Turbodbc

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* The size of the input buffers for retrieving result sets can now be set
to a certain amount of memory instead of using a fixed number of rows.
Use the optional ``read_buffer_size`` parameter of ``turbodbc.connect()`` and
set it to instances of the new top-level classes ``Megabytes`` and ``Rows``
(thanks LukasDistel).
* The read buffer size's default value has changed from 1,000 rows to
20 MB.
* The parameter ``rows_to_buffer`` of ``turbodbc.connect()`` is _deprecated_.
You can set the ``read_buffer_size`` to ``turbodbc.Rows(1000)`` for the same
effect, though it is recommended to specify the buffer size in MB.
* Internal: Libraries no longer link ``libpython.so`` for local development
(linking is already done by the Python interpreter). This was always
the case for the libraries in the packages uploaded to PyPI, so no
change was necessary here.
* Internal: Some modifications to the structure of the underlying
C++ code.

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* NumPy support is introduced to turbodbc for retrieving result sets.
Use ``cursor.fetchallnumpy`` to retrieve a result set as an ``OrderedDict``
of ``column_name: column_data`` pairs, where ``column_data`` is a NumPy ``MaskedArray``
of appropriate type.
* Internal: Single ``turbodbc_intern`` library was split up into three libraries
to keep NumPy support optional. A few files were moved because of this.

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* turbodbc now supports asynchronous I/O operations for retrieving result sets.
This means that while the main thread is busy converting an already retrieved
batch of results to Python objects, another thread fetches an additional
batch in the background. This may yield substantial performance improvements
in the right circumstances (results are retrieved in roughly the same speed
as they are converted to Python objects).

Ansynchronous I/O support is experimental. Enable it with
``turbodbc.connect('My data source name', use_async_io=True)``

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* C++ backend: ``turbodbc::column`` no longer automatically binds on
construction. Call ``bind()`` instead.

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* Result set rows are returned as native Python lists instead of a not easily
printable custom type.
* Improve performance of Python object conversion while reading result sets.
In tests with an Exasol database, performance got about 15% better.
* C++ backend: ``turbodbc::cursor`` no longer allows direct access to the C++
``field`` type. Instead, please use the ``cursor``'s ``get_query()`` method,
and construct a ``turbodbc::result_sets::field_result_set`` using the
``get_results()`` method.

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* Fix issue that only lists were allowed for specifying parameters for queries
* Improve parameter memory consumption when the database reports very large
string parameter sizes
* C++ backend: Provides more low-level ways to access the result set