- Author: Thomas Girke
- Last update: 18-Nov-2020
library(data.table) | |
?`[.data.table` | |
DT <- data.table(x=rep(c("b","a","c"),each=3), y=c(1,3,6), v=1:9) | |
X <- data.table(x=c("c","b"), v=8:7, foo=c(4,2)) | |
colnames(DT) | |
# [1] "x" "y" "v" |
## Empty list -- just use the empty environment for this. | |
nil <- function() { | |
emptyenv() | |
} | |
## Test if a list is the empty list: | |
is_empty <- function(lis) { | |
identical(lis, nil()) | |
} |
# create gh-pages branch | |
git checkout --orphan gh-pages | |
git rm -rf . | |
touch README.md | |
git add README.md | |
git commit -m 'initial gh-pages commit' | |
git push origin gh-pages | |
# add gh-pages as submodule | |
git checkout master |
--- | |
title: "twee demo" | |
author: "Jenny Bryan" | |
date: "17 August, 2014" | |
output: | |
html_document: | |
toc: TRUE | |
keep_md: TRUE | |
--- |
Whether you're trying to give back to the open source community or collaborating on your own projects, knowing how to properly fork and generate pull requests is essential. Unfortunately, it's quite easy to make mistakes or not know what you should do when you're initially learning the process. I know that I certainly had considerable initial trouble with it, and I found a lot of the information on GitHub and around the internet to be rather piecemeal and incomplete - part of the process described here, another there, common hangups in a different place, and so on.
In an attempt to coallate this information for myself and others, this short tutorial is what I've found to be fairly standard procedure for creating a fork, doing your work, issuing a pull request, and merging that pull request back into the original project.
Just head over to the GitHub page and click the "Fork" button. It's just that simple. Once you've done that, you can use your favorite git client to clone your repo or j
There are many Git workflows out there, I heavily suggest also reading the atlassian.com [Git Workflow][article] article as there is more detail then presented here.
The two prevailing workflows are [Gitflow][gitflow] and [feature branches][feature]. IMHO, being more of a subscriber to continuous integration, I feel that the feature branch workflow is better suited.
When using Bash in the command line, it leaves a bit to be desired when it comes to awareness of state. I would suggest following these instructions on [setting up GIT Bash autocompletion][git-auto].
When working with a centralized workflow the concepts are simple, master
represented the official history and is always deployable. With each now scope of work, aka feature, the developer is to create a new branch. For clarity, make sure to use descriptive names like transaction-fail-message
or github-oauth
for your branches.