Nicole White nicolewhite

Getting Started with NPM (as a developer)

As easy as 1, 2, 3!

Updated:

Aug, 08, 2022 update config docs for npm 8+
Jul 27, 2021 add private scopes
Jul 22, 2021 add dist tags
Jun 20, 2021 update for --access=public
Sep 07, 2020 update docs for npm version

Handlebars.js is a template framework for Javascript environments. It allows the construction of HTML elements using HTML and expressions wrapped in {{ }}

Limitations of {{if}}

One of the conditional block helpers Handlebars offers is the {{#if}}.

For example:

<div class="entry">

Github Events Analysis with Neo4j

On July 22, Github announced the 3rd Annual Github Data Challenge presenting multiple sources of data available.

This sounded to me a good opportunity to use their available data and import it in Neo4j in order to have a lot of fun at analyzing the data that fits naturally in a graph.

As I work mainly offline or behind military proxies that do not permit me to use the ReST API, I decided to go for the Github Archive available here, you can then download json files representing Github Events on a daily/hour basis.

If you are like me you find yourself cloning a repo, making some proposed changes and then deciding to later contributing back using the GitHub Flow convention. Below is a set of instructions I've developed for myself on how to deal with this scenario and an explanation of why it matters based on jagregory's gist.

To follow GitHub flow you should really have created a fork initially as a public representation of the forked repository and the clone that instead. My understanding is that the typical setup would have your local repository pointing to your fork as origin and the original forked repository as upstream so that you can use these keywords in other git commands.

Clone some repo (you've probably already done this step)
```
git clone [email protected]
```

	"Plot a PNG using matplotlib in a web request, using Flask."

	# Install dependencies, preferably in a virtualenv:
	#
	# pip install flask matplotlib
	#
	# Run the development server:
	#
	# python app.py
	#

	#!/usr/bin/Rscript
	library(tools)
	library(knitr)
	library(sowsear)
	opts_knit$set(progress = FALSE, verbose = FALSE)

	## We need a list of files and a package to start.
	args <- commandArgs(TRUE)
	package <- args[[1]]
	files <- args[-1]

	library(png)
	library(RCurl)
	#I got these free png silhouettes of red fox and rabbit from phylopic.org
	foxurl<-"http://phylopic.org/assets/images/submissions/51b1b6e4-129d-41a6-bbbd-c3fab459c25f.1024.png"
	raburl<-"http://phylopic.org/assets/images/submissions/1e15411c-5394-4a9d-a209-76c8ac0c331d.1024.png"
	fox_logo <- readPNG(getURLContent(foxurl))
	rab_logo <- readPNG(getURLContent(raburl))

	#utility function for embedding png images at specified fractional sizes in R plots
	#places the logo centred on a specified fraction of the the usr space,

	# How to run Neo4j GraphGists locally?

	git clone https://github.com/neo4j-contrib/rabbithole
	cd rabbithole
	mvn clean test-compile
	mvn exec:java&

	sleep 20

	# GraphGists only run in your browser, so in your asciidoc-file use the attribute at the top :neo4j-version: local

	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.
	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data
	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	- created cats/ and dogs/ subfolders inside train/ and validation/
	- put the cat pictures index 0-999 in data/train/cats