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README.md

@@ -1,12 +1,6 @@
 ---
-title: Vice Balances
-emoji: 🦀
-colorFrom: red
-colorTo: purple
-sdk: gradio
-sdk_version: 5.49.0
+title: vice_balances
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 5.31.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import requests
+import asyncio
+import aiohttp
+import pandas as pd
+import urllib
+import gradio as gr
+import os
+import numpy as np
+
+base_addresses = ["0x45e7035499bc860dA0b5666A93B97AFc51F3cD3F",'0x8Ff84fa392340d4683C57A602AC400C3D2fF5cdD','0xA6bbEFBB13BBbcA0022a270c734674146DCcf668','0x43D04107E14C19DCDd2C0D0afC33cDa458b349A3','0xA19f7F0643FF7f655D3E39D0689caa3D53944AAE']
+
+lp_wallets = ["0x45e7035499bc860dA0b5666A93B97AFc51F3cD3F"]
+
+def chunk_addresses(addresses, size):
+    return [addresses[i:i + size] for i in range(0, len(addresses), size)]
+
+API_URL = "https://api.g.alchemy.com/data/v1/yhe6L3PXmiENzS1sP9Fu4_T5E3l0QyeB/assets/tokens/by-address"
+
+async def fetch_batch(session, batch,chain):
+    json_payload = {
+        "addresses": [{"address": addr, "networks": [chain]} for addr in batch],
+        "withMetadata": True,
+        "withPrices": True,
+        "includeNativeTokens": True
+    }
+    async with session.post(API_URL, json=json_payload) as response:
+        response = await response.json()
+        return response['data']['tokens']
+
+async def get_wallet_base_balances(addresses):
+    async with aiohttp.ClientSession() as session:
+        batches = chunk_addresses(addresses, 3)
+        tasks = [fetch_batch(session, batch,"eth-mainnet") for batch in batches]
+        responses = await asyncio.gather(*tasks)
+        first_parts = []
+        rest_parts = []
+
+        for res in responses:
+            first_parts.extend(res[:3])
+            rest_parts.extend(res[3:])
+
+        responses = first_parts + rest_parts
+        df = pd.DataFrame(responses)
+        print(df)
+        for i in range(len(addresses)):
+            df.at[i,'tokenMetadata'] = {}
+
+        vice_data = {
+          "decimals": 18,
+          "logo": 'null',
+          "name": "",
+          "symbol": "VICE"
+        }
+        df['tokenMetadata'] = np.where(df['tokenAddress'] == '0xfd409bc96d126bc8a56479d4c7672015d539f96c',vice_data,df['tokenMetadata'])
+
+        df['tokenBalance'] = df['tokenBalance'].apply(lambda x : int(x,16))
+        df['decimals'] = df['tokenMetadata'].apply(lambda x : x.get('decimals',0))
+        df['tokenBalance'] = df['tokenBalance']/(10**df['decimals'])
+        for i in range(len(addresses)):
+            df.at[i, 'tokenBalance'] = df.at[i, 'tokenBalance'] / (10**18)
+        df['symbol'] = df['tokenMetadata'].apply(lambda x : x.get('symbol',''))
+        for i in range(len(addresses)):
+            df.at[i,'symbol'] = 'ETH'
+        df['currentPrice'] = df['tokenPrices'].apply(lambda x : x[0].get('value',0) if len(x) > 0 else 0)
+        df.drop(columns=['tokenPrices','tokenMetadata','network','tokenAddress'], inplace=True)
+
+        df = df.dropna()
+        df['tokenBalance'] = pd.to_numeric(df['tokenBalance'], errors='coerce')
+        df = df[df['tokenBalance'] != 0]
+        df['tokenBalance'] = pd.to_numeric(df['tokenBalance'], errors='coerce')
+        df['currentPrice'] = pd.to_numeric(df['currentPrice'], errors='coerce')
+        eth_price = df.loc[df['symbol']=='ETH','currentPrice'].values[0]
+        base_price = df.loc[df['symbol']=='VICE','currentPrice'].values[0]
+        df['value'] = df['tokenBalance'] * df['currentPrice']
+        df.drop(columns=['address','decimals'],inplace=True)
+
+        df = df[df['symbol'].isin(['VICE', 'ETH', 'USDT', 'USDC'])]
+        df= df[['symbol','tokenBalance','value']]
+        df = df.rename(columns={'tokenBalance':'amount','value':'usd_value'})
+        
+        df = df.groupby("symbol", as_index=False).sum()
+
+        return df, df['usd_value'].sum(), eth_price, base_price
+
+async def fetch_lp():
+    url = "https://public.zapper.xyz/graphql"
+    headers = {
+        "Content-Type": "application/json",
+        "x-zapper-api-key": "8fe2c210-66e0-4ef9-9505-96a901c9b042"
+    }
+
+    query = """
+    query AppBalances($addresses: [Address!]!, $first: Int = 10) {
+    portfolioV2(addresses: $addresses) {
+        appBalances {
+        totalBalanceUSD
+        byApp(first: $first) {
+            totalCount
+            edges {
+            node {
+                balanceUSD
+                app {
+                displayName
+                imgUrl
+                description
+                category { name }
+                }
+                network {
+                name
+                chainId
+                }
+                positionBalances(first: 10) {
+                edges {
+                    node {
+                    ... on AppTokenPositionBalance {
