144.96
package main
import "fmt"
func main() {
var x float32 = 144.96
var y float64 = 144.96
# ----------------------------------------------------------------------------- | |
# AI-powered Git Commit Function | |
# Copy paste this gist into your ~/.bashrc or ~/.zshrc to gain the `gcm` command. It: | |
# 1) gets the current staged changed diff | |
# 2) sends them to an LLM to write the git commit message | |
# 3) allows you to easily accept, edit, regenerate, cancel | |
# But - just read and edit the code however you like | |
# the `llm` CLI util is awesome, can get it here: https://llm.datasette.io/en/stable/ | |
gcm() { |
144.96
package main
import "fmt"
func main() {
var x float32 = 144.96
var y float64 = 144.96
// by dave | |
float[][] result; | |
float t, c; | |
float ease(float p) { | |
p = c01(p); | |
return 3*p*p - 2*p*p*p; | |
} | |
float ease(float p, float g) { |
A friend recently learned about Proebsting's law and mentioned it to me off hand. I knew about the law's existence but I never really asked myself - do I believe in it?
For people who aren't aware, Proebsting's law states:
Compiler Advances Double Computing Power Every 18 Years
Which is to say, if you upgrade your compiler every 18 years, you would expect on average your code to double in performance on the same hardware.
package main | |
import ( | |
"context" | |
"encoding/base64" | |
"flag" | |
"fmt" | |
"log" | |
container "google.golang.org/api/container/v1beta1" |
class E(BaseException): | |
def __new__(cls, *args, **kwargs): | |
return cls | |
def a(): yield | |
a().throw(E) |
package main | |
import "fmt" | |
// number of desired workers | |
const nWorkers = 10 | |
func main() { | |
// make a buffered channel with the space for my 10 workers | |
workerChan := make(chan *worker, nWorkers) |
Ever wanted to delete all your likes/favorites from Twitter but only found broken/expensive tools? You are in the right place.
setInterval(() => {
for (const d of document.querySelectorAll('div[data-testid="unlike"]')) {
d.click()
}
### JHW 2018 | |
import numpy as np | |
import umap | |
# This code from the excellent module at: | |
# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module | |
import random |
# source:http://geocities.com/SiliconValley/heights/7052/opcode.txt | |
From: mark@omnifest.uwm.edu (Mark Hopkins) | |
Newsgroups: alt.lang.asm | |
Subject: A Summary of the 80486 Opcodes and Instructions | |
(1) The 80x86 is an Octal Machine | |
This is a follow-up and revision of an article posted in alt.lang.asm on | |
7-5-92 concerning the 80x86 instruction encoding. | |
The only proper way to understand 80x86 coding is to realize that ALL 80x86 |