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        persist the table structure to DynamoDB.

        Requires a ``table_name`` parameter, which should be a simple string
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        Optionally accepts a ``schema`` parameter, which should be a list of
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        Optionally accepts a ``connection`` parameter, which should be a
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            # The simple, it-already-exists case.
            >>> conn = Table('users')

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            >>> users = Table('users', schema=[
            ...     HashKey('username'),
            ...     RangeKey('date_joined', data_type=NUMBER)
            ... ], throughput={
            ...     'read':20,
            ...     'write': 10,
            ... }, indexes=[
            ...     KeysOnlyIndex('MostRecentlyJoined', parts=[
            ...         HashKey('username')
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            ...     ]),
            ... ], global_indexes=[
            ...     GlobalAllIndex('UsersByZipcode', parts=[
            ...         HashKey('zipcode'),
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            ...     ],
            ...     throughput={
            ...       'read':10,
            ...       'write':10,
            ...     }),
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        Optionally accepts a ``connection`` parameter, which should be a
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            ... ], throughput={
            ...     'read':20,
            ...     'write': 10,
            ... }, indexes=[
            ...     KeysOnlyIndex('MostRecentlyJoined', parts=[
            ...         HashKey('username'),
            ...         RangeKey('date_joined'),
            ... ]), global_indexes=[
            ...     GlobalAllIndex('UsersByZipcode', parts=[
            ...         HashKey('zipcode'),
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            True

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        Returns ``True`` on success.

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            ...     global_index=GlobalAllIndex(
            ...         'TheIndexNameHere', parts=[
            ...             HashKey('requiredHashkey', data_type=STRING),
            ...             RangeKey('optionalRangeKey', data_type=STRING)
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        should have an integer value associated with them.

        To update ``global_indexes`` information on the ``Table``, you'll need
        to call ``Table.describe``.

        Returns ``True`` on success.

        Example::

            # To update a global index
            >>> users.update_global_secondary_index(global_indexes={
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        boolean. If you provide ``True``, it will perform
        a consistent (but more expensive) read from DynamoDB.
        (Default: ``False``)

        Optionally accepts an ``attributes`` parameter, which should be a
        list of fieldname to fetch. (Default: ``None``, which means all fields
        should be fetched)

        Returns an ``Item`` instance containing all the data for that record.

        Raises an ``ItemNotFound`` exception if the item is not found.

        Example::

            # A simple hash key.
            >>> john = users.get_item(username='johndoe')
            >>> john['first_name']
            'John'

            # A complex hash+range key.
            >>> john = users.get_item(username='johndoe', last_name='Doe')
            >>> john['first_name']
            'John'

            # A consistent read (assuming the data might have just changed).
            >>> john = users.get_item(username='johndoe', consistent=True)
            >>> john['first_name']
            'Johann'

            # With a key that is an invalid variable name in Python.
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        boolean. If you provide ``True``, it will perform
        a consistent (but more expensive) read from DynamoDB.
        (Default: ``False``)

        Optionally accepts an ``attributes`` parameter, which should be a
        list of fieldnames to fetch. (Default: ``None``, which means all fields
        should be fetched)

        Returns ``True`` if an ``Item`` is present, ``False`` if not.

        Example::

            # Simple, just hash-key schema.
            >>> users.has_item(username='johndoe')
            True

            # Complex schema, item not present.
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        Also unlike the get_item command, if the returned item has no keys
        (i.e., it does not exist in DynamoDB), a None result is returned, instead
        of an empty key object.

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            >>> user = users.lookup(username)
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        item & when your request to update the item's data is processed, which
        would typically result in some data loss.

        Requires a ``data`` parameter, which should be a dictionary of the data
        you'd like to store in DynamoDB.

        Optionally accepts an ``overwrite`` parameter, which should be a
        boolean. If you provide ``True``, this will tell DynamoDB to blindly
        overwrite whatever data is present, if any.

        Returns ``True`` on success.

        Example::

            >>> users.put_item(data={
            ...     'username': 'jane',
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        the delete. Otherwise, the item is not deleted.

        To specify the expected attribute values of the item, you can pass a
        dictionary of conditions to ``expected``. Each condition should follow
        the pattern ``<attributename>__<comparison_operator>=<value_to_expect>``.

        **IMPORTANT** - Be careful when using this method, there is no undo.

        To specify the key of the item you'd like to get, you can specify the
        key attributes as kwargs.

        Optionally accepts an ``expected`` parameter which is a dictionary of
        expected attribute value conditions.

        Optionally accepts a ``conditional_operator`` which applies to the
        expected attribute value conditions:

        + `AND` - If all of the conditions evaluate to true (default)
        + `OR` - True if at least one condition evaluates to true

        Returns ``True`` on success, ``False`` on failed conditional delete.

