Upload folder using huggingface_hub

.github/workflows/update_space.yml

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+name: Run Python script
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.9'
+
+    - name: Install Gradio
+      run: python -m pip install gradio
+
+    - name: Log in to Hugging Face
+      run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
+
+    - name: Deploy to Spaces
+      run: gradio deploy

README.md

@@ -1,12 +1,6 @@
 ---
-title: Blup Dashboard
-emoji: 🦀
-colorFrom: indigo
-colorTo: blue
-sdk: gradio
-sdk_version: 5.33.0
+title: blup-dashboard
 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
+
+addresses = [
+    "0x46dae11e3ab74C417d370FB0d467364397178f5d",
+    "0x2B3cb7D697Dd5224f3AcfC1b7EbDe77F468Dd539",
+    "0x7B04395AF49caf8C4Fd5FF716698D97f394d0d41",
+    "0x4dAFdbdB45947AB8666411AFc07F95b39Ab3841B",
+    "0xa2ebb53A922E8fe9E6949316b0018F95f0956Ce7",
+    "0x0FCc5f7845F3B2188918495f60F6294a15dc772b",
+    "0xefa59c4aE5BaBA2c1017Ce2Fc9c1E0E080e5F448",
+    "0x1C2A2D1b1A95a252AD4f9E8c9055885a1721c252",
+    "0xfCb81D6a2678D9f0798124BD3E46bA0E1Ff0C32c",
+    "0xdF04384C3AE43bD08E04692139C6B6C6Eb308B76",
+    "0xA734C747E53171261568DbBB1BCd699EDF01925c",
+    "0xC6347a0924aAbBA5E655397fbD18cb702066304b",
+    "0xc6300201821CB7026E0e73cC10dC9Ca5C623Ff15",
+    "0x2777698A53410C344e98267dB672a432c77C6Ed9",
+    "0xCCc07e973c04c607381b96eCBe3e426cc7c17B88",
+    "0xE813553077d0bfdd9615465D8A974F63bbf33aD4",
+    "0x0a045118cDb3fB0FDb50D2f91f04c56B28F5fD07",
+    "0x0bC67eE9A36f5bc8e05282E538FDe119C372a222",
+    "0x1ca7bCe8A7c4F62a3575279688D9E9ad337f6b3d",
+    "0x940665c733acBcA198306F8881c1d268E2F92DFA",
+    "0x6393613ca5a87Cc2BEe2eC3610EcAcD279FcBcD6",
+    "0xAB851cA6F8e5329Dcf9B164d312f7d5C9D41eE01",
+    "0xe2Db92758567D1D67A861F0645F850ddb6e216E8",
+    "0x4a7F42021C71Be21D3c21717743449620Abb3D25",
+    "0x2Bd99Ac1dCa390A543BD06F7712ece7B787752a5",
+    "0x8c27aa11FF3562c807C5A40e0512bDC043B39Bb0",
+    "0xB4e6dEa305a1A84FA0B2185F36de31bcE2c22005",
+    "0xA89f812f26ef2f6D89c81371A89787240c63D524",
+    "0xF7a54082215D4508CD674b270ECc37Bd281FD92d",
+    "0xc419410F5B29cdd4343013210ac194B872cF5a4B"
+]
+
+# Chunk into groups of 3
+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):
+    json_payload = {
+        "addresses": [{"address": addr, "networks": ["arb-mainnet"]} 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_balances(addresses):
+    async with aiohttp.ClientSession() as session:
+        batches = chunk_addresses(addresses, 3)
+        tasks = [fetch_batch(session, batch) 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'] = 'ETH'
+        
+        df['currentPrice'] = df['tokenPrices'].apply(lambda x : x[0].get('value',None) if len(x) > 0 else None)
+        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')
+        df['value'] = df['tokenBalance'] * df['currentPrice']
+        df.drop(columns=['address','decimals'],inplace=True)
+
+        df = df[df['symbol'].isin(['BLUP', '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()
+
+async def get_lp_balances():
+    url = "https://api.debank.com/user?id=0x275c7f2781db0b78228029f85735059c9bdd4f35"
+
+    SCRAPE_DO_TOKEN = os.getenv('SCRAPE_DO_KEY')
+
+    headers = {
+        "accept": "*/*",
+        "accept-encoding": "gzip, deflate, br, zstd",
+        "accept-language": "en-GB,en-US;q=0.9,en;q=0.8",
+        "account": '{"random_at":1749473998,"random_id":"409f9a2ab18e40d09266e2783fb7b221","user_addr":null}',
+        "origin": "https://debank.com",
+        "priority": "u=1, i",
+        "referer": "https://debank.com/",
+        "sec-ch-ua": '"Chromium";v="136", "Google Chrome";v="136", "Not.A/Brand";v="99"',
+        "sec-ch-ua-mobile": "?0",
+        "sec-ch-ua-platform": '"macOS"',
+        "sec-fetch-dest": "empty",
+        "sec-fetch-mode": "cors",
+        "sec-fetch-site": "same-site",
+        "source": "web",
+        "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36",
+        "x-api-nonce": "n_0rS1JvDi32stemeNlbalDP0AibZoN5Er25bxGuun",
+        "x-api-sign": "4a49625e6813d453f14b5801915e213a38f48146caa3e727a589ef0d5d12e99c",
+        "x-api-ts": "1749475247",
+        "x-api-ver": "v2"
+    }
+
+    encoded_url = urllib.parse.quote(url)
+    proxy_url = f"http://api.scrape.do/?token={SCRAPE_DO_TOKEN}&url={encoded_url}&forwardHeaders=True&super=True"
+    response = requests.get(proxy_url, headers=headers)
+
+    response = response.json()['data']['user']['stats']
+    top_coins = response['top_coins']
+    top_tokens = response['top_tokens']
+    coins = pd.DataFrame(top_coins)
+    tokens = pd.DataFrame(top_tokens)
+    balances = pd.concat([coins, tokens], axis=0)
+    balances.drop(columns=['id','logo_url','percent','price','chain_id'],inplace=True)
+    balances = balances[['symbol','amount','usd_value']]
+
+    return balances, balances['usd_value'].sum()
+
+async def get_all_dfs():
+    wallet_df, wallet_total = await get_wallet_balances(addresses)
+    lp_df, lp_total = await get_lp_balances()
+    final_df = pd.concat([wallet_df,lp_df],axis=0)
+    return wallet_df, wallet_total, lp_df, lp_total, final_df, final_df['usd_value'].sum()
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("## BLUP Balances and PnL")
+
+    df0_out = gr.Dataframe(label="Wallet Balances")
+    txt0_out = gr.Textbox(label="Total Value")
+
+    df1_out = gr.Dataframe(label="LP Balances")
+    txt1_out = gr.Textbox(label="Total Value")
+
+    df2_out = gr.Dataframe(label="Total Balances")
+    txt2_out = gr.Textbox(label="Total Value")
+
+    # Load from MongoDB on app load (sync function)
+    demo.load(
+    fn=  get_all_dfs, 
+    inputs = [],
+    outputs=[df0_out, txt0_out, df1_out, txt1_out, df2_out, txt2_out]
+    )
+
+demo.launch(debug=True, share=True)

requirements.txt

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+aiohttp
+nest_asyncio
+pandas
+requests
+gradio
+pymongo[srv]