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A small library for testing your code, made by tester for testers

Project description


A simple library to test your python code.

Key Features:

  • no third-party dependencies, only the standard library is used
  • no need to inherit from any classes
  • no need to name your files and/or tests with the prefix or postfix 'test' added
  • it is possible to use native python assert as well as library asserts
  • simple and understandable work with tests, data providers, checks
  • the ability to run based on a file with settings or passing arguments on the command line
  • automatic search for all tests in the current folder and subfolders
  • flexible configuration of both tests and their groups, the ability to group tests and run only selected groups
  • the ability to use both the built-in results processing tool and write your own
  • the ability to group, stop the test by timeout, parallel launch, mocking without installing additional plugins


Just use your pip

pip install checking

First test

Simple example:

from checking import *

def my_function_to_test(a,b)
    return a + b

def any_name_you_like():
    # Check  1+1=2
    equals(2, my_function_to_test(1,1))

if __name__ == '__main__':
    # Runs all tests in current module

Only functions marked with the @test annotation are considered tests and will be run, you can name your tests as you wish, the main thing is to put the @test annotation

Basic Asserts

You can use simple python assert if you like, but it recommended to use simple and readable library asserts.

Standard checks:
def checks_basic_asserts():
    is_true('1', 'Error message') # checks value is True
    is_false([], 'Error message') # checks value is False
    equals(1, 1, 'Error message') # checks two objects are equal (==)
    not_equals(1, 2, 'Error message') # checks two objects are equal (!=)
    is_none(None, 'Error message') # checks object is None
    not_none('1', 'Error message') # checks object is not None
    contains(1, [1, 2, 3], 'Error message') # checks that second argement contains first arg
    not_contains(4, [1, 2, 3], 'Error message') # checks that second argement not contains first arg

Messages in all asserts are optional, but it strongly recommended to use them!

Work with or without exceptions

If you need to check the exception raises and its message you can write test like:

def check_with_exception():
    with waiting_exception(ZeroDivisionError) as e:
        x = 1 / 0 # Here exception will be raised!
    assert e.message == 'division by zero' # Check message (using python assert)

If no exception will be raised or it will be exception of another type - test will fail. Pay attention - you must check message (if you need to) after exiting context manager, but not inside its scope!

You can't use BaseException here, and it strongly recommended not to use Exception as parent of all exceptions!

In some cases, you nedd just to run some code and make sure no exception raised. There is a special way for that:

def no_exceptions_bad():
    do_something() # Bad way! No asserts here, is that a test???

def check_no_exception_raises():
    with no_exception_expected(): # Explicitly say that we are not waiting exceptions
        do_something() # Good way!

If any exception will be raised - test will fail

Managing test during execution

Sometime you need to fail or brake test in execution time on some reason (wrong OS, parameters, etc.)

def must_fail_on_condition():
    if some_condition():
        test_fail('Expected fail!')

def must_be_broken():
    if some_condition():
        test_brake('Expected brake!')

Soft and Fluent Asserts

Soft Assert

Soft Assert is a convenient way to checks a few condition before fail. Standard test is preferably fail fast, and if some check fails - the test stops. But sometime you need to check a list of conditions, and check them to fail only at the end of the test, with all information what checks were failed. For example you have a json object and want to checks all its fields, but don't want to stop test at first failed check, because you want to know what about all other fields!


def check_all_json_fields():
    my_json = get_my_json_somethere()

    soft_assert = SoftAssert() # Creates an object of soft assert
    soft_assert.check(lambda : equals(1, my_json['field1'], 'message')) # Check field, test will not fail here!
    soft_assert.check(lambda : equals('text', my_json['field2'], 'message'))
    soft_assert.assert_all() # If something wrong, test will fail here!

Attention! You always must use assert_all() at the end of the test, only at that moment all exception (if something wrong) will be raise.

Fluent Assert

Fluent assert is just a sugar to make chains of checks for the object, they are simple, readable, but it is NOT a soft asserts! If one of the checks will fail - test stops! Fluent asserts have analogues of the basic asserts, but also have their own types, you can fimd them all at checking/classes/


def check_list_valid():
    my_list = get_my_list_somethere()


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