Python pkg_resources.resource_filename方法代碼示例

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def _test_validate(self, schema, expect_failure, input_files, input):
        """validates input yaml against schema.

        :param schema: schema yaml file
        :param expect_failure: should the validation pass or fail.
        :param input_files: pytest fixture used to access the test input files
        :param input: test input yaml doc filename"""
        schema_dir = pkg_resources.resource_filename('drydock_provisioner',
                                                     'schemas')
        schema_filename = os.path.join(schema_dir, schema)
        schema_file = open(schema_filename, 'r')
        schema = yaml.safe_load(schema_file)

        input_file = input_files.join(input)
        instance_file = open(str(input_file), 'r')
        instance = yaml.safe_load(instance_file)

        if expect_failure:
            with pytest.raises(ValidationError):
                jsonschema.validate(instance['spec'], schema['data'])
        else:
            jsonschema.validate(instance['spec'], schema['data']) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def setUp(self):
    file_path = resource_filename(Requirement.parse('google_streetview'), 'google_streetview/config.json')
    with open(file_path, 'r') as in_file:
      defaults = json.load(in_file)
    params = [{
      'size': '600x300', # max 640x640 pixels
      'location': '46.414382,10.013988',
      'heading': '151.78',
      'pitch': '-0.76',
      'key': defaults['key']
    }]
    self.results = google_streetview.api.results(params)
    tempfile = TemporaryFile()
    self.tempfile = str(tempfile.name)
    tempfile.close()
    self.tempdir = str(TemporaryDirectory().name) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def validate(ctx):
    """
    Validate the paradrop.yaml file.

    A note about versions: this command validates the chute configuration
    against the current rules for the installed version of pdtools. If
    the chute is to be installed on a Paradrop node running a different
    version, then this command may not be reliable for determining
    compatibility.
    """
    with open('paradrop.yaml', 'r') as source:
        chute = yaml.safe_load(source)

    schema_path = pkg_resources.resource_filename('pdtools', 'schemas/chute.json')
    with open(schema_path, 'r') as source:
        schema = json.load(source)

    validator = jsonschema.Draft4Validator(schema)
    for error in sorted(validator.iter_errors(chute), key=str):
        click.echo(error.message) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def test_identifier_extract_unusual(self):
        answers = [
            '\'"\'',
            '\'\"\'',
            "\'\"\'",
            "\n",
            "\t",
            r'\\ ',
            "\u3042",
            "\u3042",
            "    ",
        ]
        with open(resource_filename('calmjs.testing', join(
                'names', 'unusual.js')), encoding='utf-8') as fd:
            tree = es5(fd.read())
        for obj_node, answer in zip(interrogate.shallow_filter(
                tree, lambda node: isinstance(node, Object)), answers):
            self.assertEqual(answer, interrogate.to_identifier(
                obj_node.properties[0].left)) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def load_app(conf, not_implemented_middleware=True):
    global APPCONFIGS

    # Build the WSGI app
    cfg_path = conf.api.paste_config
    if not os.path.isabs(cfg_path):
        cfg_path = conf.find_file(cfg_path)

    if cfg_path is None or not os.path.exists(cfg_path):
        LOG.debug("No api-paste configuration file found! Using default.")
        cfg_path = os.path.abspath(pkg_resources.resource_filename(
            __name__, "api-paste.ini"))

    config = dict(conf=conf,
                  not_implemented_middleware=not_implemented_middleware)
    configkey = str(uuid.uuid4())
    APPCONFIGS[configkey] = config

