Getting Started¶
Installation¶
To install from PyPi:
python3 -m pip install pytextrank
python3 -m spacy download en_core_web_sm
If you work directly from this Git repo, be sure to install the dependencies:
python3 -m pip install -r requirements.txt
Sample Usage¶
To use pytextrank in its simplest form:
import spacy
import pytextrank
# example text
text = "Compatibility of systems of linear constraints over the set of natural numbers. Criteria of compatibility of a system of linear Diophantine equations, strict inequations, and nonstrict inequations are considered. Upper bounds for components of a minimal set of solutions and algorithms of construction of minimal generating sets of solutions for all types of systems are given. These criteria and the corresponding algorithms for constructing a minimal supporting set of solutions can be used in solving all the considered types systems and systems of mixed types."
# load a spaCy model, depending on language, scale, etc.
nlp = spacy.load("en_core_web_sm")
# add PyTextRank to the spaCy pipeline
nlp.add_pipe("textrank")
doc = nlp(text)
# examine the top-ranked phrases in the document
for phrase in doc._.phrases:
print(phrase.text)
print(phrase.rank, phrase.count)
print(phrase.chunks)
Hands-on Coding Tutorial¶
See the Tutorial notebooks for sample code and patterns to use when integrating pytextrank with other related libraries in Python.
Last update:
2021-06-29