Name: rperseus
Owner: rOpenSci
Description: Get primary texts from the Perseus Digital Library
Created: 2017-02-23 06:57:51.0
Updated: 2017-12-11 21:49:49.0
Pushed: 2017-11-28 21:49:19.0
Homepage: https://ropensci.github.io/rperseus/index.html
Size: 1224
Language: R
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Author: David Ranzolin
License: MIT
The goal of rperseus is to furnish classicists, textual critics, and R enthusiasts with texts from the Classical World. While the English translations of most texts are available through gutenbergr, rperseusreturns these works in their original language–Greek, Latin, and Hebrew.
rperseus provides access to classical texts within the Perseus Digital Library's CapiTainS environment. A wealth of Greek, Latin, and Hebrew texts are available, from Homer to Cicero to Boetheius. The Perseus Digital Library includes English translations in some cases. The base API url is http://cts.perseids.org/api/cts.
rperseus is not on CRAN, but can be installed via:
ools::install_github("ropensci/rperseus")
See the vignette to get started.
To obtain a particular text, you must first know its full Uniform Resource Name (URN). URNs can be perused in the perseus_catalog, a data frame lazily loaded into the package. For example, say I want a copy of Virgil's Aeneid:
ary(dplyr)
ary(purrr)
ary(rperseus)
id_latin <- perseus_catalog %>%
lter(group_name == "Virgil",
label == "Aeneid",
language == "lat") %>%
ll(urn) %>%
t_perseus_text()
You can also request an English translation for some texts:
id_english <- perseus_catalog %>%
lter(group_name == "Virgil",
label == "Aeneid",
language == "eng") %>%
ll(urn) %>%
t_perseus_text()
Refer to the language variable in perseus_catalog for translation availability.
You can also specify excerpts:
leth <- get_perseus_text(urn = "urn:cts:ancJewLit:hebBible.ecclesiastes.leningrad-pntd", excerpt = "1.1-1.3")
leth$text
1] "????????? ???????? ????? ??????? ??????? ??????????????? : ?????? ????????? ?????? ???????? ?????? ????????? ??????? ?????? : ???? ?????????? ????????? ??????? ???????? ????????????? ??????? ??????????? :"
You can parse any Greek excerpt, returning a data frame with each word's part of speech, gender, case, mood, voice, tense, person, number, and degree.
e_excerpt("urn:cts:greekLit:tlg0031.tlg002.perseus-grc2", "5.1-5.2") %>%
ad(7) %>%
itr::kable()
| word | form | verse | part_of_speech | person | number | tense | mood | voice | gender | case | degree | |:——–|:———|:——|:—————–|:——-|:———|:——-|:———–|:——-|:———|:———–|:——-| | ??? | ??? | 5.1 | conjunction | NA | NA | NA | NA | NA | NA | NA | NA | | ??????? | ????? | 5.1 | verb | third | plural | aorist | indicative | active | NA | NA | NA | | ??? | ??? | 5.1 | preposition | NA | NA | NA | NA | NA | NA | NA | NA | | ? | ?? | 5.1 | article | NA | singular | NA | NA | NA | neuter | accusative | NA | | ????? | ????? | 5.1 | adverb | NA | NA | NA | NA | NA | NA | NA | NA | | ? | ??? | 5.1 | article | NA | singular | NA | NA | NA | feminine | genative | NA | | ??????? | ???????? | 5.1 | noun | NA | singular | NA | NA | NA | feminine | genative | NA |
rperseus plays well with the tidyverse and tidytext. Here I obtain all of Plato's works that have English translations available:
ary(purrr)
o <- perseus_catalog %>%
lter(group_name == "Plato",
language == "eng") %>%
ll(urn) %>%
p_df(get_perseus_text)
And here's how to retrieve the Greek text from Sophocles' underrated Philoctetes before unleashing the tidytext toolkit:
ary(tidytext)
octetes <- perseus_catalog %>%
lter(group_name == "Sophocles",
label == "Philoctetes",
language == "grc") %>%
ll(urn) %>%
t_perseus_text()
octetes %>%
nest_tokens(word, text) %>%
unt(word, sort = TRUE) %>%
ti_join(greek_stop_words)
oining, by = "word"
A tibble: 3,514 x 2
word n
<chr> <int>
1 ??????????? 164
2 ?????????? 141
3 ? 119
4 ?? 74
5 ???????? 56
6 ?????? 47
7 ?? 43
8 ????? 41
9 ?? 40
0 ??? 39
... with 3,504 more rows
You can render small parallels with perseus_parallel:
le(label = c("Colossians", "1 Thessalonians", "Romans"),
excerpt = c("1.4", "1.3", "8.35-8.39")) %>%
left_join(perseus_catalog) %>%
filter(language == "grc") %>%
select(urn, excerpt) %>%
pmap_df(get_perseus_text) %>%
perseus_parallel(words_per_row = 4)
oining, by = "label"
rperseus, first get acquainted with the Perseus Digital Library, fork the repo, and send a pull request.