    LOG.info("WSGI config used: %s", cfg_path)

    appname = "gnocchi+" + conf.api.auth_mode
    app = deploy.loadapp("config:" + cfg_path, name=appname,
                         global_conf={'configkey': configkey})
    return http_proxy_to_wsgi.HTTPProxyToWSGI(
        cors.CORS(app, conf=conf), conf=conf) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def __init__(self, benign_path=None, malicious_path=None,
                 model_path=pkg_resources.resource_filename('mmbot', 'model'), retain_sample_contents=False):
        """
        Constructor to setup path variables for model and sample data and initialize object.
        :param benign_path: directory path (relative or absolute) to benign documents for the machine learning model to learn from.
        :param malicious_path: directory path (relative or absolute) to malicious documents for the machine learning model to learn from.
        :param model_path: directory where modeldata.pickle and vocab.txt files are kept.
        :param retain_sample_contents: this relates to level of detail saved in the model data.  If True, potentially sensitive
        information like extracted vba will be stored in the model's pickle file.  The benefit is that incremental
        models can be built, where adding a new file to the training set will result in only reprocessing that one new
        file.  Otherwise all files in the benign_path and malicious_path will be reprocessed each time the model is
        rebuilt.  If you are experimenting with building many models and comparing results, set this to True,
        otherwise keep it to False.
        """
        # os.path.join(os.path.dirname(__file__), 'model')
        self.clear_state()
        self.set_model_paths(benign_path, malicious_path, model_path)
        self.retain_sample_contents = retain_sample_contents 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def load_services(services):
    for service in services:
        service_plugins[service] = {}

        service_config = cf.config('config:' + service)
        if service_config is None:
            logger.error("Service `%s' has no config section" % service)
            sys.exit(1)

        service_plugins[service]['config'] = service_config

        module = cf.g('config:' + service, 'module', service)
        modulefile = resource_filename('mqttwarn.services', module + '.py')

        try:
            service_plugins[service]['module'] = load_module(modulefile)
            logger.info('Successfully loaded service "{}"'.format(service))
        except Exception as ex:
            logger.exception('Unable to load service "{}" from file "{}": {}'.format(service, modulefile, ex)) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def run_pearl_bash(
        script: str, pearl_env,
        capture_stdout: bool = False, capture_stderr: bool = False,
        check: bool = True,
        input: str = None,
        enable_xtrace: bool = False,
        enable_errexit: bool = True,
):
    """Runs a bash script within the Pearl ecosystem."""

    bash_header = _BASH_SCRIPT_HEADER_TEMPLATE.format(
        pearlhome=pearl_env.home,
        static=pkg_resources.resource_filename('pearllib', 'static/'),
    )
    script_template = '{bashheader}\nset -x\n{script}' if enable_xtrace else '{bashheader}\n{script}'
    if enable_errexit:
        script_template = 'set -e\n{}'.format(script_template)

    script = script_template.format(
        bashheader=bash_header,
        script=script,
    )
    return run_bash(script, capture_stdout=capture_stdout, capture_stderr=capture_stderr, check=check, input=input) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def create_package(pearl_env: PearlEnvironment, args: Namespace):
    """
    Creates package from template.
    """
    static = Path(pkg_resources.resource_filename('pearllib', 'static/'))
    pearl_config_template = static / 'templates/pearl-config.template'
    dest_pearl_config = args.dest_dir / 'pearl-config'
    if dest_pearl_config.exists():
        raise PackageCreateError('The pearl-config directory already exists in {}'.format(args.dest_dir))
    shutil.copytree(str(pearl_config_template), str(dest_pearl_config))

    messenger.info('Updating {} to add package in local repository...'.format(pearl_env.config_filename))
    with pearl_env.config_filename.open('a') as pearl_conf_file:
        pearl_conf_file.write('PEARL_PACKAGES["{}"] = {{"url": "{}"}}\n'.format(args.name, args.dest_dir))

    messenger.info('Run "pearl search local" to see your new local package available') 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def git_changed_submodules(git_rev='HEAD@{1}', stop_rev=None, git_root='.'):
    if stop_rev is not None:
        git_rev = "{0}..{1}".format(git_rev, stop_rev)
    diff_script = pkg_resources.resource_filename('conda_concourse_ci', 'diff-script.sh')

    diff = subprocess.check_output(['bash', diff_script, git_rev],
                                    cwd=git_root, universal_newlines=True)

