Port details |
- py-spacy Industrial-strength Natural Language Processing (NLP) in Python
- 3.8.0 textproc =2 3.7.5Version of this port present on the latest quarterly branch.
- Maintainer: sunpoet@FreeBSD.org
- Port Added: 2024-02-21 15:19:31
- Last Update: 2024-09-18 06:13:19
- Commit Hash: 5496159
- People watching this port, also watch:: jdictionary, py311-Automat, py311-python-gdsii, py39-PyOpenGL, p5-Sane
- Also Listed In: python
- License: MIT
- WWW:
- https://spacy.io/
- https://github.com/explosion/spaCy
- Description:
- spaCy is a library for advanced Natural Language Processing in Python and
Cython. It's built on the very latest research, and was designed from day one to
be used in real products.
spaCy comes with pretrained pipelines and currently supports tokenization and
training for 70+ languages. It features state-of-the-art speed and neural
network models for tagging, parsing, named entity recognition, text
classification and more, multi-task learning with pretrained transformers like
BERT, as well as a production-ready training system and easy model packaging,
deployment and workflow management.
- ¦ ¦ ¦ ¦
- Manual pages:
- FreshPorts has no man page information for this port.
- pkg-plist: as obtained via:
make generate-plist - There is no configure plist information for this port.
- Dependency lines:
-
- ${PYTHON_PKGNAMEPREFIX}spacy>0:textproc/py-spacy@${PY_FLAVOR}
- To install the port:
- cd /usr/ports/textproc/py-spacy/ && make install clean
- To add the package, run one of these commands:
- pkg install textproc/py-spacy
- pkg install py311-spacy
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above. NOTE: This is a Python port. Instead of py311-spacy listed in the above command, you can pick from the names under the Packages section.- PKGNAME: py311-spacy
- Package flavors (<flavor>: <package>)
- distinfo:
- TIMESTAMP = 1726487384
SHA256 (spacy-3.8.0.tar.gz) = 00ce46c8dbcd50deac38376c6f04e4d1b6ee67a2e4a2b64ede0cee09f203c3a7
SIZE (spacy-3.8.0.tar.gz) = 1275629
Packages (timestamps in pop-ups are UTC):
- Dependencies
- NOTE: FreshPorts displays only information on required and default dependencies. Optional dependencies are not covered.
- Build dependencies:
-
- py311-cymem>=2.0.2<2.1.0 : devel/py-cymem@py311
- py311-murmurhash>=0.28.0<1.1.0 : devel/py-murmurhash@py311
- py311-numpy>=1.19.0,1 : math/py-numpy@py311
- py311-preshed3>=3.0.2<3.1.0 : devel/py-preshed3@py311
- py311-setuptools>=0 : devel/py-setuptools@py311
- py311-thinc8>=8.3.0<8.4.0 : devel/py-thinc8@py311
- py311-wheel>=0 : devel/py-wheel@py311
- cython-3.11 : lang/cython@py311
- python3.11 : lang/python311
- py311-build>=0 : devel/py-build@py311
- py311-installer>=0 : devel/py-installer@py311
- Test dependencies:
-
- python3.11 : lang/python311
- Runtime dependencies:
-
- py311-catalogue>=2.0.6<2.1.0 : devel/py-catalogue@py311
- py311-cymem>=2.0.2<2.1.0 : devel/py-cymem@py311
- py311-Jinja2>=0 : devel/py-Jinja2@py311
- py311-langcodes>=3.2.0<4.0.0 : textproc/py-langcodes@py311
- py311-murmurhash>=0.28.0<1.1.0 : devel/py-murmurhash@py311
- py311-numpy>=1.19.0,1 : math/py-numpy@py311
- py311-packaging>=20.0 : devel/py-packaging@py311
- py311-preshed3>=3.0.2<3.1.0 : devel/py-preshed3@py311
- py311-pydantic2>=1.7.4<3.0.0 : devel/py-pydantic2@py311
- py311-requests>=2.13.0<3.0.0 : www/py-requests@py311
- py311-setuptools>=0 : devel/py-setuptools@py311
- py311-spacy-legacy>=3.0.11<3.1.0 : textproc/py-spacy-legacy@py311
- py311-spacy-loggers>=1.0.0<2.0.0 : textproc/py-spacy-loggers@py311
- py311-srsly>=2.4.3<3.0.0 : devel/py-srsly@py311
- py311-thinc8>=8.3.0<8.4.0 : devel/py-thinc8@py311
- py311-tqdm>=4.38.0<5.0.0 : misc/py-tqdm@py311
- py311-typer>=0.3.0<1.0.0 : devel/py-typer@py311
- py311-wasabi>=0.9.1<1.2.0 : textproc/py-wasabi@py311
- py311-weasel>=0.1.0<0.5.0 : devel/py-weasel@py311
- python3.11 : lang/python311
- This port is required by:
- for Run
-
- textproc/py-sense2vec
- textproc/py-spacy-llm
Configuration Options:
- No options to configure
- Options name:
- textproc_py-spacy
- USES:
- python
- FreshPorts was unable to extract/find any pkg message
- Master Sites:
|
Commit History - (may be incomplete: for full details, see links to repositories near top of page) |
Commit | Credits | Log message |
3.8.0 18 Sep 2024 06:13:19 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Update to 3.8.0
Changes: https://github.com/explosion/spaCy/releases |
3.7.6 08 Sep 2024 18:37:48 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Update to 3.7.6
Changes: https://github.com/explosion/spaCy/releases |
3.7.5_1 04 Aug 2024 17:14:12 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Allow build with py-thinc8 8.3.0
- Bump PORTREVISION for package change |
3.7.5 06 Jun 2024 16:39:41 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Update to 3.7.5
Changes: https://github.com/explosion/spaCy/releases |
3.7.4_4 20 May 2024 10:33:03 |
Vsevolod Stakhov (vsevolod) |
security/libsodium: update to 1.0.19, bump dependent ports
PR: 278259
Reported by: Andrey Korobkov <alster-vinterdalen.se> |
3.7.4_3 19 May 2024 17:15:56 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Allow build with py-typer 0.10.0+
- Bump PORTREVISION for package change |
3.7.4_2 20 Apr 2024 18:28:39 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Change *_DEPENDS from py-thinc to py-thinc8
- Bump PORTREVISION for dependency change |
3.7.4_1 08 Apr 2024 06:47:19 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Allow build with py-weasel 0.4.0
- Bump PORTREVISION for package change
Obtained
from: https://github.com/explosion/spaCy/commit/f5e85fa05a5de357ee6a516a907042ec28f4f580 |
3.7.4 09 Mar 2024 14:06:17 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Allow build with py-smart-open 7.0.1+ |
3.7.4 21 Feb 2024 15:06:09 |
Po-Chuan Hsieh (sunpoet) |
textproc/py-spacy: Add py-spacy 3.7.4
spaCy is a library for advanced Natural Language Processing in Python and
Cython. It's built on the very latest research, and was designed from day one to
be used in real products.
spaCy comes with pretrained pipelines and currently supports tokenization and
training for 70+ languages. It features state-of-the-art speed and neural
network models for tagging, parsing, named entity recognition, text
classification and more, multi-task learning with pretrained transformers like
BERT, as well as a production-ready training system and easy model packaging,
deployment and workflow management. |