it is possible to create empty streaming tables in Delta Live Tables (DLT) with only the schema specified using the DLT Python API. Here is how you can do it:

• Import the DLT module:
  import dlt

• Define the schema:
  You can specify the schema using a Python StructType or a SQL DDL string. Here is an example using a Python StructType:

from pyspark.sql.types import StructType, StructField, StringType, LongType

sales_schema = StructType([

    StructField("customer_id", StringType(), True),

    StructField("customer_name", StringType(), True),

    StructField("number_of_line_items", StringType(), True),

    StructField("order_datetime", StringType(), True),

    StructField("order_number", LongType(), True)

])

• Create the streaming table:

Use the @Dlt.table decorator to define the streaming table and specify the schema. Here is an example:

@Dlt.table(

    name="sales",

    comment="Raw data on sales",

    schema=sales_schema

)

def sales():

    return spark.readStream.format("rate").load()  # Placeholder for the actual streaming source

In this example, the sales function defines a streaming table with the specified schema. The spark.readStream.format("rate").load() is a placeholder for the actual streaming source

Please refer to: https://docs.databricks.com/en/delta-live-tables/python-ref.html