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#' Imports time series data from BCB-SGS System (Banco Central do Brasil, sistema de series temporais)
#'
#' Using BCB's oficial API at <https://www.bcb.gov.br/>, this function will download data for a specific set of ids and dates.
#' The main advantage is the use of caching and parallel computing for fast operations. You can search for available series at <http://www.bcb.gov.br/?sgs>
#'
#' @param id Id of time series. The name of the vector sets the name of the series in the output (e.g i.d <- c('SELIC' = 11)).
#' You can search for ids in the official BCB-SGS webpage <http://www.bcb.gov.br/?sgs>
#' @param first.date First date of time series
#' @param last.date Last date of time series
#' @param format.data The format of the datasets - long (default, series incremented by rows) or wide (series incremented by columns)
#' @param be.quiet Logical. Should functions output messages to screen? - FALSE (default) or TRUE
#' @param use.memoise Logical. Sets the use of caching system - TRUE (default) or FALSE
#' @param cache.path Path to save cache files - 'rbcb2_cache' (default)
#' @param do.parallel Logical for parallel data importation - FALSE (default)
#'
#' @return A dataframe with requested datasets
#' @export
#'
#' @examples
#'
#' my.id <- c('Taxa de juros - Selic' = 11)
#' df <- gbcbd_get_series(my.id, cache.path = tempdir())
gbcbd_get_series <- function(id,
first.date = Sys.Date() - 10*365,
last.date = Sys.Date(),
format.data = 'long',
be.quiet = FALSE,
use.memoise = TRUE,
cache.path = gbcbd_get_default_cache_folder(),
do.parallel = FALSE) {
# check if arguments make sense
first.date <- as.Date(first.date)
if (!methods::is(first.date, 'Date')) {
stop('Argument first.date is not a valid date!')
}
last.date <- as.Date(last.date)
if (!methods::is(last.date, 'Date')) {
stop('Argument last.date is not a valid date!')
}
if (last.date < first.date) {
stop('It seems that last.date < first.date. Check your inputs.')
}
if (is.null(names(id))) {
names(id) <- c(paste0('id = ', id))
}
possible.values <- c('long', 'wide')
if (!(format.data %in% possible.values)) {
stop(paste0('Input format.data should be "long" or "wide".'))
}
# check if ids exist
# REMOVED: Api at https://dadosabertos.bcb.gov.br/ does not contain all data from SGS
#
# df.series <- gbcbd_get_available_series(use.memoise = use.memoise,
# cache.path = cache.path)
# flag <- !(id %in% df.series$id.num)
#
# if (any(flag)) {
# failed.ids <- id[flag]
#
# stop(paste0("Can't find the following ids within the BCB-SGS system:\n\n",
# paste0(paste0(failed.ids, ' (', names(failed.ids), ')'), collapse = ', ')),
# '\n\n')
# }
#set args
my.args <- list(id = id,
series.name = names(id),
first.date = first.date,
last.date = last.date,
format.data = format.data,
be.quiet = be.quiet,
use.memoise = use.memoise,
cache.path = cache.path)
if (!do.parallel) {
my.l <- purrr::pmap(.l = my.args ,
gbcbd_get_single_series)
} else {
# find number of used cores
formals.parallel <- formals(future::plan())
used.workers <- formals.parallel$workers
available.cores <- future::availableCores()
gbcbd_message(paste0('\nRunning parallel GetBCBData with ', used.workers, ' cores (',
available.cores, ' available)',
'\n\n'),
be.quiet = be.quiet)
# test if plan() was called
msg <- utils::capture.output(future::plan())
flag <- stringr::str_detect(msg[1], 'sequential')
if (flag) {
stop(paste0('When using do.parallel = TRUE, you need to call future::plan() to configure your parallel settings. \n',
'A suggestion, write the following lines:\n\n',
'future::plan(future::multisession, workers = floor(future::availableCores()/2))',
'\n\n',
'The last line should be placed just before calling GetBCBData.\n',
'Notice it will use half of your available cores so that your OS has some room to breathe.'))
}
my.l <- furrr::future_pmap(.l = my.args,
gbcbd_get_single_series,
.progress = TRUE)
}
# check and change desired format output
if (format.data == 'long') {
df.out <- dplyr::bind_rows(my.l)
} else {
df.out <- purrr::reduce(my.l,
dplyr::full_join, by = "ref.date")
# order by date
idx <- order(df.out$ref.date)
df.out <- df.out[idx, ]
}
gbcbd_message('\n', be.quiet)
return(df.out)
}
#' Gets a single series from BCB-SGS (internal use)
#'
#' This function should not be called directly. Its a helper for gbcbd_get_series
#'
#'@noRd
gbcbd_get_single_series <- function(id,
series.name = paste0('SGS ', id),
first.date = Sys.Date()-360,
last.date = Sys.Date(),
format.data = 'long',
be.quiet = FALSE,
use.memoise = TRUE,
cache.path = gbcbd_get_default_cache_folder()) {
my.url <- sprintf('https://api.bcb.gov.br/dados/serie/bcdata.sgs.%s/dados?formato=json',
id)
my.url <- sprintf(paste0('http://api.bcb.gov.br/dados/serie/bcdata.sgs.',
'%s','/dados?formato=json&',
'dataInicial=%s&',
'dataFinal=%s'),
id,
format(first.date, '%d/%m/%Y'),
format(last.date, '%d/%m/%Y'))
gbcbd_message(paste0('\nFetching ',
series.name, ' [', id, '] ',
'from BCB-SGS'),
be.quiet)
if (use.memoise) {
gbcbd_message(' with cache ', be.quiet)
}
else {
gbcbd_message(' from Online API ', be.quiet)
}
#cache.db = memoise::cache_filesystem(cache.path)
cache.db = cache.path
fct_JSON <- gbcbd_get_JSON_fct(use.memoise,
cache.db)
df <- NULL
try({
utils::capture.output({
df <- fct_JSON(my.url)
})
})
if (is.null(df)) {
df <- dplyr::tibble(ref.date = NA,
value = NA,
id.num = id,
series.name = series.name)
warning(paste0('\n\t Error in fetching data\n'))
warning(paste0('\n\tId ', id, ' does not seem available at BCB-SGS. Check it again at : ',
'<http://www.bcb.gov.br/?sgs>'))
return(df)
} else {
gbcbd_message(paste0('\n\t Found ', nrow(df), ' observations'),
be.quiet)
}
df$data <- as.Date(df$data, '%d/%m/%Y')
df$valor <- as.numeric(df$valor, '%d/%m/%Y')
df$id.num <- id
df$series.name <- series.name
# fix for "no visible global fct definition" msg from CRAN CHECK
#data <- valor <- NULL
df <- dplyr::rename(df,
'ref.date' = 'data',
'value' = 'valor')
# change format
if (format.data == 'wide') {
df$id.num <- NULL
df$series.name <- NULL
names(df) <- c('ref.date', series.name)
}
return(df)
}
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