dlt-sidestep 0.0.8

A library that helps you build dlt pipelines by side stepping the dlt library and making your code interactive

Installation

pip install in your Databricks Notebook

%pip install dlt_sidestep

Example Usage

Note: You must define a pipeline_id variable as spark.conf.get("pipelines.id", None)

Note: You must define a g variable as globals()

`

from pyspark.sql.functions import *

from pyspark.sql.types import *

from dlt_sidestep import SideStep



pipeline_id =  spark.conf.get("pipelines.id", None)

g = globals()



if pipeline_id:

  import dlt



json_path = "/databricks-datasets/wikipedia-datasets/data-001/clickstream/raw-uncompressed-json/2015_2_clickstream.json"



step = """

@dlt.create_table(

  comment="The raw wikipedia click stream dataset, ingested from /databricks-datasets.",

  table_properties={

    "quality": "bronze"

  }

)

def clickstream_raw():

  return (

    spark.read.option("inferSchema", "true").json(json_path)

  )

"""

SideStep(step, pipeline_id, g)

df = clickstream_raw()

df.display()





step = """

@dlt.create_table(

  comment="Wikipedia clickstream dataset with cleaned-up datatypes / column names and quality expectations.",

  table_properties={

    "quality": "silver"

  }

)

@dlt.expect("valid_current_page", "current_page_id IS NOT NULL AND current_page_title IS NOT NULL")

@dlt.expect_or_fail("valid_count", "click_count > 0")

def clickstream_clean():

  return (

    dlt.read("clickstream_raw")

      .withColumn("current_page_id", expr("CAST(curr_id AS INT)"))

      .withColumn("click_count", expr("CAST(n AS INT)"))

      .withColumn("previous_page_id", expr("CAST(prev_id AS INT)"))

      .withColumnRenamed("curr_title", "current_page_title")

      .withColumnRenamed("prev_title", "previous_page_title")

      .select("current_page_id", "current_page_title", "click_count", "previous_page_id", "previous_page_title")

  )

"""

SideStep(step, pipeline_id, g)

df = clickstream_clean()

df.display()