Look at LSB init scripts for more information.
Copy to /etc/init.d:
# replace "$YOUR_SERVICE_NAME" with your service's name (whenever it's not enough obvious)| ssh-keygen -y -f private_key1.pem > public_key1.pub |
Look at LSB init scripts for more information.
Copy to /etc/init.d:
# replace "$YOUR_SERVICE_NAME" with your service's name (whenever it's not enough obvious)| # -*- coding: utf-8 -*- | |
| from datetime import datetime | |
| import urllib2 | |
| def kb_balance(account, password, resident, username): | |
| """ | |
| 국민은행 계좌 잔액 빠른조회. 빠른조회 서비스에 등록이 되어있어야 사용 가능. | |
| 빠른조회 서비스: https://obank.kbstar.com/quics?page=C018920 |
| #!/bin/bash | |
| # 1st Install https://github.com/prasmussen/gdrive | |
| # then use this script in Alfred or from CLI when you want to screenshot then upload to your gdrive | |
| # then share the link to others from your paste board | |
| # (run gdrive one first time to authenticate with Google) | |
| screencapture -tjpg -i /tmp/temp_shot_gdrive.jpg | |
| DATEFILENAME=`date +"%Y%m%d%H%M"` | |
| # use -p id to upload to a specific folder |
| { | |
| "Version": "2012-10-17", | |
| "Id": "http referer policy example", | |
| "Statement": [ | |
| { | |
| "Sid": "Allow get requests referred by www.mysite.com and mysite.com", | |
| "Effect": "Allow", | |
| "Principal": "*", | |
| "Action": "s3:GetObject", | |
| "Resource": "arn:aws:s3:::examplebucket/*", |
A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)
| function findValues(obj, key){ | |
| return findValuesHelper(obj, key, []); | |
| } | |
| function findValuesHelper(obj, key, list) { | |
| if (!obj) return list; | |
| if (obj instanceof Array) { | |
| for (var i in obj) { | |
| list = list.concat(findValuesHelper(obj[i], key, [])); | |
| } |
글쓴이: 김정주(haje01@gmail.com)
이 문서는 텐서플로우 공식 페이지 내용을 바탕으로 만들어졌습니다.
텐서플로우(TensorFlow)는 기계 학습과 딥러닝을 위해 구글에서 만든 오픈소스 라이브러리입니다. 데이터 플로우 그래프(Data Flow Graph) 방식을 사용하였습니다.
| {0: 'tench, Tinca tinca', | |
| 1: 'goldfish, Carassius auratus', | |
| 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', | |
| 3: 'tiger shark, Galeocerdo cuvieri', | |
| 4: 'hammerhead, hammerhead shark', | |
| 5: 'electric ray, crampfish, numbfish, torpedo', | |
| 6: 'stingray', | |
| 7: 'cock', | |
| 8: 'hen', | |
| 9: 'ostrich, Struthio camelus', |
| """ | |
| Shows how to do a cross join (i.e. cartesian product) between two pandas DataFrames using an example on | |
| calculating the distances between origin and destination cities. | |
| Tested with pandas 0.17.1 and 0.18 on Python 3.4 and Python 3.5 | |
| Best run this with Spyder (see https://github.com/spyder-ide/spyder) | |
| Author: Markus Konrad <post@mkonrad.net> | |
| April 2016 |