This is a small release to fix compatibility with readr v2.0.0. In addition, various minor improvements have been made across to package to get it back to CRAN.
This is a small release to fix compatibility with dplyr v1.0.0.
This is a small release to fix compatibility with tidyr v1.0.0. Furthermore, the formerly defunct functions following the old naming conventions (like find_article(), find_references(), etc.) have been removed.
This is another small release to fix compatibility with readr v1.3.0 and tibble v2.0.0. There are no other changes.
This is a small release, mainly to fix compatibility with version 1.2.0 of readr. There is one breaking change however:
jst_get_refernces have been renamed to avoid ambiguity when matching with output from jst_get_article. All columns now have a ref_* prefix.sample_ has been replaced with article_ or removed altogether.jst_define_import due to upcoming release of rlang v0.3.0.jst_get_journal_overview(most_recent = T)) had to be removed due changes on their server. I will try to find a solution with JSTOR support so we can add the functionality again.jst_define_import now prints the specification in a pretty and informative way.jst_define_import now checks the definition more extensively: jst_define_import(article = jst_get_book) or similar mis-specifications will raise an error.find_* functions is now defunct (they raise an error).This is a hotfix to resolve an issue with writing to other directories than temporary folders during tests, which should not have happend in the first place.
jstor is now part of rOpenSci.new_col for jst_unify_journal_id and jst_add_total_pages, since both built on the dev version of rlang. Once this version is on CRAN, they will be re-introduced.jst_import and jst_import_zip now use futures as a backend for parallel processing. This makes internals more compact and reduces dependencies. Furthermore this reduces the number of arguments, since the argument cores has been removed. By default, the functions run sequentially. If you want them to execute in parallel, use futures:
library(future)
plan(multiprocess)
jst_import_zip("zip-archive.zip",
import_spec = jst_define_import(article = jst_get_article),
out_file = "outfile")If you want to terminate the proceses, at least on *nix-systems you need to kill them manually (once again).
jst_*. The former group of find_* functions is now called jst_get_*, as in jst_get_article(). The previous functions have been deprecated and will be removed before submission to CRAN.file_name, and the corresponding helper to get this file name from get_basename to jst_get_file_name.There is a new set of functions which lets you directly import files from .zip-archives: jst_import_zip() and jst_define_import().
In the following example, we have a zip-archive from DfR and want to import metadata on books and articles. For all articles we want to apply jst_get_article() and jst_get_authors(), for books only jst_get_book(), and we want to read unigrams (ngram1).
First we specify what we want, and then we apply it to our zip-archive:
# specify definition
import_spec <- jst_define_import(article = c(jst_get_article, jst_get_authors),
book = jst_get_book,
ngram1 = jst_get_ngram)
# apply definition to archive
jst_import_zip("zip_archive.zip",
import_spec = import_spec,
out_file = "out_path")If the archive contains also research reports, pamphlets or other ngrams, they will not be imported. We could however change our specification, if we wanted to import all kinds of ngrams (given that we originally requested them from DfR):
# import multiple forms of ngrams
import_spec <- jst_define_import(article = c(jst_get_article, jst_get_authors),
book = jst_get_book,
ngram1 = jst_get_ngram,
ngram2 = jst_get_ngram,
ngram3 = jst_get_ngram)Note however that for larger archives, importing all ngrams takes a very long time. It is thus advisable to only import ngrams for articles which you want to analyse, i.e. most likely a subset of the initial request. The new function jst_subset_ngrams() helps you with this (see also the section on importing bigrams in the case study.
Before importing all files from a zip-archive, you can get a quick overview with jst_preview_zip().
The new vignette("known-quirks") lists common problems with data from JSTOR/DfR. Contributions with further cases are welcome!
jst_get_journal_overview() supplies a tibble with contextual information about the journals in JSTOR.jst_combine_outputs() applies jst_re_import() to a whole directory and lets you combine all related files in one go. It uses the file structure that jst_import() and jst_import_zip() provide as a heuristic: a filename with a dash and one or multiple digits at its end (filename-1.csv). All files with identical names (disregarding dash and digits) are combined into one file.jst_re_import() lets you re_import a .csv file that jstor_import() or jst_import_zip() had exported. It tries to guess the type of content based on the column names or, if column names are not available, from the number of columns, raising a warning if guessing fails and reverting to a generic import.jst_subset_ngrams() lets you create a subset of ngram files within a zip-file which you can import with jst_get_ngram().jst_clean_page() tries to turn a character vector with pages into a numeric one, jst_unify_journal_id() merges different specifications of journals into one, jst_add_total_pages() adds a total count of pages per article, and jst_augment() calls all three functions to clean the data set in one go.n_batches which lets you specify the number of batches directlyjstor_import from parallel::mclapply to foreach::foreach with snow as a backend for %dopar%.jstor_import now writes column names by default #29get_basename helps to get the basename of a file without its extensionfind_article does not coerce days and months to integer any more, since there might be information stored as text.NEWS.md file to track changes to the package.