KaneAI - World’s First E2E Software Testing Agent.Book a Demo Join TestMu Conference

How to use build_test_case method in Testify

Best Python code snippet using Testify_python

test_functional_preproc.py

Source:test_functional_preproc.py

...83    wf_inputs_string = wf_inputs_string.replace(base_dir, \84                           "BASE_DIRECTORY_HERE")85    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILE_A_HERE", 1)86    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILES_HERE")87    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)88        89    assert flag == 2, err90def test_workflow_func_motion_correct_slice_time():91    import os92    import pkg_resources as p93    from qap.functional_preproc import run_func_motion_correct94    from qap.workflow_utils import build_test_case95   96    func_scan = p.resource_filename("qap", os.path.join(test_sub_dir, \97                                    "rest_1", \98                                    "functional_scan", \99                                    "rest.nii.gz"))100    ref_graph = p.resource_filename("qap", os.path.join("test_data", \101                                    "workflow_reference", \102                                    "func_motion_correct_slice_time", \103                                    "graph_func_motion_correct" \104                                    "_slice_time.dot"))105                                    106    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \107                                     "workflow_reference", \108                                     "func_motion_correct_slice_time", \109                                     "wf_inputs.txt"))    110                                   111    # build the workflow112    wf, base_dir = run_func_motion_correct(func_scan, 0, "End", True, False)113         114    115    # get the workflow inputs of the workflow being tested116    wf_inputs_string = str(wf.inputs).replace("\n","")117    118    wf_inputs_string = wf_inputs_string.replace(base_dir, \119                           "BASE_DIRECTORY_HERE")120    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILE_A_HERE",\121                                                1)122    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILES_HERE")123    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)124        125    assert flag == 2, err126 127    128def test_workflow_functional_brain_mask_3dautomask():129    import os130    import pkg_resources as p131    from qap.functional_preproc import run_functional_brain_mask132    from qap.workflow_utils import build_test_case133   134    func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \135                                      "rest_1", \136                                      "func_motion_correct", \137                                      "rest_calc_tshift_resample_" \138                                      "volreg.nii.gz"))139    ref_graph = p.resource_filename("qap", os.path.join("test_data", \140                                    "workflow_reference", \141                                    "functional_brain_mask_3dautomask", \142                                    "graph_functional_brain_mask" \143                                    "_3dautomask.dot"))144                                    145    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \146                                    "workflow_reference", \147                                    "functional_brain_mask_3dautomask", \148                                    "wf_inputs.txt"))149                   150    # build the workflow151    wf, base_dir = run_functional_brain_mask(func_motion, use_bet=False, \152                                             run=False)153    154    # get the workflow inputs of the workflow being tested155    wf_inputs_string = str(wf.inputs).replace("\n","")156    157    wf_inputs_string = wf_inputs_string.replace(base_dir, \158                           "BASE_DIRECTORY_HERE")159    wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")160            161    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)162        163    assert flag == 2, err164 165    166    167def test_workflow_functional_brain_mask_BET():168    import os169 170    import pkg_resources as p171    from qap.functional_preproc import run_functional_brain_mask172    from qap.workflow_utils import build_test_case173   174    func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \175                                      "rest_1", \176                                      "func_motion_correct", \177                                      "rest_calc_tshift_resample_" \178                                      "volreg.nii.gz"))179                                                                        180    ref_graph = p.resource_filename("qap", os.path.join("test_data", \181                                    "workflow_reference", \182                                    "functional_brain_mask_BET", \183                                    "graph_functional_brain_mask_BET.dot"))184                                    185    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \186                                     "workflow_reference", \187                                     "functional_brain_mask_BET", \188                                     "wf_inputs.txt"))189                                   190    # build the workflow191    wf, base_dir = run_functional_brain_mask(func_motion, use_bet=True, \192                                             run=False)193    # get the workflow inputs of the workflow being tested194    wf_inputs_string = str(wf.inputs).replace("\n","")195    196    wf_inputs_string = wf_inputs_string.replace(base_dir, \197                           "BASE_DIRECTORY_HERE")198    wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")199    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)200        201    assert flag == 2, err202def test_workflow_mean_functional():203    import os204    import pkg_resources as p205    from qap.functional_preproc import run_mean_functional206    from qap.workflow_utils import build_test_case207    208    func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \209                                      "rest_1", \210                                      "func_motion_correct", \211                                      "rest_calc_tshift_resample_" \212                                      "volreg.nii.gz"))213                                    214    ref_graph = p.resource_filename("qap", os.path.join("test_data", \215                                    "workflow_reference", \216                                    "mean_functional", \217                                    "graph_mean_functional.dot"))218                                    219    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \220                                     "workflow_reference", \221                                     "mean_functional", \222                                     "wf_inputs.txt"))223                                   224    # build the workflow225    wf, base_dir = run_mean_functional(func_motion, False)226    # get the workflow inputs of the workflow being tested227    wf_inputs_string = str(wf.inputs).replace("\n","")228    229    wf_inputs_string = wf_inputs_string.replace(base_dir, \230                           "BASE_DIRECTORY_HERE")231    wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")232    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)233        234    assert flag == 2, err235def run_all_tests_functional_preproc():236    test_get_idx_whole_timeseries()237    test_get_idx_partial_timeseries()238    test_get_idx_partial_timeseries_overshoot()239    test_workflow_func_motion_correct_no_slice_time()240    test_workflow_func_motion_correct_slice_time()241    test_workflow_functional_brain_mask_3dautomask()242    test_workflow_functional_brain_mask_BET()243    test_workflow_mean_functional()   244    245    246

