similar to: reinterpreting externalptr in R

Hi, It seems that new("externalptr") is always returning the same instance, and not a new one as one would expect from a call to new(). Of course this is hard to observe: > new("externalptr") <pointer: (nil)> > new("externalptr") <pointer: (nil)> since not a lot of details are displayed. For example, it's easy to see that 2

Greetings. 2.15.0 added this behavior http://developer.r-project.org/blosxom.cgi/R-devel/NEWS/2012/03/29#n2012-03-29 o Passing R objects other than atomic vectors, functions, lists and environments to .C() is now deprecated and will give a warning. Most cases (especially NULL) are actually coding errors. NULL will be disallowed in future. This seems to make sense,

Dear all, I am confused about the inconsistent behaviors of `@<-` operator when used in different ways. Consider the following example: library(inline) # Function to generate an externalptr object with random address new_extptr <- cfunction(c(), ' SEXP val = PROTECT(ScalarLogical(1)); SEXP out = PROTECT(R_MakeExternalPtr(&val, R_NilValue, val)); UNPROTECT(2);

Hi all, I found that the finalizer of the externalPtr is not called when R is quitting. However, manually calling GC() works fine. This behavior is observed on devel R 2020-04-02 r78142 on Win and R 3.6.3 on Ubuntu. I make a reproducible package here: https://github.com/Jiefei-Wang/example Here is the detail of how to reproduce the problem, I create a temporary file in the package root path and

On Sun, 18 Mar 2018, Jialin Ma wrote: > Dear all, > > I am confused about the inconsistent behaviors of `@<-` operator when > used in different ways. Consider the following example: > > library(inline) > > # Function to generate an externalptr object with random address > new_extptr <- cfunction(c(), ' > SEXP val = PROTECT(ScalarLogical(1)); >

Given an externalptr object 'pool' which protects an R object 'prot': # SEXP prot = (a dynamically updated list with handles) SEXP pool = R_MakeExternalPtr(p, R_NilValue, prot); R_RegisterCFinalizerEx(pool, fin_pool, TRUE); WRE explains that 'prot' remains in existence as long as 'pool' is around. Does this also mean 'prot' still exists when the

Dear R friends. After having some troubles learning how to create a ffdf object, now I find myself having problems saving it. this is the data i´d like to save: str(DATA) List of 3 $ virtual: 'data.frame': 6 obs. of 7 variables: .. $ VirtualVmode : chr "double" "short" "integer" "integer" ... .. $ AsIs : logi FALSE FALSE FALSE

See R_RegisterCFinalizerEx() and set onexit to nonzero. Here: https://github.com/wch/r-source/blob/9353ddfa8d30069ad8975e0364307d710f2488d5/src/include/Rinternals.h#L1279-L1280 Gabor On Fri, Apr 3, 2020 at 1:56 PM Wang Jiefei <szwjf08 at gmail.com> wrote: > > Hi all, > > I found that the finalizer of the externalPtr is not called when R is > quitting. However, manually

Use R_RegisterFinalizerEx in your C code. See https://cran.r-project.org/doc/manuals/r-release/R-exts.html#External-pointers-and-weak-references This still gives you only "best effort"; for anything stronger you would need a different approach. In general, finalizers should only be used as a backstop, not as a primary resource management tool (in R or any other garbage-collected

Is there a 'proper' way of checking if cluster is active. For example, I create a cluster called .PBcluster > str(.PBcluster) List of 4 $ :List of 3 ..$ con :Classes 'sockconn', 'connection' atomic [1:1] 3 .. .. ..- attr(*, "conn_id")=<externalptr> ..$ host: chr "localhost" ..$ rank: int 1 ..- attr(*, "class")= chr

I am out of my league with this question. The following code starts the java imaging program ImageJ from within R, and displays an image (assuming ImageJ is installed on your computer). library(RImageJ) img <- IJ$openImage( file.choose() ) #pick an available .tif file img$show() # make the image object visible # An image is now displayed # find out about the objects involved >

Dear all, I do not completely understand following behaviour : > con <- file("test.txt") > isOpen(con) [1] FALSE > open(con) > isOpen(con) [1] TRUE > close(con) > isOpen(con) Error in isOpen(con) : invalid connection > str(con) Classes 'file', 'connection' atomic [1:1] 3 ..- attr(*, "conn_id")=<externalptr> Why do I get an

Is the following expected behavior? > mkext <- inline::cfunction(language="C", body='return R_MakeExternalPtr(NULL, install("tag"), R_NilValue);') > x <- mkext() > y <- x > attr(y, "foo") <- "bar" > attributes(x) $foo [1] "bar" I would expect that modifying y's attributes should not affect x. [Tested

Hi, All: ????? What would you suggest one use to read the data on members of the US Congress and their positions on net neutrality from "https://www.battleforthenet.com/scoreboard" into R? ????? I found recommendations for the "rvest" package to "Easily Harvest (Scrape) Web Pages".? I tried the following: URL <-

I'm trying to install the XML package on Ubuntu 10.10, and I keep getting a warning message the XML could not be found and had non-zero exit status. How can I fix this problem? > install.packages() Loading Tcl/Tk interface ... done --- Please select a CRAN mirror for use in this session --- Installing package(s) into ‘/home/amathew/R/i686-pc-linux-gnu-library/2.13’ (as ‘lib’ is

Hi all, I've been writing a package and I've run into a problem that I'm unsure how to solve. I am looking to pass a C++ class object to R so that it may be passed back to another C++ function later on to be used. I'm quite new to R and this is my first time writing a package, so I hope you can bear with me. The following is how I create the class and use

Hello all, I am attempting to run an R script that makes use of RWeka. I am running SuSE Linux 9.3 with Java 1.5.0_06, R version 2.2.1, Weka 3-4-7, and Rweka 0.2-1. CLASSPATH="/usr/local/weka-3-4-7/weka.jar:/usr/local/JGR/JGR.jar" I receive the error: NewObject("weka/core/Instances","(Ljava/io/Reader;)V",...) failed Exception in thread "main"

Hi, I am trying to run the bigmemory example provided on the http://www.bigmemory.org/ The example runs on the "airline data" and generates summary of the csv files:- library(bigmemory) library(biganalytics) x <- read.big.matrix("2005.csv", type="integer", header=TRUE, backingfile="airline.bin", descriptorfile="airline.desc",

When dealing with object holding pointers that are only valid during a single session, it would be convenient to exclude them from being saved with the session image. (I am assuming that `quit` calls `save.image` before quitting or is it internal?) Currently they are saved with the pointer converted to NULL. Its a bit surprising for users not realizing the object is no longer valid. My thought is

In this email to the R-help list: https://stat.ethz.ch/pipermail/r-help/2017-June/447474.html and in this question on Stackoverflow: https://stackoverflow.com/questions/44486643/nleqslv-memory-use-in-r Andrew Leach has raised a question about the memory usage of my package nleqslv. In a model with a loop within a function he has experienced continuously increasing memory usage by package nleqslv