import requests from bs4 import BeautifulSoup import pandas as pd import gradio as gr import time import os import json def get_rank_papers(url, progress=gr.Progress(track_tqdm=True)): base_url = "https://paperswithcode.com" session = requests.Session() headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3', 'Cache-Control': 'no-cache' } print("Time run at : ", time.ctime()) offset = 0 data_list = {} break_duplicate = 10 while True: response = session.get(url, headers=headers, params={'page': offset}) if response.status_code != 200: print('Failed to retrieve data') break soup = BeautifulSoup(response.text, 'html.parser') paper_info = soup.find_all('div', class_='row infinite-item item paper-card') if not paper_info: break for ppr in paper_info: title = ppr.find('h1').text.strip() if "paper" in ppr.find('a')['href']: link = base_url + ppr.find('a')['href'] else: link = ppr.find('a')['href'] Github_Star = ppr.find('span', class_='badge badge-secondary').text.strip().replace(',', '') pdf_link = '' try: response_link = session.get(link, headers=headers) soup_link = BeautifulSoup(response_link.text, 'html.parser') paper_info_link = soup_link.find_all('div', class_='paper-abstract') pdf_link = paper_info_link[0].find('div', class_='col-md-12').find('a')['href'] except: pass if title not in data_list: data_list[title] = {'link': link, 'Github Star': int(Github_Star), 'pdf_link': pdf_link.strip()} else: break_duplicate -= 1 if break_duplicate == 0: return data_list offset += 1 progress.update(offset) print('Data retrieval complete') return data_list def load_cached_data(cache_file): if os.path.exists(cache_file): with open(cache_file, 'r') as f: return json.load(f) return None def save_cached_data(data, cache_file): with open(cache_file, 'w') as f: json.dump(data, f) def format_dataframe(data): df = pd.DataFrame(data).T df['title'] = df.index df = df[['title', 'Github Star', 'link', 'pdf_link']] df['link'] = df['link'].apply(lambda x: f'Link') df['pdf_link'] = df['pdf_link'].apply(lambda x: f'{x}') return df def load_and_cache_data(url, cache_file): cached_data = load_cached_data(cache_file) if cached_data: print(f"Loading cached data from {cache_file}") return cached_data print(f"Fetching new data from {url}") new_data = get_rank_papers(url) save_cached_data(new_data, cache_file) return new_data def update_display(category): cache_file = f"{category}_papers_cache.json" url = f"https://paperswithcode.com/{category}" if category != "top" else "https://paperswithcode.com/" data = load_and_cache_data(url, cache_file) df = format_dataframe(data) return len(df), df.to_html(escape=False, index=False) def load_all_data(): top_count, top_html = update_display("top") new_count, new_html = update_display("latest") greatest_count, greatest_html = update_display("greatest") return top_count, top_html, new_count, new_html, greatest_count, greatest_html with gr.Blocks() as demo: gr.Markdown("