(running):分析total_ana

src/code/017_hanle_dalao_ori_pnl_gmgn.py

@@ -3,7 +3,7 @@ from base_class import BaseVariableFunction
 from base_class import *
 baseclass = BaseVariableFunction(__file__)
 
-baseclass.makedirpath(baseclass.dalao_ori_pnl_gmgn_path)
+baseclass.makedirpath(baseclass.dalao_pnl_gmgn_path)
 
 old_print = print
  
@@ -27,7 +27,18 @@ def makescreenurl( urlname,urlparam):
 # 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/eth/" ,f"{ser['tokenaddress']}?maker={str_dalaoaddress}")  , axis=1)
+    temp_df["dexurl"] = temp_df.apply(lambda ser: makescreenurl( f"https://dexscreener.com/ethereum/",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" ,
@@ -46,58 +57,56 @@ def hanle_dalao_ori_pnl_gmgn(arr_str_dalaoaddress):
                         dalao_df = pd.read_csv(baseclass.dalao_ori_pnl_gmgn_path /
                                 f"ori_gmgn_pnl_{str_dalaoaddress }.csv", dtype= object)
                         
-                        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)
-                        if len(dalao_df)==0:
-                                continue
                         
+                        
+                        
+
 
-                        arr_last_active =   dalao_df["last_active"].tolist()
+                        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["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.astype({
-                        
-                                "buy_eth":float,
-                                "profit_eth":float,
-                                "30d_txns_buy":int,
-                                "30d_txns_sell":int,
-                                
                         })
-
-                        dalao_df["profit_percent"] =     dalao_df["profit_eth"] /   dalao_df["buy_eth"]
-                    
-                        dalao_df["profit_percent"] =        dalao_df["profit_percent"].round(2)
-                
-                        dalao_df["isnengen"] = -1
-                        
-                        dalao_df["beizhu"] = -1
-                
-                        dalao_df["dexurl"] = dalao_df.apply(lambda ser: makescreenurl( f"https://dexscreener.com/eth/",f"{ser['tokenaddress']}?maker={str_dalaoaddress}")  , axis=1)
-                        dalao_df["definedurl"] = dalao_df.apply(lambda ser: makescreenurl("https://www.defined.fi/eth/" ,ser['tokenaddress'] )  , axis=1)
-
         
         
-                        dalao_df.to_excel(baseclass.dalao_ori_pnl_gmgn_path /
-                                f"ori_gmgn_pnl_{str_dalaoaddress}.xlsx", index=False )
+                        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 

src/code/018_analysis_dalao_pnl_gmgn.py

@@ -10,6 +10,10 @@ 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)
@@ -18,6 +22,7 @@ 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:
@@ -86,38 +91,21 @@ def get_ana_data_lastdays( df,    intervaldays=30):
     )
 
 
+  
 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_ori_pnl_gmgn_path / f"ori_gmgn_pnl_{str_dalaoaddress}.csv").exists():
+        if not (baseclass.dalao_pnl_gmgn_path / f"gmgn_pnl_{str_dalaoaddress}.csv").exists():
             continue
         
-        
-        cur_df = pd.read_csv( baseclass.dalao_ori_pnl_gmgn_path / f"ori_gmgn_pnl_{str_dalaoaddress}.csv",dtype=object)
+        cur_df = pd.read_csv( baseclass.dalao_pnl_gmgn_path / f"gmgn_pnl_{str_dalaoaddress}.csv",dtype=object)
         if len(cur_df)==0:
             continue
-        arr_last_active =   cur_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","")
-        cur_df["last_active"] = arr_last_active
-        cur_df['30d_txns_buy'] = cur_df['30d_txns_buy'].str.replace(',', '')
-        cur_df['30d_txns_sell'] = cur_df['30d_txns_sell'].str.replace(',', '')
-        cur_df['profit_percent'] = cur_df['profit_percent'].str.replace('>', '')
-        
-        cur_df['30d_txns_buy'] = cur_df['30d_txns_buy'].str.replace("K", '000', regex=True)
-        cur_df['30d_txns_sell'] = cur_df['30d_txns_sell'].str.replace("K", '000', regex=True)
         
-        cur_df['30d_txns_buy'] = cur_df['30d_txns_buy'].str.replace(r'[,\.]', '', regex=True)
-        
-        cur_df['30d_txns_sell'] = cur_df['30d_txns_sell'].str.replace(r'[,\.]', '', regex=True)
-            
-
+ 
         
         cur_df = cur_df.astype({
             "last_active" :  int ,
@@ -129,12 +117,10 @@ def main():
             "30d_txns_sell":  int ,
             
         })
+                
         cur_df = cur_df[ cur_df["last_active"]<=30].reset_index(drop=True)
-
-        cur_df=cur_df[cur_df["profit_eth"] !=0].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 )
+        # cur_df.to_csv( baseclass.dalao_pnl_gmgn_path / f"gmgn_pnl_{str_dalaoaddress}.csv",index  = False )
         
         if len(cur_df)==0:
             continue
@@ -188,7 +174,7 @@ def main():
             _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,
+            (_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,