Setup the server:
iperf -s
import React from 'react'; | |
import { Router as BaseRouter } from 'react-router'; | |
import { getParamNames, formatPattern } from 'react-router/lib/PatternUtils'; | |
import { createRoutes } from 'react-router/lib/RouteUtils' | |
import createBrowserHistory from 'history/lib/createBrowserHistory'; | |
import useBeforeUnload from 'history/lib/useBeforeUnload'; | |
import invariant from 'app/utils/invariant'; | |
import { each, pick, omit, sortBy } from 'lodash'; | |
const EMPTY_AREA = '@@none'; |
Recent improvements to the ClojureScript compiler have greatly simplified setting up development versus production outputs.
This example uses Figwheel as something that you want to exclude for production, but the pattern is general.
With this simple setup you only need one html file/view and it will work for developement and production.
16 января прошла встреча питерских функциональных программистов. На этой встрече собрались три сообщества:
Под зонтиком мета-сообщества piter-united.
Rich Hickey • 3 years ago
Sorry, I have to disagree with the entire premise here.
A wide variety of experiences might lead to well-roundedness, but not to greatness, nor even goodness. By constantly switching from one thing to another you are always reaching above your comfort zone, yes, but doing so by resetting your skill and knowledge level to zero.
Mastery comes from a combination of at least several of the following:
var React = require('react/addons'); | |
var ReactIgnore = { | |
displayName: 'ReactIgnore', | |
shouldComponentUpdate (){ | |
return false; | |
}, | |
render (){ | |
return React.Children.only(this.props.children); | |
} |
... or Why Pipelining Is Not That Easy
Golang Concurrency Patterns for brave and smart.
By @kachayev
In this tutorial, we'll take an in-depth view of what's happening when you execute a simple Onyx program. All of the code can be found in the Onyx Starter repository if you'd like to follow along. The code uses the development environment with HornetQ and ZooKeeper running in memory, so you don't need additional dependencies to run the example for yourself on your machine.
At the core of the program is the workflow - the flow of data that we ingest, apply transformations to, and send to an output for storage. In this program, we're going to ingest some sentences from an input source, split the sentence into individual words, play with capitalization, and add a suffix. Finally, we'll send the transformed data to an output source.
Let's examine the workflow pictorially:
Let's use Terraform to easily get a CoreOS cluster up on Digital Ocean. In this example we will get a 5 node CoreOS cluster up and running on the Digital Ocean 8GB size.
Grab a copy of Terraform for your platform from http://www.terraform.io/downloads.html. Follow the instructions at http://www.terraform.io/intro/getting-started/install.html by getting Terraform in your PATH
and testing that it works.