This file is indexed.

/usr/lib/python3/dist-packages/asdf/stream.py is in python3-asdf 1.2.1-2.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
# Licensed under a 3-clause BSD style license - see LICENSE.rst
# -*- coding: utf-8 -*-

from __future__ import absolute_import, division, unicode_literals, print_function

from .tags.core import ndarray


class Stream(ndarray.NDArrayType):
    """
    Used to put a streamed array into the tree.

    Examples
    --------
    Save a double-precision array with 1024 columns, one row at a
    time::

         >>> from asdf import AsdfFile, Stream
         >>> import numpy as np
         >>> ff = AsdfFile()
         >>> ff.tree['streamed'] = Stream([1024], np.float64)
         >>> with open('test.asdf', 'wb') as fd:
         ...     ff.write_to(fd)
         ...     for i in range(200):
         ...         nbytes = fd.write(
         ...                      np.array([i] * 1024, np.float64).tostring())
    """
    name = None
    types = []

    def __init__(self, shape, dtype, strides=None):
        self._shape = shape
        self._datatype, self._byteorder = ndarray.numpy_dtype_to_asdf_datatype(dtype)
        self._strides = strides
        self._array = None

    def _make_array(self):
        self._array = None

    @classmethod
    def reserve_blocks(cls, data, ctx):
        if isinstance(data, Stream):
            yield ctx.blocks.get_streamed_block()

    @classmethod
    def from_tree(cls, data, ctx):
        return ndarray.NDArrayType.from_tree(data, ctx)

    @classmethod
    def to_tree(cls, data, ctx):
        ctx.blocks.get_streamed_block()

        result = {}
        result['source'] = -1
        result['shape'] = ['*'] + data._shape
        result['datatype'] = data._datatype
        result['byteorder'] = data._byteorder
        if data._strides is not None:
            result['strides'] = data._strides
        return result