Raw Table Wildcards

In Raw Tables, you have the ability to use wildcards to apply changes to every row of the table you're targeting. This can be a very useful alternative to just manually duplicating your change to every row.

Basic Example

Using wildcards is very simple, you just write a * instead of the row name:

{
    "DT_PalMonsterParameter": {
        "*": {
            "WorkSuitability_EmitFlame": 5
        }
    }
}

Now every Pal should have maxed out Kindling work suitability, though it's a different story if they can utilize it! You can use wildcards for any data table and property.

Wildcards can also be used to delete all entries from a table with the syntax "*": null. This is useful for replacing an entire table with a new table by writing "*": null as the first entry. Use caution with this technique, as clearing the entire table erases any changes made by other mods.

Filters

PalSchema 0.6.0 adds the ability to use filters with wildcards which gives you better control over which rows you want to modify in bulk.

Example 1 (Single Filter)

We can use the code below to set the Kindling level of every Fire type pal to 1. WorkSuitability_EmitFlame is the internal name for Kindling.

{
    "DT_PalMonsterParameter": {
        "*": {
            "$Filters": [
                {
                    "FieldName": "ElementType1",
                    "Operation": "Equal",
                    "Value": "Fire"
                }
            ],
            "WorkSuitability_EmitFlame": 1
        }
    }
}

$Filters holds an array of filters and all of the filters must match for your changes to be applied.

A filter holds the following fields:

• FieldName - Name of the property that you want to compare against.
• Operation - Operation that you want to perform on your chosen values, in this case Equal. List of Operations along with their aliases and supported property types.
• Value or Values - Value you want to compare the current row against. This can be Value if you only need to match against one value or it can be Values if you want to allow multiple values to pass. Note that the Boolean type doesn't support Values since a boolean can only be true or false.

Example 2 (Multiple Filters)

This example sets the Hp of every building to 10000 with the material types of Stone and Wood as long as their Hp is below 10000.

{
    "DT_MapObjectMasterDataTable": {
        "*": {
            "$Filters": [
                {
                    "FieldName": "MaterialType",
                    "Operation": "Equal",
                    "Values": ["Stone", "Wood"]
                },
                {
                    "FieldName": "Hp",
                    "Operation": "LessThan",
                    "Value": 10000
                }
            ],
            "Hp": 10000
        }
    }
}

In terms of code the above would translate to this:

if ((CurrentRow.MaterialType == "Stone" or CurrentRow.MaterialType == "Wood") and CurrentRow.Hp < 10000)
    CurrentRow.Hp = 10000

Comparisons are done in A/B fashion where A is the current row being processed and B is the value you supplied to your filter.

Operations

Operation	Aliases	Supported Types
Equals	Equal, ==	FName, FString, FText, Enum, Bool, Numbers
GreaterThan	>	Numbers
GreaterThanOrEqual	>=	Numbers
LessThan	<	Numbers
LessThanOrEqual	<=	Numbers
Contains		FName, FString, FText
StartsWith		FName, FString, FText
EndsWith		FName, FString, FText

Supported Types

Only basic properties are supported as filters which are the following:

• FName, FString, FText
• Enum
• Number
• Bool