gilrosenthal

!pip install fastai
!apt-get -qq install -y libsm6 libxext6 && pip install -q -U opencv-python
import cv2
from os import path
from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag
platform = '{}{}-{}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag())

accelerator = 'cu80' if path.exists('/opt/bin/nvidia-smi') else 'cpu'

!pip install -q http://download.pytorch.org/whl/{accelerator}/torch-0.3.0.post4-{platform}-linux_x86_64.whl torchvision

nathanpeck

The information below was written in Oct 2017. In August 2019 AWS launched official support for multiple target groups per AWS ECS service. Please use that feature instead!

---

Unfortunately as of writing this (Oct 18, 2017) there is no built in integration for multiple target groups per AWS ECS service. Here are a few things you can try:

1. If your application just serves port 80 (HTTP) & port 443 (HTTPS) then you should consider using the application load balancer and terminating SSL at the load balancer. This will allow your application to function using just port 80.

dahlia

니름 스프린트 사전 준비

따라하다가 잘 되지 않을 때는 프로젝트 대화방에 오셔서 물어보시면 도와드립니다.

감 잡기

ptarjan

Scaling your API with rate limiters

The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.

In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.

Request rate limiter

This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.

manasthakur

Creating your own ag.vim

Vim provides built-in mechanisms to search through projects in the form of the grep command. However, on large projects, grep is known to be slow; and hence people have been switching to simpler searchers like ack, and faster, parallel (metal?) searchers like ag and pt. Correspondingly, several plugins have been created that integrate these tools in vim: ack.vim, ag.vim, etc.

However, it's actually very easy to get the functionalities these plugins provide (faster search, results in quickfix-window, jumps, previews, and so on) in vanilla Vim itself; in fact, Vim already populates the grep-search results in a quickfix window. We just need to tell Vim to do the following things (use-case: ag):

• Use ag as the default grep program
• Open quickfix window by default
• Create mappin

perhapsspy

Django에서 Test 쉽고 빠르게 하기

django 기본 테스트는 데이터베이스 마이그레이션 덕에 느리고 번거롭기 때문에 py.test와 model_mommy를 사용해서 빠르게 테스트를 하는 방법을 소개함.

• py.test : http://pytest.org/
• pytest-django : http://pytest-django.readthedocs.org/
• model_mommy : http://model-mommy.readthedocs.org/

테스트 파일 레이아웃

ruseel

AWS에서 docker를 쓸 때 high traffic server라면 이렇게 하는 것이 좋겠다. amazon linux를 쓴다고 하자.

ulimit

ulimit를 올려주어야 한다. /etc/security/limit.conf 에서 고쳐주어도 docker에는 적용되지 않는다. limit.conf는 PAM을 통해서 로그인했을 때만 먹는 설정이라 그렇다. docker로 띄운 process의 pid를 찾고 cat /proc/<pid>/limits를 실행해서 보면 적용되었는지 아닌지 확실하게 알 수 있다. kernel에서 직접 그 프로세스에 어떤 ulimit이 적용되었는지 확인하는 방법이다.

그래서 /etc/sysconfig/docker 파일을 만들고 아래를 추가한다.

radiatoryang

using UnityEngine;
using UnityEditor;
using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.IO;
using System.IO.Compression;
using Ionic.Zip; // this uses the Unity port of DotNetZip https://github.com/r2d2rigo/dotnetzip-for-unity

pixyj

#To get all sql queries sent by Django from py shell

import logging
l = logging.getLogger('django.db.backends')
l.setLevel(logging.DEBUG)
l.addHandler(logging.StreamHandler())


#For more info, http://stackoverflow.com/questions/971667/django-orm-how-to-view-or-log-the-executed-query