set_cache | R Documentation |
By default, epidatr re-requests data from the API on every call of fetch
.
In case you find yourself repeatedly calling the same data, you can enable
the cache using either this function for a given session, or environmental
variables for a persistent cache.
The typical recommended workflow for using the cache is to set the
environmental variables EPIDATR_USE_CACHE=TRUE
and
EPIDATR_CACHE_DIRECTORY="/your/directory/here"
in your .Renviron
, for
example by calling usethis::edit_r_environ()
.
See the parameters below for some more configurables if you're so inclined.
set_cache
(re)defines the cache to use in a particular R session. This does
not clear existing data at any previous location, but instead creates a
handle to the new cache using cachem
that seamlessly handles caching for you.
Say your cache is normally stored in some default directory, but for the
current session you want to save your results in
~/my/temporary/savedirectory
, then you would call set_cache(dir = "~/my/temporary/savedirectory")
.
Or if you know the data from 2 days ago is wrong, you could call
set_cache(days = 1)
to clear older data whenever the cache is referenced.
In both cases, these changes would only last for a single session (though the
deleted data would be gone permanently!).
An important feature of the caching in this package is that only calls which
specify either issues
before a certain date, or as_of
before a certain
date will actually cache. For example the call
pub_covidcast( source = "jhu-csse", signals = "confirmed_7dav_incidence_prop", geo_type = "state", time_type = "day", geo_values = "ca,fl", time_values = epirange(20200601, 20230801) )
won't cache, since it is possible for the cache to be invalidated by new releases with no warning. On the other hand, the call
pub_covidcast( source = "jhu-csse", signals = "confirmed_7dav_incidence_prop", geo_type = "state", time_type = "day", geo_values = "ca,fl", time_values = epirange(20200601, 20230801), as_of = "2023-08-01" )
will cache, since normal new versions of data can't invalidate it (since
they would be as_of
a later date). It is still possible that Delphi may
patch such data, but the frequency is on the order of months rather than
days. We are working on creating a public channel to communicate such
updates. While specifying issues
will usually cache, a call with
issues="*"
won't cache, since its subject to cache invalidation by normal
versioning.
On the backend, the cache uses cachem, with filenames generated using an md5 encoding of the call url. Each file corresponds to a unique epidata-API call.
set_cache(
cache_dir = NULL,
days = NULL,
max_size = NULL,
logfile = NULL,
confirm = TRUE,
startup = FALSE
)
cache_dir |
the directory in which the cache is stored. By default, this
is |
days |
the maximum length of time in days to keep any particular cached
call. By default this is |
max_size |
the size of the entire cache, in MB, at which to start
pruning entries. By default this is |
logfile |
where cachem's log of transactions is stored, relative to the
cache directory. By default, it is |
confirm |
whether to confirm directory creation. default is |
startup |
indicates whether the function is being called on
startup. Affects suppressability of the messages. Default is |
NULL
no return value, all effects are stored in the package
environment
clear_cache
to delete the old cache while making a new one,
disable_cache
to disable without deleting, and cache_info
set_cache(
cache_dir = tempdir(),
days = 14,
max_size = 512,
logfile = "logs.txt"
)
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