This package aims to introduce basic functionalities to access the Zotero API. Its main goal at this stage is to have enough functionalities to facilitate resizing the storage space used, by ordering items by attachment size, and by allowing to add items to a collection if certain criteria are met.
It now tenatively allows to create new Zotero items, and to take a csv
file (or data frame) and import it into Zotero, as long as data are
properly mapped. zoteror has function that facilitate giving to
tabular data a structure that can properly be read into Zotero. See at
the bottom of this document for an example [this is still
work-in-progress and not functional for all item/attribute types].
if(!require("remotes")) install.packages("remotes")
remotes::install_github(repo = "giocomai/zoteror")credentials <- zot_auth(cache = TRUE)The verification code that appears at the end of the URL after
authorization in browser should be input as verification PIN. If the
parameter store is enabled - AuthZot(cache=TRUE) - zoteror stores the
credentials in a local file called “zotero_credentials.rds”, which
should be considered confidential since it provides access to a given
Zotero account. If a pre-existing “zotero_credentials.rds” exists, it
is loaded automatically.
N.B. At this stage, it may be easier to actually login on Zotero, go to the (Feeds/API page in Settings)[https://www.zotero.org/settings/keys], and create an API from there.
Instead of inputting user and credentials each time a function is
run, it is easier to set them with ZotSetOptions at the beginning of
every session:
zot_set_options(user = 12345, credentials = "<API>")The respective parameters can then be left empty (NULL, which is
default) when calling functions.
key <- zot_create_collection(collection_name = "zoteror") Creates a new collection by the given name, and outputs its key. If a
collection with the same name already exists, it does not create a new
one, but rather outputs the key of the pre-existing collection.
zot_create_collection() requires an API key with write access.
item <- zot_read_item(id = "<item_id>")Outputs a list with all available information on the item.
zot_which_collection allows to find out in which collection is an
item. If the ID given refers to a ‘child item’ (e.g. a pdf attachment to
a journal article), the function looks for the collection(s) in which
the parent item is included. [attachments have separate IDs, and are
thus to be found in a collection only if the ‘parent item’
is]
item <- zot_wich_collection(id = "<item_id>")zot_add_to_collection(id = "<item_id>", collection_id = "<collection_id>")size <- zot_size(path = "/home/user/.zotero/XXXXXX.default/zotero/storage")
# by default, this was inside .mozilla/firefox subdirectory in earlier versionsIt requires the full path to the local Zotero folder. Outputs size of stored items in bytes and in human-readable Mb.
library("zoteror")
library("dplyr")
zot_set_options(user = 12345, credentials = "<API>") # insert user id and API credentials
size <- zot_size(path = "/home/user/.zotero/XXXXXX.default/zotero/storage") # full path to Zotero storage folder
bigIDs <- size %>%
filter(Size>5000000) %>%
pull(ID) # filters items larger than 5MB
big_collection_id <- zot_create_collection(collectionName = "plus5") #creates collection "plus5", and if already existing simply outputs its key
for (i in bigIDs) {
try(zot_add_to_collection(id = bigIDs$ID[i]i,
collection_id = big_collection_id))
}This adds all items larger tan 5Mb to a collection called “plus5”.
zot_add_to_collection() is inside try to prevent timeout and other
errors to stop the script. While running the script outputs the title of
items being added to the collection. Currently it goes quite slowly,
thus giving time to stop the script if something odd happens. API would
allow much more efficient ways of bulk changing items; when the package
will work more efficiently, it will still allow to keep the process
artificially slow in order to monitor potential oddities.
In order to make sure your data match Zotero fields for a given item type, you can first create a csv template for the given type and paste your data there. Not all columns need to be filled.
library(zoteror)
zot_create_csv_template(item_type = "book", cache = FALSE)
#> # A tibble: 0 x 27
#> # … with 27 variables: itemType <chr>, title <chr>, creators <chr>,
#> # abstractNote <chr>, series <chr>, seriesNumber <chr>, volume <chr>,
#> # numberOfVolumes <chr>, edition <chr>, place <chr>, publisher <chr>,
#> # date <chr>, numPages <chr>, language <chr>, ISBN <chr>, shortTitle <chr>,
#> # url <chr>, accessDate <chr>, archive <chr>, archiveLocation <chr>,
#> # libraryCatalog <chr>, callNumber <chr>, rights <chr>, extra <chr>,
#> # tags <chr>, collections <chr>, relations <chr>If you enable cache=TRUE it will store a csv file in the
zot_csv_templates sub-folder of the current working directory.
Translation in other languages of all fields are available with:
zot_get_item_types_fields(item_type = "book",
cache = "FALSE",
locale = "it")
#> field localized
#> 1 title Titolo
#> 2 abstractNote Abstract
#> 3 series Serie
#> 4 seriesNumber Numero della serie
#> 5 volume Volume
#> 6 numberOfVolumes Numero di volumi
#> 7 edition Edizione
#> 8 place Luogo di edizione
#> 9 publisher Editore
#> 10 date Data
#> 11 numPages # di Pagine
#> 12 language Lingua
#> 13 ISBN ISBN
#> 14 shortTitle Titolo abbreviato
#> 15 url URL
#> 16 accessDate Consultato
#> 17 archive Archivio
#> 18 archiveLocation Collocazione in archivio
#> 19 libraryCatalog Catalogo della biblioteca
#> 20 callNumber Segnatura
#> 21 rights Diritti
#> 22 extra ExtraInternally, Zotero does not store data in a tabular format, so some transformation will be necessary.
For example, if we have data in this format:
europe_books <-
tibble::tribble(~itemType, ~creators, ~title, ~tags,
"book", "Spinelli, Altiero; Rossi, Ernesto", "Il Manifesto di Ventotene", "europe; history")
europe_books
#> # A tibble: 1 x 4
#> itemType creators title tags
#> <chr> <chr> <chr> <chr>
#> 1 book Spinelli, Altiero; Rossi, Erne… Il Manifesto di Ventot… europe; hist…We need first to transform them in a format that fully mirrors Zotero’s data structure:
library(dplyr)
europe_books_zot <-
europe_books %>%
mutate(creators = zot_convert_creators_to_df_list(creator = creators),
tags = zot_convert_tags_to_df_list(tags = tags))
europe_books_zot
#> # A tibble: 1 x 4
#> itemType creators title tags
#> <chr> <list> <chr> <list>
#> 1 book <tibble [2 × 3]> Il Manifesto di Ventotene <tibble [2 × 1]>Having previously set your credentials, you can now upload it to your Zotero accounts.
zot_create_items(item_df = europe_books_zot,
collection = "europe")[full support for all data types and more appropriate output will be added in a future version]
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