How to use flatten_tests method in Lemoncheesecake

Best Python code snippet using lemoncheesecake

test_splitter.py

Source:test_splitter.py

1# coding: utf-82import collections3def flatten_tests(test_classes):4    """5    >>> test_classes = {x: [x] for x in range(5)}6    >>> flatten_tests(test_classes)7    [(0, 0), (1, 1), (2, 2), (3, 3), (4, 4)]8    >>> test_classes = {x: [x + 1, x + 2] for x in range(2)}9    >>> flatten_tests(test_classes)10    [(0, 1), (0, 2), (1, 2), (1, 3)]11    """12    tests = []13    for class_name, test_names in test_classes.items():14        tests += [(class_name, test_name) for test_name in test_names]15    return tests16def get_sequential_chunk(tests, modulo, modulo_index, is_sorted=False):17    """18    >>> get_sequential_chunk(range(10), 4, 0)19    [0, 1, 2]20    >>> get_sequential_chunk(range(10), 4, 1)21    [3, 4, 5]22    >>> get_sequential_chunk(range(10), 4, 2)23    [6, 7]24    >>> get_sequential_chunk(range(10), 4, 3)25    [8, 9]26    >>> get_sequential_chunk(range(10), 4, 4)27    []28    >>> get_sequential_chunk(range(10), 4, 5)29    []30    """31    if not is_sorted:32        tests = sorted(tests)33    chunk_size = len(tests) // modulo34    not_used = len(tests) % modulo35    shift = chunk_size + (modulo_index < not_used)36    start = chunk_size * modulo_index + min(modulo_index, not_used)37    end = start + shift38    return [] if end > len(tests) else tests[start:end]39def get_shuffled_chunk(tests, modulo, modulo_index, is_sorted=False):40    """41    >>> get_shuffled_chunk(range(10), 4, 0)42    [0, 4, 8]43    >>> get_shuffled_chunk(range(10), 4, 1)44    [1, 5, 9]45    >>> get_shuffled_chunk(range(10), 4, 2)46    [2, 6]47    >>> get_shuffled_chunk(range(10), 4, 3)48    [3, 7]49    >>> get_shuffled_chunk(range(10), 4, 4)50    []51    >>> get_shuffled_chunk(range(10), 4, 5)52    []53    """54    if not is_sorted:55        tests = sorted(tests)56    result_tests = []57    for i, test in enumerate(tests):58        if i % modulo == modulo_index:59            result_tests.append(test)60    return result_tests61def get_splitted_tests(test_entities, modulo, modulo_index, partition_mode, is_sorted=False):62    if partition_mode == 'SEQUENTIAL':63        return get_sequential_chunk(test_entities, modulo, modulo_index, is_sorted)64    elif partition_mode == 'MODULO':65        return get_shuffled_chunk(test_entities, modulo, modulo_index, is_sorted)66    else:67        raise ValueError("detected unknown partition mode: {}".format(partition_mode))68def filter_tests_by_modulo(test_classes, modulo, modulo_index, split_by_tests, partition_mode="SEQUENTIAL"):69    """70    >>> test_classes = {x: [x] for x in range(20)}71    >>> filter_tests_by_modulo(test_classes, 4, 0, False)72    {0: [0], 1: [1], 2: [2], 3: [3], 4: [4]}73    >>> filter_tests_by_modulo(test_classes, 4, 1, False)74    {8: [8], 9: [9], 5: [5], 6: [6], 7: [7]}75    >>> filter_tests_by_modulo(test_classes, 4, 2, False)76    {10: [10], 11: [11], 12: [12], 13: [13], 14: [14]}77    >>> dict(filter_tests_by_modulo(test_classes, 4, 0, True))78    {0: [0], 1: [1], 2: [2], 3: [3], 4: [4]}79    >>> dict(filter_tests_by_modulo(test_classes, 4, 1, True))80    {8: [8], 9: [9], 5: [5], 6: [6], 7: [7]}81    """82    if split_by_tests:83        tests = get_splitted_tests(flatten_tests(test_classes), modulo, modulo_index, partition_mode)84        test_classes = collections.defaultdict(list)85        for class_name, test_name in tests:86            test_classes[class_name].append(test_name)87        return test_classes88    else:89        target_classes = get_splitted_tests(test_classes, modulo, modulo_index, partition_mode)...

test_models.py

Source:test_models.py

...11    "ga4gh_identify": ga4gh_identify,12}13validation_fn = os.path.join(os.path.dirname(__file__), "data", "models.yaml")14validation_tests = yaml.load(open(validation_fn), Loader=yaml.SafeLoader)15def flatten_tests(vts):16    """flatten tests to (class, data, function name, exp out) tuples17    Each tuple is a test in which an object of the specified class is18    created with data, evaluated with the named function, and compared19    with the expected output.20    """21    for cls, tests in validation_tests.items():22        for t in tests:23            for fn, exp in t["out"].items():24                test_name = t.get("name", cls)25                test_name += f"-{fn}"26                yield pytest.param(cls, t["in"], fn, exp, id=test_name)27#tests, ids = zip(*list(flatten_tests(validation_tests)))28#import IPython; IPython.embed()	  ### TODO: Remove IPython.embed()29@pytest.mark.parametrize("cls,data,fn,exp", flatten_tests(validation_tests))30def test_validation(cls, data, fn, exp):31    o = models[cls](**data)32    fx = fxs[fn]...

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