(add):添加获取top trader 并分析地址

src/code/3000_get_dalao_tran_gmgnOrdex.py

@@ -0,0 +1,136 @@
+
+
+# https://dexscreener.com/solana?rankBy=trendingScoreH24&order=desc&minLiq=50000&minAge=36
+
+# 将油猴脚本获取的top trader
+from base_class import BaseVariableFunction
+from base_class import *
+baseclass = BaseVariableFunction(__file__)
+
+old_print = print
+
+
+def timestamped_print(*args, **kwargs):
+    old_print(datetime.datetime.utcnow().replace(
+        microsecond=0), *args, **kwargs)
+
+
+print = timestamped_print
+ 
+baseclass.makedirpath(baseclass.dalao_ori_tran_gmgnOrdex_path)
+baseclass.makedirpath(baseclass.dalao_tran_gmgnOrdex_path)
+baseclass.makedirpath(baseclass.dalao_merge_path)
+ 
+
+print('\n'*5)
+print(f"{'{:<6}'.format('ENTER')} {baseclass.scriptfilename} ----------------NOTE-----------NOTE---------------")
+
+def makescreenurl( urlname,urlparam):
+    # pairAddress = series[address_str]
+    urlname = urlname + urlparam
+    return '=HYPERLINK("{}","{}")'.format(urlname, urlname)
+
+ 
+        
+import re
+def filter_simple_dalao():
+
+    global arr_token_address
+
+    for tokenadd in arr_token_address:
+     
+        df_gmgn =None
+        df_dex = None
+        df =None
+  
+        if (baseclass.dalao_tran_gmgnOrdex_path /  f"{tokenadd}_top.xlsx").exists():
+            continue
+        
+        if ( baseclass.dalao_ori_tran_gmgnOrdex_path / f"{tokenadd}_top_dexscreen_sol.csv").exists():
+            df_dex =  pd.read_csv( baseclass.dalao_ori_tran_gmgnOrdex_path / f"{tokenadd}_top_dexscreen_sol.csv", dtype=object)
+            df_dex =df_dex.drop_duplicates().reset_index(drop=True)
+            df_dex =df_dex.astype({
+                "Buymoney":float,
+                "Sellmoney":float,
+                "Earn":float,
+            })
+            df_dex["Buy_sol"] = df_dex["Buymoney"] / 150
+            df_dex["Sell_sol"] = df_dex["Sellmoney"] / 150
+            df_dex["Pnl_sol"] = df_dex["Earn"] / 150
+            df_dex["Pnl_per"] = np.where(
+                    df_dex['Buy_sol'] != 0,
+                    df_dex['Pnl_sol'] / df_dex['Buy_sol'],
+                    999999,
+                )
+            df_dex =df_dex[df_dex["Pnl_per"]>0].reset_index(drop=True)
+            
+            df_dex=df_dex[[
+                'Maker',
+                'Buy_sol',
+                'Sell_sol',
+                'Pnl_sol',
+                'Pnl_per',
+                 ]]
+            
+                    
+ 
+        if ( baseclass.dalao_ori_tran_gmgnOrdex_path / f"{tokenadd}_top_gmgn_sol.csv").exists():
+            df_gmgn =  pd.read_csv( baseclass.dalao_ori_tran_gmgnOrdex_path / f"{tokenadd}_top_gmgn_sol.csv", dtype=object)
+            df_gmgn =df_gmgn.drop_duplicates().reset_index(drop=True)
+            df_gmgn =df_gmgn.astype({
+                "Buy_sol":float,
+                "Sell_sol":float,
+                "Pnl_sol":float,
+                "Pnl_per":float,
+            })
+            df_gmgn =df_gmgn[df_gmgn["Pnl_per"]>0].reset_index(drop=True)
+             
+            
+     
+       
+ 
+        df = pd.concat([ df_gmgn, df_dex  ], ignore_index=True)
+        df["Pnl_per"] = df["Pnl_per"].round(2)
+        df =df[df["Pnl_per"]>=2].reset_index(drop=True)
+        
+        df =df.sort_values(by=["Pnl_per"],ascending=True)
+        df["beizhu"] = None
+        df.loc[df["Pnl_per"]==999999,"beizhu"] = "neimu"
+  
+        # df.to_excel(baseclass.dalao_merge_path/f"total_dalao_txn_{tokenadd}.xlsx",index=False)
+        
+        print(f"enter {tokenadd}")
+        df["TokenAddress"] = tokenadd
+        
+        df =df.drop_duplicates(subset=["Maker"]).reset_index(drop=True)
+        # 示例 获取结果如下 https://www.defined.fi/sol/D6NdKrKNQPmRZCCnG1GqXtF7MMoHB7qR6GU5TkG59Qz1?maker=3ACp4T3ptTdayzWryEhT65NKZSKLjwXviBjWEy54aFdW 
+        df['DefinedURL'] = df.apply(lambda ser: makescreenurl(
+        "https://www.defined.fi/sol/", f"{ser['TokenAddress']}?maker={ser['Maker']}"), axis=1)
+            
+        df =df[ [ 
+                'Maker',
+                "beizhu",
+                 "Buy_sol" ,
+                "Sell_sol" ,
+                "Pnl_sol" ,
+                "Pnl_per",
+                "TokenAddress",
+                "DefinedURL"
+                ] ]
+        df.to_excel(baseclass.dalao_tran_gmgnOrdex_path /  f"{tokenadd}_top.xlsx",index=False )
+        
+
+ 
+    return
+
+csv_file_list = [f for f in os.listdir(
+    baseclass.dalao_ori_tran_gmgnOrdex_path) if f.endswith(".csv") ]
+arr_token_address = [tokenadd.split("_")[0] for tokenadd in csv_file_list  ]
+arr_token_address=list(set(arr_token_address))
+
+
+print("arr_token_address= ",arr_token_address)
+
+filter_simple_dalao()
+
+print(f"{'{:<6}'.format('END')} {baseclass.scriptfilename} ----------------NOTE-----------NOTE---------------")

src/code/3002_hanle_dalao_ori_pnl_gmgn_consider_0profit.py

@@ -0,0 +1,121 @@
+
+from base_class import BaseVariableFunction
+from base_class import *
+baseclass = BaseVariableFunction(__file__)
+
+baseclass.makedirpath(baseclass.dalao_pnl_gmgn_path)
+
+old_print = print
+ 
+
+def timestamped_print(*args, **kwargs):
+    old_print(datetime.datetime.utcnow().replace(
+        microsecond=0), *args, **kwargs)
+
+
+print = timestamped_print
+print('\n'*5)
+
+ 
+print(f"{'{:<6}'.format('enter')}  ----------------NOTE-----------NOTE---------------")
+
+def makescreenurl( urlname,urlparam):
+    # pairAddress = series[address_str]
+    urlname = urlname + urlparam
+    return '=HYPERLINK("{}","{}")'.format(urlname, urlname)
+
+# weth 0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2
+# USDT 0xdac17f958d2ee523a2206206994597c13d831ec7
+# USDC 0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48
+def get_temp_dalao_pnl(temp_df ,str_dalaoaddress ):
+    
+    temp_df["isnengen"] = -1
+    temp_df["beizhu"] = -1
+    temp_df["definedurl"] = temp_df.apply(lambda ser: makescreenurl("https://www.defined.fi/sol/" ,f"{ser['tokenaddress']}?maker={str_dalaoaddress}")  , axis=1)
+    temp_df["dexurl"] = temp_df.apply(lambda ser: makescreenurl( f"https://dexscreener.com/solana/",f"{ser['tokenaddress']}?maker={str_dalaoaddress}")  , axis=1)
+    
+
+
+    temp_df.to_excel(baseclass.dalao_pnl_gmgn_path / f"temp_gmgn_pnl_{str_dalaoaddress}.xlsx", index=False )
+    
+    
+arr_exclude_tokenaddress = [
+                        "0x0000000000000000000000000000000000000000",
+                        "0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2" ,
+                        "0xdac17f958d2ee523a2206206994597c13d831ec7",
+                        "0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48"]
+
+def hanle_dalao_ori_pnl_gmgn(arr_str_dalaoaddress):
+        print("enter hanle_dalao_ori_pnl_gmgn")
+        
+        for str_dalaoaddress in arr_str_dalaoaddress:
+                try:
+                        if not (baseclass.dalao_ori_pnl_gmgn_path / f"ori_gmgn_pnl_{str_dalaoaddress}.csv").exists():
+                                continue
+                        
+                        print(f"hanle_dalao_ori_pnl_gmgn str_dalaoaddress= {str_dalaoaddress}")
+                        dalao_df = pd.read_csv(baseclass.dalao_ori_pnl_gmgn_path /
+                                f"ori_gmgn_pnl_{str_dalaoaddress }.csv", dtype= object)
+                        
+
+                        dalao_df  =dalao_df[~ dalao_df["tokenaddress"].isin( arr_exclude_tokenaddress )].reset_index(drop=True)
+                        
+                        dalao_df.to_csv(baseclass.dalao_ori_pnl_gmgn_path /
+                                f"ori_gmgn_pnl_{str_dalaoaddress }.csv", index=False)
+                        
+                        
+                        arr_last_active = dalao_df["last_active"].tolist()
+                        for idx , str_last_active in enumerate(arr_last_active ):
+                                if "min"   in str_last_active  or  "h" in str_last_active or  "s" in str_last_active:
+                                        arr_last_active[idx] = "0"
+                                elif "d" in str_last_active:
+                                        arr_last_active[idx] = str_last_active.replace("d","")
+                                dalao_df["last_active"] = arr_last_active
+                        dalao_df['30d_txns_buy'] = dalao_df['30d_txns_buy'].str.replace(',', '')
+                        dalao_df['30d_txns_sell'] = dalao_df['30d_txns_sell'].str.replace(',', '')
+                        dalao_df['profit_percent'] = dalao_df['profit_percent'].str.replace('>', '')
+                        dalao_df['30d_txns_buy'] = dalao_df['30d_txns_buy'].str.replace("K", '000', regex=True)
+                        dalao_df['30d_txns_sell'] = dalao_df['30d_txns_sell'].str.replace("K", '000', regex=True)
+                        dalao_df['30d_txns_buy'] = dalao_df['30d_txns_buy'].str.replace(r'[,\.]', '', regex=True)
+                        dalao_df['30d_txns_sell'] = dalao_df['30d_txns_sell'].str.replace(r'[,\.]', '', regex=True)
+        
+                        dalao_df = dalao_df.astype({
+                                "last_active" :  int ,
+                                "profit_eth" :  float ,
+                                "profit_percent" :  float ,
+                                "buy_eth" :  float ,
+                                "sell_eth" : float  ,
+                                "30d_txns_buy" :  int ,
+                                "30d_txns_sell":  int ,
+                        
+                        })
+        
+        
+                        # dalao_df=dalao_df[dalao_df["profit_eth"] !=0].reset_index(drop=True)
+                        if len(dalao_df)==0:
+                                continue
+                        
+                        temp_df = dalao_df.copy()
+                        get_temp_dalao_pnl(temp_df=temp_df ,str_dalaoaddress=str_dalaoaddress)
+                        
+                        dalao_df.to_csv( baseclass.dalao_pnl_gmgn_path / f"gmgn_pnl_{str_dalaoaddress}.csv",index  = False )
+                        
+                        
+        
+             
+                except Exception as e:
+                        print(f"str_dalaoaddress= {str_dalaoaddress}",e)
+                        raise 
+        
+        
+
+arr_file =os.listdir(baseclass.dalao_ori_pnl_gmgn_path )
+
+
+df =  pd.read_excel( baseclass.dalao_merge_path / f"merge.xlsx", dtype=object)
+arr_str_dalaoaddress = df['dalaoaddress'].drop_duplicates().tolist()
+
+hanle_dalao_ori_pnl_gmgn(arr_str_dalaoaddress=arr_str_dalaoaddress)
+
+print(f"{'{:<6}'.format('END')} {baseclass.scriptfilename} ----------------NOTE-----------NOTE---------------")
+

