Python tempfile.NamedTemporaryFile方法代碼示例

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def test_full_tokenizer(self):
        vocab_tokens = [
            "[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn",
            "##ing", ","
        ]
        with tempfile.NamedTemporaryFile(delete=False) as vocab_writer:
            vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))

            vocab_file = vocab_writer.name

        tokenizer = tokenization.FullTokenizer(vocab_file)
        os.unlink(vocab_file)

        tokens = tokenizer.tokenize(u"UNwant\u00E9d,running")
        self.assertAllEqual(tokens, ["un", "##want", "##ed", ",", "runn", "##ing"])

        self.assertAllEqual(
            tokenizer.convert_tokens_to_ids(tokens), [7, 4, 5, 10, 8, 9]) 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def isUpdatesAvailable(cls, path):
        if sys.version_info < (3, 0):
            return False
        # pylint: disable=broad-except
        if not os.path.isfile(os.path.join(path, "files.xml")):
            return True
        try:
            available = dict()
            for it in ET.parse(os.path.join(path, "files.xml")).iter():
                if it.tag == "File":
                    available[it.text] = datetime.datetime.strptime(it.attrib["Modified"], "%d-%m-%Y")

            path = NamedTemporaryFile()
            path.close()
            urllib.request.urlretrieve("https://www.gurux.fi/obis/files.xml", path.name)
            for it in ET.parse(path.name).iter():
                if it.tag == "File":
                    tmp = datetime.datetime.strptime(it.attrib["Modified"], "%d-%m-%Y")
                    if not it.text in available or available[it.text] != tmp:
                        return True
        except Exception as e:
            print(e)
            return True
        return False 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def convert(netflow, tmpdir, opts='', prefix=None):
    '''
        Convert `nfcapd` file to a comma-separated output format.

    :param netflow : Path of binary file.
    :param tmpdir  : Path of local staging area.
    :param opts    : A set of options for `nfdump` command.
    :param prefix  : If `prefix` is specified, the file name will begin with that;
                     otherwise, a default `prefix` is used.
    :returns       : Path of CSV-converted file.
    :rtype         : ``str``
    :raises OSError: If an error occurs while executing the `nfdump` command.
    '''
    logger = logging.getLogger('SPOT.INGEST.FLOW.PROCESS')

    with tempfile.NamedTemporaryFile(prefix=prefix, dir=tmpdir, delete=False) as fp:
        command = COMMAND.format(netflow, opts, fp.name)

        logger.debug('Execute command: {0}'.format(command))
        Util.popen(command, raises=True)

        return fp.name 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def convert(logfile, tmpdir, opts='', prefix=None):
    '''
        Copy log file to the local staging area.

    :param logfile: Path of log file.
    :param tmpdir : Path of local staging area.
    :param opts   : A set of options for the `cp` command.
    :param prefix : If `prefix` is specified, the file name will begin with that;
                     otherwise, a default `prefix` is used.
    :returns      : Path of log file in local staging area.
    :rtype        : ``str``
    '''
    logger = logging.getLogger('SPOT.INGEST.PROXY.PROCESS')

    with tempfile.NamedTemporaryFile(prefix=prefix, dir=tmpdir, delete=False) as fp:
        command = COMMAND.format(opts, logfile, fp.name)

        logger.debug('Execute command: {0}'.format(command))
        Util.popen(command, raises=True)

        return fp.name 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def convert(pcap, tmpdir, opts='', prefix=None):
    '''
        Convert `pcap` file to a comma-separated output format.

    :param pcap    : Path of binary file.
    :param tmpdir  : Path of local staging area.
    :param opts    : A set of options for `tshark` command.
    :param prefix  : If `prefix` is specified, the file name will begin with that;
                     otherwise, a default `prefix` is used.
    :returns       : Path of CSV-converted file.
    :rtype         : ``str``
    :raises OSError: If an error occurs while executing the `tshark` command.
    '''
    logger = logging.getLogger('SPOT.INGEST.DNS.PROCESS')

    with tempfile.NamedTemporaryFile(prefix=prefix, dir=tmpdir, delete=False) as fp:
        command = COMMAND.format(pcap, opts, fp.name)

        logger.debug('Execute command: {0}'.format(command))
        Util.popen(command, raises=True)

