I am trying to use cl-sql for database access to sqlite3.
But I am getting the error
Couldn't load foreign libraries "libsqlite3", "sqlite3". (searched CLSQL-SYS:*FOREIGN-LIBRARY-SEARCH-PATHS*: (#P"/usr/lib/clsql/" #P"/usr/lib/"))
The same is with sqlite.
I have installed sqlite3 using apt-get and there is a file libsqlite.so.0 in /usr/lib directory.
I also tried to build sqlite3 from source but I couldn't get the so file. What is that I am doing wrong?
Your problem is that cl-sql has a third party dependency. If you inspect the implementation of cl-sql (probably under "~/quicklisp/dists/quicklisp/software/clsql-202011220-git/db-sqlite3/sqlite3-loader.lisp") you will see that the function database-type-load-foreign is trying to load a library named either "libsqlite3" or "sqlite3".
Depending on your operating system this is either looking for a .dll or .so with exactly one of those names.
Given that the version of of libsqlite.so has a different name on your particular distribution of linux, you have a number of different options to make this library work.
Install a version of sqlite3 with the correct binary
Create a soft link to your binary that redirects via ln -s /usr/lib/libsqlite.so.0 /usr/lib/libsqlite3.so (assuming libsqlite.so.0 is the file that clsql is looking for)
Add new paths to CLSQL-SYS:*FOREIGN-LIBRARY-SEARCH-PATHS* to point to the correct binary if it is installed elsewhere (via clsql:push-libary-path)
After having set the path for the default working directory as well as my first (and only) project within RStudio options I wonder why RStudio keeps creating an empty folder named "R" within my "/home" directory every time it is started.
Is there any file I could delete/edit (eventually create) to stop this annoying behaviour and if so, where is it located ?
System: Linux Mint v. 19.3
Software: RStudio v. 1.3.959 / R version 3.4.4
Thanks in advance for any hints.
Yes, you can prevent the creation of the R directory — R is configurable via a set of environment variables.
However, setting these correctly isn’t trivial. The first issue is that many R packages are sensitive to the R version they’re installed with. If you upgrade R and try to load the existing package, it may break. Therefore, the R package library path should be specific to the R version.
On clusters, an additional issue is that the same library path might be read by various cluster nodes that run on different architectures; this is rare, but it happens. In such cases, compiled R packages might need to be different depending on the architecture.
Consequently, in general the R library path needs to be specific both to the R version and the system architecture.
Next, even if you configure an alternative path R will silently ignore it if it doesn’t exist. So be sure to manually create the directory that you’ve configured.
Lastly, where to put this configuration? One option would be to put it into the user environment file, the path of which can be specified with the environment variable R_ENVIRON_USER — it defaults to $HOME/.Renviron. This isn’t ideal though, because it means the user can’t temporarily override this setting when calling R: variables in this file override the calling environment.
Instead, I recommend setting this in the user profile (e.g. $HOME/.profile). However, when you use a desktop launcher to launch your RStudio, this file won’t be read, so be sure to edit your *.desktop file accordingly.1
So in sum, add the following to your $HOME/.profile:
export R_LIBS_USER=${XDG_DATA_HOME:-$HOME/.local/share}/R/%p-library/%v
And make sure this directory exists: re-source ~/.profile (launching a new shell inside the current one is not enough), and execute
mkdir -p "$(Rscript -e 'cat(Sys.getenv("R_LIBS_USER"))')"
The above is using the XDG base dir specification, which is the de-facto standard on Linux systems.2 The path is using the placeholders %p and %v. R will fill these in with the system platform and the R version (in the form major.minor), respectively.
If you want to use a custom R configuration file (“user profile”) and/or R environment file, I suggest setting their location in the same way, by configuring R_PROFILE_USER and R_ENVIRON_USER (since their default location, once again, is in the user home directory):
export R_PROFILE_USER=${XDG_CONFIG_HOME:-$HOME/.config}/R/rprofile
export R_ENVIRON_USER=${XDG_CONFIG_HOME:-$HOME/.config}/R/renviron
1 I don’t have a Linux desktop system but I believe that editing the Env entry to the following should do it:
Exec=env R_LIBS_USER=${XDG_DATA_HOME:-$HOME/.local/share}/R/%p-library/%v /path/to/rstudio
2 Other systems require different handling. On macOS, the canonical setting for the library location would be $HOME/Library/Application Support/R/library/%v. However, setting environment variables on macOS for GUI applications is frustratingly complicated.
On Windows, the canonical location is %LOCALAPPDATA%/R/library/%v. To set this variable, use [Environment]::SetEnvironmentVariable in PowerShell or, when using cmd.exe, use setx.
I am trying to use the Treetag function in the koRpus package.