+                        type
+                        symbol
+                        balance
+                        balanceUSD
+                        price
+                        groupLabel
+                        displayProps {
+                        label
+                        images
+                        }
+                    }
+                    ... on ContractPositionBalance {
+                        type
+                        balanceUSD
+                        groupLabel
+                        tokens {
+                        metaType
+                        token {
+                            ... on BaseTokenPositionBalance {
+                            symbol
+                            balance
+                            balanceUSD
+                            }
+                        }
+                        }
+                        displayProps {
+                        label
+                        images
+                        }
+                    }
+                    }
+                }
+                }
+            }
+            }
+        }
+        }
+    }
+    }
+    """
+
+    variables = {
+        "addresses": lp_wallets,
+        "first": 5
+    }
+
+    payload = {
+        "query": query,
+        "variables": variables
+    }
+
+    response = requests.post(url, json=payload, headers=headers)
+    response = response.json()
+    df = pd.json_normalize(response['data']['portfolioV2']['appBalances']['byApp']['edges'])
+    def agg_balances(lp):
+        lps = []
+        for i in range(len(lp)):
+            two = lp['node.tokens'].iloc[i]
+            more_lp = pd.json_normalize(two)
+            more_lp['token.balance'] = more_lp['token.balance'].apply(pd.to_numeric,errors='coerce')
+            more_lp['token.balanceUSD'] = more_lp['token.balanceUSD'].apply(pd.to_numeric,errors='coerce')
+            x = more_lp.groupby('token.symbol')[['token.balance','token.balanceUSD']].sum().reset_index()
+            #x.columns = x.iloc[0]  # Set first row as column headers
+            #x = x.drop(x.index[0]).reset_index(drop=True)  # Drop the row that became header
+            #x = x.apply(pd.to_numeric, errors='coerce')  # Convert all to numeric
+            lps.append(x)
+        bals_df = pd.concat(lps, ignore_index=True)
+        bals_df['token.balance'] = bals_df['token.balance'].apply(pd.to_numeric,errors='coerce')
+        bals_df['token.balanceUSD'] = bals_df['token.balanceUSD'].apply(pd.to_numeric,errors='coerce')
+
+        bals_df.fillna(0, inplace=True)
+        bals_df = bals_df.groupby('token.symbol').sum().reset_index()
+        return bals_df
+    def get_dex_balances(df):
+        balances = []
+        if df.empty:
+            return
+        for i in range(len(pd.json_normalize(df['node.positionBalances.edges']))):
+            balances.append((df['node.app.displayName'].iloc[i],agg_balances(pd.json_normalize(df['node.positionBalances.edges'].iloc[i]))))
+
+        final_balances = []
+        for i in range(len(balances)):
+            df = balances[i]
+            dex_name = df[0]  # or extract from your grouped index
+            df_pivot = df[1].pivot_table(index=None, columns='token.symbol', values='token.balance')
+            # Add DEX column and reorder
+            df_pivot.insert(0,'DEX', dex_name)
+            # Remove the first level of row index (e.g., 'token.symbol')
+            df_pivot = df_pivot.reset_index(drop=True)
+            df_pivot.columns.name = None
+            final_balances.append(df_pivot)
+
+        final_balances = pd.concat(final_balances, ignore_index=True)
+        final_balances.fillna(0, inplace=True)
+        return final_balances
+    final_balances = get_dex_balances(df)
+    return final_balances.T.drop('DEX').reset_index().rename(columns={'index':'symbol',0:'amount'}) if final_balances else pd.DataFrame([{}])
+    
+
+async def get_all_dfs():
+    #starting_df = pd.DataFrame([{"symbol":"AIQ","amount":3000000.00,"usd_value":3000000.00*0.05},{"symbol":"ETH","amount":55.5309,"usd_value":55.5309*4486.62}])
+    df, total, eth_price, base_price = await get_wallet_base_balances(base_addresses)
+    symbols = {"VICE":base_price,"WETH":eth_price}
+    lp_df = await fetch_lp()
+    if not lp_df.empty:
+        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)
+    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}")
+    return df,lp_df
+
+with gr.Blocks() as demo:
+    gr.Markdown("## VICE Balances & PnL")
+
+    df1_out = gr.Dataframe(label="Current Balances")
+    df2_out = gr.Dataframe(label="LP Balances")
+
+    demo.load(
+    fn= get_all_dfs, 
+    inputs = [],
+    outputs=[df1_out,df2_out]
+    )
+
+
+demo.launch(debug=True, share=True)

requirements.txt

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+aiohttp
+nest_asyncio
+pandas
+requests
+gradio
+web3
+numpy