        return fp.name 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def parse_config(config_strings):
    temp_file = tempfile.NamedTemporaryFile()
    config_path = f'{temp_file.name}.py'
    with open(config_path, 'w') as f:
        f.write(config_strings)

    config = Config.fromfile(config_path)
    is_two_stage = True
    is_ssd = False
    is_retina = False
    reg_cls_agnostic = False
    if 'rpn_head' not in config.model:
        is_two_stage = False
        # check whether it is SSD
        if config.model.bbox_head.type == 'SSDHead':
            is_ssd = True
        elif config.model.bbox_head.type == 'RetinaHead':
            is_retina = True
    elif isinstance(config.model['bbox_head'], list):
        reg_cls_agnostic = True
    elif 'reg_class_agnostic' in config.model.bbox_head:
        reg_cls_agnostic = config.model.bbox_head \
            .reg_class_agnostic
    temp_file.close()
    return is_two_stage, is_ssd, is_retina, reg_cls_agnostic 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def predict_on_batch(self, inputs):
        # write test fasta file
        temp_input = tempfile.NamedTemporaryFile(suffix = ".txt")
        test_fname = temp_input.name
        encode_sequence_into_fasta_file(ofname = test_fname, seq = inputs.tolist())
        # test gkmsvm
        temp_ofp = tempfile.NamedTemporaryFile(suffix = ".txt")
        threads_option = '-T %s' % (str(self.threads))
        verbosity_option = '-v 0'
        command = ' '.join(['gkmpredict',
                            test_fname,
                            self.model_file,
                            temp_ofp.name,
                            threads_option,
                            verbosity_option])
        #process = subprocess.Popen(command, shell=True)
        #process.wait()  # wait for it to finish
        exit_code = os.system(command)
        temp_input.close()
        assert exit_code == 0
        # get classification results
        temp_ofp.seek(0)
        y = np.array([line.split()[-1] for line in temp_ofp], dtype=float)
        temp_ofp.close()
        return np.expand_dims(y, 1) 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def save_pyoptix_conf(nvcc_path, compile_args, include_dirs, library_dirs, libraries):
    try:
        config = ConfigParser()
        config.add_section('pyoptix')

        config.set('pyoptix', 'nvcc_path', nvcc_path)
        config.set('pyoptix', 'compile_args', os.pathsep.join(compile_args))
        config.set('pyoptix', 'include_dirs', os.pathsep.join(include_dirs))
        config.set('pyoptix', 'library_dirs', os.pathsep.join(library_dirs))
        config.set('pyoptix', 'libraries', os.pathsep.join(libraries))

        tmp = NamedTemporaryFile(mode='w+', delete=False)
        config.write(tmp)
        tmp.close()
        config_path = os.path.join(os.path.dirname(sys.executable), 'pyoptix.conf')
        check_call_sudo_if_fails(['cp', tmp.name, config_path])
        check_call_sudo_if_fails(['cp', tmp.name, '/etc/pyoptix.conf'])
        check_call_sudo_if_fails(['chmod', '644', config_path])
        check_call_sudo_if_fails(['chmod', '644', '/etc/pyoptix.conf'])
    except Exception as e:
        print("PyOptiX configuration could not be saved. When you use pyoptix.Compiler, "
              "nvcc path must be in PATH, OptiX library paths must be in LD_LIBRARY_PATH, and pyoptix.Compiler "
              "attributes should be set manually.") 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def test_prepareHostConfig(settings, detectSystemDevices):
    """
    Test paradrop.core.config.hostconfig.prepareHostConfig
    """
    from paradrop.core.config.hostconfig import prepareHostConfig

    devices = {
        'wan': [{'name': 'eth0'}],
        'lan': list(),
        'wifi': list()
    }
    detectSystemDevices.return_value = devices

    source = tempfile.NamedTemporaryFile(delete=True)
    source.write("{test: value}")
    source.flush()

    settings.HOST_CONFIG_FILE = source.name
    settings.DEFAULT_LAN_ADDRESS = "1.2.3.4"
    settings.DEFAULT_LAN_NETWORK = "1.0.0.0/24"

    config = prepareHostConfig()
    assert config['test'] == 'value' 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def DownloadFileTemp(self, url, max_retries=5, show_progress=False):
    """Downloads a file to temporary storage.

