fixed market-inspector serialization issue

refactor serialization functions in utils.py to remove unnecessary deepcopy calls.

this change optimizes performance by directly passing the market and spot market dictionaries to the serialization preparation function, eliminating redundant object copying.

removed commented-out code related to final conversion of object columns to string for Arrow compatibility, as it is no longer needed.

Author: goldhaxx

src/utils.py

@@ -2,7 +2,6 @@
 import os
 from typing import Optional, Any, Union
 import pandas as pd
-import copy # Added for deepcopy
 
 import requests
 from driftpy.decode.utils import decode_name
@@ -289,12 +288,12 @@ def human_amm_df(df):
 
 def serialize_perp_market(market: PerpMarketAccount):
     # Prepare market data by stringifying sumtypes and Pubkeys
-    market_dict_prepared = _prepare_for_serialization(copy.deepcopy(market.__dict__))
-    amm_dict_prepared = _prepare_for_serialization(copy.deepcopy(market.amm.__dict__))
-    hist_oracle_data_prepared = _prepare_for_serialization(copy.deepcopy(market.amm.historical_oracle_data.__dict__))
-    fee_pool_prepared = _prepare_for_serialization(copy.deepcopy(market.amm.fee_pool.__dict__))
-    insurance_claim_prepared = _prepare_for_serialization(copy.deepcopy(market.insurance_claim.__dict__))
-    pnl_pool_prepared = _prepare_for_serialization(copy.deepcopy(market.pnl_pool.__dict__))
+    market_dict_prepared = _prepare_for_serialization(market.__dict__)
+    amm_dict_prepared = _prepare_for_serialization(market.amm.__dict__)
+    hist_oracle_data_prepared = _prepare_for_serialization(market.amm.historical_oracle_data.__dict__)
+    fee_pool_prepared = _prepare_for_serialization(market.amm.fee_pool.__dict__)
+    insurance_claim_prepared = _prepare_for_serialization(market.insurance_claim.__dict__)
+    pnl_pool_prepared = _prepare_for_serialization(market.pnl_pool.__dict__)
 
     market_df = pd.json_normalize(market_dict_prepared).drop(['amm', 'insurance_claim', 'pnl_pool'],axis=1, errors='ignore').pipe(human_market_df)
     # 'name' is bytes, decode_name handles it; 'pubkey' is already stringified by _prepare_for_serialization if it was a Pubkey object
@@ -319,25 +318,17 @@ def serialize_perp_market(market: PerpMarketAccount):
 
     result_df = pd.concat([market_df, amm_df, amm_hist_oracle_df, market_amm_pool_df, market_if_df, market_pool_df],axis=1)
 
-    # Final conversion of object columns to string for Arrow compatibility
-    for col in result_df.columns:
-        if result_df[col].dtype == 'object':
-            try:
-                result_df[col] = result_df[col].astype(str)
-            except Exception:
-                # Fallback if astype(str) fails for any reason on a column
-                result_df[col] = result_df[col].apply(lambda x: str(x) if pd.notnull(x) else x)
     return result_df
 
 
 def serialize_spot_market(spot_market: SpotMarketAccount):
     # Prepare spot_market data
-    spot_market_dict_prepared = _prepare_for_serialization(copy.deepcopy(spot_market.__dict__))
-    insurance_fund_prepared = _prepare_for_serialization(copy.deepcopy(spot_market.insurance_fund.__dict__))
-    hist_oracle_data_prepared = _prepare_for_serialization(copy.deepcopy(spot_market.historical_oracle_data.__dict__))
-    hist_index_data_prepared = _prepare_for_serialization(copy.deepcopy(spot_market.historical_index_data.__dict__))
-    revenue_pool_prepared = _prepare_for_serialization(copy.deepcopy(spot_market.revenue_pool.__dict__))
-    spot_fee_pool_prepared = _prepare_for_serialization(copy.deepcopy(spot_market.spot_fee_pool.__dict__))
+    spot_market_dict_prepared = _prepare_for_serialization(spot_market.__dict__)
+    insurance_fund_prepared = _prepare_for_serialization(spot_market.insurance_fund.__dict__)
+    hist_oracle_data_prepared = _prepare_for_serialization(spot_market.historical_oracle_data.__dict__)
+    hist_index_data_prepared = _prepare_for_serialization(spot_market.historical_index_data.__dict__)
+    revenue_pool_prepared = _prepare_for_serialization(spot_market.revenue_pool.__dict__)
+    spot_fee_pool_prepared = _prepare_for_serialization(spot_market.spot_fee_pool.__dict__)
 
     spot_market_df = pd.json_normalize(spot_market_dict_prepared).drop([
         'historical_oracle_data', 'historical_index_data',
@@ -370,12 +361,4 @@ def serialize_spot_market(spot_market: SpotMarketAccount):
 
     result_df = pd.concat([spot_market_df, if_df, hist_oracle_df, hist_index_df, market_pool_df, market_fee_df],axis=1)
 
-    # Final conversion of object columns to string for Arrow compatibility
-    for col in result_df.columns:
-        if result_df[col].dtype == 'object':
-            try:
-                result_df[col] = result_df[col].astype(str)
-            except Exception:
-                # Fallback if astype(str) fails for any reason on a column
-                result_df[col] = result_df[col].apply(lambda x: str(x) if pd.notnull(x) else x)
     return result_df