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How to use run_strict method in responses

Best Python code snippet using responses

runner.py

Source:runner.py

...64    def run_simulation(self):65        return run_simulation(self.dst_root, popen=False)66    def parse_out(self):67        return parse_out(self.dst_root)68    def run_strict(self, data_map:dict):69        # If efdc_node_list or qser_node_list takes None, the value will not be changed.70        self.write(data_map)71        shell_output = self.run_simulation().decode()72        self.shell_output_list.append(shell_output)73        self.check_shell_output(shell_output)74        return self.parse_out()75    76    def run(self, data_map:dict):77        data_map_filled = data_map_fill(data_map)78        return self.run_strict(data_map_filled)79    def cleanup(self):80        # user may want to keep those files81        rmtree(self.dst_root)82        logging.debug(f"cleanup {self.dst_root}")83    def check_shell_output(self, shell_output:str):84        # TODO: do some check to raise error as early as possible85        # The parsing will fail if model itself failed to complete.86        self.shell_output_parsed_list.append(parse_shell_output(shell_output))87    def __repr__(self):88        return f"Ruuner(src_root={self.src_root}, dst_root={self.dst_root})"89    def debug(self):90        if len(self.shell_output_list) == 0:91            print("No shell output is catched")92        else:93            if len(self.shell_output_list) > 1:94                print("The size of collected shell output size > 1, show last shell output")95            print(self.shell_output_list[-1])96class RunnerInplace(Runner):97    """98    For one who don't want environment isolation (not recommended).99    """100    def __init__(self, src_root):101        self.src_root = Path(src_root)102        self.dst_root = self.src_root103        # create_simulation(src_root, dst_root)104def work(process_args: dict):105    root:str = process_args["root"]106    data_map:dict = process_args["data_map"]107    dst_root = process_args["dst_root"]108    debug_list = process_args["debug_list"]109    idx:int = process_args["idx"]110    runner = Runner(root, dst_root)111    if debug_list is not None:112        debug_list[idx] = runner113    out = runner.run_strict(data_map)114    if debug_list is None:115        runner.cleanup()        116    117    return out118def run_batch(root, data_map_list, pool_size=0, debug_list=None, dst_root_list=None, sequential=False):119    """120    sequential argument is used to control parallel related factor to help debugging121    """122    data_map_list = [x if isinstance(x, dict) else x.data_map for x in data_map_list]123    if pool_size == 0:124        pool_size = get_default_pool_size()125    if dst_root_list is None:126        dst_root_list = [None for _ in data_map_list]127    if debug_list is not None:128        assert len(debug_list) == 0, "debug_list is not None or empty list, maybe mistakenly use a previous list?"129        debug_list.extend([None for _ in data_map_list])130    process_args_list = []131    for idx, (data_map, dst_root) in enumerate(zip(data_map_list, dst_root_list)):132        process_args = {"root":root, "data_map": data_map, "debug_list": debug_list, "dst_root": dst_root, "idx": idx} 133        process_args_list.append(process_args)134    135    if not sequential:136        pool = Pool(pool_size)137        return pool.map(work, process_args_list)138    else:139        return [work(process_arg) for process_arg in process_args_list]140def work_restart(process_args: dict):141    # TODO: An valuable altnative implementation is to just rename three files rather than symbolic link142    runner: Runner = process_args["runner"]143    data_map:dict = process_args["data_map"]144    out = runner.run_strict(data_map)145    return out146def copy_restart_files(src, dst=None):147    src = Path(src)148    dst = Path(dst) if dst is not None else src149    out_to_inp = {150        "RESTART.OUT": "RESTART.INP",151        "TEMPBRST.OUT": "TEMPB.RST",152        "WQWCRST.OUT": "wqini.inp"153    }154    for out_s, inp_s in out_to_inp.items():155        src_p = src / out_s156        dst_p = dst / inp_s157        if dst_p.exists():158            dst_p.unlink()...

test.py

Source:test.py

...121    def run_compare(self, entity, extractor):122        Compare.extractor = extractor123        Compare.run_ann(self, entity)124        Compare.run_out(self, entity, extractor)125        Compare.run_strict(self)126        Compare.run_loose(self)127        Compare.write_to_file(self)128    def run_strict(self): #strict is based on matching start and end span129        if Compare.asspan is not None and Compare.psspan is not None:130            if Compare.asspan == Compare.psspan and Compare.aespan == Compare.pespan:131                Compare.scval = "TP"132            else:133                Compare.scval = "FP"134        elif Compare.asspan is not None:135            Compare.scval = "FN"136        elif Compare.psspan is not None:137            Compare.scval = "FP"138        else:139            Compare.scval = "TN"140    def run_loose(self): #loose is based on matching content string141        if Compare.avc is not None and Compare.pv is not None:142            if Compare.avc == Compare.pv:...

block_matrix.py

Source:block_matrix.py

...6from tqdm import tqdm7from numba import jit8from .socio_matrix import SocioMatrix9log = logging.getLogger()10def run_strict(metric):11    """decorator for metric functions.12    returns a np.nan in case of a RuntimeWarning13    """14    def new(i, j, m):15        with warnings.catch_warnings():16            warnings.simplefilter("error")17            try:18                return metric(i, j, m)19            except RuntimeWarning:20                log.error("Runtime Warning: i=%d, j=%d" % (i, j))21                return np.nan22    return new23@jit("double(int64, int64, float32[:, :])", nopython=True)24def euclidean_metric(i, j, m):...

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