name = "ROLE_USER" description = "User" } # Create an action to customize the authentication flow to add the roles and the username to the access token claims expected by JHipster applications. resource "auth0_action" "jhipster_action" { name = "jhipster_roles_claim" runtime = "node18" deploy = true code = <<-EOT /** * Handler that will be called during the execution of a PostLogin flow. * * @param {Event} event - Details about the user and the context in which they are logging in. * @param {PostLoginAPI} api - Interface whose methods can be used to change the behavior of the login. */ exports.onExecutePostLogin = async (event, api) => { const namespace = 'https://www.jhipster.tech'; if (event.authorization) { api.idToken.setCustomClaim(namespace + '/roles', event.authorization.roles); api.accessToken.setCustomClaim(namespace + '/roles', event.authorization.roles); } }; EOT supported_triggers { id = "post-login" version = "v3" } } # Attach the action to the login flow resource "auth0_trigger_actions" "login_flow" { trigger = "post-login" actions { id = auth0_action.jhipster_action.id display_name = auth0_action.jhipster_action.name } } # Create a test user. You can create more users here if needed resource "auth0_user" "test_user" { connection_name = "Username-Password-Authentication" name = "Jane Doe" email = "[email protected]" email_verified = true password = "passpass$12$12" # Don't set passwords like this in production! Use env variables instead. lifecycle { ignore_changes = [roles] } } resource "auth0_user_roles" "test_user_roles" { user_id = auth0_user.test_user.id roles = [auth0_role.admin.id, auth0_role.user.id] } output "auth0_webapp_client_id" { description = "Auth0 JavaMicroservices Client ID" value = auth0_client.java_ms_client.client_id } output "auth0_webapp_client_secret" { description = "Auth0 JavaMicroservices Client Secret" value = auth0_client_credentials.java_ms_client_creds.client_secret sensitive = true }

If you want a Spring backend with an Angular Frontend check out https://www.jhipster.tech. This is very nice for CRUD stuff.

Use https://www.jhipster.tech/

To test GitHub Actions, we need a new project which in this case I generated using JHipster with the configuration seen here:

exports.onExecutePostLogin = async (event, api) => { const namespace = 'https://www.jhipster.tech'; if (event.authorization) { api.idToken.setCustomClaim('preferred_username', event.user.email); api.idToken.setCustomClaim(`${namespace}/roles`, event.authorization.roles); api.accessToken.setCustomClaim(`${namespace}/roles`, event.authorization.roles); } }

What you maybe asking for is something like vaadin or jhipster which marries the front with the backend. (I don't like them tbh but it worth mentioning)

You can try this stack https://www.jhipster.tech with generator for mobile app https://github.com/jhipster/generator-jhipster-ionic.