Published on August 2, 2022

Get a notification when your R code is done executing

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

  1. Sign up for a free LogSnag account.
  2. Create your first project from the dashboard.
  3. 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

  1. Monitor your CI/CD build status for your R application
  2. Monitor your CPU usage in your R application
  3. Monitor when database goes down in your R application
  4. Monitor high disk usage in your R application
  5. Monitor when a user changes their email address in your R application
  6. Monitor failed logins in your R application
  7. Monitor failed payments for your R application
  8. Monitor memory usage in your R application
  9. Monitor MySQL downtime in your R application
  10. Monitor when a new feature is used in your R application
  11. Monitor your Postgres downtime in your R application
  12. Monitor Redis downtime in your R application
  13. Monitor suspicious activity in your R application
  14. Monitor when a user exceeds the usage limit for your R service
  15. Monitor when a user is being rate limited in your R application
  16. Send push notifications to your phone or desktop using R
  17. Track canceled subscriptions in your R application
  18. Track your R cron jobs
  19. Track when a file is uploaded to your R application
  20. Track when a form is submitted to your R application
  21. Track payment events via R
  22. Track user sign in events in R
  23. Track user signup events via R
  24. Track waitlist signup events via R
View all common use-cases with R