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Rage is my fuel
I’ve had the {plumber}
package on my radar for quite some time, but never tried it. However, a
couple of weeks ago, I finally had a reason to try it out and see how the package works.
One of my main problems in life is that my work laptop runs Windows, and my second problem is that
I need to compile \(\LaTeX\) documents (via Rmarkdown) on Windows, and it’s just a pain. Not because
of Rmarkdown, nor \(\LaTeX\), but because of Windows.
Windows and UTF-8 don’t mix well, and I’ve grown so frustrated that I thought about creating my own
Rmarkdown knitr compile farm using my Raspberry Pi 4 to solve this issue. The idea would be to send
in the encrypted .Rmd
file and get back an encrypted .pdf
file. Dear reader, you surely think
that this is overkill; let me assure you, it is not. I have wasted so much time on Windows because
Windows is a joke that cannot properly handle THE MOST COMMON TEXT ENCODING IN THE UNIVERSE that
this the only way out. Even Yihui Xie, the creator of the {knitr}
package (among many others),
wrote a blog post titled My Biggest Regret in the knitr
Package, in which he explains how Windows’
crappy handling of UTF-8 made him make a regrettable decision. The issue Yihui Xie discusses is
now resolved since {rmarkdown}
version 2, as stated in the release
notes (ctrl-f “utf-8”), but,
for some reason, I still have problems with UTF-8 on Windows. While it is a fact that characters
like the french é, è, ô, ç etc are now properly shown in a compiled document, any such character in
a plot will not show properly, as you can see in the screenshot below:
I did not really ever notice this issue in the past because I wrote 100% of my documents in English, but now that I’m a public servant in a country where French is the administrative language, man, am I having a bad time.
Now, I make sure my .Rmd
files are encoded in UTF-8, but I still get issues with plots. I tried
changing the graphics device to Cairo or {ragg}
, but I still have these issues.
Who knows, maybe this is also a case of PEBKAC, but in that case it’s still Windows’ fault for making me feel bad.
Anyway, this was reason enough for me to start developing an API that would allow me to get a nice looking PDF compiled on a serious operating system.
Getting started: Docker
I started by writing a prototype on my local machine that (sort of, but not really) worked, but to
put it on my Raspberry Pi I wanted to create a new Docker image to make deployment easier. For
this, just like I did for this other blog
post, I wrote a ’Dockerfile’ and
pushed an image to Docker Hub. The Dockerfile is heavily inspired by
hvalev’s Dockerfile, and also by the official
plumber
one you can find here. I then
built the image on my Raspberry Pi.
You can use the Dockerfile to build your own image, which you can find
here, or you can pull the one I pushed on
Docker Hub.
Now, something important: this Docker image does not contain my plumber.R
file. So the first
time you’re going to run it, it’ll fail. You’ll need to make one further adaptation on your server
first.
Put your plumber.R
where you want, and copy the path to the file.
For instance, suppose that you put the file at: /path/to/your/apis/plumber.R
.
Then, you can finally run the image like so:
docker run -d -it -p 8000:8000 -v /path/to/your/apis:/srv/plumber/ --rm --name tex-plumber tex-plumber:latest
Docker looks for a plumber file inside /srv/plumber/
but that’s inside the image; this path
gets sort of linked to your /path/to/your/apis/
and thus the plumber.R
file you put there
will be run. You can also put this there beforehand, adapt the Dockerfile and then build the image.
It’s not the most elegant way to do it, but hey, I’m a beginner.
These instructions are very general and independent from my API I’m discussing here. What follows will be specific to my API.
An API that ingests an Rmd file and spits out a compiled document
First of all, none of this would have been possible without the following Stackoverflow threads and Github repos:
- https://stackoverflow.com/questions/63808430/r-plumber-getting-as-excel-xlsx/63809737#63809737
- https://github.com/ChrisBeeley/reports_with_plumber/blob/master/plumber.R
- https://stackoverflow.com/questions/64639748/how-to-upload-a-xlsx-file-in-plumber-api-as-a-input
and Bruno Tremblay’s help on this thread I made calling for help. You’ll probably notice that the answers in the stackoverflow threads all come from Bruno Tremblay, so a big thank you to him!
