The goal of ‘mustashe’ is to save time on long-running computations by storing and reloading the resulting object after the first run. The next time the computation is run, instead of evaluating the code, the stashed object is loaded. ‘mustashe’ is great for storing intermediate objects in an analysis.
You can install the released version of ‘mustashe’ from CRAN with:
And the development version from GitHub with:
# install.packages("devtools") devtools::install_github("jhrcook/mustashe")
The ‘mustashe’ package is loaded like any other, using the
Below is a simple example of how to use the
stash() function from ‘mustashe’.
Let’s say, for part of an analysis, we are running a long simulation to generate random data
rnd_vals. This is mocked below using the
Sys.sleep() function. We can time this process using the ‘tictoc’ library.
Now, if we come back tomorrow and continue working on the same analysis, the second time this process is run the code is not evaluated because the code passed to
stash() has not changed. Instead, the random values
rnd_vals is loaded.
A common problem with storing intermediates is that they have dependencies that can change. If a dependency changes, then we want the stashed value to be updated. This is accomplished by passing the names of the dependencies to the
For instance, let’s say we are calculating some value
x. (For the following example, I will use a print statement to indicate when the code is evaluated.)
x is not changed, then the code for
foo does not get re-evaluated.
x does change, then
foo gets re-evaluated.
The inspiration for this package came from the
cache() feature in the ‘ProjectTemplate’ package. While the functionality and implementation are a bit different, this would have been far more difficult to do without referencing the source code from ‘ProjectTemplate’.