spacyr v1.4.0

Changes that can affect results

spacy_parse(), spacy_tokenize(), spacy_extract_entity() and spacy_extract_nounphrases() no longer alter the input text. Previously they deleted all backslashes and converted the literal sequences \n and \t into newlines and tabs, so that for instance C:\Users was tokenized as C, :, Users. Code that relied on literal \n being converted should now convert it in R before calling spacyr.
NA documents are now treated as empty documents, rather than as the text "NA".
spacy_tokenize(what = "sentence", remove_separators = FALSE) now keeps trailing whitespace regardless of the value of multithread, including a single space after a sentence, so that the sentences join back into the original text.
spacy_parse(nounphrase = TRUE) now returns rows in the order of the input documents, as it does without noun phrases, instead of sorted by document name. This fixes a bug where the whitespace column and any additional_attributes were assigned to the wrong tokens when the document names were not in alphabetical order.

Added spacy_installed(), which checks without starting Python whether spaCy and, optionally, given language models are installed (#197).
Added a max_length argument to spacy_initialize() to allow documents longer than spaCy’s default limit of 1,000,000 characters (#218).

spacy_install() now creates its environment with a version of Python supported by the spaCy release being installed, as declared on PyPI, rather than whichever Python is found first; if none is found, it offers to install a compatible one. For an existing environment whose Python is not supported, it stops with an error explaining how to recreate the environment, instead of failing during installation.
spacy_initialize() now explains how to install a language model that cannot be found.
Fixed spacy_download_langmodel() and spacy_install() not detecting already-installed language models with recent versions of pip (#258).
Fixed a bug in spacy_download_langmodel() that prevented installing multiple models in one function call (#249).
spacy_install() and spacy_upgrade() no longer fail on Windows when installing into a different environment after Python has been initialised in the session (#258).
Updated the installation instructions: language models are installed with spacy_download_langmodel() rather than with pip (#253), and new sections cover changing the Python version, using an existing Python or conda environment (#246), using local models (#180) and the need for git on Windows (#245). The vignette no longer describes arguments that were removed from spacy_initialize().
Requires reticulate >= 1.31.

Fixed a bug where an error during spacy_tokenize(), such as a text exceeding spaCy’s maximum length, left the spaCy pipeline disabled, so that later calls in the same session failed or silently returned no entities.
Fixed a SyntaxWarning about an invalid escape sequence on Python 3.12+ when initialising spacyr (#257, thanks to @thjbdvlt).
spacy_parse() no longer warns that lemmatization “may not work properly” for models whose name does not start with “en”.
spacy_parse() now returns a zero-row result with the usual columns and types when no document contains any tokens (for instance when all documents are NA or empty), instead of failing with dependency = TRUE or returning malformed columns.

Overhauled the spacy_install() and spacy_uninstall() functions to provide a more modern and robust installation procedure.

Added an option for using conda package manager instead of pip in spacy_install() and spacy_upgrade().
(1.21) All character inputs to spacy_parse() and spacy_tokenize() are now coerced to character, which allows them to work directly with quanteda v2 corpus objects (which are based on the character class but with special attributed), without special methods.

Fixed a bug in spacy_parse(x, nounphrase = TRUE) that occurred when no noun phrases were found in the text. (#153)
Fixed a bug in spacy_initialize() (#157). spacy_initialize() ignored Python options supplied by users when a conda environment created through spacy_install() exists.
General stability enhancements to ensure compatibility with spaCy >= 2.1

Added new commands spacy_tokenize(), spacy_extract_entity(), spacy_extract_nounphrases(), nounphrase_extract(), and nounphrase_consolidate() for direct extraction of entities, noun phrases, and tokens, and extraction of noun phrases from spacyr parsed tests.
Added a new argument additional_attributes to spacy_parse() allowing the return of any tokens-level attribute available from https://spacy.io/api/token#attributes.
Added a vignette and significantly improved the documentation site https://spacyr.quanteda.io.

Added spacy_install(), spacy_install_virtualenv(), and spacy_upgrade() to make installing or upgrading spaCy (and Python itself) easy and automatic.
Added support for multithreading in spacy_parse() via the multithreading argument. This uses the “pipes” functionality in spaCy for improved performance.

Updated for the newer spaCy 2.0 release and new language models.
Add ask = FALSE to spacy_initialize(), to find spaCy installations automatically.

Fixed a bug caused by zero-token “sentences” in spacy_parse(), by changing 1:length() to seq_along().

Fixed a bug causing non-ASCII characters to be dropped when using Python 2.7.x (#58).
Fixed issue with automatic detection of python3 when both python and python3 exist, but only python3 has spaCy installed (#62).