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app.py

@@ -11,27 +11,50 @@ import datetime
 import os
 import subprocess, json
 
-result = subprocess.run(
-    ["node", "meteora/index.js"],
-    capture_output=True,
-    text=True
-)
-
-print("STDOUT:", result.stdout)
-print("STDERR:", result.stderr)
-
-#if result.returncode != 0:
-#    raise RuntimeError(f"Node.js error: {result.stderr}")
-
-positions = json.loads(result.stdout)
-print(positions)
-lp_df_real = pd.json_normalize(positions) 
-print(lp_df_real)
-lp_df_real.drop(columns=['positionAccountAddress'],inplace=True)
-y_df_real = lp_df_real[['tokenYAddress','tokenYAmount']].copy()
-lp_df_real.rename(columns={'tokenXAddress':'symbol','tokenXAmount':'balance'},inplace=True)
-y_df_real.rename(columns={'tokenYAddress':'symbol','tokenYAmount':'balance'},inplace=True)
-final_lp_df = pd.concat([lp_df_real,y_df_real]).dropna(axis=1)
+def get_lp_positions(node_path="meteora/index.js"):
+    """
+    Runs the Node.js script, parses the output, and returns a combined DataFrame
+    with tokenX and tokenY positions.
+    """
+    try:
+        # Run Node.js script
+        result = subprocess.run(
+            ["node", node_path],
+            capture_output=True,
+            text=True
+        )
+
+        # Optional: print warnings
+        if result.stderr.strip():
+            print("Node STDERR:", result.stderr)
+
+        # Handle Node.js errors
+        if result.returncode != 0:
+            print("Node.js exited with an error")
+            return pd.DataFrame()  # return empty DataFrame on failure
+
+        # Parse JSON output
+        positions = json.loads(result.stdout) if result.stdout.strip() else []
+        if not positions:
+            return pd.DataFrame()
+
+        # Normalize JSON to DataFrame
+        lp_df_real = pd.json_normalize(positions)
+        lp_df_real.drop(columns=['positionAccountAddress'], inplace=True, errors='ignore')
+
+        # Split tokenY
+        y_df_real = lp_df_real[['tokenYAddress','tokenYAmount']].copy()
+        lp_df_real.rename(columns={'tokenXAddress':'symbol','tokenXAmount':'balance'}, inplace=True)
+        y_df_real.rename(columns={'tokenYAddress':'symbol','tokenYAmount':'balance'}, inplace=True)
+
+        # Combine tokenX and tokenY DataFrames
+        final_lp_df = pd.concat([lp_df_real, y_df_real], ignore_index=True).dropna(axis=1)
+
+        return final_lp_df
+
+    except Exception as e:
+        print(f"Error in get_lp_positions: {e}")
+        return pd.DataFrame()  # fallback empty DataFrame
 
 wallets = [
     "41KL7hbeA2dDuX6gCUFhVaozACnx2hLvGBuY4tgrpJ31",
@@ -163,8 +186,7 @@ async def get_all_dfs():
     sol_price = float(final_df.loc[final_df['symbol']=='SOL','value'] / final_df.loc[final_df['symbol']=='SOL','balance'])
     symbolMap = {'So11111111111111111111111111111111111111112':'SOL','Aq8Gocyvyyi8xk5EYxd6viUfVmVvs9T9R6mZFzZFpump':'HYPER'}
     priceMap = {'SOL':sol_price,'HYPER':hyper_price}
-    lp_df0 = final_lp_df
-    print(lp_df0)
+    lp_df0 = get_lp_positions()
     lp_df0['symbol'] = lp_df0['symbol'].map(symbolMap)
     lp_df0['value'] = lp_df0['balance'] * lp_df0['symbol'].map(priceMap)
     lp_df0 = lp_df0.groupby('symbol').agg({'balance':'sum','value':'sum'}).reset_index()

meteora/index.js

@@ -1,26 +1,32 @@
 const DLMM = require('@meteora-ag/dlmm').default;
-const {Connection, PublicKey} = require('@solana/web3.js');
+const { Connection, PublicKey } = require('@solana/web3.js');
 
 const POOL_ADDRESS = "GZ65Nw5MCJUaEEDFdpoV5CNgnyh3JDZJB6JFtAXEAjeH";
 const USER_ADDRESS = "5Xihd2FdAXZnER7HWjT8GiZm14hyPiUpGfqLLL86yaa9";
 
 (async () => {
     try {
-        const connection = new Connection('https://mainnet.helius-rpc.com/?api-key=4754acdc-8330-4d7d-98bd-b9b35af1b178');
+        const connection = new Connection(
+            'https://mainnet.helius-rpc.com/?api-key=4754acdc-8330-4d7d-98bd-b9b35af1b178'
+        );
+
         const dlmmPool = await DLMM.create(connection, new PublicKey(POOL_ADDRESS));
-        const {tokenX,tokenY}=dlmmPool
-        const {address:tokenXAddress,decimals:tokenXDecimals}=tokenX.mint;
-        const {address:tokenYAddress,decimals:tokenYDecimals}=tokenY.mint;
+        const { tokenX, tokenY } = dlmmPool;
+        const { address: tokenXAddress, decimals: tokenXDecimals } = tokenX.mint;
+        const { address: tokenYAddress, decimals: tokenYDecimals } = tokenY.mint;
 
-        const {userPositions} = await dlmmPool.getPositionsByUserAndLbPair(new PublicKey(USER_ADDRESS));
+        // Ensure userPositions is always an array
+        const { userPositions = [] } = await dlmmPool.getPositionsByUserAndLbPair(
+            new PublicKey(USER_ADDRESS)
+        );
 
         const results = [];
-        
-        userPositions.forEach((position) => {
+
+        for (const position of userPositions) {
             const { positionData } = position;
             const { totalXAmount, totalYAmount } = positionData;
-            const formattedXAmount = totalXAmount / (10 ** tokenXDecimals);
-            const formattedYAmount = totalYAmount / (10 ** tokenYDecimals);
+            const formattedXAmount = totalXAmount / 10 ** tokenXDecimals;
+            const formattedYAmount = totalYAmount / 10 ** tokenYDecimals;
 
             results.push({
                 positionAccountAddress: position.publicKey.toBase58(),
@@ -29,11 +35,14 @@ const USER_ADDRESS = "5Xihd2FdAXZnER7HWjT8GiZm14hyPiUpGfqLLL86yaa9";
                 tokenYAddress: tokenYAddress.toBase58(),
                 tokenYAmount: formattedYAmount
             });
-        });
+        }
 
-        console.log(JSON.stringify(results, null, 2));
+        // Always output a JSON array
+        console.log(JSON.stringify(results));
+        process.stdout.write("\n"); // ensure stdout flushes
     } catch (error) {
-        console.log(error);
+        // Output error as JSON to keep Python parsing safe
+        console.error(JSON.stringify({ error: error.message || error }));
         process.exit(1);
     }
-})();
+})();