I've inherited a large R codebase which has grown over a few years and a few different developers. It contains many things I'd like to delete: - Unused functions - Variable definitions that are never called - Unreachable code I'd write that myself, it would even be fun, but I don't want to reinvent the wheel. Is there an R package that can find these things? I've heard of lintr, but I'm not sure if it's the right tool, since, unfortunately, the code is in a folder (not a package) with many R files that are sourced from one master file and lintr can only check a single file or an actual package, from what I understand. A workaround of course would be to concatenate all files into one R script. I'd appreciate any hints on how to best solve this. Thanks in advance, Alex
mvbutils::foodweb produces a graphical display of the hierarchy (or network or ...) of function calls. Isolated functions are not called. This might help you. -- Mike On Wed, Nov 15, 2017 at 12:44 AM, Alexander Engelhardt <alex at chaotic-neutral.de> wrote:> I've inherited a large R codebase which has grown over a few years and a few > different developers. > > It contains many things I'd like to delete: > - Unused functions > - Variable definitions that are never called > - Unreachable code > > I'd write that myself, it would even be fun, but I don't want to reinvent > the wheel. > Is there an R package that can find these things? > > I've heard of lintr, but I'm not sure if it's the right tool, since, > unfortunately, the code is in a folder (not a package) with many R files > that are sourced from one master file and lintr can only check a single file > or an actual package, from what I understand. A workaround of course would > be to concatenate all files into one R script. > > I'd appreciate any hints on how to best solve this. > > Thanks in advance, > Alex > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
Thanks, that helps! The visualization is very messy, because I have
about 100 functions, but foodweb() returns a matrix of which function
calls which, and the functions callers.of("myfunc") and
callees.of("myfunc") do exactly what I was looking for.
?- Alex
On 11/15/2017 10:44 AM, Michael Hannon wrote:> mvbutils::foodweb produces a graphical display of the hierarchy (or
> network or ...) of function calls. Isolated functions are not called.
> This might help you.
>
> -- Mike
>
>
> On Wed, Nov 15, 2017 at 12:44 AM, Alexander Engelhardt
> <alex at chaotic-neutral.de> wrote:
>> I've inherited a large R codebase which has grown over a few years
and a few
>> different developers.
>>
>> It contains many things I'd like to delete:
>> - Unused functions
>> - Variable definitions that are never called
>> - Unreachable code
>>
>> I'd write that myself, it would even be fun, but I don't want
to reinvent
>> the wheel.
>> Is there an R package that can find these things?
>>
>> I've heard of lintr, but I'm not sure if it's the right
tool, since,
>> unfortunately, the code is in a folder (not a package) with many R
files
>> that are sourced from one master file and lintr can only check a single
file
>> or an actual package, from what I understand. A workaround of course
would
>> be to concatenate all files into one R script.
>>
>> I'd appreciate any hints on how to best solve this.
>>
>> Thanks in advance,
>> Alex
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.