Version history / changelog

From version 2.0.0, turbodbc adapts semantic versioning.

Version 4.4.0

  • Bump pybind11 version to 2.9.1
  • Bump dependency requirements to pyarrow>=1.0 and numpy>=1.19
  • Bump the used google test versions to 1.11.0

Version 4.3.1

  • Update package requirements so that pyarrow>0.17.1,<7.1 can be used.

Version 4.3.0

  • Add Python 3.10 build
  • Update package requirements so that pyarrow>0.17.1,<6.1 can be used.
  • Bump pybind11 version to 2.8.1

Version 4.2.1

  • Update package requirements so that pyarrow>0.17.1,<5.1 can be used.

Version 4.2.0

  • Update package requirements so that pyarrow>0.17.1,<4.1 can be used.
  • Set minimal Python version to 3.7 following NEP 29.

Version 4.1.2

  • Update package requirements so pyarrow>0.17.1,<3.1 can be used.

Version 4.1.1

  • Version bump as package version was not adapted.

Version 4.1.0

  • Adjust unit tests to Apache Arrow master changes.
  • Bump bundled pybind11 to 2.5.0

Version 4.0.0

  • Minimal supported python version is 3.6.X now

Version 3.4.0

  • Support Arrow 0.16.x and 0.17.x, require at least 0.15.x
  • Minimal NumPy version was bumped to 1.16

Version 3.3.0

  • Don’t override but amend CMAKE_CXX_FLAGS
  • Support Arrow 0.15.X

Version 3.2.0

  • Release GIL while fetching batches using Apache Arrow engine
  • Support Arrow 0.14.X

Version 3.1.1

  • Correctly report odbc errors when freeing the statement handle as exceptions; see Github issue 153 (thanks @byjott)
  • Support user-provided gmock/gtest, e.g. in conda environments via conda install -c conda-forge gtest gmock.
  • Make source code compatible with Apache Arrow 0.13.0

Version 3.1.0

  • Update to Apache Arrow 0.12
  • Support the unicode datatype in the Arrow support. This primarily enables MS SQL support for the Arrow adapter.
  • Windows support for the Arrow adapter.
  • Add a new entry to the build matrix that tests Python 3.7 with conda and MS SQL on Linux.
  • Big hands to @xhochy for making all these changes!

Version 3.0.0

  • Adjust generators to conform to PEP-479
  • Build wheels for Python 3.7 on Windows
  • Drop support for Python 3.4
  • Update to Apache Arrow 0.11

Version 2.7.0

  • Added new keyword argument fetch_wchar_as_char to make_options(). If set to True, wide character types (NVARCHAR) are fetched and decoded as narrow character types for compatibility with certain databases/drivers (thanks @yaxxie).
  • Added batched fetch support for Arrow as fetcharrowbatches() (thanks @mariusvniekerk).
  • Support (u)int8, (u)int16, (u)int32 Arrow columns on executemanycolumns() (thanks @xhochy).

Version 2.6.0

  • Added support for with blocks for Cursor and Connection objects. This makes turbodbc conform with PEP 343 (thanks @AtomBaf)
  • Added new keyword argument force_extra_capacity_for_unicode to make_options(). If set to True, memory allocation is modified to operate under the assumption that the database driver reports field lengths in characters, rather than code units (thanks @yaxxie).
  • Updated Apache Arrow support to work with both versions 0.8.0 and 0.9.0 (thanks @pacman82)
  • Fixed a bug that led to handle limit exceeded error messages when Cursor objects were not closed manually. With this fix, cursors are garbage collected as expected.

Version 2.5.0

  • Added an option to fetchallarrow() that fetches integer columns in the smallest possible integer type the retrieved values fit in. While this reduces the memory footprint of the resulting table, the schema of the table is now dependent on the data it contains.
  • Updated Apache Arrow support to work with version 0.8.x

Version 2.4.1

  • Fixed a memory leak on fetchallarrow() that increased the reference count of the returned table by one too much.

Version 2.4.0

  • Added support for Apache Arrow pyarrow.Table objects as the input for executemanycolumns(). In addition to direct Arrow support, this should also help with more graceful handling of Pandas DataFrames as pa.Table.from_pandas(...) handles additional corner cases of Pandas data structures. Big thanks to @xhochy!

