rPithon vs. rPython（转）

Similar to rPython, the rPithon package (http://rpithon.r-forge.r-project.org) allows users to execute Python code from R and exchange the data between Python and R. However, the underlying mechanisms between these two packages are fundamentally different. Wihle rPithon communicates with Python from R through pipes, rPython accomplishes the same task with json. A major advantage of rPithon over rPython is that multiple Python processes can be started within a R session. However, rPithon is not very robust while exchanging large data objects between R and Python.

rPython Session

 library(sqldf)
 df_in <- sqldf('select Year, Month, DayofMonth from tbl2008 limit 5000', dbname = '/home/liuwensui/Documents/data/flights.db')
 library(rPython)
 ### R DATA.FRAME TO PYTHON DICTIONARY ###
 python.assign('py_dict', df_in)
 ### PASS PYTHON DICTIONARY BACK TO R LIST
 r_list <- python.get('py_dict')
 ### CONVERT R LIST TO DATA.FRAME
 df_out <- data.frame(r_list)
 dim(df_out)
 # [1] 5000    3
 #
 # real  0m0.973s
 # user  0m0.797s
 # sys   0m0.186s

rPithon Session

 library(sqldf)
 df_in <- sqldf('select Year, Month, DayofMonth from tbl2008 limit 5000', dbname = '/home/liuwensui/Documents/data/flights.db')
 library(rPithon)
 ### R DATA.FRAME TO PYTHON DICTIONARY ###
 pithon.assign('py_dict', df_in)
 ### PASS PYTHON DICTIONARY BACK TO R LIST
 r_list <- pithon.get('py_dict')
 ### CONVERT R LIST TO DATA.FRAME
 df_out <- data.frame(r_list)
 dim(df_out)
 # [1] 5000    3
 #
 # real  0m0.984s
 # user  0m0.771s
 # sys   0m0.187s

转自：https://statcompute.wordpress.com/2015/03/30/rpithon-vs-rpython/