running

src/library/analysis_token/002_handle_dune_buy_sametoken.py → src/code/handle_dune_py/002_handle_buy_sametoken_dune.py

@@ -30,12 +30,12 @@ def handle_df_fun():
     
     merged_df["beizhu"] = None
     merged_df["lasheng_time"] =None
-    merged_df=merged_df[['token_address', 'trader_number',  'min_block_time','max_block_time' , 
-     'create_time','lasheng_time',	'gmgn',	'defined'	,'beizhu' ]]
+    merged_df=merged_df[['token_address', 'trader_number',  'min_block_time', 
+     'create_time', 'time_diff',  'lasheng_time',	'gmgn',	'defined'	,'beizhu' ]]
 
  
 
-    merged_df.to_excel(f'002_dune_buy_sametoken_{int(time.time())}.xlsx', index=False)
+    merged_df.to_excel(f'002_buy_sametoken_dune_{int(time.time())}.xlsx', index=False)
     return
  
     

src/library/analysis_token/003_handle_dune_buy_sametoken_time_diff.py → src/code/handle_dune_py/003_handle_buy_sametoken_time_diff_row_dune.py

@@ -35,7 +35,7 @@ def handle_df_fun():
  
  
 
-    merged_df.to_excel(f'003_dune_sametoken_time_diff_{int(time.time())}.xlsx', index=False)
+    merged_df.to_excel(f'003_buy_sametoken_time_diff_row_dune_{int(time.time())}.xlsx', index=False)
     return
  
     
@@ -45,7 +45,7 @@ if __name__ == "__main__":
  
     arr_file = os.listdir(os.getcwd())
   
-    arr_file = [file for file in arr_file if "dune_sametoken_time_diff" in file and file.endswith(".csv")]
+    arr_file = [file for file in arr_file if "dune_buy_sametoken_time_diff" in file and file.endswith(".csv")]
  
     arr_file.sort()
     print("read file: ",arr_file)

src/library/analysis_token/2ZoJVM15fbbDgo6s5cTTX2Sj8V4sJ47rimb7gQhGpump/002_handle_dune_buy_sametoken_dune.py

@@ -0,0 +1,79 @@
+
+# 获取每一个时间段的top20 持仓，汇总到一个excel表格中
+import pandas as pd
+import sys
+import os
+import time
+
+arr_file = []
+merged_df = None
+def makeurl( url,url_show):
+    return '=HYPERLINK("{}","{}")'.format(url,  url_show)
+
+import pytz
+def utc_2_shanghaidate(df , utc_time_col ):
+# 将字符串转换为UTC时间的datetime对象
+    # df[utc_time_col] = pd.to_datetime(df[utc_time_col], utc=True)
+    # 定义UTC+8时区
+    utc_plus_8 = pytz.timezone('Asia/Shanghai')
+    # 转换为UTC+8时间
+    df[utc_time_col] = df[utc_time_col].dt.tz_localize('UTC')
+    # # 提取时间字符串
+    # df['shanghai_date'] = df['shanghai_date'].dt.strftime('%Y-%m-%d %H:%M')
+    df[utc_time_col] = df[utc_time_col].dt.tz_convert(utc_plus_8)
+    # 提取时间字符串
+    df[utc_time_col] = df[utc_time_col].dt.strftime('%Y-%m-%d %H:%M')
+    return df
+
+
+def handle_df_fun():
+    
+    global arr_file , merged_df 
+    for index, file in enumerate(arr_file):
+        cur_df =   pd.read_csv(file )
+        cur_df =cur_df.astype({
+            "trader_number":int,
+        })
+
+        if index==0 :
+            merged_df = cur_df
+            continue
+
+    merged_df["gmgn"] = merged_df.apply(lambda ser: makeurl(
+    f"https://gmgn.ai/sol/token/{ser['token_address']}" , "gmgn" ), axis=1)
+
+    merged_df["defined"] = merged_df.apply(lambda ser: makeurl(
+     f"https://www.defined.fi/sol/{ser['token_address']}" , "defined" ), axis=1)
+    
+    merged_df["beizhu"] = None
+    merged_df["lasheng_time"] =None
+
+    
+    merged_df["min_block_time"] = pd.to_datetime(merged_df["min_block_time"]  )
+    merged_df = utc_2_shanghaidate(merged_df, "min_block_time")
+    merged_df["create_time"] = pd.to_datetime(merged_df["create_time"]  )
+    merged_df = utc_2_shanghaidate(merged_df, "create_time")
+
+    merged_df=merged_df[['token_address', 'trader_number',  'min_block_time', 
+     'create_time', 'time_diff',  'lasheng_time',	'gmgn',	'defined'	,'beizhu' ]]
+
+ 
+
+    merged_df.to_excel(f'002_dune_buy_sametoken_{int(time.time())}.xlsx', index=False)
+    return
+ 
+    
+
+if __name__ == "__main__":
+ 
+ 
+    arr_file = os.listdir(os.getcwd())
+  
+    arr_file = [file for file in arr_file if "dune_buy_sametoken_" in file and file.endswith(".csv")]
+ 
+    arr_file.sort()
+    print("read file: ",arr_file)
+    
+    handle_df_fun()
+ 
+    

