terminal:
npm i --save-dev rollup rollup-watch rollup-plugin-typescript typescript typings
npm i -S react react-dom
./node_modules/.bin/typings install react react-dom --save
mkdir src dist
touch src/index.tsx| const bcrypt = require("bcrypt"); | |
| // use this library in case your version of node doesn't support Promise | |
| // const Promise = require("promise"); | |
| let password = "hello"; | |
| let stored_hash = ""; | |
| // first generate a random salt | |
| function genSalt(password) { | |
| return new Promise((resolve, reject) => { |
| // getComponent is a function that returns a promise for a component | |
| // It will not be called until the first mount | |
| function asyncComponent(getComponent) { | |
| return class AsyncComponent extends React.Component { | |
| static Component = null; | |
| state = { Component: AsyncComponent.Component }; | |
| componentWillMount() { | |
| if (!this.state.Component) { | |
| getComponent().then(Component => { |
terminal:
npm i --save-dev rollup rollup-watch rollup-plugin-typescript typescript typings
npm i -S react react-dom
./node_modules/.bin/typings install react react-dom --save
mkdir src dist
touch src/index.tsxThe dplyr package in R makes data wrangling significantly easier.
The beauty of dplyr is that, by design, the options available are limited.
Specifically, a set of key verbs form the core of the package.
Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe.
Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R.
The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).
dplyr is organised around six key verbs:
| #!/bin/bash | |
| # Usage: | |
| # $ le-aws-upload-cert.sh | |
| echo "Current list of certificates in AWS" | |
| echo "-----------------------------------" | |
| aws iam list-server-certificates | |
| echo | |
| read -p "Domain name: " domain_name |
Functionality behind the data sources, projects, workbooks, site users, and sites on a Tableau server.