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Azure Databricks| Working with Unit Tests



Like any other program, Azure Databricks notebooks should be tested automatically to ensure code quality.

Using standard Python Test Tools is not easy because these tools are based on Python files in a file system. And a notebook doesn’t correspond to a Python file.


To enable automated testing with unittest (documentation), we proceed as follows:

  • Create a test class that contains all the tests you want
  • Execution of all defined tests

Create Notebook with the Code

We will create a simple Notebook for our test.

This notebook will implement a simple calculator, so that we can test the basic calculator operations like add ad multiply.

Create a new Notebook with the name Calculator:

class Calculator:

	def __init__(self, x = 10, y = 8):
		self.x = x
		self.y = y
	def add(self, x = None, y = None):
		if x == None: x = self.x
		if y == None: y = self.y			
		return x+y

	def subtract(self, x = None, y = None):
		if x == None: x = self.x
		if y == None: y = self.y	
		return x-y

	def multiply(self, x = None, y = None):
		if x == None: x = self.x
		if y == None: y = self.y			
		return x*y

	def divide(self, x = None, y = None):
		if x == None: x = self.x
		if y == None: y = self.y			
		if y == 0:
			raise ValueError('cannot divide by zero')
			return x/y

The notebook should look like this

To use this class, write the following lines:

c = Calculator()
print(c.add(20, 10), c.subtract(20, 10), c.multiply(20, 10), c.divide(20, 10))

Create Notebook with the Tests

Create a new Notebook in the same folder with the name Calculator.Tests.

The name is not important, but it is convenient to name the test program like the program to be tested with the suffix ‘Tests’.

Create the first command to import the Calculator Notebook

Create the Test Class

import unittest

class CalculatorTests(unittest.TestCase):
  def setUpClass(cls): = Calculator()

  def setUp(self):
    # print("this is setup for every method")

  def test_add(self):
    self.assertEqual(,5), 15, )

  def test_subtract(self):
    self.assertEqual(,5), 5)
    self.assertNotEqual(,2), 4)

  def test_multiply(self):
    self.assertEqual(,5), 50)

  def tearDown(self):
    # print("teardown for every method")

  def tearDownClass(cls):
    # print("this is teardown class")

Create the code to run the tests

suite =  unittest.TestLoader().loadTestsFromTestCase(CalculatorTests)

Azure | Cookbook Databricks

Databricks CLI

Export all Notebooks

databricks workspace list | ForEach { databricks workspace export_dir /$_ $_ }


Error in SQL statement: AnalysisException: Can not create the managed table('`demo`'). The associated location('dbfs:/user/hive/warehouse/demo') already exists.;


dbutils.fs.rm("dbfs:/user/hive/warehouse/demo/", true)

Azure | Working with Widgets


Don’t want to read the post, then explore this Azure Notebook


Define needed moduls and functions

from datetime import datetime

import pyspark.sql.functions as F

Create DataFrame for this post:

df = spark.sql("select * from diamonds")

Working with Widgets

Default Widgets


dbutils.widgets.text("W1", "1", "Text")
dbutils.widgets.combobox("W2", "3", [str(x) for x in range(1, 10)], "Combobox")
dbutils.widgets.dropdown("W3", "4", [str(x) for x in range(1, 10)], "Dropdown")

Multiselect Widgets

list = [ f"Square of {x} is {x*x}" for x in range(1, 10)]
dbutils.widgets.multiselect("W4", list[0], list, "Multi-Select")

Monitor the changes when selection values

print("Selection: ", dbutils.widgets.get("W4"))
print("Current Time =",

Filter Query by widgets

Prepare widgets


df = spark.sql("select * from diamonds")

vals = [ str(x[0]) for x in"cut").orderBy("cut").distinct().collect() ]
dbutils.widgets.dropdown("Cuts", vals[0], vals)

vals = [ str(x[0]) for x in"carat").orderBy("carat").distinct().collect() ]
dbutils.widgets.dropdown("Carat", vals[0], vals)

Now, change some values

filter_cut = dbutils.widgets.get("Cuts")
df=spark.sql(f"select * from diamonds where cut='{filter_cut}'").show()