How to determine which older version of the R package is compatible with my R version

Question

I am trying to install the "tm" package but then I get an error saying that "tm" is not available for my R version

package ‘tm’ is not available (for R version 3.0.2)

But then I saw that someone suggested I download the archived version from

http://cran.r-project.org/src/contrib/Archive/tm/?C=M;O=A

and then try installing from source.

My question is how do I determine which file there in the list is compatible with my R version?

Answer 1

I developed an answer related to the approach here, but which uses only base R (you don't need XML or devtools or anything). It also potentially handles some contingencies that may not be addressed by the solution I linked to from the other question. Since it was around 100 lines of code, rather than just post a huge function here, I rolled it into a package oldr you can get from GitHub here:

oldr package GitHub repo

The package has just one exported function, install.compatible.packages(). I have tested it on Ubuntu 18.04. I installed R 3.1.0 and installed tm (and its dependencies). The current version of tm requires R 3.2.0, so wouldn't be available via install.packages(), but my function allows its installation:

> oldr::install.compatible.packages("NLP")
Installing package into ‘/home/duckmayr/R/x86_64-unknown-linux-gnu-library/3.1’
(as ‘lib’ is unspecified)
* installing *source* package ‘NLP’ ...
** package ‘NLP’ successfully unpacked and MD5 sums checked
** R
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded
* DONE (NLP)
> oldr::install.compatible.packages("slam")
Installing package into ‘/home/duckmayr/R/x86_64-unknown-linux-gnu-library/3.1’
(as ‘lib’ is unspecified)
* installing *source* package ‘slam’ ...
** package ‘slam’ successfully unpacked and MD5 sums checked
** libs
gcc -I/opt/R/3.1.0/lib/R/include -DNDEBUG  -I/usr/local/include    -fpic  -g -O2  -c apply.c -o apply.o
gcc -I/opt/R/3.1.0/lib/R/include -DNDEBUG  -I/usr/local/include    -fpic  -g -O2  -c grouped.c -o grouped.o
gcc -I/opt/R/3.1.0/lib/R/include -DNDEBUG  -I/usr/local/include    -fpic  -g -O2  -c sparse.c -o sparse.o
gcc -I/opt/R/3.1.0/lib/R/include -DNDEBUG  -I/usr/local/include    -fpic  -g -O2  -c util.c -o util.o
gcc -shared -L/usr/local/lib -o slam.so apply.o grouped.o sparse.o util.o -L/opt/R/3.1.0/lib/R/lib -lRblas -lgfortran -lm -lquadmath -L/opt/R/3.1.0/lib/R/lib -lR
installing to /home/duckmayr/R/x86_64-unknown-linux-gnu-library/3.1/slam/libs
** R
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded
* DONE (slam)
> oldr::install.compatible.packages("tm")
Installing package into ‘/home/duckmayr/R/x86_64-unknown-linux-gnu-library/3.1’
(as ‘lib’ is unspecified)
* installing *source* package ‘tm’ ...
** package ‘tm’ successfully unpacked and MD5 sums checked
** libs
gcc -I/opt/R/3.1.0/lib/R/include -DNDEBUG  -I/usr/local/include    -fpic  -g -O2  -c copy.c -o copy.o
gcc -shared -L/usr/local/lib -o tm.so copy.o -L/opt/R/3.1.0/lib/R/lib -lR
installing to /home/duckmayr/R/x86_64-unknown-linux-gnu-library/3.1/tm/libs
** R
** data
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (tm)

Update: Testing on Windows

I now have also had the chance to test on Windows (8.1), and everything worked smoothly for installing tm to an old version of R (v. 3.1.0):

> oldr::install.compatible.packages("NLP")
Installing package into ‘C:/Users/User/Documents/R/win-library/3.1’
(as ‘lib’ is unspecified)
trying URL 'http://mirror.las.iastate.edu/CRAN/bin/windows/contrib/3.1/NLP_0.1-9.zip'
Content type 'application/zip' length 278699 bytes (272 Kb)
opened URL
downloaded 272 Kb

package ‘NLP’ successfully unpacked and MD5 sums checked

The downloaded binary packages are in
        C:\Users\User\AppData\Local\Temp\RtmpojDNlF\downloaded_packages
> oldr::install.compatible.packages("slam")
Installing package into ‘C:/Users/User/Documents/R/win-library/3.1’
(as ‘lib’ is unspecified)
trying URL 'http://mirror.las.iastate.edu/CRAN/bin/windows/contrib/3.1/slam_0.1-32.zip'
Content type 'application/zip' length 111528 bytes (108 Kb)
opened URL
downloaded 108 Kb

package ‘slam’ successfully unpacked and MD5 sums checked

The downloaded binary packages are in
        C:\Users\User\AppData\Local\Temp\RtmpojDNlF\downloaded_packages
> oldr::install.compatible.packages("tm")
Installing package into ‘C:/Users/User/Documents/R/win-library/3.1’
(as ‘lib’ is unspecified)
trying URL 'http://mirror.las.iastate.edu/CRAN/bin/windows/contrib/3.1/tm_0.6-2.zip'
Content type 'application/zip' length 710798 bytes (694 Kb)
opened URL
downloaded 694 Kb

package ‘tm’ successfully unpacked and MD5 sums checked

The downloaded binary packages are in
        C:\Users\User\AppData\Local\Temp\RtmpojDNlF\downloaded_packages

Update: Additional Parameters

Now users can specify which version of R to attempt installation for (R_version parameter), and which directory to install packages to (lib parameter), which could be useful for testing or other purposes.

Answer 2

You can use the METACRAN mirror:

Go to the blame page of the DESCRIPTION file of the package you're interested in.

E.g. for tm: https://github.com/cran/tm/blame/master/DESCRIPTION

Find the Depends line and click as many times as needed on the View blame prior to this change icon, until an old enough R version is displayed.

If you want to automate that, it may be better to use crandb (also from METACRAN).

Side note: sometimes package authors list R (≥ x.y.z) as a dependency just to be safe because they use version x.y.z and didn't do any tests with previous versions.

Answer 3

You can download the archived package and then untar and un-gzip it. The DESCRIPTION file lists the version of R that it needs. In your case the file tm_0.5-10.tar.gz (that is, the most recent archive version, but not the current version) has this line:

Depends: R (>= 3.0.0)

Version 0.6 of the tm package updated its dependency to R greater than or equal to 3.1.0.

Answer 4

Another option would be to upgrade your version of R so it is compatible with that latest version of the "tm" package. You can do that easily within R by using the following code:

# install the latest installr package: 
install.packages("installr")

# require the latest installr package: 
require(installr)

#run the command to update R
updateR()

HT: http://www.r-statistics.com/2014/07/r-3-1-1-is-released-and-how-to-quickly-update-it-on-windows-os/

Answer 5

You can use the groundhog package.

First, to find the dates you can use the cross.toc() function, which will show all publication dates for the selected packages, including R itself.

For example, to get the publication dates for tm and R:

library(groundhog) 
cross.toc(c("tm","R"))

You will get something like this:

132    3.6.1 2019-07-05       R
133    3.6.2 2019-12-12       R
134    0.7-7 2019-12-13      tm
135    3.6.3 2020-02-29       R
136    4.0.0 2020-04-24       R

If you are using R 3.6.1 you would choose a date after 2019-07-05, if you wanted the version 0.7-7 of tm a date after 2019-12-13, and then load that version with

groundhog.library('tm', '2019-12-15')