Get a notification when your R code is done executing

These days we can use R for almost anything, be it a simple function, a complex algorithm, or anything that comes to mind. Usually, what we want R to do happens very quickly, and we don't even have to wait for it to finish.

Long-running R tasks are a problem

However, sometimes you are writing a R code, process, or job that may take a long time to run. For example, you may decide to crawl a website or run a long-running parsing algorithm.

I'm sure almost every developer has, at some point, written a R code that takes a long time to run. They then had to continuously check the task, wait for it to finish running, and ensure the R code was working as expected. As you can see, this gets tedious very quickly and wastes time and effort.

Push notifications fix this problem

One common way to solve this is to track the status of our R code and send a push notification when the code is done running or when it fails. By doing so, we can leave and forget about the long-running R code and focus on the important things we need to do, and by the time something happens, we will instantly get a push notification to let us know.

To do so, we can use LogSnag to track the status of our R code. LogSnag is a simple, easy-to-use, robust event tracking and notification system that lets you track your R code and send push notifications when something happens.

Let's walk you through setting up and using LogSnag to track the status of our R code.

Setting up LogSnag

Sign up for a free LogSnag account.
Create your first project from the dashboard.
Head to settings and copy your API token.

R code snippets

Now that we have our account and project setup, we can copy the following code snippet, update the values with your information, and paste it into your code.

Using R with httr

library(httr)

headers = c(
  'Content-Type' = 'application/json',
  'Authorization' = 'Bearer YOUR_API_TOKEN'
)

body = '{
  "project": "my-project",
  "channel": "crawler",
  "event": "Crawling is complete",
  "description": "Successfully crawled 1,230 pages.",
  "icon": "🔥",
  "notify": true
}';

res <- VERB("POST", url = "https://api.logsnag.com/v1/log", body = body, add_headers(headers))

cat(content(res, 'text'))

Using R with RCurl

library(RCurl)
headers = c(
  "Content-Type" = "application/json",
  "Authorization" = "Bearer YOUR_API_TOKEN"
)
params = "{
  \"project\": \"my-project\",
  \"channel\": \"crawler\",
  \"event\": \"Crawling is complete\",
  \"description\": \"Successfully crawled 1,230 pages.\",
  \"icon\": \"🔥\",
  \"notify\": true
}"
res <- postForm("https://api.logsnag.com/v1/log", .opts=list(postfields = params, httpheader = headers, followlocation = TRUE), style = "httppost")
cat(res)

R integration details

LogSnag provides several other features that can be used to simplify your job as a developer. For example, suppose you're working with a team. In that case, you can also add the rest of your team to your LogSnag project and allow them to see the status of your R code and receive push notifications when something important happens.

LogSang also keeps track of your previous events, so you can see what has happened in the past and search through previous events. We found this to be very powerful when we are working on larger projects and need to see what has happened in the past.

In addition, LogSnag allows you to create simple dashboards, charts, and graphs that give you more insight into your code and the events you track.

Other use-cases for LogSnag

View all common use-cases with R