Version 2.3.0

  • Added an option to fetchallarrow() that enables the fetching of string columns as dictionary-encoded string columns. In most cases, this increases performance and reduces RAM usage. Arrow columns of type dictionary[string] will result in pandas.Categorical columns on conversion.
  • Updated pybind11 dependency to version 2.2+
  • Fixed a symbol visibility issue when building Arrow unit tests on systems that hide symbols by default.

Version 2.2.0

  • Added new keyword argument large_decimals_as_64_bit_types to make_options(). If set to True, decimals with more than 18 digits will be retrieved as 64 bit integers or floats as appropriate. The default retains the previous behavior of returning strings.
  • Added support for datetime64[ns] data type for executemanycolumns(). This is particularly helpful when dealing with pandas DataFrame objects, since this is the type that contains time stamps.
  • Added the keyword argument limit_varchar_results_to_max to make_options(). This allows to truncate VARCHAR(n) fields to varchar_max_character_limit characters, see the next item.
  • Added possibility to enforce NumPy and Apache Arrow requirements using extra requirements during installation: pip install turbodbc[arrow,numpy]
  • Updated Apache Arrow support to work with version 0.6.x
  • Fixed an issue with retrieving result sets with VARCHAR(max) fields and similar types. The size of the buffer allocated for such fields can be controlled with the varchar_max_character_limit option to make_options().
  • Fixed an issue with some versions of Boost that lead to problems with datetime64[us] columns with executemanycolumns(). An overflow when converting microseconds since 1970 to a database-readable timestamp could happen, badly garbling the timestamps in the process. The issue was surfaced with Debian 7’s Boost version (1.49), although the Boost issue was allegedly fixed with version 1.43.
  • Fixed an issue that lead to undefined behavior when character sequences could not be decoded into Unicode code points. The new (and defined) behavior is to ignore the offending character sequences completely.

Version 2.1.0

  • Added new method cursor.executemanycolumns() that accepts parameters in columnar fashion as a list of NumPy (masked) arrays.
  • CMake build now supports conda environments
  • CMake build offers DISABLE_CXX11_ABI option to fix linking issues with pyarrow on systems with the new C++11 compliant ABI enabled

Version 2.0.0

  • Initial support for the arrow data format with the Cursor.fetchallarrow() method. Still in alpha stage, mileage may vary (Windows not yet supported, UTF-16 unicode not yet supported). Big thanks to @xhochy!
  • prefer_unicode option now also affects column name rendering when gathering results from the database. This effectively enables support for Unicode column names for some databases.
  • Added module version number turbodbc.__version__
  • Removed deprecated performance options for connect(). Use connect(..., turbodbc_options=make_options(...)) instead.

Earlier versions (not conforming to semantic versioning)

The following versions do not conform to semantic versioning. The meaning of the major.minor.revision versions is:

  • Major: psychological ;-)
  • Minor: If incremented, this indicates a breaking change
  • Revision: If incremented, indicates non-breaking change (either feature or bug fix)

Version 1.1.2

  • Added autocommit as a keyword argument to make_options(). As the name suggests, this allows you to enable automatic COMMIT operations after each operation. It also improves compatibility with databases that do not support transactions.
  • Added autocommit property to Connection class that allows switching autocommit mode after the connection was created.
  • Fixed bug with cursor.rowcount not being reset to -1 when calls to execute() or executemany() raised exceptions.
  • Fixed bug with cursor.rowcount not showing the correct value when manipulating queries were used without placeholders, i.e., with parameters baked into the query.
  • Global interpreter lock (GIL) is released during some operations to facilitate basic multi-threading (thanks @chmp)
  • Internal: The return code SQL_SUCCESS_WITH_INFO is now treated as a success instead of an error when allocating environment, connection, and statement handles. This may improve compatibility with some databases.

Version 1.1.1

  • Windows is now _officially_ supported (64 bit, Python 3.5 and 3.6). From now on, code is automatically compiled and tested on Linux, OSX, and Windows (thanks @TWAC for support). Windows binary wheels are uploaded to pypi.
  • Added supported for fetching results in batches of NumPy objects with cursor.fetchnumpybatches() (thanks @yaxxie)
  • MSSQL is now part of the Windows test suite (thanks @TWAC)
  • connect() now allows to specify a connection_string instead of individual arguments that are then compiles into a connection string (thanks @TWAC).

