On 09/03/2018 03:59 PM, Dénes Tóth wrote:
Hi Tomas,
On 09/03/2018 11:49 AM, Tomas Kalibera wrote:
Please don't do this to get the underlying vector length (or to
achieve anything else). Setting/deleting attributes of an R object
without checking the reference count violates R semantics, which in
turn can have unpredictable results on R programs (essentially
undebuggable segfaults now or more likely later when new
optimizations or features are added to the language). Setting
attributes on objects with reference count (currently NAMED value)
greater than 0 (in some special cases 1 is ok) is cheating - please
see Writing R Extensions - and getting speedups via cheating leads to
fragile, unmaintainable and buggy code.
Hi Denes,
Please note that data.table::setattr is an exported function of a
widely used package (available from CRAN), which also has a
description in ?data.table::setattr why it might be useful.
indeed, and not your fault, but the function is cheating and that it is
in a widely used package, even exported from it, does not make it any
safer. The related optimization in base R (shallow copying) mentioned in
the documentation of data.table::setattr is on the other hand sound, it
does not break the semantics.
Of course one has to use set* functions from data.table with extreme
care, but if one does it in the right way, they can help a lot. For
example there is no real danger of using them in internal functions
where one can control what is get passed to the function or created
within the function (so when one knows that the refcount==0 condition
is true).
Extreme care is not enough as the internals can and do change (and with
the limits given by documentation, they are likely to change soon wrt to
NAMED/reference counting), not mentioning that they are very
complicated. The approach of "modify in place because we know the
reference count is 0" is particularly error prone and unnecessary. It is
unnecessary because there is documented C API for legitimate use in
packages to find out whether an object may be referenced/shared
(indirectly checks the reference count). If not, it can be modified in
place without cheating, and some packages do it. It is error prone
because the reference count can change due to many things package
developers cannot be expected to know (and again, these things change):
in set* functions for example, it will never be 0 (!), these functions
with their current API can never be implemented in current R without
breaking the semantics.
In principle one can do similar things legitimately by wrapping objects
in an environment, passing such environment (environments can
legitimately be modified in place), checking the contained objects have
reference count of 1 (not shared), and if so, modifying them in place.
But indeed, as soon as such objects become shared, there is no way out,
one has to copy (in the current R).
Best
Tomas
(Notwithstanding the above, but also supporting you argumentation, it
took me hours to debug a particular problem in one of my internal
packages, see https://github.com/Rdatatable/data.table/issues/1281)
In the present case, an important and unanswered question is (cited
from Henrik):
>>> However, I'm concerned that calling unclass(x) may trigger an
>>> expensive copy internally in some cases. Is that concern unfounded?
If no copy is made, length(unclass(x)) beats length(setattr(..)) in
all scenarios.
Doing so in packages is particularly unhelpful to the whole community
- packages should only use the public API as documented.
Similarly, getting a physical address of an object to hack around
whether R has copied it or not should certainly not be done in
packages and R code should never be working with or even obtaining
physical address of an object. This is also why one cannot obtain
such address using base R (apart in textual form from certain
diagnostic messages where it can indeed be useful for low-level
debugging).
Getting the physical address of the object was done exclusively for
demonstration purposes. I totally agree that is should not be used for
the purpose you described and I have never ever done so.
Regards,
Denes
Tomas
On 09/02/2018 01:19 AM, Dénes Tóth wrote:
The solution below introduces a dependency on data.table, but
otherwise it does what you need:
---
# special method for Foo objects
length.Foo <- function(x) {
length(unlist(x, recursive = TRUE, use.names = FALSE))
}
# an instance of a Foo object
x <- structure(list(a = 1, b = list(b1 = 1, b2 = 2)), class = "Foo")
# its length
stopifnot(length(x) == 3L)
# get its length as if it were a standard list
.length <- function(x) {
cls <- class(x)
# setattr() does not make a copy, but modifies by reference
data.table::setattr(x, "class", NULL)
# get the length
len <- base::length(x)
# re-set original classes
data.table::setattr(x, "class", cls)
# return the unclassed length
len
}
# to check that we do not make unwanted changes
orig_class <- class(x)
# check that the address in RAM does not change
a1 <- data.table::address(x)
# 'unclassed' length
stopifnot(.length(x) == 2L)
# check that address is the same
stopifnot(a1 == data.table::address(x))
# check against original class
stopifnot(identical(orig_class, class(x)))
---
On 08/24/2018 07:55 PM, Henrik Bengtsson wrote:
Is there a low-level function that returns the length of an object 'x'
- the length that for instance .subset(x) and .subset2(x) see? An
obvious candidate would be to use:
.length <- function(x) length(unclass(x))
However, I'm concerned that calling unclass(x) may trigger an
expensive copy internally in some cases. Is that concern unfounded?
Thxs,
Henrik
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