Python tarfile.open方法代碼示例

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def convert_image(inpath, outpath, size):
    """Convert an image file using ``sips``.

    Args:
        inpath (str): Path of source file.
        outpath (str): Path to destination file.
        size (int): Width and height of destination image in pixels.

    Raises:
        RuntimeError: Raised if ``sips`` exits with non-zero status.
    """
    cmd = [
        b'sips',
        b'-z', str(size), str(size),
        inpath,
        b'--out', outpath]
    # log().debug(cmd)
    with open(os.devnull, 'w') as pipe:
        retcode = subprocess.call(cmd, stdout=pipe, stderr=subprocess.STDOUT)

    if retcode != 0:
        raise RuntimeError('sips exited with %d' % retcode) 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def detect_missing_tools(distro):
    tools_dir = os.path.join('data', 'tools')
    if platform.system() == 'Windows':
        _7zip_exe = gen.resource_path(
            os.path.join(tools_dir, '7zip', '7z.exe'))
        e2fsck_exe = gen.resource_path(os.path.join(tools_dir, 'cygwin', 'e2fsck.exe'))
        resize2fs_exe = gen.resource_path(os.path.join(tools_dir, 'cygwin', 'resize2fs.exe'))
    else:
        _7zip_exe = '7z'
        e2fsck_exe = 'e2fsck'
        resize2fs_exe = 'resize2fs'
    if distro not in creator_dict or \
       creator_dict[distro][0] is not create_persistence_using_resize2fs:
        return None
    try:
        with open(os.devnull) as devnull:
            for tool in [e2fsck_exe, resize2fs_exe]:
                p = subprocess.Popen([tool], stdout=devnull, stderr=devnull)
                p.communicate()
    except FileNotFoundError:  # Windows
        return "'%s.exe' is not installed or not available for use." % tool
    except OSError:            # Linux
        return "'%s' is not installed or not available for use." % tool
    return None 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def download_figshare(file_name, file_ext, dir_path='./', change_name = None):
    prepare_data_dir(dir_path)
    url = 'https://ndownloader.figshare.com/files/' + file_name
    wget.download(url, out=dir_path)
    file_path = os.path.join(dir_path, file_name)

    if file_ext == '.zip':
        zip_ref = zipfile.ZipFile(file_path,'r')
        if change_name is not None:
            dir_path = os.path.join(dir_path, change_name)
        zip_ref.extractall(dir_path)
        zip_ref.close()
        os.remove(file_path)
    elif file_ext == '.tar.bz2':
        tar_ref = tarfile.open(file_path,'r:bz2')
        if change_name is not None:
            dir_path = os.path.join(dir_path, change_name)
        tar_ref.extractall(dir_path)
        tar_ref.close()
        os.remove(file_path)
    elif change_name is not None:
        os.rename(file_path, os.path.join(dir_path, change_name))

# Download QM9 dataset 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def __init__(self, default_compression="gz", logfile=None, verbose=True):
        """
        Constructor

        @attention:

        @param default_compression: default compression used for files
        @type default_compression: str | unicode
        @param logfile: file handler or file path to a log file
        @type logfile: file | io.FileIO | StringIO.StringIO | basestring
        @param verbose: Not verbose means that only warnings and errors will be past to stream
        @type verbose: bool

        @return: None
        @rtype: None
        """
        assert logfile is None or isinstance(logfile, basestring) or self.is_stream(logfile)
        assert isinstance(default_compression, basestring), "separator must be string"
        assert isinstance(verbose, bool), "verbose must be true or false"
        assert default_compression.lower() in self._open, "Unknown compression: '{}'".format(default_compression)

        super(Archive, self).__init__(label="Archive", default_compression=default_compression, logfile=logfile, verbose=verbose)

        self._open['tar'] = tarfile.open
        self._default_compression = default_compression 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def write_payload(self):
        port = self._port
        tar_path = self.create_payload_tar()

        log.debug(port.read_until("/ # "))
        port.write("base64 -d | tar zxf -\n")
        port.flush()
        #(tarr, tarw) = os.pipe()
        #tar = tarfile.open(mode='w|gz', fileobj=tarw)
        #tar.add("payload/patch_toon.sh")

        log.info("Transferring payload")
        with open(tar_path, 'r') as f:
            base64.encode(f, port)

        os.remove(tar_path)

