# R and C++

You are right here, if you have an R project which is not fast enough and following conditions are true. You checked for existing R libraries with good performance. Typically those would be libraries implemented in C++ with R wrappers. You checked your code for suboptimal passages and they cant be fixed within R. Then it is a good idea to use Rcpp to solve such problems as necessary loops, large recursive problems and need for advanced data structures not available in r. It makes sense to avoid a pure C++ project because we would not be able to use advantages of R.

# Related

## News

## Related Pages

- RGB & HSV, color space transformations in Python
- Python - Convolution
- Image representation and processing in Python
- Python - Jit Basics
- Python - Matplotlib
- Python - Numpy Basics
- Python - Basics
- Spatial image analysis in R
- Python and C++
- Introduction to R
- Octave and C++
- Introduction to C++
- Mapreduce in R - Prime Numbers
- Mapreduce in Python - Word Count
- Functional Programming in Matlab
- Message Passing Interface - Prime Number Calculation
- Extract Snippets from Images