src/library/analysis_token/2ZoJVM15fbbDgo6s5cTTX2Sj8V4sJ47rimb7gQhGpump/003_handle_buy_sametoken_time_diff_row_dune.py

@@ -0,0 +1,55 @@
+
+# 获取每一个时间段的top20 持仓，汇总到一个excel表格中
+import pandas as pd
+import sys
+import os
+import time
+
+arr_file = []
+merged_df = None
+def makeurl( url,url_show):
+    return '=HYPERLINK("{}","{}")'.format(url,  url_show)
+def handle_df_fun():
+    
+    global arr_file , merged_df 
+    for index, file in enumerate(arr_file):
+        cur_df =   pd.read_csv(file )
+    
+        if index==0 :
+            merged_df = cur_df
+            continue
+    merged_df["early_trader_number"] =   (merged_df['buy_create_time_diff'] < 45).groupby(merged_df['token_address']).transform('sum')
+    
+    
+
+ 
+    
+    merged_df["gmgn"] = merged_df.apply(lambda ser: makeurl(
+    f"https://gmgn.ai/sol/token/{ser['token_address']}?tab=activity&maker={ser['trader_id']}" , "gmgn" ), axis=1)
+    merged_df["defined"] = merged_df.apply(lambda ser: makeurl(
+     f"https://www.defined.fi/sol/{ser['token_address']}?maker={ser['trader_id']}" , "defined" ), axis=1)
+    
+    merged_df["beizhu"] = None
+    merged_df =  merged_df.sort_values(by=['early_trader_number','token_address','buy_create_time_diff'], ascending=[False, True,True])
+ 
+ 
+ 
+
+    merged_df.to_excel(f'003_buy_sametoken_time_diff_row_dune_{int(time.time())}.xlsx', index=False)
+    return
+ 
+    
+
+if __name__ == "__main__":
+ 
+ 
+    arr_file = os.listdir(os.getcwd())
+  
+    arr_file = [file for file in arr_file if "dune_buy_sametoken_time_diff" in file and file.endswith(".csv")]
+ 
+    arr_file.sort()
+    print("read file: ",arr_file)
+    
+    handle_df_fun()
+ 
+    

src/library/analysis_token/2ZoJVM15fbbDgo6s5cTTX2Sj8V4sJ47rimb7gQhGpump/dune_buy_sametoken_time_diff.csv

@@ -0,0 +1,130 @@
+token_address,trader_id,buy_create_time_diff,create_time,trader_number
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src/library/analysis_token/2ZoJVM15fbbDgo6s5cTTX2Sj8V4sJ47rimb7gQhGpump/dune_buy_sametoken_xx_xx.csv

@@ -0,0 +1,29 @@
+token_address,min_block_time,trader_number,create_time,time_diff
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