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Lightweight Wrapper to the ntfy.sh Service

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ntfy

ntfy (pronounce: notify) is a simple HTTP-based pub-sub notification service. It allows you to send notifications to your phone or desktop via scripts from any computer, entirely without signup, cost or setup. It’s also open source if you want to run your own. Visit ntfy.sh for more details.

{ntfy} is a lightweight R wrapper for this service. The magic sauce is just POST and GET calls equivalent to

curl -d "Process Complete 😀" ntfy.sh/yourSecretTopic 

but made to work nicely in an R workflow.

Installation

You can install the released version of {ntfy} from CRAN

install.packages("ntfy")

You can install the development version of {ntfy} from GitHub:

# install.packages("remotes")
remotes::install_github("jonocarroll/ntfy")

Functionality

Follow the instructions at ntfy.sh to install any of the mobile apps or use the web app. No sign-up or account is necessary.

Choose a topic (note: this isn’t a password-protected service, so choose something obscure) and subscribe to it on your device.

Add the topic as an environment variable, e.g.

usethis::edit_r_environ()

[...]

NTFY_TOPIC='yourSecretTopic'
#NTFY_SERVER='https://ntfy.sh'

The server will automatically be set to https://ntfy.sh unless you specify another.

This can be confirmed with

ntfy_server()
#> [1] "https://ntfy.sh"

With the package loaded, you can now send notifications which should appear on your device

library(ntfy)
ntfy_send("test from R!")
#> <httr2_response>
#> POST https://ntfy.sh/jonocarroll_ntfy_testing
#> Status: 200 OK
#> Content-Type: application/json
#> Body: In memory (152 bytes)

This can be used in many ways. One would be to notify the completion of a process. The ntfy_done() function sends a notification with the (default) body

Process completed at <Sys.time()>
slow_process <- function(x) {
  Sys.sleep(8) # sleep for 8 seconds
  x
}

mtcars |> 
  head() |> 
  slow_process() |> 
  ntfy_done()
#>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
#> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
#> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
#> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
#> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
#> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
#> Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

which results in a notification on subscribed devices

Process completed at 2023-07-04 17:00

When using the base R pipe |> the piped commands are composed together by the parser, so

f() |> 
  g() |> 
    h()

becomes

h(g(f()))

We can use this fact to time the running of a process if the last function (above, h()) is system.time(). The ntfy_done_with_timing() function does exactly this

mtcars |> 
  head() |> 
  slow_process() |> 
  ntfy_done_with_timing()
#>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
#> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
#> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
#> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
#> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
#> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
#> Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

which sends the notification

Process completed in 8.003s

Note: the {magrittr} pipe %>% works differently and does not compose the same way, so this will result in a very short time report. Wrapping an entire pipeline with ntfy_done_with_timing() will work, though

library(magrittr)
ntfy_done_with_timing(
  mtcars %>%
    head() %>% 
    slow_process()
)
#>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
#> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
#> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
#> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
#> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
#> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
#> Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

sends

Process completed in 8.004s

This service can also be used as a progress indicator via the {progressr} package - see help("handler_ntfy", package = "progressr") or https://progressr.futureverse.org/reference/handler_ntfy.html for more details.

If you’re using a topic on a server that requires authentication, you can pass auth = TRUE, along with a username and password:

ntfy_send(
  "test from R!", 
  auth = TRUE, 
  username = "example", 
  password = "super-secret-password"
)

Alternatively, you can set these as environment variables and they’ll get used by ntfy_send() automatically:

usethis::edit_r_environ()

[...]

NTFY_AUTH='TRUE'
NTFY_USERNAME='example'
NTFY_PASSWORD='super-secret-password'
ntfy_send("test from R!")