src/code/3003_analysis_dalao_pnl_gmgn_consider_0profit.py

@@ -0,0 +1,299 @@
+
+from base_class import BaseVariableFunction
+from base_class import *
+baseclass = BaseVariableFunction(__file__)
+
+old_print = print
+ 
+
+def timestamped_print(*args, **kwargs):
+    old_print(datetime.datetime.utcnow().replace(
+        microsecond=0), *args, **kwargs)
+
+def makescreenurl( urlname,urlparam):
+    # pairAddress = series[address_str]
+    urlname = urlname + urlparam
+    return '=HYPERLINK("{}","{}")'.format(urlname, urlname)
+
+print = timestamped_print
+print('\n'*5)
+print(f"{'{:<6}'.format('enter')}  ----------------NOTE-----------NOTE---------------")
+
+baseclass.makedirpath(  baseclass.dalao_pnl_gmgn_path)
+baseclass.makedirpath(baseclass.dalao_total_ana_gmgn_path)
+
+
+ 
+def get_ana_data_lastdays( df,    intervaldays=30):
+    if len(df) == 0:
+        return 0, 0, 0, 0, 0, 0, 0, 0, 0 
+ 
+    lastdf = df[df["last_active"] <=  intervaldays]
+    # 去除那些 只有卖没有买的
+    # lastdf = lastdf[lastdf['buy_eth'] != 0]
+    
+    # lastdf=lastdf[lastdf["profit_eth"] !=0] 
+        
+    # 去除 buy_eth 过小的 < 0.2 eth  
+    # lastdf = lastdf[lastdf['buy_eth'] >= 0.05]
+
+    lastdf = lastdf.reset_index(drop=True)
+    
+    
+    if len(lastdf) == 0:
+        return 0, 0, 0, 0, 0, 0, 0, 0, 0 ,0,0,0,0,0
+    
+    lastdf["profit_eth"]  = np.where(
+        lastdf['profit_eth'] != 0,
+        lastdf['profit_eth'] ,
+        lastdf['sell_eth'] - lastdf['buy_eth'],
+       
+    )
+
+ 
+    _cost_sum = lastdf['buy_eth'].sum()
+    _earn_sum = lastdf['profit_eth'].sum()
+    _cost_median = lastdf['buy_eth'].median()
+    _cost_mean = lastdf['buy_eth'].mean()
+    _earnper = _earn_sum / _cost_sum if _cost_sum != 0 else 999999
+    _trans_amount = len(lastdf)
+    lastdf['earn_percent'] = np.where(
+        lastdf['buy_eth'] != 0,
+        lastdf['profit_eth'] / lastdf['buy_eth'],
+        999999,
+    )
+    earn_per_neg100_neg50 = len( lastdf[ (lastdf["earn_percent"] >=-1) & (lastdf["earn_percent"] <=-0.5 )] )
+    earn_per_neg50_pos0 = len( lastdf[ (lastdf["earn_percent"] >-0.5)& (lastdf["earn_percent"] <=0)  ] )
+    earn_per_pos0_pos100 = len( lastdf[( lastdf["earn_percent"] >0) & (lastdf["earn_percent"] <=1 )  ] )
+    earn_per_pos100_posmax = len( lastdf[ lastdf["earn_percent"] >1 ] )
+    
+    earn_per_pos400_posmax =  len( lastdf[ lastdf["earn_percent"] > 3 ] )
+    
+    
+    earnmain_max = lastdf['profit_eth'].max()
+    _earn_difmax_sum = _earn_sum - earnmain_max
+    _cost_difmax_sum = _cost_sum - \
+        lastdf[lastdf['profit_eth'] == earnmain_max]['buy_eth'].to_list()[0]
+    _dif_earnper = (
+        _earn_difmax_sum / _cost_difmax_sum if _cost_difmax_sum != 0 else 999999
+    )
+    
+    
+    return (
+        _cost_sum,
+        _earn_sum,
+        _earnper,
+        _cost_difmax_sum,
+        _earn_difmax_sum,
+        _dif_earnper,
+        _cost_median,
+        _cost_mean,
+        _trans_amount,
+        earn_per_neg100_neg50,
+        earn_per_neg50_pos0,
+        earn_per_pos0_pos100,
+        earn_per_pos100_posmax,
+        earn_per_pos400_posmax,
+ 
+    )
+
+
+  
+def main():
+    global arr_totalAnalysis
+    for str_dalaoaddress_idx in range(0, len(arr_str_dalaoaddress)):
+        
+        str_dalaoaddress= arr_str_dalaoaddress[str_dalaoaddress_idx]
+        print(f"enter str_dalaoaddress= {str_dalaoaddress}")
+        if not (baseclass.dalao_pnl_gmgn_path / f"gmgn_pnl_{str_dalaoaddress}.csv").exists():
+            continue
+        
+        cur_df = pd.read_csv( baseclass.dalao_pnl_gmgn_path / f"gmgn_pnl_{str_dalaoaddress}.csv",dtype=object)
+        if len(cur_df)==0:
+            continue
+        
+ 
+        
+        cur_df = cur_df.astype({
+            "last_active" :  int ,
+            "profit_eth" :  float ,
+            "profit_percent" :  float ,
+            "buy_eth" :  float ,
+            "sell_eth" : float  ,
+            "30d_txns_buy" :  int ,
+            "30d_txns_sell":  int ,
+            
+        })
+                
+        cur_df = cur_df[ cur_df["last_active"]<=30].reset_index(drop=True)
+        cur_df=cur_df[cur_df["30d_txns_buy"] !=0].reset_index(drop=True)
+        # cur_df.to_csv( baseclass.dalao_pnl_gmgn_path / f"gmgn_pnl_{str_dalaoaddress}.csv",index  = False )
+        
+        if len(cur_df)==0:
+            continue
+        
+        (_07d_cost, _07d_earn, _07d_earnper, _07d_difcost, _07d_difearn, _07d_difper, 
+        _07d_costmedian, _07d_costmean,    _07d_trans ,    _07d_earn_per_neg100_neg50,
+        _07d_earn_per_neg50_pos0,        _07d_earn_per_pos0_pos100,     
+        _07d_earn_per_pos100_posmax,   _07d_earn_per_pos400_posmax  ,   ) = get_ana_data_lastdays( df=cur_df, intervaldays=7)
+        
+        # (_15d_cost, _15d_earn, _15d_earnper, _15d_difcost, _15d_difearn, _15d_difper, 
+        # _15d_costmedian, _15d_costmean,    _15d_trans ,   ) = get_ana_data_lastdays( df=cur_df, intervaldays=15)
+        
+        (_30d_cost, _30d_earn, _30d_earnper, _30d_difcost, _30d_difearn, _30d_difper, 
+        _30d_costmedian, _30d_costmean,    _30d_trans ,   _30d_earn_per_neg100_neg50,
+        _30d_earn_per_neg50_pos0,        _30d_earn_per_pos0_pos100,   
+        _30d_earn_per_pos100_posmax, _30d_earn_per_pos400_posmax ,  ) = get_ana_data_lastdays( df=cur_df, intervaldays=30)
+        
+        (_365d_cost, _365d_earn, _365d_earnper, _365d_difcost, _365d_difearn, _365d_difper, 
+        _365d_costmedian, _365d_costmean,    _365d_trans ,   _365d_earn_per_neg100_neg50,
+        _365d_earn_per_neg50_pos0,        _365d_earn_per_pos0_pos100,   
+        _365d_earn_per_pos100_posmax, _365d_earn_per_pos400_posmax ,  ) = get_ana_data_lastdays( df=cur_df, intervaldays=365)
+        
+        str_url =   f"https://gmgn.ai/sol/address/{str_dalaoaddress}"
+        
+        arr_one_ana_data = [
+            str_dalaoaddress,
+           
+            '=HYPERLINK("{}","{}")'.format(str_url, str_url),
+            "",
+    
+            _07d_cost,
+            _07d_earn,
+            _07d_earnper,
+            _07d_difcost,
+            _07d_difearn,
+            _07d_difper,
+            _07d_costmedian,
+            _07d_costmean,
+            _07d_trans,
+            _07d_earn_per_neg100_neg50,
+            _07d_earn_per_neg50_pos0,
+            _07d_earn_per_pos0_pos100,
+            _07d_earn_per_pos100_posmax,
+           (_07d_earn_per_pos100_posmax -_07d_earn_per_neg100_neg50 ) / _07d_trans if _07d_trans!=0 else 0,
+           (_07d_earn_per_pos400_posmax *2 +    _07d_earn_per_pos100_posmax - _07d_earn_per_pos400_posmax  -_07d_earn_per_neg100_neg50  ) / _07d_trans if _07d_trans!=0 else 0,
+
+
+            _30d_cost,
+            _30d_earn,
+            _30d_earnper,
+            _30d_difcost,
+            _30d_difearn,
+            _30d_difper,
+            _30d_costmedian,
+            _30d_costmean,
+            _30d_trans,
+            _30d_earn_per_neg100_neg50,
+            _30d_earn_per_neg50_pos0,
+            _30d_earn_per_pos0_pos100,
+            _30d_earn_per_pos100_posmax,
+            (_30d_earn_per_pos100_posmax -_30d_earn_per_neg100_neg50 )/ _30d_trans if _30d_trans!=0 else 0,
+            (_30d_earn_per_pos400_posmax *2 + _30d_earn_per_pos100_posmax - _30d_earn_per_pos400_posmax  -_30d_earn_per_neg100_neg50  ) / _30d_trans if _30d_trans!=0 else 0,
+
+
+            _365d_cost,
+            _365d_earn,
+            _365d_earnper,
+            _365d_difcost,
+            _365d_difearn,
+            _365d_difper,
+            _365d_costmedian,
+            _365d_costmean,
+            _365d_trans,
+     
+
+
+        ]
+        arr_totalAnalysis.append(arr_one_ana_data)
+        if len(arr_totalAnalysis )%50==0:
+            save_total_ana_df()
+
+
+    
+TotalAnalysis_columns = [
+    "add",
+    "url",
+    "beizhu",
+ 
+
+    "07d_cost",
+    "07d_earn",
+    "07d_earnper",
+    "07d_difcost",
+    "07d_difearn",
+    "07d_difper",
+    "07d_costmedian",
+    "07d_costmean",
+    "07d_trans",
+    "07d_earn_per_neg100_neg50",
+    "07d_earn_per_neg50_pos0",
+    "07d_earn_per_pos0_pos100",
+    "07d_earn_per_pos100_posmax",
+    "07d_earn_pos_dif",
+    "07d_earn_pos_dif_4x",
+		
+ 
+    "30d_cost",
+    "30d_earn",
+    "30d_earnper",
+    "30d_difcost",
+    "30d_difearn",
+    "30d_difper",
+    "30d_costmedian",
+    "30d_costmean",
+    "30d_trans",
+    "30d_earn_per_neg100_neg50",
+    "30d_earn_per_neg50_pos0",
+    "30d_earn_per_pos0_pos100",
+    "30d_earn_per_pos100_posmax",
+    "30d_earn_pos_dif",
+    "30d_earn_pos_dif_4x",
+    
+    
+    "365d_cost",
+    "365d_earn",
+    "365d_earnper",
+    "365d_difcost",
+    "365d_difearn",
+    "365d_difper",
+    "365d_costmedian",
+    "365d_costmean",
+    "365d_trans",
+
+    
+    
+
+]
+
+
+def save_total_ana_df():
+    cur_time = int(time.time())
+    # cur_time=cur_time/1000
+ 
+    TotalAnalysis_df = pd.DataFrame(
+        data=arr_totalAnalysis, columns=TotalAnalysis_columns
+    )
+
+    TotalAnalysis_df = TotalAnalysis_df.round(4)
+    TotalAnalysis_df = TotalAnalysis_df.sort_values(by=["add"], ascending=[
+        True]).reset_index(drop=True)
+ 
+ 
+    TotalAnalysis_df.to_excel(
+        baseclass.dalao_total_ana_gmgn_path/f"totalana.xlsx", index=False)
+
+         
+df =  pd.read_excel( baseclass.dalao_merge_path / f"merge.xlsx", dtype=object)
+
+arr_str_dalaoaddress = df['dalaoaddress'].drop_duplicates().tolist()
+
+
+arr_totalAnalysis = []
+   
+main()
+save_total_ana_df()
+     
+    
+print(f"{'{:<6}'.format('END')} {baseclass.scriptfilename} ----------------NOTE-----------NOTE---------------")
+

