Caching requests from the UN Comtrade API

There is four reasons why we might want to use caching for our requests to the UN Comtrade API:

The UN Comtrade API at times can be a bit slow 🐌
Free users only have a limited amount of requests 💸
We might want to insulate our analysis against updates to the official data 📦
It saves energy and is climate friendly to not repeat requests that return the same data every time. 🌍

The package offers a caching option, that is fairly easy to use.

The basics of caching 💽

When you set the respective argument to TRUE, a directory named comtradr will be set up in your cache directory. This is determined by the rappdirs::user_cache_dir function. It has the default values for a cache as used by cachem::cache_disk.

See here: https://cachem.r-lib.org/reference/cache_disk.html

and here: https://rappdirs.r-lib.org/reference/user_cache_dir.html

#### Now
q <- ct_get_data(reporter = "USA", 
               partner = c("DEU", "FRA", "JPN", "MEX"), 
               flow_direction = "import",
               start_date = 2020,
               end_date = 2023,
               cache = TRUE) # <----- set this argument to TRUE

If you want to modify these parameters, you need to set environment variables. You can use the usethis::edit_r_environ(scope = 'project) function to set them only for your current project.

ℹ️ Restart your R Session after setting the environment variables! 💡

The parameters are:

COMTRADR_CACHE_MAX_SIZE = Maximum size of the cache, in bytes. If the cache exceeds this size, cached objects will be removed according to the value of the evict. Use Inf for no size limit. The default is 1 gigabyte.
COMTRADR_CACHE_MAX_AGE = Maximum age of files in cache before they are evicted, in seconds. Use Inf for no age limit.
COMTRADR_CACHE_MAX_N = Maximum number of objects in the cache. If the number of objects exceeds this value, then cached objects will be removed according to the value of evict. Use Inf for no limit of number of items.
R_USER_CACHE_DIR = Directory where the cached files will be saved.

See here for the details on pruning and other functions of cachem: https://cachem.r-lib.org/reference/cache_disk.html