Multtestlib has been devised to aid Python testers in expediting their testing processes through multiprocessing. This approach allows customizable utilization of the computer's available processor cores, facilitating workload distribution and consequent reduction in the overall execution time of the test suite.
Multtestlib is available on PyPi and can be installed using the pip command:
pip install multtestlib
Multtestlib requires Python 3.7 or later to run.
For multiprocessing usage, the input parameters of the test functions and their respective expected values must be stored in lists. During the test processing, multtestlib will take care of distributing and managing the data contained in the lists - and functions - among the processor cores indicated in the test program.
The signature of the methods in multtestlib: mtl.command(cpu, list_1, list_2, expected_list, subject_to_test)
Where:
mtl: It is the suggested alias for multtestlib;
.command: Specifies the test command (see table below), which is a function of mtl;
cpu: The amount of CPU cores designated for running the test. It could be defined either statically, by the developer/tester, or dynamically with the command cpu = mtl.max_cpu();
list_1: The test requires the provision of this initial set of input parameters. The package passes the iteration element as an input parameter of the code unit under test, no matter what type of data it contains;
list_2: If needed, this parameter specifies the second input list of the unit being evaluated. If a second parameter is not necessary, the list should be substituted with "";
expected_list: Identifies the list that holds the anticipated outcome values for every test;
subject_to_test: This parameter specifies the unit that will undergo testing. It could be a function, a class method, or a list of code units for testing purposes.
Here is a code example illustrating the usage of multtestlib:
# It is strongly recommended to create a test function to be called by the main() function.
# But, multtestlib supports any coding style in Python.
import multtestlib as mtl
# Class to be tested
class Cube:
def __init__(self, side_length):
self.side_length = side_length
def calculate_volume(self):
return self.side_length ** 3
# Functions to be tested
def add(a, b):
return (a + b)
def subtract(a, b):
return a - b
# Wrapper function to test a class method
# When testing methods of a class, create a function (outside of the class)
# to invoke it:
# def method(object):
# return object.method()
def calculate_volume(cube):
return cube.calculate_volume()
# The tester function
def tester():
argument_list_a = [1, 2, 3, 5, 7, 9]
argument_list_b = [2, 3, 4, 4, 3, 6]
expected_list = [3, 5, 7, 1, 4, 2]
functions_list = [add, add, add, subtract, subtract, subtract]
argument_list_cube = [Cube(3), Cube(4), Cube(5)]
expected_list_cube = [27, 64, 125]
functions_list_cube = [calculate_volume, calculate_volume, calculate_volume]
cpu = 4
mtl.test_equal(cpu, argument_list_a, argument_list_b, expected_list, functions_list)
mtl.test_equal(cpu, argument_list_cube, "", expected_list_cube, functions_list_cube)
if __name__ == "__main__":
mtl.init()
tester()
mtl.end()
During the unit testing process, a document with the extension .csv is created which presents the results of each test carried out. The document is named in a standardized way as mtl-yymmdd-hhmmss.csv.
The test results are recorded in columns, as follows:
Test Name: Is the mtl command used in the test;
Tested: Function or method being tested;
Input1: First argument (a) sent to the test;
Input2: Second argument (b) sent to the test;
Expected: Desired result after test processing;
Received: Value received as a result of the test;
Result: Pass or Fail, indicates whether the test was successful or a failure occurred;
Execution Time (seconds): Specific test execution time, in seconds.
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