vgrichina

#!/bin/bash
# git-interactive-merge
# Taken from: http://www.angrylibertarian.com/node/53
from=$1
to=$2

if [[ ( -z $from ) || ( -z $to ) ]]; then
    echo "Usage:"
    echo "  git-interactive-merge <from-branch> <to-branch>"
    exit 1

mxcl

#!/bin/sh
# Just copy and paste the lines below (all at once, it won't work line by line!)
# MAKE SURE YOU ARE HAPPY WITH WHAT IT DOES FIRST! THERE IS NO WARRANTY!

function abort {
  echo "$1"
  exit 1
}

set -e

jjdelc

[
    {
        "hex": "#EFDECD", 
        "name": "Almond", 
        "rgb": "(239, 222, 205)"
    }, 
    {
        "hex": "#CD9575", 
        "name": "Antique Brass", 
        "rgb": "(205, 149, 117)"

sarim

#!/bin/sh

function print_bar {
    GDONE=$1
    GPROG='['
    for i in $(seq 1 1 $GDONE)
    do
       GPROG=$GPROG'#'
    done

kevin-smets

Default

Powerlevel10k

fappel

import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;

@Retention( RetentionPolicy.RUNTIME )
@Target( {
  java.lang.annotation.ElementType.METHOD
} )
public @interface Repeat {
  public abstract int times();

rarylson

-- AppleScript to create a new file in Finder
--
-- Use it in Automator, with the following configuration:
-- - Service receives: no input
-- - In: Finder.app
--
-- References:
--  - http://apple.stackexchange.com/a/129702
--  - http://stackoverflow.com/a/6125252/2530295
--  - http://www.russellbeattie.com/blog/fun-with-the-os-x-finder-and-applescript

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

conormm

R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs:

nzw0301

*2vec papers

1. act2vec, trace2vec, log2vec, model2vec https://link.springer.com/chapter/10.1007/978-3-319-98648-7_18
2. apk2vec https://arxiv.org/abs/1809.05693
3. app2vec http://paul.rutgers.edu/~qma/research/ma_app2vec.pdf
4. ast2vec https://arxiv.org/abs/2103.11614
5. attribute2vec https://arxiv.org/abs/2004.01375
6. author2vec http://dl.acm.org/citation.cfm?id=2889382
7. baller2vec https://arxiv.org/abs/2102.03291
8. bb2vec https://arxiv.org/abs/1809.09621