src/code/2002_gmgn_playwright_chrome.py → src/code/base_2002_3001_get_dalao_ori_pnl_gmgn_playwright_firefox.py

@@ -16,7 +16,7 @@ baseclass = BaseVariableFunction(__file__)
 
 
 
-baseclass.makedirpath(baseclass.library_path)
+ 
 baseclass.makedirpath(baseclass.dalao_ori_pnl_gmgn_path)
  
 old_print = print
@@ -31,7 +31,7 @@ print = timestamped_print
 print('\n'*5)
 
  
-print(f"{'{:<6}'.format('enter')}  ----------------NOTE-----------NOTE---------------")
+print(f"{'{:<6}'.format('ENTER')} {baseclass.scriptfilename} ----------------NOTE-----------NOTE---------------")
 
 
 number_chars_arr = ["k", "m", "b", "t", "p"]
@@ -47,14 +47,42 @@ number_chars_obj = {
 
 
 activities_columns = ['tokenaddress', 'tokenname',  'last_active', 
-                      'profit_sol',   'profit_percent', 
-                    'buy_sol', 'sell_sol',  
+                      'profit_eth',   'profit_percent', 
+                    'buy_eth', 'sell_eth',  
                     '30d_txns_buy','30d_txns_sell',  ]
 
  
+async def check_tbody_isfull(page ,str_dalaoaddress):
+    table = page.locator('div[aria-labelledby="tabs-leftTabs--tab-0"]')
+    tbody_ = table.locator(
+        'tbody')
+    arr_trs = await tbody_.locator('tr').all()
+    print( f"{str_dalaoaddress} arr_trs len =", len(arr_trs))
+    if len(arr_trs)>=200:
+        return True
+    if len(arr_trs)==0:
+        return False
 
+    last_tr = arr_trs[-1]
+    arr_tds = await last_tr.locator('td').all()
+    p_token_last_active =  arr_tds[0].locator("p")
+    str_token_last_active =( await p_token_last_active.text_content()).strip()
+    if "--"   in str_token_last_active :
+        return True
+    
+    if "d" not in str_token_last_active :
+        return False
+    str_token_last_active=str_token_last_active.replace("d","")
+    number_token_last_active =  int(str_token_last_active)
+    print( f" {str_dalaoaddress} number_token_last_active =",   (number_token_last_active))
+    if number_token_last_active>360:
+        return True
+    else :
+        return False
+     
 
 async def do_some_thing(playwright, cur_arr_str_dalaoaddress, cur_arr_str_dalaoUrl):
+    global dalao_len
 
 
     # browser =  playwright.chromium.launch(headless=True)
@@ -64,19 +92,12 @@ async def do_some_thing(playwright, cur_arr_str_dalaoaddress, cur_arr_str_dalaoU
     # context = browser.new_context()
     context.set_default_timeout(28000)
     # context = await browser.new_context()
-    arr_page = [None]*10
-    # arr_page[0] = await context.new_page()
-    # # page = arr_page[0]
-    # await arr_page[0].goto(
-    #     "https://gmgn.ai/" , timeout=100000)
-   
+    arr_page = [None]*dalao_len
     
     global set_str_dalaoaddress
     arr_str_dalaoaddress = cur_arr_str_dalaoaddress
     arr_str_dalaoUrl = cur_arr_str_dalaoUrl
     
-    dalao_len = 6
-    
     for str_dalaoaddress_idx in range(0, len(arr_str_dalaoaddress) , dalao_len):
         cur_arr_str_dalaoaddress = []
         cur_arr_str_dalaoUrl = []
@@ -99,25 +120,22 @@ async def do_some_thing(playwright, cur_arr_str_dalaoaddress, cur_arr_str_dalaoU
 
         # 获取 交易token较少的        
         # done, pending = await asyncio.wait(tasks_for_wait, timeout=60)
-
-        done, pending = await asyncio.wait(tasks_for_wait, timeout=200)
-    
-    
+        done, pending = await asyncio.wait(tasks_for_wait, timeout=300)
+        # for page in arr_page:
+        #     if page is not None:
+        #         print(f"do_some_thing  close")
+        #         await page.close()
     
-    # await page.wait_for_timeout(3000)
-    # time.sleep(5.5)
-    # await page.close()
     await asyncio.sleep(3)
     await context.close()
 async def handle_one_page( idx_page,context, arr_page, str_dalaoaddress , str_dalaoUrl ):
     global set_str_dalaoaddress
     page = None
     try:
-    
         arr_page[idx_page] = await context.new_page()
-        await   arr_page[idx_page].goto( str_dalaoUrl, timeout=29000)
+        await   arr_page[idx_page].goto(str_dalaoUrl, timeout=29000)
         page =  arr_page[idx_page]
-        sleep_time = random.randint(10,30)
+        sleep_time = random.randint(10,20)
         sleep_time=sleep_time/10
 
         await asyncio.sleep(sleep_time)
@@ -143,10 +161,10 @@ async def handle_one_page( idx_page,context, arr_page, str_dalaoaddress , str_da
                 break
             await page.evaluate(
                 "window.scrollTo(0, document.body.scrollHeight);")
-            await asyncio.sleep(1)
+            await asyncio.sleep(2)
             await page.evaluate(
                 "window.scrollTo(0, document.body.scrollHeight);")
-            await asyncio.sleep(1)
+            await asyncio.sleep(3)
             cur_page_height = await page.evaluate(
                 "document.documentElement.scrollHeight")
             print(f"prev_page_height={prev_page_height} cur_page_height={cur_page_height}  ")
@@ -158,24 +176,19 @@ async def handle_one_page( idx_page,context, arr_page, str_dalaoaddress , str_da
         while True:
             try:
                 tbody_data = await get_tbody_data(page=page, str_dalaoaddress=str_dalaoaddress)
-
-            except Exception as e:
-                    
+            except Exception as e: 
                 print(traceback.format_exc())
                 await asyncio.sleep(2)
                 raise
-              
             if tbody_data is None:
                 await asyncio.sleep(0.8)
                 raise("tbody_data is None")
-              
             else:
                 break
         dalao_df = pd.DataFrame(
             tbody_data, columns=activities_columns)
         dalao_df.to_csv(baseclass.dalao_ori_pnl_gmgn_path /
                 f"ori_gmgn_pnl_{str_dalaoaddress}.csv", index=False)
-
         set_str_dalaoaddress.discard(str_dalaoaddress)
 
     except Exception as e:
@@ -184,36 +197,7 @@ async def handle_one_page( idx_page,context, arr_page, str_dalaoaddress , str_da
         print(f"str_dalaoaddress= {str_dalaoaddress} close")
         await page.close()
 