Version 1.1.0

  • Added support for databases that require Unicode data to be transported in UCS-2/UCS-16 format rather than UTF-8, e.g., MSSQL.
  • Added _experimental_ support for Windows source distribution builds. Windows builds are not fully (or automatically) tested yet, and still require significant effort on the user side to compile (thanks @TWAC for this initial version)
  • Added new cursor.fetchnumpybatches() method which returns a generator to iterate over result sets in batch sizes as defined by buffer size or rowcount (thanks @yaxxie)
  • Added make_options() function that take all performance and compatibility settings as keyword arguments.
  • Deprecated all performance options (read_buffer_size, use_async_io, and parameter_sets_to_buffer) for connect(). Please move these keyword arguments to make_options(). Then, set connect{}’s new keyword argument turbodbc_options to the result of make_options(). This effectively separates performance options from options passed to the ODBC connection string.
  • Removed deprecated option rows_to_buffer from turbodbc.connect() (see version 0.4.1 for details).
  • The order of arguments for turbodbc.connect() has changed; this may affect you if you have not used keyword arguments.
  • The behavior of cursor.fetchallnumpy() has changed a little. The mask attribute of a generated numpy.MaskedArray instance is shortened to False from the previous [False, ..., False] if the mask is False for all entries. This can cause problems when you access individual indices of the mask.
  • Updated pybind11 requirement to at least 2.1.0.
  • Internal: Some types have changed to accomodate for Linux/OSX/Windows compatibility. In particular, a few long types were converted to intptr_t and int64_t where appropriate. In particular, this affects the field type that may be used by C++ end users (so they exist).

Version 1.0.5

  • Internal: Remove some const pointers to resolve some compile issues with xcode 6.4 (thanks @xhochy)

Version 1.0.4

  • Added possibility to set unixodbc include and library directories in Required for conda builds.

Version 1.0.3

  • Improved compatibility with ODBC drivers (e.g. FreeTDS) that do not support ODBC’s SQLDescribeParam() function by using a default parameter type.
  • Used a default parameter type when the ODBC driver cannot determine a parameter’s type, for example when using column expressions for INSERT statements.
  • Improved compatibility with some ODBC drivers (e.g. Microsoft’s official MSSQL ODBC driver) for setting timestamps with fractional seconds.

Version 1.0.2

  • Added support for chaining operations to Cursor.execute() and Cursor.executemany(). This allows one-liners such as cursor.execute("SELECT 42").fetchallnumpy().
  • Right before a database connection is closed, any open transactions are explicitly rolled back. This improves compatibility with ODBC drivers that do not perform automatic rollbacks such as Microsoft’s official ODBC driver.
  • Improved stability of turbodbc when facing errors while closing connections, statements, and environments. In earlier versions, connection timeouts etc. could have lead to the Python process’s termination.
  • Source distribution now contains license, readme, and changelog.

Version 1.0.1

  • Added support for OSX

Version 1.0.0

  • Added support for Python 3. Python 2 is still supported as well. Tested with Python 2.7, 3.4, 3.5, and 3.6.
  • Added six package as dependency
  • Turbodbc uses pybind11 instead of Boost.Python to generate its Python bindings. pybind11 is available as a Python package and automatically installed when you install turbodbc. Other boost libraries are still required for other aspects of the code.
  • A more modern compiler is required due to the pybind11 dependency. GCC 4.8 will suffice.
  • Internal: Move remaining stuff depending on python to turbodbc_python
  • Internal: Now requires CMake 2.8.12+ (get it with pip install cmake)

Version 0.5.1

  • Fixed build issue with older numpy versions, e.g., 1.8 (thanks @xhochy)

Version 0.5.0

  • Improved performance of parameter-based operations.
  • Internal: Major modifications to the way parameters are handled.

Version 0.4.1

  • 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 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.

Version 0.4.0

  • 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.

Version 0.3.0

  • 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)

Version 0.2.5

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

Version 0.2.4

  • 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.

Version 0.2.3

  • 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

Version 0.2.2

  • Fix issue that dsn parameter was always present in the connection string even if it was not set by the user’s call to connect()
  • Internal: First version to run on Travis.
  • Internal: Use pytest instead of unittest for testing
  • Internal: Allow for integration tests to run in custom environment
  • Internal: Simplify integration test configuration

Version 0.2.1

  • Internal: Change C++ test framework to Google Test

Version 0.2.0

  • New parameter types supported: bool,, datetime.datetime
  • cursor.rowcount returns number of affected rows for manipulating queries
  • Connection supports rollback()
  • Improved handling of string parameters

Version 0.1.0

Initial release