def fetch_smalltable_rows(table_handle: smalltable.Table,
                          keys: Sequence[Union[bytes, str]],
                          require_all_keys: bool = False,
) -> Mapping[bytes, Tuple[str]]:
    """Fetches rows from a Smalltable.

    Retrieves rows pertaining to the given keys from the Table instance
    represented by table_handle.  String keys will be UTF-8 encoded.

    Args:
        table_handle: An open smalltable.Table instance.
        keys: A sequence of strings representing the key of each table
          row to fetch.  String keys will be UTF-8 encoded.
        require_all_keys: If True only rows with values set for all keys will be
          returned.

    Returns:
        A dict mapping keys to the corresponding table row data
        fetched. Each row is represented as a tuple of strings. For
        example:

        {b'Serak': ('Rigel VII', 'Preparer'),
         b'Zim': ('Irk', 'Invader'),
         b'Lrrr': ('Omicron Persei 8', 'Emperor')}

        Returned keys are always bytes.  If a key from the keys argument is
        missing from the dictionary, then that row was not found in the
        table (and require_all_keys must have been False).

    Raises:
        IOError: An error occurred accessing the smalltable.

    Examples:
        Examples should be written in doctest format, and should illustrate how
        to use the function.

        >>> print([i for i in example_generator(4)])
        [0, 1, 2, 3]
    """

"""Docstring for the example.py module.

Modules names should have short, all-lowercase names.  The module name may
have underscores if this improves readability.

Every module should have a docstring at the very top of the file.  The
module's docstring may extend over multiple lines.  If your docstring does
extend over multiple lines, the closing three quotation marks must be on
a line by itself, preferably preceded by a blank line.

"""
from __future__ import division, absolute_import, print_function

import os  # standard library imports first

# Do NOT import using *, e.g. from numpy import *
#
# Import the module using
#
#   import numpy
#
# instead or import individual functions as needed, e.g
#
#  from numpy import array, zeros
#
# If you prefer the use of abbreviated module names, we suggest the
# convention used by NumPy itself::

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

# These abbreviated names are not to be used in docstrings; users must
# be able to paste and execute docstrings after importing only the
# numpy module itself, unabbreviated.

Several sentences providing an extended description. Refer to
variables using back-ticks, e.g. `var`.

Parameters
----------
var1 : array_like
    Array_like means all those objects -- lists, nested lists, etc. --
    that can be converted to an array.  We can also refer to
    variables like `var1`.
var2 : int
    The type above can either refer to an actual Python type
    (e.g. ``int``), or describe the type of the variable in more
    detail, e.g. ``(N,) ndarray`` or ``array_like``.
*args : iterable
    Other arguments.
long_var_name : {'hi', 'ho'}, optional
    Choices in brackets, default first when optional.
**kwargs : dict
    Keyword arguments.

Returns
-------
type
    Explanation of anonymous return value of type ``type``.
describe : type
    Explanation of return value named `describe`.
out : type
    Explanation of `out`.
type_without_description

Other Parameters
----------------
only_seldom_used_keywords : type
    Explanation.
common_parameters_listed_above : type
    Explanation.

Raises
------
BadException
    Because you shouldn't have done that.

See Also
--------
numpy.array : Relationship (optional).
numpy.ndarray : Relationship (optional), which could be fairly long, in
                which case the line wraps here.
numpy.dot, numpy.linalg.norm, numpy.eye

Notes
-----
Notes about the implementation algorithm (if needed).

This can have multiple paragraphs.

You may include some math:

.. math:: X(e^{j\omega } ) = x(n)e^{ - j\omega n}

And even use a Greek symbol like :math:`\omega` inline.

References
----------
Cite the relevant literature, e.g. [1]_.  You may also cite these
references in the notes section above.

.. [1] O. McNoleg, "The integration of GIS, remote sensing,
   expert systems and adaptive co-kriging for environmental habitat
   modelling of the Highland Haggis using object-oriented, fuzzy-logic
   and neural-network techniques," Computers & Geosciences, vol. 22,
   pp. 585-588, 1996.

Examples
--------
These are written in doctest format, and should illustrate how to
use the function.

>>> a = [1, 2, 3]
>>> print([x + 3 for x in a])
[4, 5, 6]
>>> print("a\nb")
a
b
"""
# After closing class docstring, there should be one blank line to
# separate following codes (according to PEP257).
# But for function, method and module, there should be no blank lines
# after closing the docstring.
pass