在 Windows 上使用 Rtools 和 Rcpp 附带的不同 gcc 版本

Question

Before I embark on updating gcc, has anyone actually attempted this, and can they confirm building R from source is required to update the gcc version one uses to compile c++ code with Rcpp (ie not necessarily for package authoring and certainly not for CRAN-valid packages)?

See Dirk's answer to this question, and the follow-on comment from the original poster How to use gcc 4.8.1 with Rcpp on Windows .

Answer 1

Rebuilding R from source does not appear necessary. Here are the steps I used for a Windows 7 x64 system, running R 3.1.1 with Rtools 3.1.0.1942 . The implications of this update to gcc have not been thoroughly tested:

1. Start a clean R session and remove.packages("Rcpp") and anything else Rcpp related. Close R session.
2. Download and run MinGW-builds from Link to MinGW-builds installer .
3. Select gcc version 4.8.1/Arch x64/Threads posix/Exception sjlj /Build rev 5 and install to [Drive]:\\Rtools\\mingw-builds\\ ...

4. Update the system PATH variable to include these entries in the following order (at or near the top of PATH ): [Drive]:\\R\\R-3.1.1\\bin\\x64;[Drive]:\\Rtools\\bin;[Drive]:\\Rtools\\mingw-build\\x64-4.8.1-posix-sjlj-rev5\\mingw64\\bin\\; the 3rd path entry replaces the one included by the Rtools installer: [Drive]:\\Rtools\\gcc-4.6.3\\bin

5. Restart, or otherwise, to reflect PATH changes.

6. Start a clean R session and run install.packages("Rcpp") and repeat for all the other packages that were removed in step 1.

These steps have been followed using R 3.1.1 (2014-07-10) with Rcpp 0.11.2 . It is easiest to do this using rgui.exe , and not via an IDE such as RStudio , due to the silent loading of previous workspaces and packages of the latter.

Test set-up by running system('gcc -v') in a R session to obtain:

COLLECT_GCC=F:\Rtools\MINGW-~1\X64-48~1.1-P\mingw64\bin\gcc.exe
COLLECT_LTO_WRAPPER=f:/rtools/mingw-~1/x64-48~1.1-p/mingw64/bin/../libexec/gcc/x86_64-w64-mingw32/4.8.1/lto-wrapper.exe
Target: x86_64-w64-mingw32
[Edited Config info]
Thread model: posix
gcc version 4.8.1 (rev5, Built by MinGW-W64 project) 

To confirm a selection of compiler bugs present with gcc 4.6.3 to 4.8.0 are no more, as well as test some new C++11 features available with gcc 4.8.* , in a R session running Rcpp::sourceCpp on the following code, saved as .cpp file, should generate no compiler warnings or errors (whereas this will totally fail using gcc 4.6.3 ):

#include <Rcpp.h>

// [[Rcpp::plugins("cpp11")]]


template<typename T>
struct Wrap 
{
    int test2(int depth)
    {
        m_test++;
        std::vector<int> v = { 0, 1, 2, 3 };
        return depth == 0? 1 : std::accumulate(
             v.begin(), v.end(), int(0), [=](int sub, int const&) {
             return sub + test2(depth - 1);
             });   
    }

    int m_test = 0;
};


  struct X
{
  template <class T> static void bar() {}

  template <class T> void foo(T p) 
  {
    [&] { bar<T>(); };
  }
};

// [[Rcpp::export]]
double inheriting(int in_){

struct A { 
  A(int u){
    hello = u*u/2.0;
  }; 
double hello;
};

struct B: A { using A::A; };

  B b(in_);
  return(b.hello);
}

// [[Rcpp::export]]
void test_lambda(int in_)
{
  X x;
  x.foo(in_);
}

// [[Rcpp::export]]
int test_bug_4_7_2(int in_){

Wrap<int> w;
return w.test2(in_);
}

Answer 2

Here I describe how we can use GCC v8.1.0 with Rtools to compile source packages in R.

This is tested on Windows 10 64 bit Home edition with R v3.5.0 and Rtools35 .

1. Install R
2. Install Rtools . The default installation location will be C:\\Rtools . You will see following subfolders inside Rtools :

3. Set the path so that Rtools is in path by editing environment variable as below:

4. Delete whatever is present inside mingw_64 subfolder inside Rtools .
5. Now go to download gcc from this MinGW distro . Download mingw-16.0-without-git.exe .

Install in its default location. Note that by default, it will get installed in MinGW\\ folder. Copy/Cut whatever is inside this MinGW\\ folder.

6. Go to mingw_64 subfolder inside Rtools and paste whatever been copied/cut in step 5. After pasting you will see this 👇 inside mingw_64 sub-folder:

6. Test your setup to compile C/C++ code in R package rdatatable with following lines in R console:

    remove.packages("data.table") install.packages("data.table", type = "source", repos = "http://Rdatatable.github.io/data.table")

If successful, you will find something like this:

It compiles Rcpp from source too !

It can compile all R packages with compiled code, except those with dependencies on external libraries.