-async def check_tbody_isfull(page ,str_dalaoaddress):
-    table = page.locator('div[aria-labelledby="tabs-leftTabs--tab-0"]')
-    tbody_ = table.locator(
-        'tbody')
-    arr_trs = await tbody_.locator('tr').all()
-    print( f"{str_dalaoaddress} arr_trs len =", len(arr_trs))
-    if len(arr_trs)>=160:
-        return True
-    if len(arr_trs)==0:
-        return False
 
-    last_tr = arr_trs[-1]
-    
-    arr_tds = await last_tr.locator('td').all()
-    
-    p_token_last_active =  arr_tds[0].locator("p")
-    str_token_last_active =( await p_token_last_active.text_content()).strip()
-    if "--"   in str_token_last_active :
-        return True
-    
-    if "d" not in str_token_last_active :
-        return False
-    str_token_last_active=str_token_last_active.replace("d","")
-    number_token_last_active =  int(str_token_last_active)
-    print( f" {str_dalaoaddress} number_token_last_active =",   (number_token_last_active))
-    if number_token_last_active>30:
-        return True
-    else :
-        return False
-     
 
 async def get_tbody_data(page, str_dalaoaddress):
     arr_tokenlink = None
@@ -229,9 +213,13 @@ async def get_tbody_data(page, str_dalaoaddress):
     
         await asyncio.sleep(3)
         arr_trs = await tbody_.locator('tr').all()
-        arr_trs=arr_trs[0:160]
+        arr_trs=arr_trs[0:200]
         arr_trs_datares = []
+        flag_end = False
         for idx_tr_ in range(0, len(arr_trs)):
+            
+            if flag_end == True :
+                break
             if(idx_tr_ %20==0):
                 print(f"get_tbody_data {str_dalaoaddress} {idx_tr_}")
             arr_tds_datares = [None]*9
@@ -241,19 +229,16 @@ async def get_tbody_data(page, str_dalaoaddress):
             tr_ = arr_trs[idx_tr_]
             listen_tr_ = tr_
             arr_tds = await tr_.locator('td').all()
+            is_warning = False
             # 共有10列 
             # 'Token/Last Active', 'Unrealized',  '30D Realized Profit', 
             #           'Total Profit',  'Balance',   
             #           'Position %',  'Bought', 
             #             'Sold',   '30D TXs','Ahare'
-                        
             for idx_td_ in range(0, len(arr_tds)):
-                
                 td_ = arr_tds[idx_td_]
                 listen_td_ =td_
-                 
                 if (idx_td_ == 0):
-                    
                     # Token/Last Active
                     arr_tokenlink = await td_.locator("a").all()
                     href_tokenaddress_name = await  arr_tokenlink[0].get_attribute('href')
@@ -268,7 +253,6 @@ async def get_tbody_data(page, str_dalaoaddress):
                         str_tokenname = str_tokenname + "_"+str_tokenaddress[0:4]
                     else:  
                         str_tokenname = await div_title.get_attribute('title')
-         
                     str_tokenname = re.sub(r'[^!-~]', '', str_tokenname)
                     str_tokenname = str_tokenname.replace(",","")
                     if str_tokenname=="":
@@ -278,8 +262,24 @@ async def get_tbody_data(page, str_dalaoaddress):
                                        
                     str_token_last_active = (await p_token_last_active.text_content()).strip()
                     if str_token_last_active == "--":
+                        flag_end = True
                         arr_trs_datares.pop()
                         break
+                    
+                    if "min"   in str_token_last_active  or  "h" in str_token_last_active or  "s" in str_token_last_active:
+                        str_token_last_active = "0d"
+                    temp_str_token_last_active=str_token_last_active.replace("d","")
+                    number_token_last_active =  int(temp_str_token_last_active)
+                   
+                    if number_token_last_active > 45:
+                        flag_end = True
+                        arr_trs_datares.pop()
+                        break
+                    
+                    g_warning =   td_.locator('g[clip-path="url(#clip0_6068_12422)"]')
+                    if (await g_warning.count()) != 0:
+                        is_warning = True
+        
                     arr_tds_datares[0] = str_tokenaddress
                     arr_tds_datares[1] = str_tokenname
                     arr_tds_datares[2] = str_token_last_active
@@ -300,7 +300,7 @@ async def get_tbody_data(page, str_dalaoaddress):
                     if "$" in str_profit_sol:
                         raise Exception("$ in Total Profit")
                     
-                    str_profit_sol =  re.sub(r'[sol,%\+><sol]', "", str_profit_sol)
+                    str_profit_sol =  re.sub(r'[sol,%\+><]', "", str_profit_sol)
                     str_profit_sol=str_profit_sol.strip()
                     str_profit_percent =  re.sub(r'[sol,%\+><]', "", str_profit_percent)
                     str_profit_percent=str_profit_percent.strip()
@@ -326,6 +326,9 @@ async def get_tbody_data(page, str_dalaoaddress):
                 
                     arr_tds_datares[3] = str_profit_sol
                     arr_tds_datares[4] = str(  round ( ( float(str_profit_percent) /100),2)   )
+                    if is_warning ==True:
+                        arr_tds_datares[4]="-1"
+                        
  
                 elif (idx_td_ == 4):
                     # balance
@@ -345,14 +348,12 @@ async def get_tbody_data(page, str_dalaoaddress):
                     str_buy_sol =  re.sub(r'[sol,%\+><]', "", str_buy_sol)
                     str_buy_sol=str_buy_sol.strip()
                 
-                    
                     for str_number_char in number_chars_arr  :
                         if str_number_char in str_buy_sol:
                             str_buy_sol=str_buy_sol.replace( str_number_char  ,"")
                             number_buy_sol = float(str_buy_sol) * 10 ** number_chars_obj[str_number_char]
                             str_buy_sol = str(number_buy_sol)
            
-                            
                     arr_tds_datares[5] = str_buy_sol
                     
                    
@@ -371,19 +372,17 @@ async def get_tbody_data(page, str_dalaoaddress):
                             
                     arr_tds_datares[6] = str_sell_sol
                     
-          
                 elif (idx_td_ == 8):
                     #30d txns
                     
                     str_30d_txns= (await td_.text_content()).strip()
-                    # str_30d_txns = re.sub(r'\s+', '', str_30d_txns)
+               
                     str_30d_txns =  re.sub(r'[\s,><]', "", str_30d_txns)
           
                     arr_30dtxns = str_30d_txns.split("/")
                     str_buy_txns = arr_30dtxns[0]
                     str_sell_txns =arr_30dtxns[1]
                     
-
                     for str_number_char in number_chars_arr :
                         if str_number_char in str_buy_txns:
                             str_buy_txns=str_buy_txns.replace( str_number_char  ,"")
@@ -395,17 +394,20 @@ async def get_tbody_data(page, str_dalaoaddress):
                                 str_sell_txns = float(str_sell_txns) * 10 ** number_chars_obj[str_number_char]
                                 str_sell_txns = str(str_sell_txns)
 							
-                    
-                    
                     arr_tds_datares[7] = str_buy_txns
                     arr_tds_datares[8] = str_sell_txns
                                  
         return arr_trs_datares
 
     except Exception as e:
-        print( "error",str_dalaoaddress,     "listen_tr_=",(await listen_tr_.text_content()), 
+        print("error e= ",e)
+        # print( "error",str_dalaoaddress, "listen_tr_=",(await listen_tr_.text_content()), 
+        #       "listen_td_=",  (await listen_td_.text_content()) 
+        #       )
+        print( "error",str_dalaoaddress,  
               "listen_td_=",  (await listen_td_.text_content()) 
               )
+                
         raise
 
 
@@ -417,19 +419,15 @@ async def get_onedriver_swapactivities(cur_arr_str_dalaoaddress, cur_arr_str_dal
 
 async def main():
     print("enter main()")
-    # tasks = [get_onedriver_swapactivities(
-    #     arr_split_str_dalaoaddress[idx_driver], arr_split_str_dalaoSwapUrl[idx_driver] ) for idx_driver in range(0, driver_len)]
-
-    # await asyncio.gather(*tasks)
-    
-    await  get_onedriver_swapactivities( arr_split_str_dalaoaddress[0], arr_split_str_dalaoSwapUrl[0] )  
+  
+    await  get_onedriver_swapactivities( arr_str_dalaoaddress   , arr_str_dalaoUrl )  
         
  
     
 
 
 
-df =  pd.read_excel( baseclass.dalao_merge_defined_path / f"merge_defined.xlsx", dtype=object)
+df =  pd.read_excel( baseclass.dalao_merge_path / f"merge.xlsx", dtype=object)
 
 arr_str_dalaoaddress = df['dalaoaddress'].drop_duplicates().tolist()
 
