Christophe Dervieux cderv

Gerrit vs Github: for code review and codebase management

Sure, Github wins on the UI. Hands down. But, despite my initial annoyance with Gerrit when I first started using it almost a year ago, I am now a convert. Fully. Let me tell you why.

Note: This is an opinionated (on purpose) piece. I assume your preferences are like mine on certain ideas, such as:

Fast-forward submits to the target branch are better than allowing merge commits to the target branch. The reason I personally prefer this is that, even if a non-conflicting merge to the target branch is possible, the fact that the review/pull request is not up to date with the latest on the target branch means feature branch test suite runs in the CI pipeline reporting on the review/PR may not be accurate. Another minor point is that forced merge commits are annoying as fuck (opinion) and clutter up Git log histories unnecessarily and I prefer clean histories.
Atomic/related changes all in one commit is something worth striving for. Having your dev

If you were to give recommendations to your "little brother/sister" on things that they need to do to become a data scientist, what would those things be?

I think the "Data Science Venn Diagram" (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram) is a great place to start. You need three things to be a good data scientist:

Statistical knowledge
Programming/hacking skills
Domain expertise

Statistical knowledge

Converting a Word Document to Markdown in One Move

The Problem

A lot of important government documents are created and saved in Microsoft Word (*.docx). But Microsoft Word is a proprietary format, and it's not really useful for presenting documents on the web. So, I wanted to find a way to convert a .docx file into markdown.

Installing Pandoc

On a mac you can use homebrew by running the command brew install pandoc.

The Solution

Dplyr is a well known R package to work on structured data, either in memory or in DB and, more recently, in cluster. The in memory implementations have in general capabilities that are not found in the others, so the notion of backend is used with a bit of a poetic license. Even the different DB and cluster backends differ in subtle ways. But it sure is better than writing SQL directly! Here I provide a list of backends with links to the packages that implement them when necessary. I've done my best to provide links to active projects, but I am not endorsing any of them. Do your own testing. Enjoy and please contribute any corrections or additions, in the comments.

Backend	Package
data.frame	builtin
data.table	builtin
arrays	builtin
SQLite	builtin
PostgreSQL/Redshift	builtin

Configure Git to use a proxy

In Brief

You may need to configure a proxy server if you're having trouble cloning or fetching from a remote repository or getting an error like unable to access '...' Couldn't resolve host '...'.

Consider something like:

Markdown License badges

Collection of License badges for your Project's README file.
This list includes the most common open source and open data licenses.
Easily copy and paste the code under the badges into your Markdown files.

Notes

The badges do not fully replace the license informations for your projects, they are only emblems for the README, that the user can see the License at first glance.

Translations: (No guarantee that the translations are up-to-date)

🇫🇷 Cette liste en français

	## this snippet was the original gist but the Rmd solution below is even nicer

	## auto-generate a visual index as README.md in current working directory
	fig_files <- list.files(pattern = "jpg$") # change to png$ as needed!
	writeLines(paste0(fig_files, "\n",
	"![`", fig_files, "`](", fig_files, ")\n\n"), "README.md")

	#' ---
	#' output:
	#' html_document:
	#' keep_md: TRUE
	#' ---

	#+ include = FALSE
	library(dplyr)

	#' Responses to [my

	import __builtin__


	def fake_input(prompt):
	print prompt
	return "trgy"

	__builtin__.raw_input = fake_input

	name = raw_input("Enter your name >")

	# Installing TOR on mac: brew install tor
	# Run TOR on custom port: tor --SOCKSPort 9050

	# Check the 'origin' field in the response to verify TOR is working.
	library(httr)
	GET("https://httpbin.org/get", use_proxy("socks5://localhost:9050"))

	# Set proxy in curl
	library(curl)
	h <- new_handle(proxy = "socks5://localhost:9050")