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#!/usr/bin/env python3
"""
arXiv 论文搜索脚本
用于搜索 arXiv 上与脑电解码相关的论文。
用法:
python arxiv_search.py --query "EEG speech decoding" --max-results 50
python arxiv_search.py --keywords EEG speech decoding --months 3
"""
import argparse
import feedparser
import re
from datetime import datetime, timedelta
from typing import List, Dict, Optional
from urllib.parse import quote_plus
def search_arxiv(
query: str,
max_results: int = 50,
categories: Optional[List[str]] = None,
months: int = 3
) -> List[Dict]:
"""
搜索 arXiv 论文
Args:
query: 搜索查询字符串
max_results: 最大结果数
categories: arXiv 分类列表 (如 ['cs.CV', 'cs.LG'])
months: 搜索最近几个月的论文
Returns:
论文列表，每个论文包含标题、作者、摘要、链接等信息
"""
# 构建 arXiv API 查询
base_url = "http://export.arxiv.org/api/query?"
# 添加分类过滤
if categories:
cat_query = " OR ".join([f"cat:{cat}" for cat in categories])
search_query = f"search_query=({quote_plus(cat_query)})+AND+all:{quote_plus(query)}"
else:
search_query = f"search_query=all:{quote_plus(query)}"
# 其他参数
params = f"&start=0&max_results={max_results}&sortBy=submittedDate&sortOrder=descending"
url = base_url + search_query + params
print(f"正在搜索: {url}")
# 执行查询
feed = feedparser.parse(url)
papers = []
# 计算时间截止
cutoff_date = datetime.now() - timedelta(days=months * 30)
for entry in feed.entries:
# 解析日期
published = datetime(*entry.published_parsed[:6])
# 时间过滤
if published < cutoff_date:
continue
# 解析作者
authors = [author.name for author in entry.authors]
first_author = authors[0] if authors else "Unknown"
# 解析 arXiv ID
arxiv_id = entry.id.split("/abs/")[-1]
arxiv_link = f"https://arxiv.org/abs/{arxiv_id}"
# 解析摘要（去除多余空白）
summary = re.sub(r'\s+', ' ', entry.summary).strip()
paper = {
"title": entry.title,
"authors": authors,
"first_author": first_author,
"summary": summary,
"published": published.strftime("%Y-%m-%d"),
"arxiv_id": arxiv_id,
"arxiv_link": arxiv_link,
"pdf_link": f"https://arxiv.org/pdf/{arxiv_id}.pdf",
"categories": [tag.term for tag in entry.tags],
}
papers.append(paper)
print(f"找到 {len(papers)} 篇相关论文（最近{months}个月）")
return papers
def print_papers(papers: List[Dict], limit: int = 10):
"""打印论文列表"""
print(f"\n=== 最近 {min(limit, len(papers))} 篇论文 ===\n")
for i, paper in enumerate(papers[:limit]):
print(f"[{i+1}] {paper['title']}")
print(f" 作者: {paper['first_author']} et al.")
print(f" 发表: {paper['published']}")
print(f" 链接: {paper['arxiv_link']}")
print(f" 摘要: {paper['summary'][:150]}...")
print()
def main():
parser = argparse.ArgumentParser(description="搜索 arXiv 论文")
parser.add_argument("--query", "-q", type=str, help="搜索查询字符串")
parser.add_argument("--keywords", "-k", nargs="+", help="搜索关键词列表")
parser.add_argument("--max-results", "-n", type=int, default=50, help="最大结果数")
parser.add_argument("--categories", "-c", nargs="+",
default=["cs.CV", "cs.LG", "q-bio.NC"],
help="arXiv 分类")
parser.add_argument("--months", "-m", type=int, default=3,
help="搜索最近几个月的论文")
parser.add_argument("--output", "-o", type=str, help="输出 JSON 文件路径")
args = parser.parse_args()
# 构建查询
if args.query:
query = args.query
elif args.keywords:
query = "+".join(args.keywords)
else:
# 默认查询：脑电语音解码
query = "EEG+speech+decoding"
# 执行搜索
papers = search_arxiv(
query=query,
max_results=args.max_results,
categories=args.categories,
months=args.months
)
# 打印结果
print_papers(papers, limit=10)
# 输出 JSON
if args.output:
import json
with open(args.output, 'w', encoding='utf-8') as f:
json.dump(papers, f, ensure_ascii=False, indent=2)
print(f"\n结果已保存到 {args.output}")
if __name__ == "__main__":
main()
|