@@ -438,34 +436,28 @@ for str_dalaoaddress in temp_arr_dalaoaddress:
     if (baseclass.dalao_ori_pnl_gmgn_path /
             f"ori_gmgn_pnl_{str_dalaoaddress}.csv").exists():
         arr_str_dalaoaddress.remove(str_dalaoaddress)
-        
+
+    
+
+# arr_str_dalaoaddress = [
+#     "6P4aHkv7oTbwMK6P57sVsejE52jNFeEvYhQMEBpNNN1U",
+#     "JD38n7ynKYcgPpF7k1BhXEeREu1KqptU93fVGy3S624k"
+# ]
 arr_str_dalaoUrl = [
 f"https://gmgn.ai/sol/address/{str_dalaoaddress}" for str_dalaoaddress in arr_str_dalaoaddress]
 
 print('arr_str_dalaoaddress', len(arr_str_dalaoaddress))
-driver_len = 1 if len(arr_str_dalaoaddress) >= 1 else len(
-    arr_str_dalaoaddress)
-arr_driver = [None]*driver_len
-arr_wait = [None]*driver_len
-arr_home_handle = [None]*driver_len
-arr_split_str_dalaoaddress = [None]*driver_len
-arr_split_str_dalaoSwapUrl = [None]*driver_len
-len_split_str_dalaoaddress = int(len(arr_str_dalaoaddress)/driver_len)+1
-
-for idx_driver in range(0, driver_len):
-    arr_split_str_dalaoaddress[idx_driver] = arr_str_dalaoaddress[idx_driver *
-                                                                  len_split_str_dalaoaddress: (idx_driver+1)*len_split_str_dalaoaddress]
-    arr_split_str_dalaoSwapUrl[idx_driver] = arr_str_dalaoUrl[idx_driver *
-                                                                  len_split_str_dalaoaddress: (idx_driver+1)*len_split_str_dalaoaddress]
-
+ 
 
 set_str_dalaoaddress = set(arr_str_dalaoaddress)
 
+ 
 
-
-  
+dalao_len = 1
 USER_DIR_PATH =  baseclass.browsercookie_path   
 baseclass.makedirpath(USER_DIR_PATH)
 asyncio.run(main())
-# main()
-print(f"{'{:<6}'.format('END')}  ----------------NOTE-----------NOTE---------------")
+
+
+print(f"{'{:<6}'.format('END')} {baseclass.scriptfilename} ----------------NOTE-----------NOTE---------------")
+

src/code/base_class.py

@@ -53,7 +53,14 @@ class BaseVariableFunction:
         
         
         self.dalao_ori_tran_defined_path = self.librarydata_path/"dalao_ori_tran_defined/"
+        self.dalao_ori_tran_gmgnOrdex_path = self.librarydata_path/"dalao_ori_tran_gmgnOrdex/"
+        self.dalao_tran_gmgnOrdex_path = self.librarydata_path/"dalao_tran_gmgnOrdex/"
+        
+        
+        
         self.dalao_tran_defined_path = self.librarydata_path/"dalao_tran_defined/"
+        
+        
  
         self.dalao_transfer_solanafm_path = self.librarydata_path / \
             "dalao_transfer_solanafm/"

src/code/tamper_get_top_trader_sol_dexscreener.js

@@ -0,0 +1,303 @@
+// ==UserScript==
+// @name         DexScreen-GetTopTrader
+// @namespace    http://tampermonkey.net/
+// @version      2024-10-19
+// @description  try to take over the world!
+// @author       You
+// @match        https://dexscreener.com/solana/*
+// @icon         https://www.google.com/s2/favicons?sz=64&domain=dexscreener.com
+// @grant        none
+// ==/UserScript==
+// ==/UserScript==
+
+
+
+function funcDownload(content, filename) {
+    console.log('begin download');
+    // 创建隐藏的可下载链接
+    var eleLink = document.createElement('a');
+    eleLink.download = filename;
+    eleLink.style.display = 'none';
+    // 字符内容转变成blob地址
+    var blob = new Blob([content]);
+    eleLink.href = URL.createObjectURL(blob);
+    // 触发点击
+    document.body.appendChild(eleLink);
+    eleLink.click();
+    // 然后移除
+    document.body.removeChild(eleLink);
+}
+
+
+
+
+function sleep(sleepdelay) {
+    return new Promise((resolve, reject) => {
+        setTimeout(() => {
+            resolve(sleepdelay);
+        }, sleepdelay);
+    })
+}
+
+var number_chars_obj = {
+    "k": 3,
+    "m": 6,
+    "b": 9,
+    "t": 12,
+    "p": 15
+};
+
+var number_chars_arr = ["k", "m", "b", "t", "p"];
+
+function get_thead_arr() {
+    // let titlearr = _thead.innerText.trim().split(/\r?\n/);
+
+
+    titlearr = [
+        "Rank",
+        "Maker",
+        "Buymoney",
+        "Sellmoney",
+        "Earn",
+        "Earnper",
+        "Buycount",
+        "Sellcount",
+        "Buyamount",
+        "Sellamount",
+        "Amountper",
+
+
+    ]
+    return titlearr;
+}
+
+
+function save_resdata() {
+    console.log("enter save_resdata");
+
+    res_data.forEach((val, index, arr) => { arr[index] = val.join() + "\n" });
+    let urlpathname = window.location.pathname.slice(1).split('/');
+    urlpathname = urlpathname.pop()
+
+    funcDownload(res_data.join(""), urlpathname + "_top_dexscreen_sol" + "_" + parseInt(Date.now() / 1000) + ".csv");
+    res_data = [];
+
+}
+
+
+function get_tbodyarr(tbody_arr) {
+    let urlpathname_arr = window.location.pathname.slice(1).split('/');
+    let token_address = urlpathname_arr[1];
+
+    for (let idx = 0; idx < tbody_arr.length; idx++) {
+        let tr = tbody_arr[idx];
+        let tds_arr = Array.from(tr.children);
+        let td_value_obj = {
+            "Rank": "0",
+            "Maker": "",
+            "Buymoney": 0,
+            "Sellmoney": 0,
+            "Earn": 0,
+            "Earnper": 0,
+            "Buycount": 0,
+            "Sellcount": 0,
+            "Buyamount": 0,
+            "Sellamount": 0,
+            "Amountper": 0,
+
+
+
+        }
+        let temp_innertext;
+        for (let i = 0; i < tds_arr.length; i++) {
+            if (i == 1 || i == 4 || i == 5 || i == 6 || i == 7) {
+                continue;
+            } else if (i == 0) {
+                let td_innerText = tds_arr[i].innerText.trim().replace(/#/g, "");
+                td_value_obj.Rank = td_innerText;
+
+            }
+            else if (i == 8) {
+                td_value_obj.Maker = tds_arr[i].querySelector("a").href.split('/').pop();
+
+            } else if (i == 2 || i == 3) {
+                // 获取 Bought
+                // '<$0.1\n10/1 txns'
+                // '-'
+                let td_innerText = tds_arr[i].innerText.trim().toLowerCase();
+                let money = 0, amount = 0, count = 0;
+
+                if (td_innerText == "-") {
+                    if (i == 2) {
+                        td_value_obj.Buycount = 0;
+                        td_value_obj.Buymoney = 0;
+                    } else {
+                        td_value_obj.Sellcount = 0;
+                        td_value_obj.Sellmoney = 0;
+                    }
+                    continue;
+                }
+                if (td_innerText.indexOf("$") == -1) {
+                    console.log("idx=", idx, "td_innerText=", td_innerText);
+                    throw ("td_innerText error");
+                }
+
+                td_innerText = td_innerText.replace(/[(\$),]/g, "");
+                let td_innerText_arr = td_innerText.split(/\r?\n/);
+                td_innerText_arr.forEach((val, index, arr) => {
+                    arr[index] = val.trim();
+                });
+
+                // 获取buymoney / sellmoney  '<0.1' '11.5' '11.5k' '11.5m' 其他更大的数值
+                if (td_innerText_arr[0].indexOf("<") != -1) {
+                    // td_value_obj.Buymoney = 0.1;
+                    money = 0.1;
+                } else {
+                    if (!isNaN(td_innerText_arr[0])) {
+                        // td_value_obj.Buy
+                        money = parseFloat(td_innerText_arr[0]);
+
+                    } else {
+                        for (let number_char of number_chars_arr) {
+                            if (td_innerText_arr[0].indexOf(number_char) != -1) {
+                                money = parseFloat(td_innerText_arr[0]) * 10 ** number_chars_obj[number_char];
+                            }
+                        }
+
+                    }
+
+                }
+                let temp_td_innerText = td_innerText_arr.pop();
+                let temp_td_innerText_arr = temp_td_innerText.split("/");
+                td_innerText_arr = [...td_innerText_arr, ...temp_td_innerText_arr];
+                td_innerText_arr.forEach((val, index, arr) => {
+                    arr[index] = val.trim();
+                });
+                console.log("td_innerText_arr=", td_innerText_arr);
+
+                //获取buyamount sellamount
+
+                for (let number_char of number_chars_arr) {
+                    // 如果有k , m 等 需要转化为字符串
+                    if (td_innerText_arr[1].indexOf(number_char) != -1) {
+                        amount = String(parseInt(parseFloat(td_innerText_arr[1])) * 1000) + '0'.repeat(number_chars_obj[number_char] - 3);
+                        break;
+                    }
+                }
+                if (amount === 0) {
+                    amount = parseFloat(td_innerText_arr[1]);
+
+                }
+
+
+                // 获取buycount  1 txns
+                td_innerText_arr[2] = td_innerText_arr[2].split(" ")[0].trim();
+                // td_value_obj.Buy
+                count = td_innerText_arr[2];
+
+                if (i == 2) {
+                    td_value_obj.Buycount = count;
+                    td_value_obj.Buymoney = money;
+                    td_value_obj.Buyamount = amount;
+                } else if (i == 3) {
+                    td_value_obj.Sellcount = count;
+                    td_value_obj.Sellmoney = money;
+                    td_value_obj.Sellamount = amount;
+                }
+
+
+            }
+
+        }
+        td_value_obj.Earn = td_value_obj.Sellmoney - td_value_obj.Buymoney;
+        td_value_obj.Earnper = td_value_obj.Buymoney == 0 ? 999999 : td_value_obj.Earn / td_value_obj.Buymoney;
+
+        if (typeof (td_value_obj.Sellamount) == 'string') {
+            if (typeof (td_value_obj.Buyamount) == 'string') {
+                if (td_value_obj.Sellamount.length > td_value_obj.Buyamount.length) {
+                    td_value_obj.Amountper = 10;
+                } else if (td_value_obj.Sellamount.length == td_value_obj.Buyamount.length) {
+                    td_value_obj.Amountper = parseFloat(td_value_obj.Sellamount.slice(0, 2)) / parseFloat(td_value_obj.Buyamount.slice(0, 2));
+                } else {
+                    td_value_obj.Amountper = 0.1;
+                }
+            } else {
+                td_value_obj.Amountper = 10;
+            }
+        } else {
+            if (td_value_obj.Sellamount == 0) {
+                td_value_obj.Amountper = 0;
+            } else if (typeof (td_value_obj.Buyamount) == 'string') {
+                td_value_obj.Amountper = 0.1;
+            }
+            else {
+                td_value_obj.Amountper = td_value_obj.Buyamount == 0 ? 999999 : parseFloat(td_value_obj.Sellamount) / parseFloat(td_value_obj.Buyamount);
+
+            }
+        }
+
+
+
+        let td_value_arr = Object.values(td_value_obj);
+
+        res_data.push(td_value_arr);
+
+    }
+
+}
+var res_data = [];
+// window.addEventListener('load', () => {
+
+(async function () {
+    console.log("enter load");
+    await sleep(6000);
+    console.log("create button");
+
+    var mydivbox = document.createElement("div");
+
+    var button_tran = document.createElement("button");//创建 获取toptran一个按钮
+    mydivbox.appendChild(button_tran);
+    button_tran.className = "tam-mybutton-gettran"
+    button_tran.textContent = "gettran"; //按钮内容
+    button_tran.style.width = "90px"; //按钮宽度
+    button_tran.style.height = "30px"; //按钮高度
+    button_tran.style.align = "center"; //文本居中
+    button_tran.style.color = "blue"; //按钮文字颜色
+    button_tran.style.background = "#e33e33"; //按钮底色
+    button_tran.style.border = "1px solid #e33e33"; //边框属性
+
+
+    mydivbox.style.position = "fixed";
+    mydivbox.style.top = "80px";
+    mydivbox.style.right = "40px";
+    document.body.appendChild(mydivbox);
+
+    button_tran.addEventListener("click", clickButton); //监听按钮点击事件
+
+
+
+
+
+
+    function clickButton() {
+        res_data = [];
+
+        let table_div_ep1 = document.getElementsByClassName('custom-1vjv7zm')[0];
+
+        let div_table = table_div_ep1.getElementsByClassName('custom-1kikirr')[0];
+
+        let titlearr = get_thead_arr();
+        res_data.push(titlearr);
+        let tbody_arr = Array.from(div_table.children);
+        tbody_arr.shift();
+        get_tbodyarr(tbody_arr);
+        save_resdata();
+
+
+
+    }
+
+
+
+})();
+

