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.pyimport spacyimport pytextrank # 这行要加# load a spaCy model, depending on language, scale, etc.# python -m spacy download ennlp = 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 pipelinenlp.add_pipe("textrank")doc = nlp(text)words = []# examine the top-ranked phrases in the documentfor phrase in doc._.phrases: # print(phrase.rank, phrase.count) print(phrase.chunks[0]) words.append(phrase.chunks[0])print(words)