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spacy_install() and spacy_uninstall() functions to provide a more modern and robust installation procedure.pip in spacy_install() and spacy_upgrade().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.spacy_parse(x, nounphrase = TRUE) that occurred when no noun phrases were found in the text. (#153)spacy_initialize() (#157). spacy_initialize() ignored Python options supplied by users when a conda environment created through spacy_install() exists.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.additional_attributes to spacy_parse() allowing the return of any tokens-level attribute available from https://spacy.io/api/token#attributes.spacy_install(), spacy_install_virtualenv(), and spacy_upgrade() to make installing or upgrading spaCy (and Python itself) easy and automatic.spacy_parse() via the multithreading argument. This uses the “pipes” functionality in spaCy for improved performance..Rprofilespacy_initialize(entity = FALSE) (#91).bash_profile.ask = FALSE to spacy_initialize(), to find spaCy installations automatically.spacy_parse(), by changing 1:length() to seq_along().These binaries (installable software) and packages are in development.
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