Create a target that downloads file from one or more URLs and automatically reruns when the remote data changes (according to the ETags or last-modified time stamps).

tar_download(
  name,
  urls,
  paths,
  method = NULL,
  quiet = TRUE,
  mode = "w",
  cacheOK = TRUE,
  extra = NULL,
  headers = NULL,
  iteration = targets::tar_option_get("iteration"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue")
)

Arguments

name

Symbol, name of the target. Subsequent targets can refer to this name symbolically to induce a dependency relationship: e.g. tar_target(downstream_target, f(upstream_target)) is a target named downstream_target which depends on a target upstream_target and a function f(). In addition, a target's name determines its random number generator seed. In this way, each target runs with a reproducible seed so someone else running the same pipeline should get the same results, and no two targets in the same pipeline share the same seed. (Even dynamic branches have different names and thus different seeds.) You can recover the seed of a completed target with tar_meta(your_target, seed) and run set.seed() on the result to locally recreate the target's initial RNG state.

urls

Character vector of URLs to track and download. Must be known and declared before the pipeline runs.

paths

Character vector of local file paths to download each of the URLs. Must be known and declared before the pipeline runs.

method

Method to be used for downloading files. Current download methods are "internal", "wininet" (Windows only) "libcurl", "wget" and "curl", and there is a value "auto": see ‘Details’ and ‘Note’.

The method can also be set through the option "download.file.method": see options().

quiet

If TRUE, suppress status messages (if any), and the progress bar.

mode

character. The mode with which to write the file. Useful values are "w", "wb" (binary), "a" (append) and "ab". Not used for methods "wget" and "curl". See also ‘Details’, notably about using "wb" for Windows.

cacheOK

logical. Is a server-side cached value acceptable?

extra

character vector of additional command-line arguments for the "wget" and "curl" methods.

headers

named character vector of HTTP headers to use in HTTP requests. It is ignored for non-HTTP URLs. The User-Agent header, coming from the HTTPUserAgent option (see options) is used as the first header, automatically.

iteration

Character of length 1, name of the iteration mode of the target. Choices:

  • "vector": branching happens with vctrs::vec_slice() and aggregation happens with vctrs::vec_c().

  • "list", branching happens with [[]] and aggregation happens with list().

  • "group": dplyr::group_by()-like functionality to branch over subsets of a data frame. The target's return value must be a data frame with a special tar_group column of consecutive integers from 1 through the number of groups. Each integer designates a group, and a branch is created for each collection of rows in a group. See the tar_group() function to see how you can create the special tar_group column with dplyr::group_by().

error

Character of length 1, what to do if the target stops and throws an error. Options:

  • "stop": the whole pipeline stops and throws an error.

  • "continue": the whole pipeline keeps going.

  • "abridge": any currently running targets keep running, but no new targets launch after that. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)

memory

Character of length 1, memory strategy. If "persistent", the target stays in memory until the end of the pipeline (unless storage is "worker", in which case targets unloads the value from memory right after storing it in order to avoid sending copious data over a network). If "transient", the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files such as format = "aws_file", this memory strategy applies to temporary local copies of the file in _targets/scratch/": "persistent" means they remain until the end of the pipeline, and "transient" means they get deleted from the file system as soon as possible. The former conserves bandwidth, and the latter conserves local storage.

garbage_collection

Logical, whether to run base::gc() just before the target runs.

deployment

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). If "worker", the target builds on a parallel worker. If "main", the target builds on the host machine / process managing the pipeline.

priority

Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get built earlier (and polled earlier in tar_make_future()).

resources

Object returned by tar_resources() with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities of targets. See tar_resources() for details.

storage

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's return value is sent back to the host machine and saved/uploaded locally.

  • "worker": the worker saves/uploads the value.

  • "none": almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except when retrieval = "none").

    If you select storage = "none", then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file" or "aws_file") it is the responsibility of the user to write to tar_path() from inside the target. An example target could look something like tar_target(x, saveRDS("value", tar_path(create_dir = TRUE)); "ignored", storage = "none")`.

    The distinguishing feature of storage = "none" (as opposed to format = "file" or "aws_file") is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary, storage = "none" is completely unnecessary if format is "file" or "aws_file".

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's dependencies are loaded on the host machine and sent to the worker before the target builds.

  • "worker": the worker loads the targets dependencies.

  • "none": the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.

Value

A list of two target objects, one upstream and one downstream. The upstream one watches a URL for changes, and the downstream one downloads it. See the "Target objects" section for background.

Details

tar_download() creates a pair of targets, one upstream and one downstream. The upstream target uses format = "url" (see targets::tar_target()) to track files at one or more URLs, and automatically invalidate the target if the ETags or last-modified time stamps change. The downstream target depends on the upstream one, downloads the files, and tracks them using format = "file".

Target objects

Most tarchetypes functions are target factories, which means they return target objects or lists of target objects. Target objects represent skippable steps of the analysis pipeline as described at https://books.ropensci.org/targets/. Please read the walkthrough at https://books.ropensci.org/targets/walkthrough.html to understand the role of target objects in analysis pipelines.

For developers, https://wlandau.github.io/targetopia/contributing.html#target-factories explains target factories (functions like this one which generate targets) and the design specification at https://books.ropensci.org/targets-design/ details the structure and composition of target objects.

See also

Other targets with custom invalidation rules: tar_change(), tar_force(), tar_skip()

Examples

if (identical(Sys.getenv("TAR_LONG_EXAMPLES"), "true")) { targets::tar_dir({ # tar_dir() runs code from a temporary directory. targets::tar_script({ list( tarchetypes::tar_download( x, urls = c("https://httpbin.org/etag/test", "https://r-project.org"), paths = c("downloaded_file_1", "downloaded_file_2") ) ) }) targets::tar_make() targets::tar_read(x) }) }