makeRun your project (build the targets).
make(plan, targets = drake::possible_targets(plan), envir = parent.frame(),
verbose = TRUE, parallelism = drake::default_parallelism(), jobs = 1,
packages = (.packages()), prework = character(0),
prepend = character(0), command = "make",
args = drake::default_system2_args(jobs = jobs, verbose = verbose))workflow plan data frame.
A workflow plan data frame is a data frame
with a target column and a command column.
Targets are the objects and files that drake generates,
and commands are the pieces of R code that produce them.
Use the function plan() to generate workflow plan
data frames easily, and see functions analyses(),
summaries(), evaluate(),
expand(), and gather() for
easy ways to generate large workflow plan data frames.
character string, names of targets to build. Dependencies are built too.
environment to use. Defaults to the current
workspace, so you should not need to worry about this
most of the time. A deep copy of envir is made,
so you don't need to worry about your workspace being modified
by make. The deep copy inherits from the global environment.
Wherever necessary, objects and functions are imported
from envir and the global environment and
then reproducibly tracked as dependencies.
logical, whether to print progress to the console. Skipped objects are not printed.
character, type of parallelism to use.
See parallelism_choices() for the choices
for this argument, and run ?parallelism_choices
for an explanation of each.
To use parallelism at all, be sure that jobs >= 2. If
parallelism is "mclapply", drake will use
parallel::mclapply() to distribute targets across
parallel processes wherever possible. (This is not possible on
Windows.) Setting parallelism to "parLapply"
is similar, except that it uses parallel::parLapply().
It works on Windows, but it requires more overhead (except
if jobs == 1, in which case no "cluster" is created).
If "Makefile", drake will write
and execute a Makefile to distribute targets across separate
R sessions. The vignettes (vignette(package = "drake"))
show how to turn those R
sessions into separate jobs on a cluster. Read the vignettes
to learn how to take advantage of multiple nodes on a
supercomputer. WARNING: the Makefile is NOT standalone.
Do not run outside of make().
For parallelism == "Makefile", Windows users will need
to download and install Rtools.
number of parallel processes or jobs to run.
Windows users should not set jobs > 1 if
parallelism is "mclapply" because
mclapply() is based on forking. Windows users
who use parallelism == "Makefile" will need to
download and install Rtools.
character vector packages to load, in the order
they should be loaded. Defaults to (.packages()), so you
shouldn't usually need to set this manually. Just call
library() to load your packages before make().
However, sometimes packages need to be strictly forced to load
in a certian order, especially if parallelism is
"Makefile". To do this, do not use library()
or require() or loadNamespace() or
attachNamespace() to load any libraries beforehand.
Just list your packages in the packages argument in the order
you want them to be loaded.
If parallelism is "mclapply",
the necessary packages
are loaded once before any targets are built. If parallelism is
"Makefile", the necessary packages are loaded once on
initialization and then once again for each target right
before that target is built.
character vector of lines of code to run
before build time. This code can be used to
load packages, set options, etc., although the packages in the
packages argument are loaded before any prework is done.
If parallelism is "mclapply", the prework
is run once before any targets are built. If parallelism is
"Makefile", the prework is run once on initialization
and then once again for each target right before that target is built.
lines to prepend to the Makefile if parallelism
is "Makefile". See the vignettes
(vignette(package = "drake"))
to learn how to use prepend
to take advantage of multiple nodes of a supercomputer.
character scalar, command to call the Makefile
generated for distributed computing.
Only applies when parallelism is "Makefile".
Defaults to the usual "make", but it could also be
"lsmake" on supporting systems, for example.
command and args are executed via
system2(command, args) to run the Makefile.
If args has something like "--jobs=2", or if
jobs >= 2 and args is left alone, targets
will be distributed over independent parallel R sessions
wherever possible.
command line arguments to call the Makefile for
distributed computing. For advanced users only. If set,
jobs and verbose are overwritten as they apply to the
Makefile.
command and args are executed via
system2(command, args) to run the Makefile.
If args has something like "--jobs=2", or if
jobs >= 2 and args is left alone, targets
will be distributed over independent parallel R sessions
wherever possible.