src/code/tamper_get_top_trader_sol_gmgn.js

@@ -0,0 +1,367 @@
+// ==UserScript==
+// @name         GMGN-Get-Top
+// @namespace    http://tampermonkey.net/
+// @version      2024-10-19
+// @description  try to take over the world!
+// @author       You
+// @match        https://gmgn.ai/sol/token/*
+// @icon         https://www.google.com/s2/favicons?sz=64&domain=gmgn.ai
+// @grant        none
+// ==/UserScript==
+
+
+function funcDownload(content, filename) {
+    console.log('begin download');
+    // 创建隐藏的可下载链接
+    let eleLink = document.createElement('a');
+    eleLink.download = filename;
+    eleLink.style.display = 'none';
+    // 字符内容转变成blob地址
+    let blob = new Blob([content]);
+    eleLink.href = URL.createObjectURL(blob);
+    // 触发点击
+    document.body.appendChild(eleLink);
+    eleLink.click();
+    // 然后移除
+    document.body.removeChild(eleLink);
+}
+
+
+function sleep(sleepdelay) {
+    return new Promise((resolve, reject) => {
+        setTimeout(() => {
+            resolve(sleepdelay);
+        }, sleepdelay);
+    })
+}
+var number_chars_obj = {
+    "k": 3,
+    "m": 6,
+    "b": 9,
+    "t": 12,
+    "p": 15
+};
+
+
+var number_chars_arr = ["k", "m", "b", "t", "p"];
+
+function get_thead_arr() {
+
+    // let titlearr = _thead.innerText.trim().split(/\r?\n/);
+    let titlearr = ['Maker', 'SOL', 'Buy_sol', 'Sell_sol', 'Pnl_sol', 'Pnl_per'];
+    return titlearr;
+}
+
+
+
+var pre_timestamp = -1;
+var now_timestamp = -1;
+async function get_tbody_data() {
+
+    let div_has_tran_table = document.querySelector("div.chakra-tabs__tab-panels.css-2zi8qu");
+    let tbody = div_has_tran_table.querySelector("tbody.g-table-tbody");
+
+    let arr_tbody_trs;
+    arr_tbody_trs = Array.from(tbody.children);
+    arr_tbody_trs.shift();
+
+
+    for (let i = 0; i < arr_tbody_trs.length; i++) {
+
+        let arr_tds;
+        arr_tds = Array.from(arr_tbody_trs[i].children);
+
+        let tdtexts = [];
+        // if (arr_tds.length != 10) {
+        //     continue;
+        // }
+        for (let i = 0; i < arr_tds.length; i++) {
+            if (i == 0) {
+                // trader
+                let a_element = arr_tds[i].querySelector("a");
+                let str_trader = a_element.href.split('/').pop();
+                tdtexts.push(str_trader);
+
+            }
+            else if (i == 1) {
+                //sol balance   
+
+                let str_balance = arr_tds[i].innerText.trim().replace(/[,]/g, "").trim();
+                str_balance = str_balance.replace(/\s+/g, "");
+
+                str_balance = str_balance.toLowerCase();
+                let float_balance;
+
+                float_balance = parseFloat(str_balance);
+                for (let number_char of number_chars_arr) {
+                    if (str_balance.indexOf(number_char) != -1) {
+                        float_balance = parseFloat(str_balance) * 10 ** number_chars_obj[number_char];
+                    }
+                }
+                tdtexts.push(float_balance);
+
+            } else if (i == 2) {
+                // bought
+
+
+                let str_sol = "0";
+                let str_token_amount = "0";
+                let float_sol;
+
+                let arr_sol_amount = arr_tds[i].children[0].children;
+                if (arr_sol_amount.length == 1) {
+                    tdtexts.push(0);
+                    continue;
+                }
+
+                str_sol = arr_sol_amount[0].innerText.trim().toLowerCase();
+                str_sol = str_sol.replace(/[sol,%\+><]/g, "").trim();
+                if (str_sol == "--") {
+                    str_sol = "0";
+                }
+
+                float_sol = parseFloat(str_sol);
+                for (let number_char of number_chars_arr) {
+                    if (str_sol.indexOf(number_char) != -1) {
+                        float_sol = parseFloat(str_sol) * 10 ** number_chars_obj[number_char];
+                    }
+                }
+                tdtexts.push(float_sol);
+
+            } else if (i == 3) {
+                // sold
+                let str_sol = "0";
+                let str_token_amount = "0";
+                let float_sol;
+
+                let arr_sol_amount = arr_tds[i].children[0].children;
+                if (arr_sol_amount.length == 1) {
+                    tdtexts.push(0);
+                    continue;
+                }
+
+                str_sol = arr_sol_amount[0].innerText.trim().toLowerCase();
+                str_sol = str_sol.replace(/[sol,%\+><]/g, "").trim();
+                if (str_sol == "--") {
+                    str_sol = "0";
+                }
+
+                float_sol = parseFloat(str_sol);
+                for (let number_char of number_chars_arr) {
+                    if (str_sol.indexOf(number_char) != -1) {
+                        float_sol = parseFloat(str_sol) * 10 ** number_chars_obj[number_char];
+                    }
+                }
+                tdtexts.push(float_sol);
+
+
+
+
+            } else if (i == 4) {
+                // pnl
+
+                let str_sol = "0";
+                let str_percent = "0";
+                let float_sol = 0;
+                let float_percent = 0;
+
+                let arr_sol_percent = arr_tds[i].children[0].children;
+
+
+                str_sol = arr_sol_percent[0].innerText.trim().toLowerCase();
+                str_sol = str_sol.replace(/[sol,%\+><]/g, "").trim();
+                str_percent = arr_sol_percent[1].innerText.trim().toLowerCase();
+                str_percent = str_percent.replace(/[sol,%\+><]/g, "").trim();
+
+                if (str_sol == "--") {
+                    str_sol = "0";
+                }
+
+                if (str_percent == "--") {
+                    str_percent = "999999";
+                }
+
+
+                float_sol = parseFloat(str_sol);
+                float_percent = parseFloat(str_percent);
+                for (let number_char of number_chars_arr) {
+                    if (str_sol.indexOf(number_char) != -1) {
+                        float_sol = parseFloat(str_sol) * 10 ** number_chars_obj[number_char];
+                    }
+                    if (str_percent.indexOf(number_char) != -1) {
+                        float_percent = parseFloat(str_percent) * 10 ** number_chars_obj[number_char];
+                    }
+
+                }
+                tdtexts.push(float_sol);
+                tdtexts.push(float_percent);
+
+            } else if (i == 5) {
+                // Realized
+                continue;
+            }
+            else if (i == 6) {
+                // UnRealized
+                continue
+
+            } else if (i == 7) {
+                // Avg Cost/Sold
+
+            } else if (i == 8) {
+                // TXs
+
+            } else if (i == 9) {
+                // Last Active
+
+            }
+
+        }
+        res_data.push(tdtexts);
+
+    }
+
+
+}
+
+function save_resdata() {
+    console.log("enter save_resdata");
+    res_data.forEach((val, index, arr) => { arr[index] = val.join() + "\n" });
+    let urlpathname = window.location.pathname.slice(1).split('/');
+    urlpathname = urlpathname.pop()
+
+    funcDownload(res_data.join(""), urlpathname + "_top_gmgn_sol" + "_" + parseInt(Date.now() / 1000) + ".csv");
+    res_data = [];
+
+}
+function autoScroll() {
+    console.log("enter autoScroll");
+
+    let interval;
+    let scroll_times = 15;
+
+    let div_has_tran_table = document.querySelector("div.chakra-tabs__tab-panels.css-2zi8qu");
+    let tbody = div_has_tran_table.querySelector("div.css-1o2kb31 tbody.g-table-tbody");
+
+
+    async function down() {
+        interval = setInterval(async () => {
+
+            let tbodytrs;
+
+            if (scroll_times > 0) {
+
+                await sleep(150);
+                tbodytrs = tbody.children;
+                tbodytrs[tbodytrs.length - 1].scrollIntoView({ behavior: "smooth", block: "start" });
+
+
+            } else {
+                clearInterval(interval);
+                await get_tbody_data();
+                save_resdata();
+                return;
+
+            }
+            scroll_times--;
+
+
+            tbodytrs = tbody.children;
+            if (tbodytrs.length == 101) {
+                clearInterval(interval);
+                await get_tbody_data();
+                save_resdata();
+                return;
+
+            }
+
+            await sleep(300);
+        }, 1200)
+
+    }
+
+    down()
+
+}
+
+
+
+var res_data = [];
+var sTop = 0;
+
+// window.addEventListener('load', async () => {
+
+(async function () {
+    console.log("enter load");
+    await sleep(6000);
+    console.log("create button");
+
+    var mydivbox = document.createElement("div");
+
+    var button_tran = document.createElement("button");//创建 获取toptran一个按钮
+    mydivbox.appendChild(button_tran);
+    button_tran.className = "tam-mybutton-gettran"
+    button_tran.textContent = "gettran"; //按钮内容
+    button_tran.style.width = "90px"; //按钮宽度
+    button_tran.style.height = "30px"; //按钮高度
+    button_tran.style.align = "center"; //文本居中
+    button_tran.style.color = "blue"; //按钮文字颜色
+    button_tran.style.background = "#e33e33"; //按钮底色
+    button_tran.style.border = "1px solid #e33e33"; //边框属性
+
+
+    mydivbox.style.position = "fixed";
+    mydivbox.style.top = "80px";
+    mydivbox.style.right = "40px";
+    document.body.appendChild(mydivbox);
+
+    button_tran.addEventListener("click", clickButton); //监听按钮点击事件
+
+    async function clickButton() {
+        res_data = [];
+
+        console.log("enter clickButton res_data=", res_data);
+        let div_chakra_tabs = document.querySelector('[role="tablist"]');
+        let arr_buttons_chakra = Array.from(div_chakra_tabs.querySelectorAll("button"));
+        let button_top_trader = undefined;
+        for (let button of arr_buttons_chakra) {
+            if (button.innerText.includes("Top Traders")) {
+                button_top_trader = button;
+                break;
+            }
+        }
+        if (button_top_trader == undefined) {
+            console.log("no button_top_trader");
+            return;
+        }
+        await button_top_trader.click();
+        await sleep(7000);
+
+        let div_has_tran_table;
+        let _tbody;
+        let _thead;
+
+        // chakra-tabs__tablist css-1p75jc5
+        div_has_tran_table = document.querySelector("div.chakra-tabs__tab-panels.css-2zi8qu");
+        _tbody = div_has_tran_table.querySelector("div.css-1o2kb31 tbody.g-table-tbody");
+        _thead = div_has_tran_table.querySelector("div.css-1o2kb31 thead.g-table-thead");
+        let arr_th = _thead.querySelectorAll("th");
+        let click_USD = arr_th[1].querySelector("div.css-1vimx2u");
+        if (click_USD.innerText.includes("USD")) {
+            await click_USD.click();
+            await sleep(4000);
+        }
+
+
+
+
+        let titlearr = get_thead_arr();
+        res_data.push(titlearr);
+        autoScroll();
+
+    }
+
+})();
+
+
+
+

