Create app.py

app.py

@@ -0,0 +1,160 @@
+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']]
+    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
+
+def load_all_data():
+    top_count, top_df = update_display("top")
+    new_count, new_df = update_display("latest")
+    greatest_count, greatest_df = update_display("greatest")
+    return top_count, top_df, new_count, new_df, greatest_count, greatest_df
+
+def save_dataframe_generic(df, filename):
+    try:
+        df.to_csv(filename, index=False)
+        return "Dataframe saved successfully."
+    except Exception as e:
+        return f"Error saving dataframe: {e}"
+
+def load_dataframe_generic(filename):
+    try:
+        if os.path.exists(filename):
+            df = pd.read_csv(filename)
+            return df, "Dataframe loaded successfully."
+        else:
+            return pd.DataFrame(), "Dataframe file not found."
+    except Exception as e:
+        return pd.DataFrame(), f"Error loading dataframe: {e}"
+
+with gr.Blocks() as demo:
+    gr.Markdown("<h1><center>Papers Leaderboard</center></h1>")
+
+    with gr.Tab("Top Trending Papers"):
+        top_count = gr.Textbox(label="Number of Papers Fetched")
+        top_df = gr.DataFrame(interactive=True)
+        top_button = gr.Button("Refresh Leaderboard")
+        top_load_button = gr.Button("Load Dataframe")
+        top_save_button = gr.Button("Save Dataframe")
+        top_save_status = gr.Textbox(label="Status")
+
+        top_button.click(fn=lambda: update_display("top"), inputs=None, outputs=[top_count, top_df])
+        top_save_button.click(fn=lambda df: save_dataframe_generic(df, 'top_dataframe.csv'), inputs=top_df, outputs=top_save_status)
+        top_load_button.click(fn=lambda: load_dataframe_generic('top_dataframe.csv'), inputs=None, outputs=[top_df, top_save_status])
+
+    with gr.Tab("New Papers"):
+        new_count = gr.Textbox(label="Number of Papers Fetched")
+        new_df = gr.DataFrame(interactive=True)
+        new_button = gr.Button("Refresh Leaderboard")
+        new_load_button = gr.Button("Load Dataframe")
+        new_save_button = gr.Button("Save Dataframe")
+        new_save_status = gr.Textbox(label="Status")
+
+        new_button.click(fn=lambda: update_display("latest"), inputs=None, outputs=[new_count, new_df])
+        new_save_button.click(fn=lambda df: save_dataframe_generic(df, 'new_dataframe.csv'), inputs=new_df, outputs=new_save_status)
+        new_load_button.click(fn=lambda: load_dataframe_generic('new_dataframe.csv'), inputs=None, outputs=[new_df, new_save_status])
+
+    with gr.Tab("Greatest Papers"):
+        greatest_count = gr.Textbox(label="Number of Papers Fetched")
+        greatest_df = gr.DataFrame(interactive=True)
+        greatest_button = gr.Button("Refresh Leaderboard")
+        greatest_load_button = gr.Button("Load Dataframe")
+        greatest_save_button = gr.Button("Save Dataframe")
+        greatest_save_status = gr.Textbox(label="Status")
+
+        greatest_button.click(fn=lambda: update_display("greatest"), inputs=None, outputs=[greatest_count, greatest_df])
+        greatest_save_button.click(fn=lambda df: save_dataframe_generic(df, 'greatest_dataframe.csv'), inputs=greatest_df, outputs=greatest_save_status)
+        greatest_load_button.click(fn=lambda: load_dataframe_generic('greatest_dataframe.csv'), inputs=None, outputs=[greatest_df, greatest_save_status])
+
+    # Load initial data for all tabs
+    demo.load(fn=load_all_data, outputs=[top_count, top_df, new_count, new_df, greatest_count, greatest_df])
+
+# Launch the Gradio interface with a public link
+demo.launch(share=True)