    submodule_changed_files = [line.split() for line in diff.splitlines()]

    submodules_with_recipe_changes = []
    for submodule in submodule_changed_files:
        for file in submodule:
            if 'recipe/' in file and submodule[0] not in submodules_with_recipe_changes:
                submodules_with_recipe_changes.append(submodule[0])

    return submodules_with_recipe_changes 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def test_pydist():
    """Make sure pydist.json exists and validates against our schema."""
    # XXX this test may need manual cleanup of older wheels

    import jsonschema

    def open_json(filename):
        return json.loads(open(filename, 'rb').read().decode('utf-8'))

    pymeta_schema = open_json(resource_filename('wheel.test',
                                                'pydist-schema.json'))
    valid = 0
    for dist in ("simple.dist", "complex-dist"):
        basedir = pkg_resources.resource_filename('wheel.test', dist)
        for (dirname, subdirs, filenames) in os.walk(basedir):
            for filename in filenames:
                if filename.endswith('.whl'):
                    whl = ZipFile(os.path.join(dirname, filename))
                    for entry in whl.infolist():
                        if entry.filename.endswith('/metadata.json'):
                            pymeta = json.loads(whl.read(entry).decode('utf-8'))
                            jsonschema.validate(pymeta, pymeta_schema)
                            valid += 1
    assert valid > 0, "No metadata.json found" 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def get_outputnode_spec():
    """
    Generate outputnode's fields from I/O spec file.

    Examples
    --------
    >>> get_outputnode_spec()  # doctest: +NORMALIZE_WHITESPACE
    ['t1w_preproc', 't1w_mask', 't1w_dseg', 't1w_tpms',
    'std_preproc', 'std_mask', 'std_dseg', 'std_tpms',
    'anat2std_xfm', 'std2anat_xfm',
    't1w_aseg', 't1w_aparc',
    't1w2fsnative_xfm', 'fsnative2t1w_xfm',
    'surfaces']

    """
    spec = loads(Path(pkgrf('smriprep', 'data/io_spec.json')).read_text())["queries"]
    fields = ['_'.join((m, s)) for m in ('t1w', 'std') for s in spec["baseline"].keys()]
    fields += [s for s in spec["std_xfms"].keys()]
    fields += [s for s in spec["surfaces"].keys()]
    return fields 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def frost(x, severity=1):
    c = [(1, 0.4),
         (0.8, 0.6),
         (0.7, 0.7),
         (0.65, 0.7),
         (0.6, 0.75)][severity - 1]
    idx = np.random.randint(5)
    filename = [resource_filename(__name__, 'frost/frost1.png'),
                resource_filename(__name__, 'frost/frost2.png'),
                resource_filename(__name__, 'frost/frost3.png'),
                resource_filename(__name__, 'frost/frost4.jpg'),
                resource_filename(__name__, 'frost/frost5.jpg'),
                resource_filename(__name__, 'frost/frost6.jpg')][idx]
    frost = cv2.imread(filename)
    # randomly crop and convert to rgb
    x_start, y_start = np.random.randint(0, frost.shape[0] - 224), np.random.randint(0, frost.shape[1] - 224)
    frost = frost[x_start:x_start + 224, y_start:y_start + 224][..., [2, 1, 0]]

    return np.clip(c[0] * np.array(x) + c[1] * frost, 0, 255) 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def _get_schema_dir(self):
        return pkg_resources.resource_filename('drydock_provisioner',
                                               'schemas')

    # Mapping of handlers for different document kinds 

# 需要導入模塊: import pkg_resources [as 別名]
# 或者: from pkg_resources import resource_filename [as 別名]
def __init__(self):
        self.__default_gen_file = resource_filename("cisco.bass.avclass", 'default.generics')
        self.__default_alias_file = resource_filename("cisco.bass.avclass", 'default.aliases')
        self.__default_category_file = resource_filename("cisco.bass.avclass", 'default.categories')