Upload folder using huggingface_hub

.gradio/certificate.pem

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

README.md

@@ -1,12 +1,6 @@
 ---
-title: Maiga Balances
-emoji: 💻
-colorFrom: purple
-colorTo: red
+title: maiga_balances
+app_file: maiga_balances.py
 sdk: gradio
-sdk_version: 5.46.0
-app_file: app.py
-pinned: false
+sdk_version: 5.31.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

maiga_balances.py

@@ -0,0 +1,99 @@
+import requests
+import asyncio
+import aiohttp
+import pandas as pd
+import urllib
+import gradio as gr
+import os
+
+base_addresses = ["0x5f442A85165f91b3d2f77145EcCa795B274953Dc",'0x92E67370553B2EF8b46E7d1182aF7525a7a6BC87','0xD20FD94715c9E3a906295eFF62895e0F42ad2C43',"0xc49182156fCdC7038E68ce5cA90522c04280B10d"]
+
+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,"bnb-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)
+        for i in range(len(addresses)):
+            df.at[i,'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'] = 'BNB'
+        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')
+        bnb_price = df.loc[df['symbol']=='BNB','currentPrice'].values[0]
+        #base_price = df.loc[df['symbol']=='AIQ','currentPrice'].values[0]
+        df['value'] = df['tokenBalance'] * df['currentPrice']
+        df.drop(columns=['address','decimals'],inplace=True)
+
+        df = df[df['symbol'].isin(['MAIGA', 'BNB', 'USDT', 'USDC'])]
+        df= df[['symbol','tokenBalance','value']]
+        df = df.rename(columns={'tokenBalance':'amount','value':'usd_value'})
+        print(df)
+        df = df.groupby("symbol", as_index=False).sum()
+
+
+        return df, df['usd_value'].sum(), bnb_price
+
+
+async def get_all_dfs():
+    starting_df = pd.DataFrame([{"symbol":"MAIGA","amount":500000-300000,"usd_value":(500000-300000)*0.065213}])
+    base_df, total, bnb_price = await get_wallet_base_balances(base_addresses)
+    maiga_delta = float(base_df.loc[base_df['symbol']=="MAIGA","amount"].values[0]) - float(starting_df.loc[starting_df['symbol']=="MAIGA","amount"].values[0])
+    bnb_delta = float(base_df.loc[base_df['symbol']=="BNB","amount"].values[0])
+    position = (bnb_delta*bnb_price)/maiga_delta
+    return starting_df,base_df,abs(position)
+    
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("## AIQ Balances & PnL")
+
+    df0_out = gr.Dataframe(label="Starting Balances")
+    df1_out = gr.Dataframe(label="Current Balances")
+    position = gr.Textbox(label="Avg Sell")
+
+    demo.load(
+    fn= get_all_dfs, 
+    inputs = [],
+    outputs=[df0_out,df1_out,position]
+    )
+
+
+demo.launch(debug=True, share=True)

requirements.txt

@@ -0,0 +1,4 @@
+requests
+aiohttp
+pandas
+gradio