add burnttensor app

app.py

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+import bittensor as bt
+from substrateinterface import Keypair
+import gradio as gr
+import pandas as pd
+
+
+def get_incentive_percent_for_key(key, sn, incentive, substrate) -> tuple[float, int]:
+    uid = substrate.query('SubtensorModule', 'Uids', [sn, key])
+    if uid and uid.value is not None:
+        owner_incentive = int(incentive[uid.value])
+        if owner_incentive > 0:
+            return (owner_incentive / 65535) * 100, uid.value
+    return -1, -1
+
+
+def fetch_incentive_data() -> pd.DataFrame:
+    print("Starting data fetch...")
+    data = []
+    subtensor = bt.subtensor(network="finney")
+    substrate = subtensor.substrate
+        
+    for sn in range(128):
+        incentive = substrate.query("SubtensorModule", "Incentive", [sn])
+        owner_ck = substrate.query('SubtensorModule', 'SubnetOwner', [sn])
+        assert incentive, "WTF"
+        assert owner_ck, "WTF"
+        sn_link = f"[{sn}](https://taostats.io/subnets/{sn})"
+
+        ck_incentive, ck_uid = get_incentive_percent_for_key(owner_ck, sn, incentive, substrate)
+        if ck_incentive > 0:
+            print(f"Found incentive for SN {sn} owner coldkey.")
+            address_link = f"[{owner_ck}](https://taostats.io/coldkey/{owner_ck})"
+            data.append([sn_link, f"{ck_incentive:.2f}%", ck_uid, "Coldkey", address_link])
+            continue
+
+        owner_hks = substrate.query("SubtensorModule", "OwnedHotkeys", [owner_ck])
+        if owner_hks and owner_hks.value:
+            for byte_array in owner_hks.value:
+                owner_hk = Keypair(public_key=bytes(byte_array[0]), ss58_format=42).ss58_address
+                hk_incentive, hk_uid = get_incentive_percent_for_key(owner_hk, sn, incentive, substrate)
+                if hk_incentive > 0:
+                    print(f"Found incentive for SN {sn} owner hotkey.")
+                    address_link = f"[{owner_hk}](https://taostats.io/hotkey/{owner_hk})"
+                    data.append([sn_link, f"{hk_incentive:.2f}%", hk_uid, "Hotkey", address_link])
+                    break
+        
+    df = pd.DataFrame(data, columns=["Subnet", "Incentive", "UID", "Key Type", "Address"]) #type: ignore
+    return df
+
+
+with gr.Blocks(title="Bittensor Subnet Incentives") as demo:
+    gr.Markdown(
+        """
+        # Bittensor Subnet Burn Dashboard
+        This dashboard displays the burn percentage set by subnet owners for miners.
+        Click the 'Refresh' button to fetch the latest data.
+        """
+    )
+
+    refresh_button = gr.Button("Refresh Data")
+    output_df = gr.DataFrame(
+        headers=["Subnet", "Burn", "UID", "Key", "Address"],
+        datatype=["markdown", "str", "number", "str", "markdown"],
+        label="Subnet Incentive Data",
+        interactive=False,
+        row_count=(60, "dynamic"),
+        col_count=(5, "fixed")
+    )
+
+    demo.load(fetch_incentive_data, None, output_df)
+    demo.launch()

requirements.txt

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+bittensor