The easiest way to get a well rising bread is to use high-protein flour >=12g / 100g https://www.instagram.com/p/BiJhdU_gHkd
Kitchen temperature for reference is 23, but a hot kitchen will significantly speed up the process.
package graphPermissions | |
import java.util.UUID | |
import org.scalatest.prop.Checkers.check | |
import org.scalatest.prop.{Generator, PropertyChecks} | |
import org.scalatest.{FunSpec, Matchers} | |
import org.scalacheck.{Shrink, Prop => ScalaCheckProp} | |
import org.scalacheck.ScalacheckShapeless._ | |
import org.scalacheck.util.Pretty |
sealed trait Command | |
case class CreatePotato(sort: String) extends Command | |
case class CookPotato() extends Command | |
case class EatPotato() extends Command | |
object Command { | |
import cats.data.State |
The easiest way to get a well rising bread is to use high-protein flour >=12g / 100g https://www.instagram.com/p/BiJhdU_gHkd
Kitchen temperature for reference is 23, but a hot kitchen will significantly speed up the process.
Based on this question with some adjustments https://stackoverflow.com/questions/20220270/posting-multipart-form-data-with-apache-bench-ab
You'll need a text file post_data.txt
with the following contents:
from Wikipedia: "Ad hoc polymorphism is a dispatch mechanism: control moving through one named function is dispatched to various other functions without having to specify the exact function being called. Overloading allows multiple functions taking different types to be defined with the same name; the compiler or interpreter automatically ensures that the right function is called. This way, functions appending lists of integers, lists of strings, lists of real numbers, and so on could be written, and all be called append—and the right append function would be called based on the type of lists being appended. This differs from parametric polymorphism, in which the function would need to be written
How to run:
ghc fractal.hs
./fractal
TODO:
fibo 0 = 1 | |
fibo 1 = 1 | |
fibo k = memo_fibo (k - 1) + memo_fibo (k - 2) | |
memo_fibo :: Int -> Int | |
memo_fibo = ((map fibo [0..]) !! ) | |
-- memo_fibo k = ((map fibo [0..]) !! k) | |
-- this doesn't get memoized | |
-- https://stackoverflow.com/questions/11466284/how-is-this-fibonacci-function-memoized |
from sys import byteorder | |
from array import array | |
from struct import pack | |
import pyaudio | |
import wave | |
THRESHOLD = 5000 | |
CHUNK_SIZE = 4096 | |
FORMAT = pyaudio.paInt16 |
package tree.Tree | |
class Tree(rootValue: Int) { | |
class Node(var parent: Option[Node], var children: Set[Node], var data: Int) { | |
} | |
var root : Node = new Node(None, Set(), rootValue) | |
def addLeaf(parent: Node, data: Int): Node = { |
git describe --tags | |
#example: v0.0-237-g114b509 | |
# last tag - commits since last tag - g for github - hash of commit |