diff --git a/data/maker/__init__.py b/data/maker/__init__.py
index 2921b46..184bca4 100644
--- a/data/maker/__init__.py
+++ b/data/maker/__init__.py
@@ -64,7 +64,7 @@ class Learner(Process):
         # self.logpath= _args['logpath'] if 'logpath' in _args else 'logs'
         # sel.max_epoc
     def log(self,**_args):
-        self.lock.acquire()
+        # self.lock.acquire()
         try:
             logger = transport.factory.instance(**self.store['logger']) if 'logger' in self.store else transport.factory.instance(provider='console',context='write',lock=True)
             _args = dict({'ndx':self.ndx,'module':self.name,'table':self.info['from'],'info':self.info['context'],**_args})
@@ -78,7 +78,8 @@ class Learner(Process):
             print (e)
             pass
         finally:
-            self.lock.release()
+            # self.lock.release()
+            pass
     def get_schema(self):
         if self.store['source']['provider'] != 'bigquery' :
             return [{'name':self._df.dtypes.index.tolist()[i],'type':self._df.dtypes.astype(str).tolist()[i]}for i in range(self._df.dtypes.shape[0])]
@@ -222,7 +223,7 @@ class Generator (Learner):
                 values[index] = values[index].astype(_type)
                 x += values.tolist()
             if x :   
-                _log['input']['diff_pct'] = 100 * (1 - np.divide( (_df[name].dropna() == x).sum(),_df[name].dropna().size))
+                _log['input']['identical_percentage'] = 100 * (1 - np.divide( (_df[name].dropna() == x).sum(),_df[name].dropna().size))
                 _df[name] = x  #np.array(x,dtype=np.int64) if 'int' in _type  else np.arry(x,dtype=np.float64)
                 
                 self.log(**_log)
@@ -243,14 +244,15 @@ class Generator (Learner):
         day = np.random.randint(1,_end)
 
         #-- synthetic date
-        _date = datetime(year=year,month=month,day=day)
-        FORMAT =  '%Y-%m-%d'
-        if 'format' in self.info and 'field' in _args and _args['field'] in self.info['format']:
+        _date = datetime(year=year,month=month,day=day) #,minute=0,hour=0,second=0)
+        FORMAT =  '%Y-%d-%m'
+        _name = _args['field'] if 'field' in _args else None
+        if 'format' in self.info and _name in self.info['format']:
             _name = _args['field']
             FORMAT = self.info['format'][_name]
 
 
-        
+        # print ([_name,FORMAT, _date.strftime(FORMAT)])
         r = []
         if offset :
             r = [_date.strftime(FORMAT)]
@@ -277,7 +279,7 @@ class Generator (Learner):
                 r[name] = FORMAT
                 
                 
-                _df[name] = pd.to_datetime(_df[name], format=FORMAT).astype(str) #.astype('datetime64[ns]')
+                _df[name] = pd.to_datetime(_df[name], format=FORMAT).astype('datetime64[ns]')
         if r :
             self.log(**{'action':'format','input':r})
         return _df
@@ -308,12 +310,13 @@ class Generator (Learner):
 
                     years = _df[iname]
                     _dates = [self.make_date(year=year,field=name) for year in years]
-                    if _dates :
-                        _df[name] = _dates            
+                    if _dates :                        
+                        _df[name] = _dates
             
             _schema = self.get_schema()
             _schema = [{'name':_item.name,'type':_item.field_type} for _item in _schema]
             _df = self.format(_df,_schema)
+            
             writer.write(_df,schema=_schema)
         
         self.log(**{'action':'write','input':{'rows':N,'candidates':len(_candidates)}})