With his help, I was able to clob together this API:
#* Knit Rmarkdown document #* @param data:file The Rmd file #* @param string The output format #* @post /knit # We use serializer contentType, the pdf serializer is the plot output from grDevices # Since the content is already in the right format from render, we just need to set # the content-type #* @serializer contentType list(type = "application/gzip") function(data, output_format) { # Save the RMD file to a temporary location rmd_doc <- file.path(tempdir(), names(data)) writeBin(data[[1]], rmd_doc) # render document to the selected output format # (file will be saved side by side with source and with the right extension) output <- rmarkdown::render(rmd_doc, output_format) tar("output.tar.gz", normalizePath(output), compression = "gzip", tar = "tar") # remove files on exit on.exit({file.remove(rmd_doc, output, "output.tar.gz")}, add = TRUE) # Include file in response as attachment value <- readBin("output.tar.gz", "raw", file.info("output.tar.gz")$size) plumber::as_attachment(value, basename("output.tar.gz")) }
This will go inside the plumber.R
script. When the Docker image is running, you can hit the
endpoint /knit
to knit a document. But before discussing how to hit the API, let’s go through
the above code.
function(data, output_format) { # Save the RMD file to a temporary location rmd_doc <- file.path(tempdir(), names(data)) writeBin(data[[1]], rmd_doc)
This function takes two arguments: data
and output_format
. data
is your Rmd file (I should
have named this better… oh well) that you will send via a POST. The Rmd will get written to a
temporary location. In a previous version of the function I’ve used writeLines
instead of
writeBin
which works as well.
The next lines render the output as the provided output format (through the second argument,
output_format
) and the output file gets compressed to a tar.gz
archive. Why? The first reason
is, obviously, to save precious bandwidth. The second, most important reason, is for the API to
be able to download it.
output <- rmarkdown::render(rmd_doc, output_format) tar("output.tar.gz", normalizePath(output), compression = "gzip", tar = "tar")
The way I understand how this works, is that if you want your API to return an attachment, you need to set the right content type. This is done by decorating the function with the right serializer:
#* @serializer contentType list(type = "application/gzip")
At first I only wanted PDF files, and thus set the pdf
serializer. This was a mistake, as the
pdf
serializer is only used if the API is supposed to return a plot (in the pdf format).
When this was pointed out to me (in the Rstudio forums), Bruno Tremblay showed me the right solution:
#* @serializer contentType list(type = "application/pdf")
which worked! However, I then thought about how I would make the API more flexible by allowing the
user to compile any format, and this is when I thought about compressing the file and returning
a tar.gz
file instead.
The first line of the final lines:
on.exit({file.remove(rmd_doc, output, "output.tar.gz")}, add = TRUE) # Include file in response as attachment value <- readBin("output.tar.gz", "raw", file.info("output.tar.gz")$size) plumber::as_attachment(value, basename("output.tar.gz"))
simply clean up after exiting. The final lines read in the compressed file in a variable called
variable
which then gets downloaded automatically as an attachment.
Ok, so now, how do I get a document compiled? With the following script:
library(httr) library(magrittr) my_file <- "testmark" res <- POST( "http://url_to_compile_farm:8000/knit?output_format=html_document", body = list( data = upload_file(paste0(my_file, ".Rmd"), "text/plain") ) ) %>% content() names(res) output_filename <- file(paste0(my_file, ".tar.gz"), "wb") writeBin(object = res, con = output_filename) close(output_filename)
This script is saved in a folder which also contains testmark.Rmd
, which is the Rmarkdown file
I want to compile (and which gets sent to the server as the data
argument).
You’ll notice in the url that the second argument from my API is defined there:
"http://url_to_compile_farm:8000/knit?output_format=html_document"
you can change html_document
to pdf_document
or word_document
to get a PDF or Word document
respectively.
I’m pretty happy with this solution, even though it’s quite rough, and still needs some adjustments. For instance, I want to make sure that I can leave this API running without worry; so I need to build in some authentication mechanism, which will probably be quite primitive, but perhaps good enough. I also need to send and receive encrypted documents, and not plain text.
Further reading
If you’re into tinkering with Raspberry Pi’s, Rstudio Server an {plumber}, Tyler Littlefield has a pretty cool github repo with lots of interesting stuff. Definitely give it a look!
Hope you enjoyed! If you found this blog post useful, you might want to follow me on twitter for blog post updates and buy me an espresso or paypal.me, or buy my ebook on Leanpub. You can also watch my videos on youtube. So much content for you to consoom!
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