I was working on a logger that writes metrics every time a warning or an error is logged. I tried to provide additional metric tags depending on the log annotations. And it didn't work. I was adding an annotation and I could see its value somewhere deep in the stack trace but the annotations value was empty.
Turned out that ZIO has two log annotation mechanisms that work in parallel.
This post is a confession about multiple overlapping mistakes we made when trying to measure API request times. These errors went unnoticed for months because wrong statistics still look realistic. Hopefully, this post will help you avoid such fails.
Problem: Imagine a sequence 1504170715041707*n mod 4503599627370517 where n is an integer increasing from 1. Find the subsequence of this sequence where every next element is smaller than the previous one.
All the solutions I've read about include brute force calculations. I found a better one, and I can't stop myself from posting it.
This is the last part of my learnings during writing a sudoku solver. It's about several iterations of a property-based test refactoring in an attempt to find the best way to generate input data.
I keep writing about my learnings during writing a sudoku solver. This time we touch solver's logic and I have something to share about making the big functions out of the small ones.
Sometimes you're trying to solve a puzzle so hard so you have to write a program to solve it. That happened to me with one specific sudoku so I wrote a sudoku solver.
I did some learning during this and I want to share them here. This part is about injecting validation into the type system.
I'm currently learning functional programming with scala and as a practice I've implemented FizzBuzz. To be honest, I made three different implementations of FizzBuzz but only the third one is good.
Stream.from(1) # Create infinite lazy stream from 1
.map { (_, "") } # convert it to (number, word) tuple
.map { x => if (x._1 % 3 == 0) (x._1, x._2 + "Fizz") else x } # Add "Fizz" to each 3rd word
.map { x => if (x._1 % 5 == 0) (x._1, x._2 + "Buzz") else x } # Add "Buzz" to each 5th word
.map { x => if (x._2 != "") x._2 else x._1.toString } # Take word or number
.take(30) # Limit stream length
.foreach(println) # Run everything and print results
It's even much better than usual imperative implementation and here's why.