The CSV parser connector allows you to parse the text input data into an output with your column definitions.
You can define the comma , or semicolon ; to be the column separators helping to parse the text. In case your text input includes the header values as well, you will click the option CSV header.
Next, you have several options to set the date and number format.
Finally, you configure the columns, which are required to be parsed. Either you can select all the columns or specify the columns based on their indexes or names.
Configuration
CSV format configuration
Column separator
Columns separator dividing data of single columns. Currently available separators:
-
Comma
, -
Semicolon
;
If the parsed text is using another separator to divide data, consider using any of the available data manipulation connectors to replace the dividers before the parsing step.
CSV header
Check this box, if the first row of the file contains the header (information about the column names). If you fail to check the box, the headers will be considered as part of the data.
Date and number format
Date and number format
Select the appropriate input date and number format from the list or use the option to define your custom format.
Available date and number formats:
Invariant
| Pattern type | Pattern | Example |
|---|---|---|
| LongDatePattern | "dddd, MMMM d, yyyy" | "Tuesday, July 10, 2023" |
| ShortDatePattern | "M/d/yyyy" | "7/10/2023" |
| LongTimePattern | "h:mm:ss tt" | "4:30:15 PM" |
| ShortTimePattern | "h:mm tt" | "4:30 PM" |
| NumberFormatPattern | "#,0.###" | "1,234.567" |
Please note that the invariant culture is a culture-independent representation that does not vary with the specific culture settings. Therefore, the patterns and examples provided for the invariant culture will be consistent across different cultures and can be used as a standard format.
Czech republic cs-CZ
| Pattern type | Pattern | Example |
|---|---|---|
| LongDatePattern | "dddd d. MMMM yyyy" | "úterý 10. července 2023" |
| ShortDatePattern | "dd.MM.yyyy" | "10.07.2023" |
| LongTimePattern | "H:mm:ss" | "16:30:15" |
| ShortTimePattern | "H:mm" | "16:30" |
| NumberFormatPattern | "0,0.###" | "1 234,567" |
German (Germany) de-DE
| Pattern type | Pattern | Example |
|---|---|---|
| LongDatePattern | "dddd d. MMMM yyyy" | "Dienstag, 10. Juli 2023" |
| ShortDatePattern | "dd.MM.yyyy" | "10.07.2023" |
| LongTimePattern | "H:mm:ss" | "16:30:15" |
| ShortTimePattern | "H:mm" | "16:30" |
| NumberFormatPattern | "0,0.###" | "1.234,567" |
English (United States) en-US
| Pattern type | Pattern | Example |
|---|---|---|
| LongDatePattern | "dddd, MMMM d, yyyy" | "Tuesday, July 10, 2023" |
| ShortDatePattern | "M/d/yyyy" | "7/10/2023" |
| LongTimePattern | "h:mm:ss tt" | "4:30:15 PM" |
| ShortTimePattern | "h:mm tt" | "4:30 PM" |
| NumberFormatPattern | "#,0.###" | "1,234.567" |
Custom - If custom is used, make sure the section Decimal separator and the DateTime format are filled.
Decimal separator
Select the decimal separator:
-
Decimal Point (e.g. 3.14)
-
Decimal Comma (e.g. 3,14)
DateTime format
Specify the date time format. Follow the C## conventions (case sensitive). The default value is set to: yyyy-MM-dd.
CSV column list configuration
Parsed columns
Select the columns, which should be part of the output. Available options:
-
All columns - Takes all parsed columns from the input.
-
List of column indexes - Select this option if you want to restrict and even reorder the parsed columns in the output. If using this option, define the column indexes in the field List of parsed columns.
-
List of column names - Select this option if you want to restrict and even reorder the parsed columns in the output. If using this option, define the column names in the field List of parsed columns.
List of parsed columns
Items filled in this field must be divided by the selected separator set in the configuration section CSV format - either comma , or semicolon ;.
Example:
Using the List of column indexes and setting the comma as the separator: 1, 3, 5 you will include the first, third, and fifth columns into the output.
Using the List of column names and setting the semicolon as the separator: ColumnName4, ColumnName1, Column2 you will include the fourth, first, and second columns into the output.
Input & Output Schema
Input
Text (ver. 1.0.0)
| Column | Data type | Allow null | Description |
|---|---|---|---|
| Text | String | No | Converted plain text. |
Output
Data schema is mandatory
The connector requires mandatory input or output data schema, which must be selected by the user from the existing data schema repository or a new one must be created. The connector will fail without structured data.
Release notes
3.3.1
- Plugin binaries update as a result of included connector change.
3.3.0
- Fixed Date and number format configuration title.
3.2.1
- Fixed shared nuget package versions.