Python TarFile.addfile方法代码示例

# 需要导入模块: from tarfile import TarFile [as 别名]
# 或者: from tarfile.TarFile import addfile [as 别名]
    def move_certs(self, paths):
        self.log.info("Staging internal ssl certs for %s", self._log_name)
        yield self.pull_image(self.move_certs_image)
        # create the volume
        volume_name = self.format_volume_name(self.certs_volume_name, self)
        # create volume passes even if it already exists
        self.log.info("Creating ssl volume %s for %s", volume_name, self._log_name)
        yield self.docker('create_volume', volume_name)

        # create a tar archive of the internal cert files
        # docker.put_archive takes a tarfile and a running container
        # and unpacks the archive into the container
        nb_paths = {}
        tar_buf = BytesIO()
        archive = TarFile(fileobj=tar_buf, mode='w')
        for key, hub_path in paths.items():
            fname = os.path.basename(hub_path)
            nb_paths[key] = '/certs/' + fname
            with open(hub_path, 'rb') as f:
                content = f.read()
            tarinfo = TarInfo(name=fname)
            tarinfo.size = len(content)
            tarinfo.mtime = os.stat(hub_path).st_mtime
            tarinfo.mode = 0o644
            archive.addfile(tarinfo, BytesIO(content))
        archive.close()
        tar_buf.seek(0)

        # run a container to stage the certs,
        # mounting the volume at /certs/
        host_config = self.client.create_host_config(
            binds={
                volume_name: {"bind": "/certs", "mode": "rw"},
            },
        )
        container = yield self.docker('create_container',
            self.move_certs_image,
            volumes=["/certs"],
            host_config=host_config,
        )

        container_id = container['Id']
        self.log.debug(
            "Container %s is creating ssl certs for %s",
            container_id[:12], self._log_name,
        )
        # start the container
        yield self.docker('start', container_id)
        # stage the archive to the container
        try:
            yield self.docker(
                'put_archive',
                container=container_id,
                path='/certs',
                data=tar_buf,
            )
        finally:
            yield self.docker('remove_container', container_id)
        return nb_paths

# 需要导入模块: from tarfile import TarFile [as 别名]
# 或者: from tarfile.TarFile import addfile [as 别名]
 def generate_tar(entries):
     tar_buf = BytesIO()
     tar_file = TarFile(mode="w", fileobj=tar_buf)
     for path, contents in entries.items():
         tar_info = TarInfo(name=path)
         tar_info.size = len(contents)
         tar_file.addfile(tar_info, fileobj=BytesIO(contents))
     return BytesIO(tar_buf.getvalue())

# 需要导入模块: from tarfile import TarFile [as 别名]
# 或者: from tarfile.TarFile import addfile [as 别名]
def replace_or_append_file_to_layer(file_to_replace: str,
                                    content_or_path: bytes,
                                    img: tarfile.TarFile):
    # Is content or path?
    if not os.path.exists(content_or_path):

        # Is a content
        t = tarfile.TarInfo(file_to_replace)
        t.size = len(content_or_path)
        img.addfile(t, io.BytesIO(content_or_path))

    else:
        # Is a path
        img.add(content_or_path, file_to_replace)

# 需要导入模块: from tarfile import TarFile [as 别名]
# 或者: from tarfile.TarFile import addfile [as 别名]
    def run(self, args, argv):
        # Create a temporary tarball with our whole build context and
        # dockerfile for the update
        tmp = tempfile.NamedTemporaryFile(suffix="dckr.tar.gz")
        tmp_tar = TarFile(fileobj=tmp, mode='w')

        # Add the executable to the tarball, using the current
        # configured binfmt_misc path. If we don't get a path then we
        # only need the support libraries copied
        ff, enabled = _check_binfmt_misc(args.executable)

        if not enabled:
            print("binfmt_misc not enabled, update disabled")
            return 1

        if ff:
            tmp_tar.add(args.executable, arcname=ff)

