APEX Interactive Grid: Cell Selection as Default

When you want to copy a specific value from an Interactive Grid, you would need to change Row Selection to Cell Selection in the Actions menu.
When you don't want to expose the Actions-menu, or just to make it more convenient for your users, having Cell Selection as the Default might be more convenient.
To change this the Default, and set Cell Selection as the Default, add the following code to the Javascript Initialization Code section:

function(config) {
    config.defaultGridViewOptions = {
        selectCells: true
    }

    return config;
}

Parse CSV-file in different Character Set with APEX_DATA_PARSER

When there are special characters in a CSV-file, and the file is in a different characterset than which you expect, parsing it can give unexpected results.
From different suppliers we get CSV-file, which need to be parsed and stored in the database. This is done by using APEX_DATA_PARSER.
APEX_DATA_PARSER is very flexible and allows several file-formats: JSON, XML, CSV and even native Excel XLSX.
The files are uploaded to the database (in the background) and processed. And this works like a charm,... until... one of the suppliers provided a CSV-file in a different character set, with special characters.

Below is an example of this file:

This file is uploaded to a database table with the following structure:

  Name         Null? Type          
------------ ----- ------------- 
MIME_TYPE          VARCHAR2(255) 
FILENAME           VARCHAR2(400) 
BLOB_CONTENT       BLOB  
  

The following query is used to parse the file and extract the data:

SQL> select p.col001
  2        ,p.col002
  3        ,p.col003
  4    from a
  5   cross
  6    apply apex_data_parser.parse (p_content => a.blob_content
  7                                 ,p_file_name => a.filename
  8                                 ) p
  9* /

COL001                     COL002     COL003     
__________________________ __________ __________ 
R�sselsheim am Main        3.000      624.760    
Gnutz                      1.000      139.490    
�ach-Palenberg             1.000      139.490    
Syke                       1.000      242.600    
H�kirchen-Siegertsbrunn    1.000      136.980    
Eberhardzell               1.000      233.810    
heinsberg                  1.000      67.840     
Hohndorf                   3.000      304.800    
Nidderau                   3.000      385.890    
N�n-Hardenberg             1.000      239.680    
Kl��1.000                  185.000               
K                          2.000      237.880    
W�rselen                   1.000      196.500    
Gl�ckstadt                 1.000      136.980    
Dessau-Ro�au               1.000      5.900      

15 rows selected. 

As you can see in the results above, the special characters have been removed. When a word in the first column ends in a special character, the parsing of the rest of the line is also messed up, there is a NULL in Column 3 while there should be a value.
Of course this has everything to do with the characterset of the uploaded file.

With the following command in a Terminal-window on Mac, it is possible to get information about the file, including the characterset:

  file -I name of the file
  

In my case that would yield the following results:

file -I charset.csv
charset.csv: text/plain; charset=iso-8859-1
  

This means that the file is in the characterset: ISO-8859-1

To find out which characterset this maps to in the database, the following query can help:

  SQL> select value
  2    from v$nls_valid_values
  3   where parameter  ='CHARACTERSET'
  4     and value like '%8859%'
  5* /

VALUE             
_________________ 
WE8ISO8859P1      
EE8ISO8859P2      
SE8ISO8859P3      
NEE8ISO8859P4     
CL8ISO8859P5      
AR8ISO8859P6      
EL8ISO8859P7      
IW8ISO8859P8      
WE8ISO8859P9      
NE8ISO8859P10     
WE8ISO8859P15     
BLT8ISO8859P13    
CEL8ISO8859P14    
AZ8ISO8859P9E     

14 rows selected.
  

From this list WE8ISO8859P1 is selected and passed in into the APEX_DATA_PARSER function:

SQL> select p.col001
  2        ,p.col002
  3        ,p.col003
  4    from all_csvs a
  5   cross
  6    apply apex_data_parser.parse (p_content => a.blob_content
  7                                 ,p_file_name => a.filename
  8                                 ,p_file_charset => 'WE8ISO8859P1'
  9                                 ) p
 10* /

COL001                        COL002    COL003     
_____________________________ _________ __________ 
Rüsselsheim am Main           3.000     624.760    
Gnutz                         1.000     139.490    
Übach-Palenberg               1.000     139.490    
Syke                          1.000     242.600    
Höhenkirchen-Siegertsbrunn    1.000     136.980    
Eberhardzell                  1.000     233.810    
heinsberg                     1.000     67.840     
Hohndorf                      3.000     304.800    
Nidderau                      3.000     385.890    
Nörten-Hardenberg             1.000     239.680    
Klüß                          1.000     185.000    
Köln                          2.000     237.880    
Würselen                      1.000     196.500    
Glückstadt                    1.000     136.980    
Dessau-Roßlau                 1.000     5.900      

15 rows selected.

And now all is well.