All the ways that NULL can cause chaos in your SQL outcomes.

100% Human Authored - Both Code/Doc

In this series,

We build a production-ready containerized RESTful API server application using following packages and tools.

1. Go Standard Library net/http: The most idiomatic way to write web API applications in Go.
2. Chi: The most idiomatic router with middleware and route groups support.
3. Zerolog: Zero Allocation JSON Logger and Faster than slog.
4. Goose: The database migration CLI builder library with lease dependency.
5. Gorm CLI: Generate Go generics-based, type safe, repository functions with no runtime wrappers.
6. Swag and Validator v10: The most prominent OpenAPI specification generator and validation library in Go.

Codebase: https://github.com/learning-cloud-native-go/myapp (1000+ GitHub stars- Since 2019) \ Doc: https://learning-cloud-native-go.github.io/docs/building-a-containerized-restful-api/

If anybody wanna check Rust implementation: https://learning-rust.github.io/labs/building-a-containerized-restful-api/

Cats-Actors is a Cats Effect native actor library: typed messages, functional state, supervision, and the familiar ! operator, all in F[_].

What is new in this release:

- ControlledTestKit, a new trait in the cats-actors-testkit module. It

provisions an ActorSystem[IO] inside Cats Effect's TestControl and ticks the

simulated clock for you, so scheduled work and timeouts resolve without real

waiting. A one hour receive timeout is now an ordinary unit test that finishes

in milliseconds.

- Receive timeouts, the supervisor restart window and the dead letter mailbox

idle check now read Clock[F].monotonic instead of System.currentTimeMillis, so

they all honour simulated time.

- New TestKit assertions, expectMsgTypeCountN and expectMsgTypeSingle, which

count messages of a type and do not depend on when they arrive relative to

the call.

- Breaking: ActorSystem.uptime is now F[Long] rather than Long.

Scala 2.13 and 3, on JVM, Scala.js and Scala Native.

```

resolvers += "jitpack" at "https://jitpack.io"

libraryDependencies += "com.github.cloudmark.cats-actors" %%% "cats-actors" % "2.2.0"

libraryDependencies += "com.github.cloudmark.cats-actors" %%% "cats-actors-testkit" % "2.2.0" % Test

```

Write up: https://cloudmark.github.io/Cats-Actors-Controlling-Time/

Repo: https://github.com/cloudmark/cats-actors

Feedback and issues welcome.

HashMaps are incredibly convenient, but treating them like a magical black box can make it easy to overlook where their performance comes from.

In this article, I explain how HashMaps work using a simple implementation in Rust. I go through hash collisions and linear probing, why primary clustering hurts performance, load factors, resizing, and more.

The implementation is intentionally simplified, but it gives a good picture of what's actually happening underneath a HashMap.

Let me know your thoughts or any feedback you have!

All writing, illustrations, and code are my own. AI was used to clean up wording and catch grammatical mistakes.