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R wrapper to spaCy NLP
| Date | Stars |
|---|---|
| 2026-07-24 | 253 |
| 2026-07-25 | 253 |
| 2026-07-28 | 253 |
| 2026-07-30 | 253 |
| 2026-08-06 | 253 |
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# [](https://spacyr.quanteda.io)
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An R wrapper to the spaCy “industrial strength natural language
processing” Python library from <https://spacy.io>.
## Installing the package
1. Install the **spacyr** R package:
- From CRAN:
``` r
install.packages("spacyr")
```
- From GitHub:
To install the latest package from source, you can simply run the
following.
``` r
remotes::install_github("quanteda/spacyr")
```
2. Install spaCy and requirements
Simply run:
``` r
library(spacyr)
spacy_install()
```
If you want to install a specific version, simply add it to the
install command:
``` r
library(spacyr)
spacy_install(version = "apple")
```
Check the helpful version tool on <https://spacy.io/usage> and to
see what is available.
3. (optional) Add more language models
If left unchanged, `spacy_install()` adds the default
“en_core_web_sm” model. You can add more language models with
`spacy_download_langmodel()`. For instance, to install a small and
efficient German language model:
``` r
spacy_download_langmodel("de_core_news_sm")
```
Check out available models at <https://spacy.io/usage/models>.
If you run into any problems, you can try the manual installation path
described below.
### Manual installation and troubleshooting
`spacy_install()` performs a number of tasks to set up a virtual
environment in which spaCy is installed. Virtual environments are the
recommended way to install Python applications, as the lack of central
dependency conflict control (which is performed by CRAN in the
`R`-world) means that conflicts between packages are a lot more common.
Hence each Python package and its dependencies are usually installed in
their own folder.
Usually, none of this should concern you. However, experience shows that
some systems run into problems during installation that are hard to
foresee by developers. Below, we therefore explain how you can perform
the steps in `spacy_install()` manually, to debug any problems that
might occur. Please only file a GitHub issue after you have tried to
manually run through the steps, so we can provide you with more targeted
help.
1. Install Python
You can use your own installation of Python for the steps below. By
default, `spacy_install()` downloads and installs a minimal Python
version in the default directory used by the `reticulate` package
for simplicity. This can be done with a single command:
``` r
python_exe <- reticulate::install_python()
```
The function returns the path to the Python executable file. You can
run this again at any time to get that path (the installation is
skipped if the files are already present). If you prefer to use a
specific version of Python, you can use this function to install it
and it will be picked up by `spacyr`.
2. Set up a virtual environment
By default, `spacyr` uses an environment called “r-spacyr”, which is
located in a directory managed by `retiExcerpt of 6,073 characters
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matched fp:05c596baa592b84e, topic:nlp, topic:spacy, readme:natural language processing