        port.flush()
        port.reset_input_buffer()
        port.write("\x04")
        port.flush() 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def get_caltech101_data():
    url = "https://s3.us-east-2.amazonaws.com/mxnet-public/101_ObjectCategories.tar.gz"
    dataset_name = "101_ObjectCategories"
    data_folder = "data"
    if not os.path.isdir(data_folder):
        os.makedirs(data_folder)
    tar_path = mx.gluon.utils.download(url, path=data_folder)
    if (not os.path.isdir(os.path.join(data_folder, "101_ObjectCategories")) or
        not os.path.isdir(os.path.join(data_folder, "101_ObjectCategories_test"))):
        tar = tarfile.open(tar_path, "r:gz")
        tar.extractall(data_folder)
        tar.close()
        print('Data extracted')
    training_path = os.path.join(data_folder, dataset_name)
    testing_path = os.path.join(data_folder, "{}_test".format(dataset_name))
    return training_path, testing_path 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def resolve(ctx):
    from PIL import Image
    if isinstance(ctx, list):
        ctx = [ctx[0]]
    net.load_parameters('superres.params', ctx=ctx)
    img = Image.open(opt.resolve_img).convert('YCbCr')
    y, cb, cr = img.split()
    data = mx.nd.expand_dims(mx.nd.expand_dims(mx.nd.array(y), axis=0), axis=0)
    out_img_y = mx.nd.reshape(net(data), shape=(-3, -2)).asnumpy()
    out_img_y = out_img_y.clip(0, 255)
    out_img_y = Image.fromarray(np.uint8(out_img_y[0]), mode='L')

    out_img_cb = cb.resize(out_img_y.size, Image.BICUBIC)
    out_img_cr = cr.resize(out_img_y.size, Image.BICUBIC)
    out_img = Image.merge('YCbCr', [out_img_y, out_img_cb, out_img_cr]).convert('RGB')

    out_img.save('resolved.png') 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def _get_data(self):
        if self._train:
            data, label = self._train_data, self._train_label
        else:
            data, label = self._test_data, self._test_label

        namespace = 'gluon/dataset/'+self._namespace
        data_file = download(_get_repo_file_url(namespace, data[0]),
                             path=self._root,
                             sha1_hash=data[1])
        label_file = download(_get_repo_file_url(namespace, label[0]),
                              path=self._root,
                              sha1_hash=label[1])

        with gzip.open(label_file, 'rb') as fin:
            struct.unpack(">II", fin.read(8))
            label = np.frombuffer(fin.read(), dtype=np.uint8).astype(np.int32)

        with gzip.open(data_file, 'rb') as fin:
            struct.unpack(">IIII", fin.read(16))
            data = np.frombuffer(fin.read(), dtype=np.uint8)
            data = data.reshape(len(label), 28, 28, 1)

        self._data = nd.array(data, dtype=data.dtype)
        self._label = label 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def test_image_detiter(self):
        im_list = [_generate_objects() + [x] for x in TestImage.IMAGES]
        det_iter = mx.image.ImageDetIter(2, (3, 300, 300), imglist=im_list, path_root='')
        for _ in range(3):
            for batch in det_iter:
                pass
            det_iter.reset()

        val_iter = mx.image.ImageDetIter(2, (3, 300, 300), imglist=im_list, path_root='')
        det_iter = val_iter.sync_label_shape(det_iter)

        # test file list
        fname = './data/test_imagedetiter.lst'
        im_list = [[k] + _generate_objects() + [x] for k, x in enumerate(TestImage.IMAGES)]
        with open(fname, 'w') as f:
            for line in im_list:
                line = '\t'.join([str(k) for k in line])
                f.write(line + '\n')

        det_iter = mx.image.ImageDetIter(2, (3, 400, 400), path_imglist=fname,
            path_root='')
        for batch in det_iter:
            pass 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def _download_and_uncompress_dataset(dataset_dir):
  """Downloads cifar10 and uncompresses it locally.

  Args:
    dataset_dir: The directory where the temporary files are stored.
  """
  filename = _DATA_URL.split('/')[-1]
  filepath = os.path.join(dataset_dir, filename)

  if not os.path.exists(filepath):
    def _progress(count, block_size, total_size):
      sys.stdout.write('\r>> Downloading %s %.1f%%' % (
          filename, float(count * block_size) / float(total_size) * 100.0))
      sys.stdout.flush()
    filepath, _ = urllib.request.urlretrieve(_DATA_URL, filepath, _progress)
    print()
    statinfo = os.stat(filepath)
    print('Successfully downloaded', filename, statinfo.st_size, 'bytes.')
    tarfile.open(filepath, 'r:gz').extractall(dataset_dir) 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def download_and_uncompress_tarball(tarball_url, dataset_dir):
  """Downloads the `tarball_url` and uncompresses it locally.

