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app.py

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+import os
+import requests
+import pandas as pd
+import gradio as gr
+from huggingface_hub.hf_api import SpaceInfo
+from pathlib import Path
+
+
+path = f"https://huggingface.co/api/spaces" 	
+
+    
+def get_NAACL_spaces():
+    r = requests.get(path)
+    d = r.json()
+    spaces = [SpaceInfo(**x) for x in d]
+    blocks_spaces = {}
+    for i in range(0,len(spaces)):
+        if spaces[i].id.split('/')[0] == 'NAACL2022' and hasattr(spaces[i], 'likes') and spaces[i].id != 'NAACL2022/Leaderboard' and spaces[i].id != 'NAACL2022/README':
+            blocks_spaces[spaces[i].id]=spaces[i].likes
+    df = pd.DataFrame(
+    [{"Spaces_Name": Spaces, "likes": likes} for Spaces,likes in blocks_spaces.items()])
+    df = df.sort_values(by=['likes'],ascending=False)
+    return df
+
+
+block = gr.Blocks()
+
+with block:    
+    gr.Markdown("""Leaderboard for the most popular NAACL 2022 Spaces. To learn more and join, see <a href="https://huggingface.co/NAACL2022" target="_blank" style="text-decoration: underline">NAACL 2022 Event</a>""")
+    with gr.Tabs():
+        with gr.TabItem("NAACL 2022 Leaderboard"):
+            with gr.Row():
+                data = gr.Dataframe(type="pandas")
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(get_NAACL_spaces, inputs=None, outputs=data)
+
+    block.load(get_NAACL_spaces, inputs=None, outputs=data)                
+block.launch()