wzed

<?php

/*
*  Using a key => value pair with the yield keyword is
*  the cleanest method I could find to add identifiers or tags
*  to asynchronous concurrent requests in Guzzle,
*  so you can identify which response is from which request!
*/

$client = new GuzzleHttp\Client(['base_uri' => 'http://httpbin.org']);

HomoEfficio

package homo.efficio.json.jackson.custom.serialization;

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.module.SimpleModule;
import homo.efficio.json.jackson.custom.serialization.domain.CellPhone;
import homo.efficio.json.jackson.custom.serialization.domain.FamilyMember;
import homo.efficio.json.jackson.custom.serialization.domain.MobileVendor;
import homo.efficio.json.jackson.custom.serialization.serializer.CellPhoneSerializer;
import homo.efficio.json.jackson.custom.serialization.serializer.FamilyMemberSerializer;

themsaid

trait HasEnums
{
    /**
     * The array of enumerators of a given group.
     *
     * @param null|string $group
     * @return array
     */
    static function enums($group = null)
    {

lesstif

#!/usr/bin/env bash

## Installation
## curl -o /usr/local/bin/serve-php.sh https://gist.githubusercontent.com/lesstif/82c107282241c7a52ad9/raw 
## chmod +x /usr/local/bin/serve-php.sh

SA="/etc/nginx/sites-available/"
SE="/etc/nginx/sites-enabled/"

test=0

appkr

Contract Killer

The popular open-source contract for web designers and developers by Stuff & Nonsense

• Originally published: 23rd December 2008
• Revised date: October 8th 2015
• Original post

---

cmaas

<?php

trait CastsValueObjects
{
    protected function castAttribute($key, $value)
    {
        $castToClass = $this->getValueObjectCastType($key);
        // no Value Object? simply pass this up to the parent
        if (!$castToClass) {
            return parent::castAttribute($key, $value);

haje01

텐서플로우 시작하기

글쓴이: 김정주(haje01@gmail.com)

이 문서는 텐서플로우 공식 페이지 내용을 바탕으로 만들어졌습니다.

---

소개

텐서플로우(TensorFlow)는 기계 학습과 딥러닝을 위해 구글에서 만든 오픈소스 라이브러리입니다. 데이터 플로우 그래프(Data Flow Graph) 방식을 사용하였습니다.

nkt

wrk -t4 -c400 -d10s http://127.0.0.1:1337/

PHP

Running 10s test @ http://127.0.0.1:1337/
  4 threads and 400 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
 Latency 7.02ms 6.94ms 82.86ms 85.27%

sheck

.highlight .hll { background-color: #ffffcc }
.highlight  { background: #151718; color: #d4d7d6; background-color: #151718 }
.highlight .c { color: #41535b; background-color: #151718 } /* Comment */
.highlight .err { color: #d4d7d6; background-color: #151718 } /* Error */
.highlight .esc { color: #d4d7d6; background-color: #151718 } /* Escape */
.highlight .g { color: #d4d7d6; background-color: #151718 } /* Generic */
.highlight .k { color: #9fca56; background-color: #151718 } /* Keyword */
.highlight .l { color: #d4d7d6; background-color: #151718 } /* Literal */
.highlight .n { color: #d4d7d6; background-color: #151718 } /* Name */
.highlight .o { color: #d4d7d6; background-color: #151718 } /* Operator */

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)