knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" )
To-do list apps can be great on the go, with nifty UIs, APIs and hooks into all kinds of services.
I couldn't find a wrapper for "Remember the Milk" in R, so here's my attempt at that, to allow the level of automation and statistical geekery to which R users are accustomed.
Start with the basics, creating tasks, but with an R twist: vectorize your add_tasks.
tasks <- c("watch lectures ^wed =\"2 hours\"", "do reading ^thu =\"2 hours\"", "do problem set ^fri =\"4 hours\"", "review problem set ^sat =\"1 hour\"") rtm_add_task(paste(tasks, "*weekly #MyClass"))
Pick them randomly!
quick_tasks <- rtm_search("list:Household timeEstimate\"< 30 minutes\"") (todays_tasks <- sample(quick_tasks, 3)) ## add notes to one of them notes_add(todays_tasks[1,], note_title = "get this plunger model", note_text = "XT-9000D... it has super suction power!") ## then complete them when done complete(todays_tasks)
Move tasks around, postpone them, using R functions.
inbox <- rtm_search("list:Inbox") rule_fun <- function(task) { if(grepl("narf", task[["name"]])) postpone(task) else if (grepl("zort", task[["name"]])) moveTo(task, "ImportantResearch") else if (grepl("poit", task[["name"]])) setTags(task, "#chainletter #plan") } ## note: needs to be split by "task.id" b/c "id" and "name" ## might not be unique plyr::d_ply(inbox, "task.id", rule_fun, .progress = "text")
ggplot2? DiagrammeR? Shiny?
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