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Have you ever wanted to see your favourite social media posts in your command line? No? Me neither, but at least hrbrmstr has a few months ago. Or to be honest, I don’t know which social media site he prefers, but Bluesky is currently my favourite. With the ease of use and algorithmic curation that I loved about Twitter before its demise and the super interesting and easy to work with AT protocol, which should make Bluesky “billionaire-proof”1, I’m hopeful that this social network it here to stay.
Recently, I have published the atrrr
package with a few friends, so I thought I could remove the pesky Python part from hrbrmstr’s command line interface.
Along the way, I also looked into how one can write a command line tool with R.
I really love using command line tools2 and was always a bit disappointed that people don’t seem to write them in R.
After spending some time on this, I have to say: it’s not that bad, especially given the packages docopt
and cli
, but it’s definitly a bit more manual than in Python.
But let’s have a look at the result first:
< video src="https://www.johannesbgruber.eu/img/rbsky.mp4" width="450" controls="">Video
And here is of course the commented source code (also available as a GitHub Gist):
#!/usr/bin/Rscript # Command line application Bluesky feed reader based on atrrr. # # Make executable with `chmod u+x rbsky`. # # If you are on macOS, you should replace the first line with: # # #!/usr/local/bin/Rscript # # Not sure how to make it work in Windows ¯\_(ツ)_/¯ # # based on https://rud.is/b/2023/07/07/poor-dudes-janky-bluesky-feed-reader-cli-via-r-python/ library(atrrr) library(cli) library(lubridate, include.only = c("as.period", "interval"), quietly = TRUE, warn.conflicts = FALSE) if (!require("docopt", quietly = TRUE)) install.packages("docopt") library(docopt) # function to displace time since a post was made ago <- function(t) { as.period(Sys.time() - t) |> as.character() |> tolower() |> gsub("\\d+\\.\\d+s", "ago", x = _) } # docopt can produce some documentation when you run `rbsky -h` doc <- "Usage: rbsky [-a ALGO] [-n NUM] [-t S] [-h] -a --algorithm ALGO algorithm used to sort the posts [e.g., \"reverse-chronological\"] -n --n_posts NUM Maximum number of records to return [default: 25] -t --timeout S Time to wait before displaying the next post [default. 0.5 seconds] -h --help show this help text" # this line parses the arguments passed from the command line and makes sure the # documentation is shown when `rbsky -h` is run args <- docopt(doc) if (is.null(args$n_posts)) args$n_posts <- 25L if (is.null(args$timeout)) args$timeout <- 0.5 # get feed feed <- get_own_timeline(algorithm = args$algorithm, limit = as.integer(args$n_posts), verbose = FALSE) # print feed for (i in seq_along(feed$uri)) { item <- feed[i, ] cli({ # headline from author • time since post cli_h1(c(col_blue(item$author_name), " • ", col_silver(ago(item$indexed_at)))) # text of post in italic (not all terminals support it) cli_text(style_italic("{item$text}")) # print quoted text if available quote <- purrr::pluck(item, "embed_data", 1, "external") if (!is.null(quote)) { cli_blockquote("{quote$title}\n{quote$text}", citation = quote$uri) } # display that posts contains image(s) imgs <- length(purrr::pluck(item, "embed_data", 1, "images")) if (imgs > 0) { cli_text(col_green("[{imgs} IMAGE{?S}]")) } # new line before next post cli_text("\n") }) # wait a little before showing the next post Sys.sleep(args$timeout) }
I added the location of the file to my PATH3 with export PATH="/home/johannes/bin/:$PATH"
to make it run without typing e.g., Rscript rbsky
or ./rbsky
.
And there you go.
If you want to explore how to search and analyse posts from Bluesky and then post the results via R
, have a look at the atrrr
–pkgdown
site: https://jbgruber.github.io/atrrr/.
Once the protocol fulfils its vision that one can always take their follower network and posts to a different site using the protocol.↩︎
I liked this summary of reasons to use them https://youtu.be/Q1dwzi5DKio.↩︎
The PATH environment variable is the location of one or several directories that your system searches for executables.↩︎
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