        Example::

            # A simple hash key.
            >>> users.delete_item(username='johndoe')
            True

            # A complex hash+range key.
            >>> users.delete_item(username='jane', last_name='Doe')
            True

            # With a key that is an invalid variable name in Python.
            # Also, assumes a different schema than previous examples.
            >>> users.delete_item(**{
            ...     'date-joined': 127549192,
            ... })
            True

            # Conditional delete
            >>> users.delete_item(username='johndoe',
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            True
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            ...         'owner': 1,
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            ...     # Nothing across the wire yet.
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            ...     # Still no requests sent.
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            ...         'username': 'jane',
            ...         'first_name': 'Jane',
            ...         'last_name': 'Doe',
            ...         'date_joined': 127436192,
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        **Note** - You can not query against arbitrary fields within the data
        stored in DynamoDB unless you specify ``query_filter`` values.

        To specify the filters of the items you'd like to get, you can specify
        the filters as kwargs. Each filter kwarg should follow the pattern
        ``<fieldname>__<filter_operation>=<value_to_look_for>``. Query filters
        are specified in the same way.

        Optionally accepts a ``limit`` parameter, which should be an integer
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        all results)

        Optionally accepts an ``index`` parameter, which should be a string of
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        (Default: ``None``)

        Optionally accepts a ``reverse`` parameter, which will present the
        results in reverse order. (Default: ``False`` - normal order)

        Optionally accepts a ``consistent`` parameter, which should be a
        boolean. If you provide ``True``, it will force a consistent read of
        the data (more expensive). (Default: ``False`` - use eventually
        consistent reads)

        Optionally accepts a ``attributes`` parameter, which should be a
        tuple. If you provide any attributes only these will be fetched
        from DynamoDB. This uses the ``AttributesToGet`` and set's
        ``Select`` to ``SPECIFIC_ATTRIBUTES`` API.

        Optionally accepts a ``max_page_size`` parameter, which should be an
        integer count of the maximum number of items to retrieve
        **per-request**. This is useful in making faster requests & prevent
        the scan from drowning out other queries. (Default: ``None`` -
        fetch as many as DynamoDB will return)

        Optionally accepts a ``query_filter`` which is a dictionary of filter
        conditions against any arbitrary field in the returned data.

        Optionally accepts a ``conditional_operator`` which applies to the
        query filter conditions:

        + `AND` - True if all filter conditions evaluate to true (default)
        + `OR` - True if at least one filter condition evaluates to true

        Returns a ``ResultSet`` containing ``Item``s, which transparently handles the pagination of
        results you get back.

        Example::

            # Look for last names equal to "Doe".
            >>> results = users.query(last_name__eq='Doe')
            >>> for res in results:
            ...     print res['first_name']
            'John'
            'Jane'

            # Look for last names beginning with "D", in reverse order, limit 3.
            >>> results = users.query(
            ...     last_name__beginswith='D',
            ...     reverse=True,
            ...     limit=3
            ... )
            >>> for res in results:
            ...     print res['first_name']
            'Alice'
            'Jane'
            'John'

            # Use an LSI & a consistent read.
            >>> results = users.query(
            ...     date_joined__gte=1236451000,
            ...     owner__eq=1,
            ...     index='DateJoinedIndex',
            ...     consistent=True
            ... )
            >>> for res in results:
            ...     print res['first_name']
            'Alice'
            'Bob'
            'John'
            'Fred'

            # Filter by non-indexed field(s)
            >>> results = users.query(
            ...     last_name__eq='Doe',
            ...     reverse=True,
            ...     query_filter={
            ...         'first_name__beginswith': 'A'
            ...     }
            ... )
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            'Alice Doe'

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        To specify the filters of the items you'd like to get, you can specify
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        (Default: ``None``)

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        Optionally accepts a ``conditional_operator`` which applies to the
        query filter conditions:

        + `AND` - True if all filter conditions evaluate to true (default)
        + `OR` - True if at least one filter condition evaluates to true

        Optionally accept a ``exclusive_start_key`` which is used to get
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        Returns an integer which represents the exact amount of matched
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        :type scan_index_forward: boolean
        :param scan_index_forward: Specifies ascending (true) or descending
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        If ScanIndexForward is not specified, the results are returned in
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        :type limit: integer
        :param limit: The maximum number of items to evaluate (not necessarily
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        Example::

            # Look for last names equal to "Doe".
            >>> users.query_count(last_name__eq='Doe')
            5

            # Use an LSI & a consistent read.
            >>> users.query_count(
            ...     date_joined__gte=1236451000,
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            2

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