arturaz

Here's a single worked example you can paste. One domain, both languages, and an experiment he can run himself in ten minutes.

---

The domain

A payment attempt has exactly three outcomes:

• Succeeded — we have a transaction id.
• Declined — we have a reason code.

arturaz

Disclaimer: I use Scala since 2012 and am author of doobie-typesafe and yantl libraries and a contributor to Laminar and Mill build tool. This is also generated by GPT 5 with a prompt tailored from my instructions and reviewed by me.

---

Short answer: given what you already do (C#, TypeScript, Rust, React, .NET/Express/Axum), I’d seriously pick Scala 3 as your “functional programming language,” not Haskell/Elm/PureScript, and lean on the modern FP ecosystem on top of it.

You get:

• Pure FP when you want it (Cats Effect / ZIO / Kyo).
• A “real” industrial ecosystem for web APIs, CLIs, and UIs.

arturaz

#!/bin/bash

# --- Parallel Rate Limit Tester (v11 - Preserve Exit Status) ---
# This version preserves the final progress line on exit, ensuring full
# context is available for failures or user-initiated aborts (Ctrl+C).

# --- Usage ---
# ./rate_limit_tester.sh <URL> [parallel_requests] [max_requests] [min_delay_ms]

# --- Dependencies ---

arturaz

Okay, let's trace the history of tech hype cycles, keeping in mind that while the term "Hype Cycle" was popularized by Gartner in 1995, the underlying pattern of excitement, disillusionment, and eventual productivity has existed for much longer.

Understanding the Gartner Hype Cycle Model (Briefly)

Before diving into history, it's helpful to remember the typical stages Gartner defined:

1. Technology Trigger: A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest emerge.
2. Peak of Inflated Expectations: Early publicity produces success stories—often accompanied by scores of failures. Much enthusiasm and unrealistic projections. Investment pours in.
3. Trough of Disillusionment: Interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters.
4. Slope of Enlightenment: More

arturaz

Okay, let's break down why this happens in Scala 3 (and largely in Scala 2 as well). The core reason lies in the distinction between name resolution and overloading resolution.

1. Name Resolution First: When the compiler encounters a name like normalMeth, its first job is to figure out what that name refers to in the current scope. It looks at:

   • Local definitions
   • Members of the enclosing class/object/trait
   • Inherited members
   • Imported names

2. Imports Bring Names:

• import A.* brings the name normalMeth (which refers specifically to the method A.normalMeth) into the current scope.

arturaz

package app.utils

import app.data.{AppPushNotificationsState, PushNotificationData}
import cats.Applicative
import com.raquo.airstream.state.StrictSignal
import framework.utils.JSLogger
import retry.syntax.*
import retry.{HandlerDecision, RetryPolicies}
import typings.tauriAppsApi as tauri
import typings.tauriAppsPluginProcess.tauriAppsPluginProcessRequire

arturaz

/*
 * Decompiled with CFR 0.151.
 */
package cats.effect.resource_shared_memoized;

import cats.effect.kernel.Resource;
import java.io.Serializable;
import scala.Function0;
import scala.Function1;
import scala.None$;

arturaz

#!/usr/bin/env ruby
# Run this file to generate `.kamal/secrets`.

# List of secrets to generate
# Either:
#   - String: the secret name
#   - Array: [secret_name, note_id]
secrets = [
  ["RAPIDRX_POSTGRESQL_PASSWORD", "RAPIDRX_DEV_POSTGRESQL_PASSWORD"],
  "RAPIDRX_KAMAL_REGISTRY_PASSWORD"

arturaz

package app.prelude.utils

import neotype.Newtype
import io.scalaland.chimney.PartialTransformer
import alleycats.Empty
import app.prelude.Prelude.upickle_
import io.scalaland.chimney.partial.Result.Errors
import io.scalaland.chimney.Transformer

arturaz

package app.webclient_prelude.utils

import com.raquo.airstream.core.Signal
import com.raquo.airstream.split.SplittableSignal
import com.raquo.airstream.state.Var

/** Like [[Var.zoom]] but is not required to have an [[com.raquo.airstream.ownership.Owner]]. */
trait UpdatableSignal[A] { self =>

  /** The [[Signal]] which is most likely mapped from a [[Var]]. */