  Args:
    tarball_url: The URL of a tarball file.
    dataset_dir: The directory where the temporary files are stored.
  """
  filename = tarball_url.split('/')[-1]
  filepath = os.path.join(dataset_dir, filename)

  def _progress(count, block_size, total_size):
    sys.stdout.write('\r>> Downloading %s %.1f%%' % (
        filename, float(count * block_size) / float(total_size) * 100.0))
    sys.stdout.flush()
  filepath, _ = urllib.request.urlretrieve(tarball_url, filepath, _progress)
  print()
  statinfo = os.stat(filepath)
  print('Successfully downloaded', filename, statinfo.st_size, 'bytes.')
  tarfile.open(filepath, 'r:gz').extractall(dataset_dir) 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def maybe_download_and_extract():
  """Download and extract the tarball from Alex's website."""
  dest_directory = FLAGS.data_dir
  if not os.path.exists(dest_directory):
    os.makedirs(dest_directory)
  filename = DATA_URL.split('/')[-1]
  filepath = os.path.join(dest_directory, filename)
  if not os.path.exists(filepath):
    def _progress(count, block_size, total_size):
      sys.stdout.write('\r>> Downloading %s %.1f%%' % (filename,
          float(count * block_size) / float(total_size) * 100.0))
      sys.stdout.flush()
    filepath, _ = urllib.request.urlretrieve(DATA_URL, filepath, _progress)
    print()
    statinfo = os.stat(filepath)
    print('Successfully downloaded', filename, statinfo.st_size, 'bytes.')
  extracted_dir_path = os.path.join(dest_directory, 'cifar-10-batches-bin')
  if not os.path.exists(extracted_dir_path):
    tarfile.open(filepath, 'r:gz').extractall(dest_directory) 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def extract_mnist_data(filename, num_images, image_size, pixel_depth):
  """
  Extract the images into a 4D tensor [image index, y, x, channels].

  Values are rescaled from [0, 255] down to [-0.5, 0.5].
  """
  # if not os.path.exists(file):
  if not tf.gfile.Exists(filename+".npy"):
    with gzip.open(filename) as bytestream:
      bytestream.read(16)
      buf = bytestream.read(image_size * image_size * num_images)
      data = np.frombuffer(buf, dtype=np.uint8).astype(np.float32)
      data = (data - (pixel_depth / 2.0)) / pixel_depth
      data = data.reshape(num_images, image_size, image_size, 1)
      np.save(filename, data)
      return data
  else:
    with tf.gfile.Open(filename+".npy", mode='r') as file_obj:
      return np.load(file_obj) 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def get_wmt_enfr_dev_set(directory):
  """Download the WMT en-fr training corpus to directory unless it's there."""
  dev_name = "newstest2013"
  dev_path = os.path.join(directory, dev_name)
  if not (tf.gfile.Exists(dev_path + ".fr") and
          tf.gfile.Exists(dev_path + ".en")):
    dev_file = maybe_download(directory, "dev-v2.tgz", _WMT_ENFR_DEV_URL)
    print "Extracting tgz file %s" % dev_file
    with tarfile.open(dev_file, "r:gz") as dev_tar:
      fr_dev_file = dev_tar.getmember("dev/" + dev_name + ".fr")
      en_dev_file = dev_tar.getmember("dev/" + dev_name + ".en")
      fr_dev_file.name = dev_name + ".fr"  # Extract without "dev/" prefix.
      en_dev_file.name = dev_name + ".en"
      dev_tar.extract(fr_dev_file, directory)
      dev_tar.extract(en_dev_file, directory)
  return dev_path 

# 需要導入模塊: import tarfile [as 別名]
# 或者: from tarfile import open [as 別名]
def create(ctx):
    """
    Install a chute from the working directory.
    """
    url = "{}/chutes/".format(ctx.obj['base_url'])
    headers = {'Content-Type': 'application/x-tar'}

    if not os.path.exists("paradrop.yaml"):
        raise Exception("No paradrop.yaml file found in working directory.")

    with tempfile.TemporaryFile() as temp:
        tar = tarfile.open(fileobj=temp, mode="w")
        for dirName, subdirList, fileList in os.walk('.'):
            for fname in fileList:
                path = os.path.join(dirName, fname)
                arcname = os.path.normpath(path)
                tar.add(path, arcname=arcname)
        tar.close()

        temp.seek(0)
        res = router_request("POST", url, headers=headers, data=temp)
        data = res.json()
        ctx.invoke(watch, change_id=data['change_id'])