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Create dependency tree plots from SpaCy Doc objects

Project description

visualise-spacy-tree

An alternative to SpaCy's visualizer, built on GraphViz.

Custom plot image

Prerequisites

Installation

With pip:

pip install visualise-spacy-tree

Or from source:

git clone https://github.com/cyclecycle/visualise-spacy-tree.git visualise_spacy_tree
cd visualise_spacy_tree
python setup.py install

Usage

# Parse a string to create SpaCy Doc object
import en_core_web_sm

text = 'Forging involves the shaping of metal using localized compressive forces.'

nlp = en_core_web_sm.load()
doc = nlp(text)

# Create the plot
import visualise_spacy_tree
plot = visualise_spacy_tree.plot(doc)

# Write it to a file (it's png format)
with open('parse_tree.png', 'wb') as f:
    f.write(plot)

# If you're using Jupyter notebook, you can render it inline
from IPython.display import Image, display
display(Image(plot))

# Override node attributes like so
from spacy.tokens import Token
Token.set_extension('plot', default={})  # Create a token underscore extension
for token in doc:
    node_text = '{0} [{1}])'.format(token.orth_, token.i)
    token._.plot['text'] = node_text
    if token.dep_ == 'ROOT':
        token._.plot['color'] = 'green'

'''
You can set any valid GraphViz dot attribute in 'plot'.
See GraphViz docs for reference of possible node attributes:
https://graphviz.gitlab.io/_pages/doc/info/attrs.html
'''

Running the tests

pytest

Acknowledgements

Uses:

Contributions

Are welcome :)

Project details


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