Data Source Filters can use parameters, advanced operators, regular expressions, and normal values to filter results.
Data Source Filters are rules used by a data source to filter the entries it fetches from a section. The rules are field-based, meaning each rule checks against the content of a single field. Data Source filters are analogous to SQL’s WHERE clauses, defining the conditions you want matched in order for an entry to be returned. If all of a data source's filters evaluate to true for a given entry, it will be included in the result set.
Filters are added to a data source in the data source editor.
When adding multiple filter rules to a data source, note that all filters will have to return true in order for an entry to be included in the results. In other words, the filter rules are joined with AND rather than OR.
If a filter pattern contains only a parameter, and that parameter isn't set when the data source is executed, the filter rule will be ignored and the data source will execute as if the filter didn't exist.
A data source filter rule consists of a field and a filter pattern against which the field's content is matched. The field is selected from a dropdown of all fields in the current section. The pattern is entered into a text input, and can accept any combination of the following kinds of input:
Input | Description | Examples
----- | ----------- | --------
Literal values | Words, phrases, or numbers to be matched. | my-entry-title, 2009-11-30
Parameters | Parameters, which must appear inside curly braces to signal that they need to be evaluated. | {$param}
Parameter Enumerators | Default value if a parameter is not set | {$color:red}
Union Operator | Comma to delimit items in a set of possible matching values joined by OR. | red, blue, green
Intersection Operator | Plus signs to delimit items in a set of required matching values joined by AND. | red+blue+green
Range Operators | The keyword to, or the key phrases earlier than and later than, used to match numbers and dates. | later than {$today}, 10 to 100
Regular Expressions | The regexp: keyword followed by a MySQL regexp pattern. | ^b
The above can be mixed and matched, meaning patterns like the following are possible:
{$color:black}-mens-fleeceearlier than {$today}regexp: {$param}s?Data source filters and parameters are each at their most powerful when used together. The combination of the two is essential for building a dynamic Symphony project.