src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_29BjsvgtMuUGxU232v4v1z2a8dxhtXM8d8sL7NYZ8FXc.csv

@@ -1,161 +0,0 @@
-tokenaddress,tokenname,last_active,profit_sol,profit_percent,buy_sol,sell_sol,30d_txns_buy,30d_txns_sell
-9cC36bMZCt9fF53eLBQCago1czw5L9GRHZBL5adWEyAu,SOFAC,43min,0,0.0,0,0,0,0
-3s5FEJdm7WLtVvTTNEHhdX4Y5DLNhT8ATYFBNaJkpump,MOONY,45min,0.283,0.02,13.88,14.17,1,1
-AF7oQAr7z1FgWSJ4asQHXPcTzu8oraT3Be8XQGFupump,fuzzi,45min,0.036,0.09,0.39,0.426,1,1
-D7zweePrcNPqBqH5aYarKvUiZK5o95fY3SJCc9STpump,H1N1,52min,0.035,0.02,1.62,1.66,1,1
-F5zTuUGTvzG22xVhUzbgt95RMqJXJmGXMmooUG7Hpump,skelly,1h,0.117,0.04,3.27,3.38,1,1
-867pZKASjSKJs4BSM4rKKd6w1TWEzytr1KDb8vDLop76,cook,1h,0.292,0.1,2.95,3.24,1,1
-8vBVf5NgmhYyMxsgJ5d8ZwJFY4nXaXPnum23cVobpump,SWN,2h,0.015,0.03,0.551,0.565,1,1
-9csJPJmstMoFNcQ5KwX5YGhSz9fs2ERzd5QR5zH1pump,unknown_9csJ,2h,0.101,0.06,1.68,1.78,1,1
-87PEUCRQxYDV3J22yJKGmV2gPnyg7ecumdaRskAGpump,CAT5,2h,0.278,0.07,3.82,4.1,1,1
-ARwGfAcDsieFvzEhvHfzkpZ4SuBvNc5CG3fZ6yWmpump,milton,2h,0.004,0.03,0.154,0.159,1,1
-9JWr199RPGhXoVqomZgK2gDTsGHFsgD4FnTnCgy5pump,dow,2h,0.024,0.05,0.45,0.474,1,1
-BbWnjzvUfbhU9nGec595FLT5c14CzCTSnL3xZLQspump,silkroad,2h,1.36,0.28,4.81,6.17,1,1
-FvceEL5ns2AHRRVjKGWuJen1kyg4yveSESUnVqdBpump,LUCY,2h,0.126,0.03,4.14,4.26,1,1
-6WksuhSqR5PoveXazrmSWqtPopcJbC3b5fVc2JXZpump,Kali,2h,0.202,0.03,6.09,6.29,1,1
-6k4eLYQ7ndGaTypz2bf5pVuJnnnDPhxPbPLFfS9rpump,miu,3h,0.35,0.06,6.02,6.37,2,2
-DxxaQvKUdBgzoV4F9eQQ1KUvQB6wb2jDVKcF96Mspump,Lucy,3h,0.076,0.05,1.63,1.7,1,1
-ZiPGN2Mb5cbHoptQk598A44Kfowo51BigaNAirGpump,ASTRA,3h,0.886,0.03,30.5,31.38,1,1
-Ew2V6Z6HDAqUvfwwdd8SCAwfpnfQipkZFnDepcsEpump,FAG,3h,0.057,0.02,2.45,2.51,1,1
-3kW5szmuoJg7MVsfE4wvufFaceQz3ANUqE8hSZAgpump,core,3h,0.042,0.08,0.546,0.588,1,1
-FFAuveUnrAnbsBzV3GtAjr7YpJqMj5Bx7upKW14Jpump,CraigSteve,3h,0.019,0.06,0.328,0.347,1,1
-9ZX8vkRsZqymViJ2RgbiXNoLN9xCPxMxpX2pnTrazGZd,Cheeky,3h,0.04,0.02,1.69,1.73,1,1
-D8oynV68jW3DvZsRcwUTZiWrk8eVvFmWRZGMTC9Upump,Hayami,3h,0.023,0.04,0.52,0.543,1,1
-9cqVbWEamyTwtyBA2HdTYL2qiDNfFfd2DVtjCRu2pump,come,3h,0.012,0.03,0.379,0.391,1,1
-GqeEfLsQf2gTqLopRw2ogK3Djsg7T6JKg47yskucpump,SARKlE,3h,0.013,0.02,0.577,0.59,1,1
-93BxEFKzf1nuUmCvsxZabWnhMvaUJSPTyM6YTjuNpump,$DUMPY,4h,0.154,0.04,3.89,4.05,1,1
-5MUmX5hAG54qNSDgjWGMpcUkprtEQSgFfddLCUsKpump,PTB,4h,0.17,0.06,2.65,2.82,1,1
-2BdKjcbkkXaQkHajm8Ly3A684C7pDhRoXeV4ijatpump,Miyazaki,4h,0.235,0.03,6.88,7.11,1,1
-Ehi15ig52X4eS7BMitP5iQyX1chMfB8sBddCyJ5opump,DUDE,4h,0.093,0.07,1.37,1.46,1,1
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_29b7ech9iDueYkdogrE9Tqyyo9Nsug3Hbfv7U4xD6phW.csv

@@ -0,0 +1,21 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2MbgWbgvXfDfAqCzHj4ur4eWJSZjcsfXC2Zg2BhKnMjR.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2QygD8bDsfK1XCAnFxFtpPddzbJbamhXvKqcLQ8cELzE.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2S3sq1jGSEmhxbTz9Kt6XSJwstpHkErK4Zip3g54V9jY.csv

@@ -0,0 +1,63 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2TPnBYwEJztSMLUpfxd2tiiU62dc6NMJcenqfWejzmNH.csv

@@ -0,0 +1,82 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2kpd5Mcu8i6GYJDR9Fqnmw16YCNgf1F19TgxkvoKiNzZ.csv

@@ -0,0 +1,2 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2ogFTf6Y5JmRM8P6KHt3ed1MdnjFw6k71vhsJ95nrTbW.csv

@@ -1,161 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2yxcX8mKf655pGhptrSwzMQujsynxvfSz7xSs6ZV3pYb.csv

