CSV

with the csv app in {{product name}} , you can create and parse csv text you do not need to establish a connection to use the csv app csv modules you can use the following modules to build your {{scenario plural lowercase}} aggregators create csv merges selected text items and returns them in the csv format the create csv aggregator lets you create csv text from received text values field description source module select the app module you are using to aggregate the fields you need aggregate fields select the fields you want to aggregate from the list of available fields include headers in the first row when selected, includes the headers in the result delimiter select the delimiter character to separate the values if you select other , a delimiter character field will populate below where you can specify the character delimiter character specify which delimiter character is used to separate the values if you selected other it must be only one character newline select the newline that is used to indicate the end of a line of text group by enter the filter to group the results for example, a date stop processing after an empty aggregation when selected, the {{scenario singular lowercase}} stops when there are no results example export google contacts to a csv file the create csv module provides you with a list of options as checkboxes if you are selecting contact's id and full name, then the results are returned in a text format export google contacts to a csv file create csv (advanced) merges selected text items and returns them in the csv format employs data structure to define csv columns in the resulting csv file the create csv (advanced) aggregator lets you create a csv text from received text values it employs a data structure that defines the csv columns in the resulting csv file once defined, the columns appear as fields in the csv module setup, available for mapping field description source module select the app module you are using to aggregate the fields you need data structure select the data structure to aggregate the fields in the way you want see csv docid\ qvswjlpvwkeinptqwpgsg after defining the data structure, you can map the items to the corresponding fields aggregate fields provides a list of fields you want to aggregate include headers in the first row when selected, includes headings in the first row delimiter select the delimiter character to separate the values if you select other , a delimiter character field will populate below where you can specify the character delimiter character specify which delimiter character is used to separate the values if you selected other it must be only one character newline select the newline that is used to indicate the end of a line of text group by enter the filter to group the results for example, a date stop processing after an empty aggregation when selected, the make stops when there are no results example export google contacts to a csv file the create csv (advanced) module provides you with the option to create a data structure with the aggregating fields you needed if you are defining a data structure with full name and email then the results are returned in a text format export google contacts to a csv file advanced transformers parse csv parses a csv file the parse csv transformer lets you parse a csv text from a received text value or a file if your data comes in binary form (typically from a file), you have to use the tostring() function to convert the binary data to string field description number of columns specity the number of columns in the csv file csv contains headers when selected, includes the headers in the result delimiter select the delimiter character to separate the values if you select other , a delimiter character field will populate below where you can specify the character delimiter character specify which delimiter character is used to separate the values if you selected other it must be only one character preserve quotes inside unquoted field select yes or no csv if your data comes in binary form, you have to use the tostring function to convert it to string example transforming complex data to csv for example, you would like to export your google contacts to a csv file with two columns "full name" and "email" the output bundle from the google contacts > get contacts from a group module has the following structure (see on the right) the email addresses are stored inside the emails\[] item, which is an array of collections, each collection containing two items label and email if you employ the simple create csv module, you are offered a list of checkboxes corresponding to a bundle's top level items if you attempt to tick full name and emails items, the create csv module will produce the following output, which is probably not what you wished for "emails","fullname" "\[object object]","shon winer" "\[object object]","lizeth fulmore" "\[object object]","hilario gullatt" "\[object object]","abby eisenbarth" since the item full name is of simple type text it is exported just fine but the item emails , which is of a complex type array of collections, is exported as \[object object] that is how collections and arrays are transformed to text by default to export content of the email item of the first collection of the emails\[] array instead, it is necessary to employ the create csv (advanced) module the module will enable you to define individual columns of your csv file and map items to them, including the nested ones insert the module create csv (advanced) in a {{scenario singular lowercase}} and open its configuration click the add button next to the data structure field to create a new data structure input a name for the data structure and click the add item button to add the individual columns if you wish to export two columns "full name" and "email", the resulting data structure would look like this once you have successfully defined the data structure, fields corresponding to each individual column should appear in the configuration of the create csv (advanced) module so you can map the items take the first item from the emails\[] array and map its item email to the field/column email run the {{scenario singular lowercase}} since the item emails\[1] email mapped to column email is of simple type text, it will be exported correctly now "full name","email" "shon winer","shon\@winer com" "lizeth fulmore","lizeth\@fulmore com" "hilario gullatt","hilario\@gullatt com" "abby eisenbarth","abby\@eisenbarth com" adding a data structure you can add the data structures by clicking add item in the specification field one item represents one column adding a data structure fill in the details in the add item dialog field description name enter the name of the property for the data structure for example, full name label enter a label for the data structure type select the data type array collection date text number boolean binary data default enter a default value for the property required when selected, indicates that the value is required