similar to: unserialize and eager execution

Are the functions 'R_Unserialize' and 'R_InitFileInPStream' allowed to be used in R packages? I guess I'm just not clear on the implications of this comment in 'Rinternals.h': /* The connection interface is not yet available to packages. To allow limited use of connection pointers this defines the opaque pointer type. */ I have a function in the

Hi, I am developing a tool for converting a large data frame stored in an uncompressed binary (XDR) RData file to a delimited text file. The data frame is too large to load() and extract rows from on a typical PC. I'm looking to parse through the file and extract individual entries without loading the whole thing into memory. In terms of some C source functions, instead of doing

Hi, sorry if this question is trivial or unclear, this is my first venture into mixed C/R programming (I am reasonably experienced in each separately). I am trying to write a serialization function for a format called typedbytes, which is used as an interchange format in Hadoop circles. Since I would need to serialize according to the internal R format many small R objects I looked at the c

Hi all, I am not able to export an ALTREP object when `gctorture` is on in the worker. The package simplemmap can be used to reproduce the problem. See the example below ``` ## Create a temporary file filePath <- tempfile() con <- file(filePath, "wrb") writeBin(rep(0.0,10),con) close(con) library(simplemmap) library(parallel) cl <- makeCluster(1) x <- mmap(filePath,

This Index: src/main/altrep.c =================================================================== --- src/main/altrep.c (revision 79385) +++ src/main/altrep.c (working copy) @@ -275,10 +275,11 @@ SEXP psym = ALTREP_SERIALIZED_CLASS_PKGSYM(info); SEXP class = LookupClass(csym, psym); if (class == NULL) { - SEXP pname = ScalarString(PRINTNAME(psym)); + SEXP pname =

I ran into an interesting error unserializing a file created with ascii=TRUE: R 3.5.1 (Windows or Linux): > unserialize(serialize(list(raw=as.raw(c(39,41))), NULL, version=2, ascii=TRUE)) Error in unserialize(serialize(list(raw = as.raw(c(39, 41))), NULL, version = 2, : ReadItem: unknown type 29, perhaps written by later version of R The same error happens when the

I stumbled upon the following: f <- parallel::mcparallel(raw(0L)) parallel::mccollect(f) # $`77083` # NULL but f <- parallel::mcparallel(raw(1L)) parallel::mccollect(f) # Error in unserialize(r) : read error traceback() # 2: unserialize(r) # 1: parallel::mccollect(f) (restarting because the above appears to corrupt the R session) f <- parallel::mcparallel(raw(2L))

Thanks for the report. Will look into it when I get a chance unless someone else gets there first. A simpler reprex: ## create and serialize a memmory-mapped file object filePath <- "x.dat" con <- file(filePath, "wrb") writeBin(rep(0.0,10),con) close(con) library(simplemmap) x <- mmap(filePath, "double") saveRDS(x, file = "x.Rds") ## in a

Hi folks, I've attached a patch to the svn trunk that improves the performance of the serialize/unserialize interface for vector types. The current implementation: a) invokes the R_XDREncode operation for each element of the vector type, and b) uses a switch statement to determine the stream type for each element of the vector type. I've added R_XDREncodeVector/R_XDRDecodeVector functions

On Mon, 13 May 2024 09:54:27 -0500 (CDT) luke-tierney--- via R-devel <r-devel at r-project.org> wrote: > Looks like I added that warning 22 years ago, so that should be enough > notice :-). I'll look into removing it now. Dear Luke, I've got a somewhat niche use case: as a way of protecting myself against rogue *.rds files and vulnerabilities in the C code, I've been

I found that also; fixed in r79386 in the trunk. Will port to R-patched shortly. Best, luke On Thu, 29 Oct 2020, Martin Morgan wrote: > This > > Index: src/main/altrep.c > =================================================================== > --- src/main/altrep.c (revision 79385) > +++ src/main/altrep.c (working copy) > @@ -275,10 +275,11 @@ > SEXP psym =

I don''t even know if this is possible. I want to use an object as an attribute for one of my classes. I can save it to the db fine, looks like...but I need to be able to use it after I pull the object from the db. Right now the attribute is just a String, but I need it to be a Runt::Intersect object. Does anyone know how I can unserialize the attribute so I can use it as an object?

I see this on MacOS as well, so likely not platform dependent. A little more diddling to try to narrow it down: > unserialize(serialize(as.raw(1), NULL, version=2, ascii=TRUE)) [1] 30 > unserialize(serialize(list(as.raw(1)), NULL, version=2, ascii=TRUE)) [[1]] [1] 30 > unserialize(serialize(list(raw=as.raw(1)), NULL, version=2, ascii=TRUE)) Error in unserialize(serialize(list(raw =

Hi there, I'm trying to do something like a migration of an R program. I've got a function and some variables in an interactive-session: r <- .5 ## estimatePi references r estimatePi <- function(seed) { set.seed(seed) numDraws <- 1e+05 x <- runif(numDraws, min = -r, max = r) y <- runif(numDraws, min = -r, max = r) inCircle <- ifelse((x^2 + y^2)^0.5

I use recordPlot() to save plots to disk that I render later to a variety of formats. This works fine for base R plots and ggplot2 plots, and also used to work for lattice plots. However somewhere in version 2.14 things stopped working for lattice plots. Here is an example: library(lattice); histogram(rnorm(100)); x <- recordPlot(); saveRDS(x, "myplot.rds"); y <-

Hi there, I'm writing an R extension that has a C component that relies on two third party libraries that I'm bundling with the extension. I'd like to statically link my resulting extension so that I can rely on the bundled versions of the libraries I'm distributing, so there's two questions - 1, does R allow statically linked C extensions to be used at runtime? 2, are there

Hi all, I'm working with some huge array in R and I need to load several ones to apply some functions that requires to have all my arrays values for each cell... To make it possible, I would like to load only a part (for example 100 cells) of all my arrays, apply my function, delete all cells loaded, loaded following cells and so on. Is it possible to unserialize (or load) only a

Dear R-Users, I need a very fast and reliable database solution so I try to serialize a data.frame (to binary data) and to store this data to an SQLite database. This is what I tried to do: library(RSQLite) con <- dbDriver("SQLite") db <- dbConnect(con, "test") dbSendQuery(db, 'CREATE TABLE frames("simID" INT, "data" BLOB)') data.bin <-

Someone solved the problem of saving R-objects to a database? These are the two varaints I've tried so far without success: 1) ser = rawToChar(serialize(obj, NULL, ascii=TRUE)) dbSendQuery(link, paste("insert into table values(1, '",ser,"')",sep='')) The field to save the object in the MySQL Database is of type text. unser = dbGetQuery(link,"select

Hi, I've got a C extension structured roughly like: package/ src/ Makevars foo.c some-lib/... some-other-lib/.. where foo.c and Makevars define dependencies on some-lib and some-other-lib. Currently I'm having Makevars configure;make install some-lib and some-other-lib into a local build directory, which produces shard libraries that ultimately I reference for foo.o in