SpaCy-1.7 python3
- Installs English tagger, parser and NER
- Installs English GloVe vectors
- Build locally
docker build -t spacy-nlp:en .
- (OR) Get latest from hub.docker.com
docker pull pasupulaphani/spacy-nlp:en
sh test.sh
docker run -it spacy-nlp /bin/bash
SpaCy with zeromq bindings
- Build locally
docker build -f Dockerfile.zeromq -t spacy-nlp-zeromq:en .
- (OR) Get latest from hub.docker.com
docker pull pasupulaphani/spacy-nlp-zeromq:en
docker run --publish 4242:4242 -it spacy-nlp-zeromq:en
- (OR) Start manually
docker run -v ${PWD}:/usr/zeromq --publish 4242:4242 --entrypoint=/bin/bash -it spacy-nlp-zeromq:en
python3 /usr/zeromq/zeromq/server.py
$ zerorpc tcp://0.0.0.0:4242 parse "hotel new york"
u'[{"tag": "NN", "text": "hotel new york"}]'
$ zerorpc tcp://0.0.0.0:4242 entities "hotels in london"
u'[{"end": 6, "start": 0, "text": "hotels", "type": ""}, {"end": 16, "start": 10, "text": "london", "type": ""}]'
$ zerorpc tcp://0.0.0.0:4242 nounChunks "hotels in london"
u'[{"text": "hotels"}, {"text": "london"}]'
Check if port is open
if ! nc -z 0.0.0.0 4242 2>&1 >/dev/null; then echo "NOT AVAILABLE"; fi