The code I have used is
tagged.text <-treetag("C:/Rec_By_Others.txt",treetagger="manual",lang="en",TT.options=list(path="C:\\Program Files\\TreeTagger", preset="en"))
But I keep encountering with the following error.
Error in matrix(unlist(strsplit(tagged.text, "\t")), ncol = 3, byrow = TRUE, :
'data' must be of a vector type, was 'NULL'
What do I do ?
Your code seems correct to me, but I had the same error message. I could not find any solution for this problem until today. I finally found that I had a problem with the PERL installation, so I reinstalled a new version of PERL. Then, I checked if TreeTagger worked properly by applying the README TreeTagger instruction, that is:
Installation
Install a Perl interpreter (if you have not already installed one). You can download a Perl interpreter for Windows for free at http://www.activestate.com/activeperl/
Extract the zip file (if it was not extracted yet) and move the TreeTagger directory to the root directory of drive C:.
Download the parameter files for the languages you need, decompress them (e.g. using Winzip or 7zip) and move them to the subdirectory TreeTagger/lib. Rename the parameter files to -utf8.par Example: Rename french-par-linux-3.2-utf8.bin to french-utf8.par Non-UTF8 parameter files are not supported anymore.
Add the path C:\TreeTagger\bin to the PATH environment variable. The necessary steps differ from one Windows version to the other.
Open a command prompt window and type the command set PATH=C:\TreeTagger\bin;%PATH%
Go to the directory C:\TreeTagger cd c:\TreeTagger
Now you can test the tagger, e.g. by analyzing this file with the command tag-english INSTALL.txt If you install the TreeTagger in a different directory, you have to modify the first path in the batch files tag-*.bat using an editor such as Wordpad.
Note also that:
if you install the TreeTagger in a different directory, you have to
modify the first path in the batch files tag-.bat using an editor
such as Wordpad.
I hope this help.
I have downloaded PDFtoText in mac and wrote following code to convert pdf files to text:
pdf_to_load =("~/my_directory/my.pdf")
system(paste('pdftotext', pdf_to_load))
The code runs well but I am not able to see my.txt in the source directory nor it has been saved anywhere in the folders. Where I went wrong?
One of my mentors were able to run the same code in his computer and he was able to see the converted .txt file.
Kindly guide.
You get a wrong result if the default PDF extraction engine is not found on your computer, see ?tm::readPDF. Those engines are not part of R or of the tm package, and it depends on your computer whether the necessary programs are already installed.
The easiest solution is to install the programs pdftotext and pdfinfo (you'll need both), which you can obtain as precompiled binaries here.
Once these programs are correctly installed, you should be able to extract the text of the PDF file without a system call, by using the readPDF() function of the tm package
library(tm)
my_pdf_txt <- readPDF(control=list(text="-layout"))(elem=list(uri="~/my_directory/my.pdf"), language="en")
I have attempted to install R and R studio on the local drive on my work computer as opposed to the organization network folder because anything that runs through the network is really slow. When installing, the destination path shows that it's my local C:drive. However, when I install a new package, the default path shown is my network drive and there is no option to change:
.libPaths()
[1] "\\\\The library/path/I/don't/want"
[2] "C:/Program Files/R/R-3.2.1/library"
I'm running windows 7 professional. How can I remove library path [1] and make path [2] my primary for all base packages and all new packages that I install?
Windows 7/10: If your C:\Program Files (or wherever R is installed) is blocked for writing, as mine is, then you'll get frustrated editing RProfile.site (as I did). As specified in the accepted answer, I updated R_LIBS_USER and it worked. However, even after reading the fine manual several times and extensive searching, it took me several hours to do this. In the spirit of saving someone else time...
Let's assume you want your packages to reside in C:\R\Library:
Create the folder C:\R\Library. Next I need to add this folder to the R_LIBS_USER path:
Click Start --> Control Panel --> User Accounts --> Change my environmental variables
The Environmental Variables window pops up. If you see R_LIBS_USER, highlight it and click Edit. Otherwise click New. Both actions open a window with fields for Variable and Value.
In my case, R_LIBS_USER was already there, and Value was a path to my desktop. I added to the path the folder that I created, separated by semicolon. C:\R\Library;C:\Users\Eric.Krantz\Desktop\R stuff\Packages.
(NOTE: In the last step, I could have removed the path to the Desktop location and simply left C:\R\Library).
See help(Startup) and help(.libPaths) as you have several possibilities where this may have gotten set. Among them are
setting R_LIBS_USER
assigning .libPaths() in .Rprofile or Rprofile.site
and more.
In this particular case you need to go backwards and unset whereever \\\\The library/path/I/don't/want is set.
