| /* ==UserStyle== | |
| @name www.youtube.com | |
| @namespace github.com/openstyles/stylus | |
| @version 1.0.0 | |
| @description A new userstyle | |
| @author noghartt | |
| ==/UserStyle== */ | |
| @-moz-document url-prefix("https://www.youtube.com/") { | |
| /* Remove all references to Shorts. */ |
Locate the section for your github remote in the .git/config file. It looks like this:
[remote "origin"]
fetch = +refs/heads/*:refs/remotes/origin/*
url = git@github.com:joyent/node.git
Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this:
| ast.exe: ast.c | |
| gcc -Werror -Wswitch -Wimplicit-fallthrough ast.c -o ast.exe | |
| clean: | |
| rm -f *.o *.exe *.s a.out | |
| test.s: ast.exe | |
| ./ast.exe > test.s |
| impl<V: Value> core::str::FromStr for NonNormalizingDec<V> { | |
| type Err = &'static str; | |
| #[inline(never)] | |
| #[rustfmt::skip] | |
| fn from_str(s: &str) -> Result<Self, Self::Err> { | |
| /// Converts an ASCII decimal digit to an int. | |
| /// | |
| /// In release builds, no range checks are performed and passing a | |
| /// non-digit character will result is undefined (yet safe) behavior. |
A list of links containing cool references, resources and things related to books about Computer Science and related.
| {-# OPTIONS --copatterns #-} | |
| module UntypedLambda where | |
| open import Size | |
| open import Function | |
| mutual | |
| data Delay (A : Set) (i : Size) : Set where |
ported from https://hub.darcs.net/dolio/agda-share/browse/PHOASNorm.agda
JS
const Lam = bod => lam => app => vah => lam(bod);
const App = fun => arg => lam => app => vah => app(fun)(arg);
const Var = exp => lam => app => vah => vah(exp);
const nz = v => nz => ns => nz(v);
Today, John Tromp - creator of the Binary λ-Calculus, and one of the smartest functional wizards alive - ported his famous prime number generator (first published 12 years ago!) to HVM:
I've recently been amazed, if not mind-blown, by how a very simple, "one-line" SAT solver on Interaction Nets can outperform brute-force by orders of magnitude by exploiting "superposed booleans" and optimal evaluation of λ-expressions. In this brief note, I'll provide some background for you to understand how this works, and then I'll present a simple code you can run in your own computer to observe and replicate this effect. Note this is a new observation, so I know little about how this algorithm behaves asymptotically, but I find it quite