drake_history {drake}R Documentation

History and provenance [Stable]


See the history and provenance of your targets: what you ran, when you ran it, the function arguments you used, and how to get old data back.


drake_history(cache = NULL, history = NULL, analyze = TRUE, verbose = NULL)



drake cache as created by new_cache(). See also drake_cache().


Logical, whether to record the build history of your targets. You can also supply a txtq, which is how drake records history. Must be TRUE for drake_history() to work later.


Logical, whether to analyze drake_plan() commands for arguments to function calls. Could be slow because this requires parsing and analyzing lots of R code.


Deprecated on 2019-09-11.


drake_history() returns a data frame with the following columns.

If analyze is TRUE, various other columns are included to show the explicitly-named length-1 arguments to function calls in the commands. See the "Provenance" section for more details.


A data frame of target history.


If analyze is TRUE, drake scans your drake_plan() commands for function arguments and mentions them in the history. A function argument shows up if and only if: 1. It has length 1.
2. It is atomic, i.e. a base type: logical, integer, real, complex, character, or raw.
3. It is explicitly named in the function call, For example, x is detected as 1 in fn(list(x = 1)) but not f(list(1)). The exceptions are file_out(), file_in(), and knitr_in(). For example, filename is detected as "my_file.csv" in process_data(filename = file_in("my_file.csv")). NB: in process_data(filename = file_in("a", "b")) filename is not detected because the value must be atomic.


## Not run: 
isolate_example("contain side-effects", {
if (requireNamespace("knitr", quietly = TRUE)) {
# First, let's iterate on a drake workflow.
make(my_plan, history = TRUE, verbose = 0L)
# Naturally, we'll make updates to our targets along the way.
reg2 <- function(d) {
  d$x2 <- d$x ^ 3
  lm(y ~ x2, data = d)
make(my_plan, history = TRUE, verbose = 0L)
# The history is a data frame about all the recorded runs of your targets.
out <- drake_history(analyze = TRUE)
# Let's use the history to recover the oldest version
# of our regression2_small target.
oldest_reg2_small <- max(which(out$target == "regression2_small"))
hash_oldest_reg2_small <- out[oldest_reg2_small, ]$hash
cache <- drake_cache()
# If you run clean(), drake can still find all the targets.
# But if you run clean() with garbage collection,
# older versions of your targets may be gone.
clean(large, garbage_collection = TRUE)

## End(Not run)

[Package drake version 7.13.9 Index]