Cache the value of an R expression to an RDS file
Save the value of an expression to a cache file (of the RDS format). Next time the value is loaded from the file if it exists.
cache_rds( expr = { }, rerun = FALSE, file = "cache.rds", dir = "cache/", hash = NULL, clean = getOption("xfun.cache_rds.clean", TRUE), ... )
expr |
An R expression. |
rerun |
Whether to delete the RDS file, rerun the expression, and save the result again (i.e., invalidate the cache if it exists). |
file |
The base (see Details) cache filename under the directory
specified by the |
dir |
The path of the RDS file is partially determined by
|
hash |
A |
clean |
Whether to clean up the old cache files automatically when
|
... |
Other arguments to be passed to |
Note that the file
argument does not provide the full cache filename.
The actual name of the cache file is of the form ‘BASENAME_HASH.rds’,
where ‘BASENAME’ is the base name provided via the ‘file’ argument
(e.g., if file = 'foo.rds'
, BASENAME
would be ‘foo’), and
‘HASH’ is the MD5 hash (also called the ‘checksum’) calculated
from the R code provided to the expr
argument and the value of the
hash
argument, which means when the code or the hash
argument
changes, the ‘HASH’ string may also change, and the old cache will be
invalidated (if it exists). If you want to find the cache file, look for
‘.rds’ files that contain 32 hexadecimal digits (consisting of 0-9 and
a-z) at the end of the filename.
The possible ways to invalidate the cache are: 1) change the code in
expr
argument; 2) delete the cache file manually or automatically
through the argument rerun = TRUE
; and 3) change the value of the
hash
argument. The first two ways should be obvious. For the third
way, it makes it possible to automatically invalidate the cache based on
changes in certain R objects. For example, when you run cache_rds({ x +
y })
, you may want to invalidate the cache to rerun { x + y }
when
the value of x
or y
has been changed, and you can tell
cache_rds()
to do so by cache_rds({ x + y }, hash = list(x,
y))
. The value of the argument hash
is expected to be a list, but it
can also take a special value, "auto"
, which means
cache_rds(expr)
will try to automatically figure out the global
variables in expr
, return a list of their values, and use this list as
the actual value of hash
. This behavior is most likely to be what you
really want: if the code in expr
uses an external global variable, you
may want to invalidate the cache if the value of the global variable has
changed. Here a “global variable” means a variable not created locally
in expr
, e.g., for cache_rds({ x <- 1; x + y })
, x
is a
local variable, and y
is (most likely to be) a global variable, so
changes in y
should invalidate the cache. However, you know your own
code the best. If you want to be completely sure when to invalidate the
cache, you can always provide a list of objects explicitly rather than
relying on hash = "auto"
.
By default (the argument clean = TRUE
), old cache files will be
automatically cleaned up. Sometimes you may want to use clean = FALSE
(set the R global option options(xfun.cache_rds.clean = FALSE)
if you
want FALSE
to be the default). For example, you may not have decided
which version of code to use, and you can keep the cache of both versions
with clean = FALSE
, so when you switch between the two versions of
code, it will still be fast to run the code.
If the cache file does not exist, run the expression and save the result to the file, otherwise read the cache file and return the value.
Changes in the code in the expr
argument do not necessarily
always invalidate the cache, if the changed code is parsed
to
the same expression as the previous version of the code. For example, if
you have run cache_rds({Sys.sleep(5);1+1})
before, running
cache_rds({ Sys.sleep( 5 ) ; 1 + 1 })
will use the cache, because
the two expressions are essentially the same (they only differ in white
spaces). Usually you can add/delete white spaces or comments to your code
in expr
without invalidating the cache. See the package vignette
vignette('xfun', package = 'xfun')
for more examples.
When this function is called in a code chunk of a knitr document, you may not want to provide the filename or directory of the cache file, because they have reasonable defaults.
Side-effects (such as plots or printed output) will not be cached. The
cache only stores the last value of the expression in expr
.
f = tempfile() # the cache file compute = function(...) { res = xfun::cache_rds({ Sys.sleep(1) 1:10 }, file = f, dir = "", ...) res } compute() # takes one second compute() # returns 1:10 immediately compute() # fast again compute(rerun = TRUE) # one second to rerun compute() file.remove(f)
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