Create app.py

app.py

@@ -0,0 +1,71 @@
+import gradio as gr
+import requests
+import time
+from typing import Any
+from communex.client import CommuneClient
+from communex.balance import from_nano
+import json
+
+netuid = 0
+node_url = "wss://commune.api.onfinality.io/public-ws"
+
+def get_com_price() -> Any:
+    retries = 5
+    for i in range(0, retries):
+        try:
+            return float(requests.get("https://api.mexc.com/api/v3/avgPrice?symbol=COMAIUSDT").json()["price"])
+        except Exception as e:
+            print(e)
+            if i == retries - 1:
+                raise
+            time.sleep(retries)
+    raise RuntimeError()
+
+def get_score():
+    com_price = get_com_price()
+    blocks_in_day = 10_800
+    client = CommuneClient(node_url)
+    emission = client.query("Emission", params=[netuid])
+    distribution_dict: dict[int, float] = {}
+    for uid, emi in enumerate(emission):
+        distribution_dict[uid] = ((emi / 10**11) * blocks_in_day) * com_price
+    return distribution_dict
+
+def load_leaderboard():
+    with open("leaderboard.json", "r") as f:
+        leaderboard_data = json.load(f)
+    return leaderboard_data
+
+def save_leaderboard():
+    scores = get_score()
+    sorted_scores = sorted(scores.items(), key=lambda x: x[1], reverse=True)
+    leaderboard_data = []
+    for rank, (uid, score) in enumerate(sorted_scores, start=1):
+        leaderboard_data.append({"rank": rank, "uid": uid, "score": score})
+    with open("leaderboard.json", "w") as f:
+        json.dump(leaderboard_data, f)
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Commune Leaderboard")
+    
+    leaderboard_data = load_leaderboard()
+    
+    leaderboard_table = gr.components.DataFrame(
+        value=leaderboard_data,
+        headers=["rank", "uid", "score"],
+        datatype=["number", "number", "number"],
+        interactive=False,
+        visible=True
+    )
+    
+    refresh_button = gr.Button("Refresh Leaderboard")
+    
+    def refresh_leaderboard():
+        save_leaderboard()
+        updated_data = load_leaderboard()
+        return gr.components.DataFrame.update(value=updated_data)
+    
+    refresh_button.click(fn=refresh_leaderboard, outputs=leaderboard_table)
+
+if __name__ == "__main__":
+    demo.launch()