test_anatomical_preproc.py

Source:test_anatomical_preproc.py

...27    28    wf_inputs_string = wf_inputs_string.replace(base_dir, \29                           "BASE_DIRECTORY_HERE")30    wf_inputs_string = wf_inputs_string.replace(anat_scan, "IN_FILE_HERE")31    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)32        33    assert flag == 2, err34  35    36def test_workflow_anatomical_skullstrip():37    ''' unit test for the anatomical skullstrip workflow BUILDER '''38    import os39    import commands40    41    import pkg_resources as p42    from qap.anatomical_preproc import run_anatomical_skullstrip43    from qap.workflow_utils import build_test_case44    anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \45                                        "anat_1", \46                                        "anatomical_reorient", \47                                        "mprage_resample.nii.gz"))48    ref_graph = p.resource_filename("qap", os.path.join("test_data", \49                                    "workflow_reference", \50                                    "anatomical_skullstrip", \51                                    "graph_anatomical_skullstrip.dot"))52                                    53    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \54                                     "workflow_reference", \55                                     "anatomical_skullstrip", \56                                     "wf_inputs.txt"))57    # build the workflow and return it58    wf, base_dir = run_anatomical_skullstrip(anat_reorient, False)59    # get the workflow inputs of the workflow being tested60    wf_inputs_string = str(wf.inputs).replace("\n","")61    62    wf_inputs_string = wf_inputs_string.replace(base_dir, \63                           "base_directory_here")64    wf_inputs_string = wf_inputs_string.replace(anat_reorient, "in_file_here", 1)65    wf_inputs_string = wf_inputs_string.replace(anat_reorient, "in_file_a_here")66    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)67        68    assert flag == 2, err69def test_workflow_flirt_anatomical_linear_registration():70    ''' unit test for the anatomical reorient workflow BUILDER '''71    import os72    import pkg_resources as p73    from qap.anatomical_preproc import run_flirt_anatomical_linear_registration74    from qap.workflow_utils import build_test_case75    anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \76                                     "anat_1", \77                                     "anatomical_brain", \78                                     "mprage_resample_calc.nii.gz"))79    template_brain = p.resource_filename("qap", os.path.join("test_data", \80                                         "MNI152_T1_2mm_brain.nii.gz"))81    ref_graph = p.resource_filename("qap", os.path.join("test_data", \82                                    "workflow_reference", \83                                    "flirt_anatomical_linear_registration", \84                                    "graph_flirt_anatomical_linear" \85                                    "_registration.dot"))86                                    87    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \88                                     "workflow_reference", \89                                     "flirt_anatomical_linear_registration", \90                                     "wf_inputs.txt"))91    # build the workflow and return it92    wf, base_dir = run_flirt_anatomical_linear_registration(anat_brain, \93                                                            template_brain, \94                                                            False)95    # get the workflow inputs of the workflow being tested96    wf_inputs_string = str(wf.inputs).replace("\n","")97    98    wf_inputs_string = wf_inputs_string.replace(base_dir, \99                           "base_directory_here")100    wf_inputs_string = wf_inputs_string.replace(anat_brain, "in_file_here")101    wf_inputs_string = wf_inputs_string.replace(template_brain, \102                                                    "reference_here")103    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)104        105    assert flag == 2, err106       107    108def test_workflow_segmentation():109    ''' unit test for the segmentation workflow BUILDER '''110    import os111    import commands112    113    import pkg_resources as p114    from qap.anatomical_preproc import run_segmentation_workflow115    from qap.workflow_utils import build_test_case116    anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \117                                     "anat_1", \118                                     "anatomical_brain", \119                                     "mprage_resample_calc.nii.gz"))120    ref_graph = p.resource_filename("qap", os.path.join("test_data", \121                                    "workflow_reference", \122                                    "segmentation", \123                                    "graph_segmentation.dot"))124    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \125                                     "workflow_reference", \126                                     "segmentation", \127                                     "wf_inputs.txt"))128    # build the workflow and return it129    wf, base_dir = run_segmentation_workflow(anat_brain, False)130    # get the workflow inputs of the workflow being tested131    wf_inputs_string = str(wf.inputs).replace("\n","")132    133    wf_inputs_string = wf_inputs_string.replace(base_dir, \134                           "base_directory_here")135    list_input = "['" + anat_brain + "']"136    wf_inputs_string = wf_inputs_string.replace(list_input, "in_files_here")137    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)138        139    assert flag == 2, err140def run_all_tests_anatomical_preproc():141    test_workflow_anatomical_reorient()142    test_workflow_anatomical_skullstrip()143    test_workflow_flirt_anatomical_linear_registration()...