To otherwise ignore it you need to override it use explicitly i.e. via
library("somePackage", lib.loc=.libPaths()[-1])
when loading a package.
Facing the very same problem (avoiding the default path in a network) I came up to this solution with the hints given in other answers.
The solution is editing the Rprofile file to overwrite the variable R_LIBS_USER which by default points to the home directory.
Here the steps:
Create the target destination folder for the libraries, e.g.,
~\target.
Find the Rprofile file. In my case it was at C:\Program Files\R\R-3.3.3\library\base\R\Rprofile.
Edit the file and change the definition the variable R_LIBS_USER. In my case, I replaced the this line file.path(Sys.getenv("R_USER"), "R", with file.path("~\target", "R",.
The documentation that support this solution is here
Original file with:
if(!nzchar(Sys.getenv("R_LIBS_USER")))
Sys.setenv(R_LIBS_USER=
file.path(Sys.getenv("R_USER"), "R",
"win-library",
paste(R.version$major,
sub("\\..*$", "", R.version$minor),
sep=".")
))
Modified file:
if(!nzchar(Sys.getenv("R_LIBS_USER")))
Sys.setenv(R_LIBS_USER=
file.path("~\target", "R",
"win-library",
paste(R.version$major,
sub("\\..*$", "", R.version$minor),
sep=".")
))
Windows 10 on a Network
Having your packages stored on the network drive can slow down the performance of R / R Studio considerably, and you spend a lot of time waiting for the libraries to load/install, due to the bottlenecks of having to retrieve and push data over the server back to your local host. See the following for instructions on how to create an .RProfile on your local machine:
Create a directory called C:\Users\xxxxxx\Documents\R\3.4 (or whatever R version you are using, and where you will store your local R packages- your directory location may be different than mine)
On R Console, type Sys.getenv("HOME") to get your home directory (this is where your .RProfile will be stored and R will always check there for packages- and this is on the network if packages are stored there)
Create a file called .Rprofile and place it in :\YOUR\HOME\DIRECTORY\ON_NETWORK (the directory you get after typing Sys.getenv("HOME") in R Console)
File contents of .Rprofile should be like this:
#search 2 places for packages- install new packages to first directory- load built-in packages from the second (this is from your base R package- will be different for some)
.libPaths(c("C:\Users\xxxxxx\Documents\R\3.4", "C:/Program Files/Microsoft/R Client/R_SERVER/library"))
message("*** Setting libPath to local hard drive ***")
#insert a sleep command at line 12 of the unpackPkgZip function. So, just after the package is unzipped.
trace(utils:::unpackPkgZip, quote(Sys.sleep(2)), at=12L, print=TRUE)
message("*** Add 2 second delay when installing packages, to accommodate virus scanner for R 3.4 (fixed in R 3.5+)***")
# fix problem with tcltk for sqldf package: https://github.com/ggrothendieck/sqldf#problem-involvling-tcltk
options(gsubfn.engine = "R")
message("*** Successfully loaded .Rprofile ***")
Restart R Studio and verify that you see that the messages above are displayed.
Now you can enjoy faster performance of your application on local host, vs. storing the packages on the network and slowing everything down.
I was struggling for a while with this as my work computer (with Windows 10) created the default user library on a network drive, which would slow down R and RStudio to an unusable state.
In case this helps someone, this is the easiest way I found, without requiring admin rights:
make sure the directory you want to install your packages into exists. If you want to respect the convention, use: C:\Users\username\R\win-library\rversion (for example, something like: C:\Users\janebloggs\R\win-library\3.6)
create a .Renviron file in your home directory (which might be on the network drive?), and in it, write one single line that defines the R_LIBS_USER variable to be your custom path:
R_LIBS_USER=C:\Users\janebloggs\R\win-library\3.6
(feel free to add comments too, with lines starting with #)
If a .Renviron file exists, R will read it at startup and use the variables as they are defined in there, before running the code in the .Rprofile. You can read about it in help(Startup).
Now it should be persistent between sessions!
After a couple of hours of trying to solve the issue in several ways, some of which are described here, for me (on Win 10) the option of creating a Renviron file worked, but a little different from what was written here above.
The task is to change the value of the variable R_LIBS_USER. To do this two steps needed:
Create the file named Renviron (without dot) in the folder \Program\etc\ (Program is the directory where R is installed--for example, for me it was C:\Program Files\R\R-4.0.0\etc)
Insert a line in Renviron with new path: R_LIBS_USER = "C:/R/Library"
After that, reboot R and use .libPaths() to confirm the default directory changed.
I think I tried all of the above and it didn't work for me. This worked, though:
In home directory, make a file called ".Renviron"
In that file, write:
.libPaths(new = "/my/path/to/libs")
Save and restart R if you had it open