@@ -1,151 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_2zUiWaf5GZDqFCP4yyZKv3v18hxTxfgvLfHXYzKWt8si.csv

@@ -0,0 +1,27 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3BL9WU9z77xSR7EU4V1oRd15KibKUAjscHbw1Kp21BUD.csv

@@ -0,0 +1,66 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3Dp2NyiSx5Vc4b4jS6trW6Dh8RfDrmMiJ2KX2nP7pYKk.csv

@@ -0,0 +1,251 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3FNpgyw5LeNJV7DMQNS4CEJbo1Gu2g4TShkMJBwh2p3P.csv

@@ -0,0 +1,68 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3Gxp6U6x8znLEbFWxuLUWW5iMcxWiMyMRzMbztQkcxxp.csv

@@ -1,161 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3JxeQCZ1ze7xb728BezgEojLdfrUwX4ikLj1st9J6FWm.csv

@@ -0,0 +1,87 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3KnJpDj2mjK4bTzPoLeF49rf4HXvfDzgdgNYT2HwjYcL.csv

@@ -1,161 +0,0 @@
-tokenaddress,tokenname,last_active,profit_sol,profit_percent,buy_sol,sell_sol,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3Loi32tiBiaWs5PXMvBiYpG2q51K6cy8aw5bScQvcyBR.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3aFLVMQqVTdHfkHMb83ihJWmSzswDQ91MmnFMkh8DNJ5.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3hEmVgueDVeF5kjZWyCikxRwP8akv8sypShxESHkbUe3.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3i6jt3EcfWQMzBvbcnA5byiRq12Qbm2LDht9vG3FvuHw.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3oxKo6yxZT3n19fr8WKoDzJTRwXWBw6PpXME3SpKuRTt.csv

@@ -0,0 +1,101 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_3y3iRuxdiHXBAh2crRJpPEruzC6r1PrrK2gnRtUoHqJv.csv

@@ -0,0 +1,11 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_45Lt5Ho31gB6UFTTxXBEvNdpu12o1vt4joYHz7y3dbbD.csv

@@ -0,0 +1,22 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_4625pi6asX1CpKmw1apw3mnGxxntS7F95ALqhWLgVoCr.csv

@@ -0,0 +1,25 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_4Beb1WA1s5EEo2b2LuXTXPg7H7zNPLTxG9ruXCRsYLBf.csv

@@ -0,0 +1,93 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_4HbsoMK95w3uYjLp41em3iKtNqhQv4XJpboQPGf7DJUJ.csv

@@ -0,0 +1,38 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_4hPgt9Nn2YLRDfuVvEqivQezWL4EPDhcHRsEEMoKVVjq.csv

@@ -1,101 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_4o1yvPgfVQrgoJi3jpRUYpmJz5eNctTuqg1QgRCQPQdu.csv

@@ -1,161 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_4rZeAyb7BZv1G1nWisVDF5pUf3kgNnG6HH89BXSq7b1q.csv

@@ -0,0 +1,24 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_4s7VYGzC7UBAVptb8YSYrr8MdMt21WQiHEdg2PUjZaNh.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_52Bp55PzKr8n1dGf6pbzqwSPTqrMyuRYekuhxJsDd6e.csv

@@ -1,28 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_54EiavhVatcFbcRHKm2swd6eB8reyib3kTkDGScoGjGK.csv

@@ -0,0 +1,151 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_5ArBMY4h29CMbD7VbUJr5WKSDfMxprAFyqX7Jekf58dR.csv

@@ -0,0 +1,21 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_5JYz2tsZVhU4AZ5PxDNux6GV31unTVa4ohuvEjJ2K5TJ.csv

@@ -0,0 +1,60 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_5KkkbpykJCz69zHrPSovZQcAVwZKpeQeRRhZtQXrRzeo.csv

@@ -1,101 +0,0 @@
-tokenaddress,tokenname,last_active,profit_sol,profit_percent,buy_sol,sell_sol,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_5Y4UFiZ2njsmqN6LdhvGWERv4bUaVtok3L2pq25sKgod.csv

@@ -0,0 +1,58 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_5Yd2ZezSDxN49AmGz1PWfJk3YGcSLNrAHbmGEGrU89cJ.csv

@@ -0,0 +1,101 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_5ZzRvjZZw4JiDbPQc7NuG9wp4wDjXoWiQo6JpSSYxQZe.csv

@@ -0,0 +1,101 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_5d8caBnhvXTGLDnmiFRUQySNMTXnMtygsSqurtSeMpPk.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_65mY5Ha1uq1sRTrFVkyHMKEkhqTispdFvcNr9LfEvTDH.csv

@@ -0,0 +1,64 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_66vC4wzfotKUhLEcW2mSfeW3t3rjqCGR9wh36Vb4BjCC.csv

@@ -1,161 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_6P4aHkv7oTbwMK6P57sVsejE52jNFeEvYhQMEBpNNN1U.csv

@@ -0,0 +1,201 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_6YHcrghddkYMf6zu9vs8WtZkBUMBTEQvvSPVUEqnDYXf.csv

@@ -0,0 +1,211 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_6YZfhiHMaX7vx3uGUfWCFKk1QyhpZC9sPsakBhZyp33Q.csv

@@ -0,0 +1,94 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_6YyUUEE6fN82uCKtVPx8TkHwKbDdswEu7EVv55edwxaC.csv

@@ -0,0 +1,51 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_6x89UcaCuygwSzT6mrvbZ1mqxV88EpvHEtdj76DUyuAJ.csv

@@ -0,0 +1,16 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_75keYa82Q2LLvhSFS4f3JjPqDjPC2nBs9XGnhXEmJhvm.csv

@@ -1,151 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_7LABrmDb5oHWpQADkFpnejEEAcyCkxWSaUbgKNrsP4K.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_7RKhrv7hRHXa7Z7nY4BS6EJ2V3S1zqUAtowgJ52n8Rrt.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_7aHRuzc2dk4ikLXkFBgBrSj8qiZhU26GyCn9hcRqiqTC.csv

@@ -0,0 +1,45 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_7prnYXsJt6nbJRnaVx9JradaDXjfDH7hNuMmMJaELpF9.csv

@@ -0,0 +1,30 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_81sxX2z5wNb2zwFTEDf9Fdt6PhbXk4Cy21LWVmcTVdwo.csv

@@ -0,0 +1,55 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_8Bz4pyrdYaeuJfEyFm2d7cYpaQeNVR1P2dPovoZjdwtV.csv

@@ -0,0 +1,35 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_8LLRaGJqZgSuDf9maW1ohb5G1SRqCuKbLX6vdUNWpFp2.csv

@@ -0,0 +1,251 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_964BLXV3tnww1Ki1fPe6JvH1wm6YLUHMmXkVUCo4vYFS.csv

@@ -1,161 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_97JwcqkqKfPEkRk7WzRo9aDu4ut7FoXoobTPJuy95Ts4.csv

@@ -0,0 +1,41 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_9FmeS15VAZjtpY8VSvt2ThfLUFEzQYoGBD1ErHPYNsY4.csv

@@ -0,0 +1,201 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_9HQ2FDrnYjDgPdiRxdp3HsbrzgLgkwx13XZ3As2DcpJ5.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_9MFYCwDxmiqXdsAqzy5j7xVCv1cWuhLD9ytYTNyJsy4H.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_9SkVetBKeJYwxen42eozNY4eyafBU3Zm1LDEZSBXRNY8.csv

@@ -0,0 +1,32 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_9d2HTebtsaur61A1cSjqjtwnYgjrd1JLz8TPpBan9YvQ.csv

@@ -0,0 +1,93 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_9mkQDdUrcyPAmsBDEJquDLWCEnRK8Ryoxw6ncHCbjjXd.csv

@@ -0,0 +1,151 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_9rkHWgqFUAcCENkeY1iHH3wopVgdss4fZFnigi8iPWvq.csv

@@ -0,0 +1,101 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_ABUqmjGYiZd4mFxVa2ZV4zZUUbB7a7U7EvoPkw4YHvC6.csv

@@ -0,0 +1,39 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_AQ4BF3vkycfQXRqwSo5CsPuxGQLHVPyDaeCWNrsDHagb.csv

@@ -0,0 +1,24 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_AQcMhwZdwJ3hRwF5tYXZkCUjsrsBM1ot5GBZeKeNUMaY.csv

@@ -0,0 +1,101 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_AaavyHrRcm7WiQXeyCM2pTMtnpcLB5bN2WPMP4FyMjJW.csv

@@ -0,0 +1,60 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_AgBe4DzK6iFkCABTgEKvtwvnr7h3UqpWeFiuPw9UR2tN.csv

@@ -0,0 +1,151 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_ApMKK9gY5acUcrFQ54n9pxJVmogcRSDMFnYFtbJoWHz2.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_AqF1VQcw1L2k5uNHH3itY7QMkVz19k6E3JKrR6BsRJ9Y.csv

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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_AutanKZsLpydgGV3RgDdijyWYgcGgjy6jxFY7WCxtu28.csv

@@ -0,0 +1,101 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_B2knF41mAK1JEBgWuNf9bUA9gBMuU2rm3WXHUrpuPNdu.csv

@@ -0,0 +1,33 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_B4PSJCv6JnUjXbFx5iZ2d9rE5vyuFHismMCBWbwd5Vyd.csv

@@ -0,0 +1,64 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_B4wBF3ccG7LG9Tb3veDr3zZvgovBiJ2uthkEeHCRfd6S.csv

@@ -0,0 +1,15 @@
+tokenaddress,tokenname,last_active,profit_eth,profit_percent,buy_eth,sell_eth,30d_txns_buy,30d_txns_sell
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_BLWup5KiH8Rg1WtP7Fz2Nr99ueaGPjLHJqG1ieQXAu6z.csv

@@ -1,161 +0,0 @@
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src/librarydata/dalao_ori_pnl_gmgn/ori_gmgn_pnl_BWAPhpZN5sTorKtnd9p9huviz1Kq9QSBmQpFSunEENQG.csv

@@ -0,0 +1,104 @@
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