    Args:
      url:  The address of the file to be downloaded.
      max_retries:  The number of times to attempt to download
        a file if the first attempt fails.
      show_progress: Print download progress to stdout (overrides default).

    Returns:
      A string containing a path to the temporary file.
    """
    destination = tempfile.NamedTemporaryFile()
    self._save_location = destination.name
    destination.close()
    if self._beyondcorp.CheckBeyondCorp():
      url = self._SetUrl(url)
      max_retries = -1
    file_stream = self._OpenStream(url, max_retries)
    self._StreamToDisk(file_stream, show_progress)
    return self._save_location 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def test_csv():
    expected = '\n'.join([
        'source_context, test_context',
        'smother/tests/demo.py:11,test2',
        'smother/tests/demo.py:4,test4',
        '',
    ])

    runner = CliRunner()

    with NamedTemporaryFile(mode='w+') as tf:
        result = runner.invoke(
            cli,
            ['-r', 'smother/tests/.smother_2',
             'csv',
             tf.name
             ]
        )
        assert result.exit_code == 0
        tf.seek(0)
        assert tf.read() == expected 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def test_semantic_csv():
    expected = '\n'.join([
        'source_context, test_context',
        'smother.tests.demo,test4',
        'smother.tests.demo:bar,test2',
        '',
    ])

    runner = CliRunner()

    with NamedTemporaryFile(mode='w+') as tf:
        result = runner.invoke(
            cli,
            ['-r', 'smother/tests/.smother_2',
             '--semantic',
             'csv',
             tf.name
             ]
        )
        assert result.exit_code == 0
        tf.seek(0)
        assert tf.read() == expected 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def translate_files_slurm(args, cmds, expected_output_files):
    conda_env = '/private/home/pipibjc/.conda/envs/fairseq-20190509'
    for cmd in cmds:
        with TempFile('w') as script:
            sh = f"""#!/bin/bash
            source activate {conda_env}
            {cmd}
            """
            print(sh)
            script.write(sh)
            script.flush()
            cmd = f"sbatch --gres=gpu:1 -c {args.cpu + 2} {args.sbatch_args} --time=15:0:0 {script.name}"
            import sys
            print(cmd, file=sys.stderr)
            check_call(cmd, shell=True)

    # wait for all outputs has finished
    num_finished = 0
    while num_finished < len(expected_output_files):
        num_finished = 0
        for output_file in expected_output_files:
            num_finished += 1 if check_finished(output_file) else 0
        if num_finished < len(expected_output_files):
            time.sleep(3 * 60)
            print("sleeping for 3m ...") 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def gatys(content, style, outfile, size, weight, stylescale, algparams):
    """Runs Gatys et al style-transfer algorithm

    References:
        * https://arxiv.org/abs/1508.06576
        * https://github.com/jcjohnson/neural-style
    """
    # Gatys can only process one combination of content, style, weight and scale at a time, so we need to iterate
    tmpout = NamedTemporaryFile(suffix=".png")
    runalgorithm("gatys", [
        "-content_image", content,
        "-style_image", style,
        "-style_weight", weight * 100,  # Because content weight is 100
        "-style_scale", stylescale,
        "-output_image", tmpout.name,
        "-image_size", size if size is not None else shape(content)[0],
        *algparams
    ])
    # Transform to original file format
    convert(tmpout.name, outfile)
    tmpout.close() 

# 需要導入模塊: import tempfile [as 別名]
# 或者: from tempfile import NamedTemporaryFile [as 別名]
def __on_apply(self, *__):
        from ...models import BackupJSON
        try:
            paraphrase = self.paraphrase_widget.entry.get_text()
            if not paraphrase:
                paraphrase = " "
            output_file = path.join(GLib.get_user_cache_dir(),
                                    path.basename(NamedTemporaryFile().name))
            status = GPG.get_default().decrypt_json(self._filename, paraphrase, output_file)
            if status.ok:
                BackupJSON.import_file(output_file)
                self.destroy()
            else:
                self.__send_notification(_("There was an error during the import of the encrypted file."))

        except AttributeError:
            Logger.error("[GPG] Invalid JSON file.")