这是一个最简单的例子，对一篇英文文章提取关键词，不涉及词性分析等。
# -*- coding: utf-8 -*-
# @Author : meng_zhihao
# @Email : 312141830@qq.com
# @File : text-rank.py
import spacy
import pytextrank # 这行要加
# load a spaCy model, depending on language, scale, etc.
# python -m spacy download en
nlp = spacy.load("en_core_web_sm") # 导入模块是最耗时的，所以做成服务的时候要避免重复导入！ 这个是middle包，可以试试en_core_web_lg
# 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."
with open('5.txt')as f:
text = f.read()
# add PyTextRank to the spaCy pipeline
nlp.add_pipe("textrank")
doc = nlp(text)
words = []
# examine the top-ranked phrases in the document
for phrase in doc._.phrases:
# print(phrase.rank, phrase.count)
print(phrase.chunks[0])
words.append(phrase.chunks[0])
print(words)