        # Add any associated libraries
        libs = _get_so_libs(args.executable)
        if libs:
            for l in libs:
                tmp_tar.add(os.path.realpath(l), arcname=l)

        # Create a Docker buildfile
        df = StringIO()
        df.write("FROM %s\n" % args.tag)
        df.write("ADD . /\n")
        df.seek(0)

        df_tar = TarInfo(name="Dockerfile")
        df_tar.size = len(df.buf)
        tmp_tar.addfile(df_tar, fileobj=df)

        tmp_tar.close()

        # reset the file pointers
        tmp.flush()
        tmp.seek(0)

        # Run the build with our tarball context
        dkr = Docker()
        dkr.update_image(args.tag, tmp, quiet=args.quiet)

        return 0

# 需要导入模块: from tarfile import TarFile [as 别名]
# 或者: from tarfile.TarFile import addfile [as 别名]
    def save_to_file(self, f):
        tar = TarFile(f, "w")

        # save info file
        f = StringIO(repr((self.agedesc, self.generation)))
        info = tar.gettarinfo(None, "info.py", f)
        tar.addfile(info, f)
        f.close()

        # save agents
        for i in range(len(self.agents)):
            f = StringIO()
            self.agents[i].save_to_file(f)
            info = tar.gettarinfo(None, str(i)+".agt", f)
            tar.addfile(info, f)
            f.close()

        tar.close()                

# 需要导入模块: from tarfile import TarFile [as 别名]
# 或者: from tarfile.TarFile import addfile [as 别名]
    def run(self, args, argv):
        # Create a temporary tarball with our whole build context and
        # dockerfile for the update
        tmp = tempfile.NamedTemporaryFile(suffix="dckr.tar.gz")
        tmp_tar = TarFile(fileobj=tmp, mode='w')

        # Add the executable to the tarball
        bn = os.path.basename(args.executable)
        ff = "/usr/bin/%s" % bn
        tmp_tar.add(args.executable, arcname=ff)

        # Add any associated libraries
        libs = _get_so_libs(args.executable)
        if libs:
            for l in libs:
                tmp_tar.add(os.path.realpath(l), arcname=l)

        # Create a Docker buildfile
        df = StringIO()
        df.write("FROM %s\n" % args.tag)
        df.write("ADD . /\n")
        df.seek(0)

        df_tar = TarInfo(name="Dockerfile")
        df_tar.size = len(df.buf)
        tmp_tar.addfile(df_tar, fileobj=df)

        tmp_tar.close()

        # reset the file pointers
        tmp.flush()
        tmp.seek(0)

        # Run the build with our tarball context
        dkr = Docker()
        dkr.update_image(args.tag, tmp, quiet=args.quiet)

        return 0

# 需要导入模块: from tarfile import TarFile [as 别名]
# 或者: from tarfile.TarFile import addfile [as 别名]
    def plot_predictions(self):
        epoch, batch, data = self.get_next_batch(train=False)  # get a test batch
        num_classes = self.test_data_provider.get_num_classes()
        NUM_ROWS = 2
        NUM_COLS = 4
        NUM_IMGS = NUM_ROWS * NUM_COLS if not self.save_preds else data[0].shape[1]
        NUM_TOP_CLASSES = min(num_classes, 5)  # show this many top labels
        NUM_OUTPUTS = self.model_state["layers"][self.softmax_name]["outputs"]
        PRED_IDX = 1

        label_names = [lab.split(",")[0] for lab in self.test_data_provider.batch_meta["label_names"]]
        if self.only_errors:
            preds = n.zeros((data[0].shape[1], NUM_OUTPUTS), dtype=n.single)
        else:
            preds = n.zeros((NUM_IMGS, NUM_OUTPUTS), dtype=n.single)
            # rand_idx = nr.permutation(n.r_[n.arange(1), n.where(data[1] == 552)[1], n.where(data[1] == 795)[1], n.where(data[1] == 449)[1], n.where(data[1] == 274)[1]])[:NUM_IMGS]
            rand_idx = nr.randint(0, data[0].shape[1], NUM_IMGS)
            if NUM_IMGS < data[0].shape[1]:
                data = [n.require(d[:, rand_idx], requirements="C") for d in data]
        #        data += [preds]
        # Run the model
        print [d.shape for d in data], preds.shape
        self.libmodel.startFeatureWriter(data, [preds], [self.softmax_name])
        IGPUModel.finish_batch(self)
        print preds
        data[0] = self.test_data_provider.get_plottable_data(data[0])