The history of the notifications sent can be retrieved as well, with control over how far back to search (example output shown)

ntfy_history(since = "1h")
#>             id       time   event           topic
#> 1 0oDpk4oisfNO 1667988383 message yourSecretTopic
#> 2 4Fcy9kIL0m6Z 1667988413 message yourSecretTopic
#> 3 AGXn4q0CirFT 1667990983 message yourSecretTopic
#>                                    message
#> 1                             test from R!
#> 2 Process completed at 2022-11-09 17:31:03
#> 3              Process completed in 8.003s

API

The full ntfy.sh API should be supported, including sending a title and tags

Images

Images can be sent within notifications by specifying as image either the filename or a ggplot2 object (which will be saved to a temporary file)

library(ggplot2)
#> 
#> Attaching package: 'ggplot2'
#> The following object is masked from 'package:base':
#> 
#>     is.element
p <- ggplot(mtcars, (aes(mpg, wt))) + 
  geom_point() + 
  geom_smooth() + 
  labs(title = "ggplot images in {ntfy}")
ntfy_send("ggplot2 images in notifications!", 
          tags = c("tada", "chart"),
          image = p)
#> Saving 7 x 5 in image
#> `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
#> <httr2_response>
#> 
#> POST https://ntfy.sh/jonocarroll_ntfy_testing
#> 
#> Status: 200 OK
#> 
#> Content-Type: application/json
#> 
#> Body: In memory (335 bytes)

Emoji

Supported tags (emoji) can be sent with the tags argument (one or more). These can be searched or shown with show_emoji() which will look for a given name in the compatible values, or search for it in the compatible metadata.

The compatible data is stored as emoji

data("emoji")
head(emoji)
#> # A tibble: 6 × 6
#>   emoji aliases         tags      category          description  unicode_version
#>   <chr> <chr>           <list>    <chr>             <chr>        <chr>          
#> 1 👎    -1              <chr [2]> People & Body     thumbs down  6.0            
#> 2 👍    +1              <chr [2]> People & Body     thumbs up    6.0            
#> 3 💯    100             <chr [2]> Smileys & Emotion hundred poi… 6.0            
#> 4 🔢    1234            <chr [1]> Symbols           input numbe… 6.0            
#> 5 🥇    1st_place_medal <chr [1]> Activities        1st place m… 9.0            
#> 6 🥈    2nd_place_medal <chr [1]> Activities        2nd place m… 9.0

with the tags stored as tags for easy auto-complete

ntfy_send(message = "sending with tags!", 
          tags = c(tags$cat, tags$dog)
)
#> <httr2_response>
#> POST https://ntfy.sh/jonocarroll_ntfy_testing
#> Status: 200 OK
#> Content-Type: application/json
#> Body: In memory (179 bytes)

The compatible emoji can be shown with

show_emoji("rofl")
#> 
#>  🤣 rofl 
#> 

If the name is not found in aliases (the compatible names) it will be searched in tags

show_emoji("lol")
#> Unable to find that name directly.
#> Did you perhaps want...
#> 
#>  🤣 rofl 
#> 

show_emoji("pet")
#> Unable to find that name directly.
#> Did you perhaps want...
#> 
#>  🐱 cat 
#>  🐶 dog 
#>  🐹 hamster 
#> 

You can force this behaviour with

show_emoji("dog", search = TRUE)
#> 
#>  🐶 dog 
#> 
#> Did you perhaps want...
#> 
#>  🐩 poodle 
#> 

Similar Services

  • {Rpushbullet} offers similar functionality, but requires sign-up / an API key
  • {beepr} can play a sound when a process completes
  • IFTTT has an API and can be configured to send messages with e.g. nifffty
  • This blog post details many ways to send notifications, via email, text, Slack, and MS Teams

Privacy

Q: “Will you know what topics exist, can you spy on me?”

A: Refer to the FAQ

Contributing

If this service is useful to you, consider donating to the developer via GitHub sponsors. If this package is useful to you, I also accept donations via GitHub sponsors.

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Lightweight Wrapper to the ntfy.sh Service

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