Upload folder using huggingface_hub

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----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=
+-----END CERTIFICATE-----

app.py

@@ -9,7 +9,7 @@ import numpy as np
 
 base_addresses = ["0x45e7035499bc860dA0b5666A93B97AFc51F3cD3F",'0x8Ff84fa392340d4683C57A602AC400C3D2fF5cdD','0xA6bbEFBB13BBbcA0022a270c734674146DCcf668','0x43D04107E14C19DCDd2C0D0afC33cDa458b349A3','0xA19f7F0643FF7f655D3E39D0689caa3D53944AAE']
 
-lp_wallets = ["0x45e7035499bc860dA0b5666A93B97AFc51F3cD3F"]
+lp_wallets = ["0x45e7035499bc860dA0b5666A93B97AFc51F3cD3F",'0x8Ff84fa392340d4683C57A602AC400C3D2fF5cdD','0xA6bbEFBB13BBbcA0022a270c734674146DCcf668','0x43D04107E14C19DCDd2C0D0afC33cDa458b349A3','0xA19f7F0643FF7f655D3E39D0689caa3D53944AAE']
 
 def chunk_addresses(addresses, size):
     return [addresses[i:i + size] for i in range(0, len(addresses), size)]
@@ -77,12 +77,13 @@ async def get_wallet_base_balances(addresses):
         df_lp_only = df[df['address'] == '0x45e7035499bc860da0b5666a93b97afc51f3cd3f'].copy()
         df_lp_only = df_lp_only[['symbol','tokenBalance','value']]
         df_lp_only = df_lp_only.rename(columns={'tokenBalance':'amount','value':'usd_value'})
-        df= df[['symbol','tokenBalance','value']]
-        df = df.rename(columns={'tokenBalance':'amount','value':'usd_value'})
+        taker_df = df[df['address'] != '0x45e7035499bc860da0b5666a93b97afc51f3cd3f'].copy()
+        taker_df= taker_df[['symbol','tokenBalance','value']]
+        taker_df = taker_df.rename(columns={'tokenBalance':'amount','value':'usd_value'})
         
-        df = df.groupby("symbol", as_index=False).sum()
+        taker_df = taker_df.groupby("symbol", as_index=False).sum()
 
-        return df, df['usd_value'].sum(), eth_price, base_price, df_lp_only
+        return taker_df, taker_df['usd_value'].sum(), eth_price, base_price, df_lp_only
 
 async def fetch_lp():
     url = "https://public.zapper.xyz/graphql"
@@ -227,25 +228,34 @@ async def get_all_dfs():
         lp_df['price'] = lp_df['symbol'].map(symbols)
         lp_df['price'] = lp_df['price'] * lp_df['amount']
         lp_df.rename(columns={"price":"usd_value"},inplace=True)
+
+    total_current_balances = pd.concat([df,lp_df,df_lp_only]).groupby('symbol').agg({'amount':'sum','usd_value':'sum'}).reset_index()
     for col in ['amount','usd_value']:
         df[col] = pd.to_numeric(df[col], errors='coerce')
         df[col] = df[col].apply(lambda x: f"{x:,.2f}")
         df_lp_only[col] = pd.to_numeric(df_lp_only[col], errors='coerce')
         df_lp_only[col] = df_lp_only[col].apply(lambda x: f"{x:,.2f}")
-    return starting_df,df,lp_df,df_lp_only
+        lp_df[col] = pd.to_numeric(lp_df[col], errors='coerce')
+        lp_df[col] = lp_df[col].apply(lambda x: f"{x:,.2f}")
+        total_current_balances[col] = pd.to_numeric(total_current_balances[col], errors='coerce')
+        total_current_balances[col] = total_current_balances[col].apply(lambda x: f"{x:,.2f}")
+
+    
+    return starting_df,df,lp_df,df_lp_only,total_current_balances
 
 with gr.Blocks() as demo:
     gr.Markdown("## VICE Balances & PnL")
 
     df0_out = gr.Dataframe(label="Starting Balances")
-    df1_out = gr.Dataframe(label="Current Balances")
+    df1_out = gr.Dataframe(label="Taker Balances")
     df3_out = gr.Dataframe(label="LP Wallet Balances")
     df2_out = gr.Dataframe(label="LP Position Balances")
+    df4_out = gr.Dataframe(label="Total Current Balances")
     
     demo.load(
     fn= get_all_dfs, 
     inputs = [],
-    outputs=[df0_out,df1_out,df2_out,df3_out]
+    outputs=[df0_out,df1_out,df2_out,df3_out,df4_out]
     )