unittest-pyspark 0.0.5

Extension to unittest for pySpark

unittest-pyspark

Extensions for testing pyspark with unittest and doctest.

These utils can be used in standalone Python or in Databricks notebooks.

Usage With Doctest

from unittest_pyspark import get_spark
spark = get_spark()

def go_spark():
    """
    >>> spark.sql("SELECT 'hello world'").show()
    +-----------+
    |hello world|
    +-----------+
    |hello world|
    +-----------+
    <BLANKLINE>
    >>> spark.createDataFrame([{'hello':'world'}], 'hello:string').show()
    +-----+
    |hello|
    +-----+
    |world|
    +-----+
    <BLANKLINE>
    """
    pass

import doctest
doctest.testmod()

Usage With Unittest

Here is a simple unittest test case, which can be used as template for pySpark test case.

import unittest
from unittest_pyspark import as_list, get_spark
import pyspark.sql.types as pst

class Test_Spark(unittest.TestCase):
  def setUp(self):
      self.spark = get_spark()

  def test_i_can_fly(self):
    input = [ pst.Row(a=1, b=2)]
    input_df = self.spark.createDataFrame(input)

    expect = [{'a':1}]

    actual_df = input_df.select("a")
    actual = as_list(actual_df)

    self.assertEqual(actual, expect)

You can find this entire example in the tests.test_sample module. To execute it from the command line:

python -m unittest tests.test_sample

Usage With Unittest and Databricks

To execute the unittest test cases in Databricks, add following cell:

from unittest_pyspark.unittest import *
if __name__ == "__main__":
  execute_test_cases(discover_test_cases())

Above code will automatically discover all test cases (unittest.TestCase sub classes) defined in the global scope and execute them.

Build package

You will need setuptools and twine:

pip install --upgrade setuptools
pip install --upgrade wheel

Build and upload:

python setup.py sdist bdist_wheel
python -m twine upload dist/*