Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discuss around concrete examples, not hand-waving abstractions. Don't say you did something, provide a URL that proves it.
Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.
| library(shiny) | |
| library(datasets) | |
| Logged = FALSE; | |
| PASSWORD <- data.frame(Brukernavn = "withr", Passord = "25d55ad283aa400af464c76d713c07ad") | |
| # Define server logic required to summarize and view the selected dataset | |
| shinyServer(function(input, output) { | |
| source("www/Login.R", local = TRUE) | |
| observe({ | |
| if (USER$Logged == TRUE) { |
| #' Email a user a report is ready | |
| #' | |
| #' Requires an account at Mailgun: https://mailgun.com | |
| #' Pre-verification can only send to a whitelist of emails you configure | |
| #' | |
| #' @param email Email to send to | |
| #' @param mail_message Any extra info | |
| #' | |
| #' @return TRUE if successful email sent | |
| #' @import httr |
| Okay so here's the setup: | |
| [-] The primary server API is exposed via Flask (Python) and all static files, including all html, css, js is served by nginx. | |
| [-] Python is exposing an API at url http://domain.com/api/download/<file_id>, where file_id is a database id for the file that we're interested in downloading. | |
| 1. User wants to download a file, so we spawn a new window with the url '/api/download/<file_id>' | |
| 2. Nginx intercepts the request, sees that it starts with /api/, and then forwards the request to Flask, which is being served on port 5000. | |
| 3. Flask routes the request to its download method, retrieves the pertinent data from the file_id, and constructs additional header settings to make nginx happy and to force the browser to see the file stream as a download request instead of the browser just trying to open the file in a new window. Flask then returns the modified header stream to nginx | |
| 4. Nginx is finally ready to do some work. While parsing the headers for the incoming request, it encounters "X |
Title: Project Title Author: First Last Email: Email@Example.com Address: 1234 Street, City, State 12345 Phone: (XXX)XXX-XXXX Affiliation: www.LaCroixDesign.net Copyright: 2015 Company Name Keywords: Proposal, Web Design Date: March 13, 2015
| import simplejson as json | |
| import requests | |
| #your spreadsheet key here. I'm using an example from the Victorian election campaign | |
| key = "1THJ6MgfEk-1egiPFeDuvs4qEi02xTpz4fq9RtO7GijQ" | |
| #google api request urls - I'm doing the first one just to get nice key values (there's probably a better way to do this) | |
| url1 = "https://spreadsheets.google.com/feeds/cells/" + key + "/od6/public/values?alt=json" |
| <script language="JavaScript" type="text/javascript"> | |
| // Comcast Cable Communications, LLC Proprietary. Copyright 2012. | |
| // Intended use is to display browser notifications for critical and time sensitive alerts. | |
| var SYS_URL='/e8f6b078-0f35-11de-85c5-efc5ef23aa1f/aupm/notify.do'; | |
| // var image_url='http://servicealerts.comcast.net:8080/images/mt'; | |
| var image_url='http://xfinity.comcast.net/constantguard/BotAssistance/notice/images'; | |
| var headertext1='<strong>Comcast Courtesy Notice</strong>'; | |
| var textline1='You have reached 90% of your <b>monthly data usage allowance</b>.'; | |
| var textline2='Please sign in for more information and to remove this alert.'; | |
| var acknowledgebutton='<a href=\"#\" onClick="document.location.href=\''+SYS_URL+'?dispatch=redirect&redirectName=login¶mName=bmUid\'" title="Sign in to acknowledge" style="color: #FFFFFF;"><img alt="Sign in to acknowledge" src="'+image_url+'/mt_signin.png"/></a>'; |
Tested on a standard $5/mo DigitalOcean VPS running Ubuntu 16.04.
| This post examines the features of [R Markdown](http://www.rstudio.org/docs/authoring/using_markdown) | |
| using [knitr](http://yihui.name/knitr/) in Rstudio 0.96. | |
| This combination of tools provides an exciting improvement in usability for | |
| [reproducible analysis](http://stats.stackexchange.com/a/15006/183). | |
| Specifically, this post | |
| (1) discusses getting started with R Markdown and `knitr` in Rstudio 0.96; | |
| (2) provides a basic example of producing console output and plots using R Markdown; | |
| (3) highlights several code chunk options such as caching and controlling how input and output is displayed; | |
| (4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and | |
| (5) discusses the implications of R Markdown. |
