To expand on werners's answer, you can use the Delta API to get this information. I suggest you use scala to access it. Here is some example code that would pull out

First we make a trial merge to test with. Here firstDelta is just 1000 rows, with values 1 to 1000.

%python
from delta.tables import DeltaTable
 
firstDelta = DeltaTable.forName(spark, "firstDF")
secondDF = spark.range(998, 1004)
 
firstDelta.alias("first").merge(
    secondDF.alias("second"),
    "first.id = second.id") \
  .whenNotMatchedInsertAll() \
  .execute()

Next we extract one of the operation metrics from this merge operation:

%scala
import io.delta.tables._
 
val firstDF = DeltaTable.forName("firstDF")
val operationMetrics = firstDF.history(1).select("operationMetrics").collect()(0)(0).asInstanceOf[Map[String,String]]
 
operationMetrics("numTargetRowsInserted")

This returns 3, since 1001 , 1002, and 1003 were added.

Similarly, you can do this with your Delta table after your updates to the target table.