bug fix with type inference

data/maker/__init__.py

@@ -282,9 +282,11 @@ class Generator (Learner):
             
             if _item['type'].upper() in ['DATE','DATETIME','TIMESTAMP'] :
                 FORMAT = '%Y-%m-%d'
+                
                 try:
                     #
                     #-- Sometimes data isn't all it's meant to be
+                    SIZE = -1
                     if 'format' in self.info and name in self.info['format'] :
                         FORMAT = self.info['format'][name]
                         SIZE = 10
@@ -292,20 +294,34 @@ class Generator (Learner):
                             FORMAT = '%Y-%m-%d %H:%M:%S'
                             SIZE = 19
                     
+                    if SIZE > 0 :
+                        
+                        values = pd.to_datetime(_df[name], format=FORMAT).astype(str)
+                        _df[name] = [_date[:SIZE] for _date in values]
+                       
+                    
                     r[name] = FORMAT
-                    _df[name] = pd.to_datetime(_df[name], format=FORMAT) #.astype('datetime64[ns]')
+                    # _df[name] = pd.to_datetime(_df[name], format=FORMAT) #.astype('datetime64[ns]')
                     if _item['type'] in ['DATETIME','TIMESTAMP']:                   
                         pass #;_df[name] = _df[name].fillna('').astype('datetime64[ns]')
-                    else:
-                        _df[name] = _df[name].astype(str)
+                    
                 except Exception as e:
                     pass
                 finally:
                     pass
             else:
-                # print (_item)
-                pass
-        _df = _df.replace('NaT','').replace('NA','')
+                
+                #
+                # Because types are inferred on the basis of the sample being processed they can sometimes be wrong
+                #   To help disambiguate we add the schema information
+                _type = None
+                if 'int' in _df[name].dtypes.name or 'int' in _item['type'].lower():                    
+                    _type = np.int
+                elif 'float' in _df[name].dtypes.name or 'float' in _item['type'].lower():
+                    _type = np.float
+                if _type :
+                    _df[name] = _df[name].fillna(0).replace('',0).astype(_type)
+        # _df = _df.replace('NaT','').replace('NA','')
         
         if r :
             self.log(**{'action':'format','input':r})
@@ -319,7 +335,7 @@ class Generator (Learner):
         _store['context'] = 'write' #-- Just in case
         if 'table' not in _store :
             _store['table'] = self.info['from']
-        writer = transport.factory.instance(**_store)
+        
         N = 0
         for _iodf in _candidates :
             _df = self._df.copy()
@@ -346,7 +362,9 @@ class Generator (Learner):
             _schema = [{'name':_item.name,'type':_item.field_type} for _item in _schema]
             _df = self.format(_df,_schema)
             
+            writer = transport.factory.instance(**_store)
             writer.write(_df,schema=_schema)
+            # _df.to_csv('foo.csv')
         
         self.log(**{'action':'write','input':{'rows':N,'candidates':len(_candidates)}})
 class Shuffle(Generator):    

data/maker/prepare/__init__.py

@@ -209,6 +209,7 @@ class Input :
         # @NOTE: For some reason, there is an out of memory error created here, this seems to fix it (go figure)
         #
         _matrix = np.array([np.repeat(0,cols.size) for i in range(0,row_count)])
+        
         [np.put(_matrix[i], np.where(cols ==  rows[i])  ,1)for i in np.arange(row_count) if np.where(cols == rows[i])[0].size > 0]
         # else:
         #     _matrix = cp.zeros([row_count,cols.size])