This function does not apply to
in-memory caches such as storr_environment()
.
this_cache(path = drake::default_cache_path(), force = FALSE,
verbose = drake::default_verbose(), fetch_cache = NULL,
console_log_file = NULL)
file path of the cache
deprecated is compatible with your current version of drake.
logical or numeric, control printing to the console.
Use pkgconfig
to set the default value of verbose
for your R session:
for example, pkgconfig::set_config("drake::verbose" = 2)
.
0
or FALSE
: print nothing.
1
or TRUE
: print only targets to build.
2
: also print checks and cache info.
3
: also print any potentially missing items.
4
: also print imports and writes to the cache.
character vector containing lines of code.
The purpose of this code is to fetch the storr
cache
with a command like storr_rds()
or storr_dbi()
,
but customized. This feature is experimental. It will turn out
to be necessary if you are using both custom non-RDS caches
and distributed parallelism (parallelism = "future_lapply"
or "Makefile"
) because the distributed R sessions
need to know how to load the cache.
character scalar,
connection object (such as stdout()
) or NULL
.
If NULL
, console output will be printed
to the R console using message()
.
If a character scalar, console_log_file
should be the name of a flat file, and
console output will be appended to that file.
If a connection object (e.g. stdout()
)
warnings and messages will be sent to the connection.
For example, if console_log_file
is stdout()
,
warnings and messages are printed to the console in real time
(in addition to the usual in-bulk printing
after each target finishes).
A drake/storr cache at the specified path, if it exists.
# NOT RUN {
test_with_dir("Quarantine side effects.", {
clean(destroy = TRUE)
try(x <- this_cache(), silent = FALSE) # The cache does not exist yet.
load_mtcars_example() # Get the code with drake_example("mtcars").
make(my_plan) # Run the project, build the targets.
y <- this_cache() # Now, there is a cache.
z <- this_cache(".drake") # Same as above.
manual <- new_cache("manual_cache") # Make a new cache.
manual2 <- get_cache("manual_cache") # Get the new cache.
})
# }
Run the code above in your browser using DataLab