- Update to Release 3.0.5
+ Bugs fixed
* No longer allow installation if Python 3 but < 3.5.
* Fixed error `undefined symbol: DATAPTR` if R < 3.5.
- Update to Release 3.0.4
+ Bugs fixed
* Fixed conversion of `pandas` :class:`Series` of dtype `pandas.Int32Dtype`,
or `pandas.Int64Dtype`.
- Update to Release 3.0.3
+ Bugs fixed
* Fixed the evaluation of R code using the "R magic" was delaying all
output to the end of the execution of that code, independently of
whether the attribute `cache_display_data` was `True` or `False`.
* Fixed conversion of :class:`pandas.Series` of `dtype` "object" when
all items are either all of the same type or are :obj:`None`.
- Update to Release 3.0.2
+ Bugs fixed
* Failing to import `pandas` or `numpy` when loading the "R magic" extension
for jupyter/ipython was hiding the cause of the error in the `ImportError`
exception.
* Fallback when an R `POSIXct` vector does not had an attribute `"tzone"`.
* Callback for console reset was not set during R initialization.
* Fixed rternalized function returning rpy2 objects.
* `--vanilla` is no longer among the default options used to initialize R.
- Update to Release 3.0.1
+ Bugs fixed
* Script to install R packages for docker image never made it to version
control.
* Conversion of R arrays/matrices into numpy object trigged a segfault
during garbage collection.
- Update to Release 3.0.0
+ New features
* rpy2 can be installed without a development environment.
* Unit tests are now relying on the Python module `pytest`.
* :attr:`rpy2.rinterface.NA_Integer` is now only defined when the embedded R
is initialized.
+ Changes
* complete rewrite of :mod:`rpy2.rinterface`.
:mod:`cffi` is now used to interface with the R compiled shared library.
This allows ABI calls and removes the need to compile binaries. However, if
compilation is available (when installing or preparing pre-compiled binaries)
faster implementations of performance bottlenecks will be available.
* calling :func:`rpy2.rinterface.endr` multiple times is now only ending R
the first time it is called (note: an ended R cannot successfully be
re-initialized).
* The conversion system in the mod:`rpy2.robjects.conversion` now has only
two conversions `py2rpy` and rpy2py`. `py2rpy` tries to convert any
Python object into an object rpy2 can use with R and `rpy2py` tries
to convert any rpy2 object into a either a non-rpy2 Python object or
a mod:`rpy2.robjects` level object.
* The method `get` for R environments is now called `find()` to avoid
confusion with the method of the same name in Python (:meth:`dict.get`).
* :class:`rpy2.robjects.vectors.Vector`, :class:`rpy2.robjects.vectors.Matrix`,
and :class:`rpy2.robjects.vectors.Array` can no longer be used to create
R arrays of unspecified type. New type-specific classes (for example for
vectors :class:`rpy2.robjects.vectors.IntVector`,
:class:`rpy2.robjects.vectors.BoolVector`,
:class:`rpy2.robjects.vectors.FloatVector`,
:class:`rpy2.robjects.vectors.ComplexVector`, or
:class:`rpy2.robjects.vectors.StrVector`) should be used instead.
* mod:`rpy2.rpy_classic`, an implementation of the `rpy` interface using
:mod:`rpy2.rinterface` is no longer available.
* :class:`rpy2.robjects.ParsedCode` and
:class:`rpy2.robjects.SourceCode` are moved to
:class:`rpy2.robjects.packages.ParsedCode` and
:class:`rpy2.robjects.packages.SourceCode`.
+ Bugs fixed
* Row names in R data frames were lost when converting to pandas data frames.
+ Known issues
* Mismatch between R's POSIXlt `wday` and Python time struct_time's `tm_wday`.
- Update to Release 2.9.6
+ Bugs fixed
* Latest release of :mod:`pandas` deprecated :meth:`DataFrame.from_items`.
* Latest release of :mod:`pandas` requires categories to be a list
(not an other sequence).
+ Known issues
* The numpy buffer implemented by R arrays is broken for complex numbers