json.py

Source:json.py

...62    """Check to see if specified test at endpoint should be auto run"""63    with open(directory) as stream:64        data = json.load(stream)65        test_data = data[endpoint]66        auto_run = parse.build_test_case(test_data, test_name)["auto_run"]67        return auto_run68def endpoint_load_all_tests(directory, endpoint):69    """Load list of all test cases from an endpoint"""70    with open(directory) as stream:71        data = json.load(stream)72        test_dict = data[endpoint]73        LOG.debug("Loaded test data : %s", test_dict)74        return test_dict75def endpoint_load_test_case(directory, endpoint, test_name):76    """Load test description, payload, and expected results at index"""77    with open(directory) as stream:78        data = json.load(stream)79        test_data = data[endpoint]80        return parse.build_test_case(test_data, test_name)81def endpoint_load_base_path(directory, endpoint):82    """Load base path from endpoint"""83    return endpoint_load_test_path(directory, endpoint, BASE)84def endpoint_load_test_path(directory, endpoint, test_name):85    """Load expected path for specified endpoint and test"""86    with open(directory) as stream:87        data = json.load(stream)88        test_data = data[endpoint]89        path = parse.build_test_case(test_data, test_name)["path"]90        return path91def endpoint_load_base_parameters(directory, endpoint):92    """Load base parameters from endpoint"""93    return endpoint_load_test_parameters(directory, endpoint, BASE)94def endpoint_load_test_parameters(directory, endpoint, test_name):95    """Load expected parameters for specified endpoint and test"""96    with open(directory) as stream:97        data = json.load(stream)98        test_data = data[endpoint]99        parameters = parse.build_test_case(test_data, test_name)["parameters"]100        return parameters101def endpoint_load_base_payload(directory, endpoint):102    """Load base payload from endpoint"""103    return endpoint_load_test_payload(directory, endpoint, BASE)104def endpoint_load_test_payload(directory, endpoint, test_name):105    """Load expected payload for specified endpoint and test"""106    with open(directory) as stream:107        data = json.load(stream)108        test_data = data[endpoint]109        payload = parse.build_test_case(test_data, test_name)["payload"]110        return payload111def endpoint_load_base_status_codes(directory, endpoint):112    """Load base status_code from endpoint"""113    return endpoint_load_test_status_codes(directory, endpoint, BASE)114def endpoint_load_test_status_codes(directory, endpoint, test_name):115    """Load expected status code for specified endpoint and test"""116    with open(directory) as stream:117        data = json.load(stream)118        test_data = data[endpoint]119        status_codes = parse.build_test_case(test_data, test_name)["status_code"]120        return status_codes121def endpoint_load_base_response(directory, endpoint):122    """Load base response from endpoint"""123    return endpoint_load_test_response(directory, endpoint, BASE)124def endpoint_load_test_response(directory, endpoint, test_name):125    """Load expected response for specified endpoint and test"""126    with open(directory) as stream:127        data = json.load(stream)128        test_data = data[endpoint]129        response = parse.build_test_case(test_data, test_name)["response"]130        return response131###################################################################################################132# JSON Utilites133###################################################################################################134def load_response_data(response):135    """Return the data of the response body"""136    try:137        response_data = json.loads(response.text)138    except json.decoder.JSONDecodeError:139        response_data = {}...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.