rPithon vs. rPython

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

 1 library(sqldf)
 2 df_in <- sqldf(select Year, Month, DayofMonth from tbl2008 limit 5000, dbname = /home/liuwensui/Documents/data/flights.db)
 3 library(rPython)
 4 ### R DATA.FRAME TO PYTHON DICTIONARY ###
 5 python.assign(py_dict, df_in)
 6 ### PASS PYTHON DICTIONARY BACK TO R LIST
 7 r_list <- python.get(py_dict)
 8 ### CONVERT R LIST TO DATA.FRAME
 9 df_out <- data.frame(r_list)
10 dim(df_out)
11 # [1] 5000    3
12 #
13 # real  0m0.973s
14 # user  0m0.797s
15 # sys   0m0.186s

rPithon Session

 1 library(sqldf)
 2 df_in <- sqldf(select Year, Month, DayofMonth from tbl2008 limit 5000, dbname = /home/liuwensui/Documents/data/flights.db)
 3 library(rPithon)
 4 ### R DATA.FRAME TO PYTHON DICTIONARY ###
 5 pithon.assign(py_dict, df_in)
 6 ### PASS PYTHON DICTIONARY BACK TO R LIST
 7 r_list <- pithon.get(py_dict)
 8 ### CONVERT R LIST TO DATA.FRAME
 9 df_out <- data.frame(r_list)
10 dim(df_out)
11 # [1] 5000    3
12 #
13 # real  0m0.984s
14 # user  0m0.771s
15 # sys   0m0.187s

郑重声明:本站内容如果来自互联网及其他传播媒体,其版权均属原媒体及文章作者所有。转载目的在于传递更多信息及用于网络分享,并不代表本站赞同其观点和对其真实性负责,也不构成任何其他建议。