        if self.save_preds:
            if not gfile.Exists(self.save_preds):
                gfile.MakeDirs(self.save_preds)
            preds_thresh = preds > 0.5  # Binarize predictions
            data[0] = data[0] * 255.0
            data[0][data[0] < 0] = 0
            data[0][data[0] > 255] = 255
            data[0] = n.require(data[0], dtype=n.uint8)
            dir_name = "%s_predictions_batch_%d" % (os.path.basename(self.save_file), batch)
            tar_name = os.path.join(self.save_preds, "%s.tar" % dir_name)
            tfo = gfile.GFile(tar_name, "w")
            tf = TarFile(fileobj=tfo, mode="w")
            for img_idx in xrange(NUM_IMGS):
                img = data[0][img_idx, :, :, :]
                imsave = Image.fromarray(img)
                prefix = (
                    "CORRECT"
                    if data[1][0, img_idx] == preds_thresh[img_idx, PRED_IDX]
                    else "FALSE_POS"
                    if preds_thresh[img_idx, PRED_IDX] == 1
                    else "FALSE_NEG"
                )
                file_name = "%s_%.2f_%d_%05d_%d.png" % (
                    prefix,
                    preds[img_idx, PRED_IDX],
                    batch,
                    img_idx,
                    data[1][0, img_idx],
                )
                #                gf = gfile.GFile(file_name, "w")
                file_string = StringIO()
                imsave.save(file_string, "PNG")
                tarinf = TarInfo(os.path.join(dir_name, file_name))
                tarinf.size = file_string.tell()
                file_string.seek(0)
                tf.addfile(tarinf, file_string)
            tf.close()
            tfo.close()
            #                gf.close()
            print "Wrote %d prediction PNGs to %s" % (preds.shape[0], tar_name)
        else:
            fig = pl.figure(3, figsize=(12, 9))
            fig.text(0.4, 0.95, "%s test samples" % ("Mistaken" if self.only_errors else "Random"))
            if self.only_errors:
                # what the net got wrong
                if NUM_OUTPUTS > 1:
                    err_idx = [i for i, p in enumerate(preds.argmax(axis=1)) if p not in n.where(data[2][:, i] > 0)[0]]
                else:
                    err_idx = n.where(data[1][0, :] != preds[:, 0].T)[0]
                    print err_idx
                err_idx = r.sample(err_idx, min(len(err_idx), NUM_IMGS))
                data[0], data[1], preds = data[0][:, err_idx], data[1][:, err_idx], preds[err_idx, :]

            import matplotlib.gridspec as gridspec
            import matplotlib.colors as colors

            cconv = colors.ColorConverter()
            gs = gridspec.GridSpec(NUM_ROWS * 2, NUM_COLS, width_ratios=[1] * NUM_COLS, height_ratios=[2, 1] * NUM_ROWS)
            # print data[1]
            for row in xrange(NUM_ROWS):
                for col in xrange(NUM_COLS):
                    img_idx = row * NUM_COLS + col
                    if data[0].shape[0] <= img_idx:
                        break
                    pl.subplot(gs[(row * 2) * NUM_COLS + col])
                    # pl.subplot(NUM_ROWS*2, NUM_COLS, row * 2 * NUM_COLS + col + 1)
                    pl.xticks([])
                    pl.yticks([])
                    img = data[0][img_idx, :, :, :]
                    img = img.squeeze()
                    if len(img.shape) > 2:  # more than 2 dimensions
                        if img.shape[2] is 2:  # if two channels
                            # copy 2nd to 3rd channel for visualization
#.........这里部分代码省略.........