python-rpy2-3.2.6-bp156.3.2

- Update to 3.2.6
  + Bugs fixed
  * The conversion of date/time object with specified timezones
    was wrong when different than the local time zone
  * Iterating over :mod:`rpy2.situation.iter_info()` could result
    in a error because of a typo in the code.
  + Changes
  * :mod:`pandas` 1.0.0 breaks the conversion layer. A warning
    is not emitted whenever trying to use `pandas` >= 1.0.

- Update to 3.2.5
  * Delimit multi-line expressions with parenthesis rather than backslash.
  * Use Rf_initEmbeddedR(), remove setup_Rmainloop() (not necessary, it seems).
- Update to 3.2.4
  * Fix ABI mode
- Update to 3.2.3
  * Backport fix for segfault when parsing.

- Update to version 3.2.2
  + Bugs fixed
  * Python format error when trying to report that the system is not reported
    on Windows.
  * The setup script would error on build if R is not installed. It is now
    printing an error message.
- Update to version 3.2.1
  + Bugs fixed
  * The wrapper for the R package `dbplyr` could not import the underlying
    package (refactoring elsewhere was not propagated there).
  * Creating R objects called `names` `globalenv` caused the method
    :meth:`Sexp.names` to fail.
  * Whenever the pandas conversion was activated :class:`FloatSexpVector` instances
    with the R class `POSIXct` attached where not corrected mapped back to pandas
    datetime arrays..
  * Fix installation when an installation when a prefix without write access is used.
- Update to version 3.2.0
  + New features
  * rpy2 can built and used with :mod:`cffi`'s ABI or API modes (releases 3.0.x and
    3.1.x were using the ABI mode exclusively). At the time of writing the default
    is still the ABI mode but the choice can be controlled through the environment variable
    `RPY2_CFFI_MODE`. If set, possible values are `ABI` (default if the environment
    variable is not set), `API`, or `BOTH`. When the latter, both `API` and `ABI`
    modes are built, and the choice of which one to use can be made at run time.
  + Changes
  * The "consoleread" callback (reading input to the R console) is now assuming UTF-8
    (was previously assuming ASCII) and is no longer trying to add a "new line" character
    at the end of the input.
  * Querying an R environment with an invalid key will generate a :class:`TypeError`
    or a :class:`ValueError` depending on the issue (rather than always :class:`ValueError`
    before.
  + Bugs fixed
  * `setup.py` is now again compatible with Python2.
  * Unit tests were failing if numpy is not installed.
  * :mod:`rpy2.situation` is no longer breaking when R is not the in path and
    there is no environment variable `R_HOME`.
  * Build script for the cffi interface is now using the environment
    variable `R_HOME` whenever defined (rather that always infer it from the
    R in the PATH).
  * Converting R strings back to Python was incorrectly using `Latin1` while `UTF-8` was
    intended.
- Update to version 3.1.0
  + New features
  * Python matrix multiplication (`__matmul__` / `@`) added to
    R :class:`Matrix` objects.
  * An :class:`threading.RLock` is added to :mod:`rpy2.rinterface_lib.openrlib` and is
    used by the context manager :func:`rpy2.rinterface_lib.memorymanagement.rmemory`
    to ensure that protect/unprotect cycles cannot be broken by thread switching, at least
    as long as the context manager is used to handle such cycles (see issue #571).
  * The documentation covers the use of notebooks (mainly Jupyter/Jupyterlab).
  * The PNG output in Jupyter notebooks R cells can now specify an argument `--type`
    (passed as the named argument `type` in the R function `png`).
    For example on some Linux systems and R installations, the type `cairo`
    can fix issues when alpha transparency is used.
  + Changes
  * Added callbacks for `ptr_R_Busy()` and `ptr_R_ProcessEvents()`.
  * `rstart` now an objects in :mod:`rpy2.rinterface_lib.embedded`
    (set to `None` until R is initialized).
  * Unit tests are included in a subpackage :mod:`rpy2.tests` as was the
    case before release 3.0.0.
  * Experimental initialization for Microsoft Windows.
  * :mod:`rpy2.situation` is now also reporting the rpy2 version.
  * :func:`rpy2.robjecs.package_utils.default_symbol_check_after` was
    renamed  :func:`rpy2.robjecs.package_utils.default_symbol_resolve`.
    The named parameters `default_symbol_check_after` present in few methods
    in :mod:`rpy2.robjects.packages` and :mod:`rpy2.robjects.functions` were
    modified to keep a consistent naming.
  * Trying to instantiate an :class:`rpy2.rlike.container.OrdDict` with a
    a :class:`dict` will result in a :class:`TypeError` rather than a
    :class:`ValueError`.
  * Methods of :class:`rpy2.rlike.container.OrdDict` now raises a
    :class:`NotImplementedError` when not implemented.
  * The creation of R vectors from Python sequences is now relying on a method
    :meth:`_populate_r_vector` that allows vectorized implementation to
    to improve speed.
  * Continuous integration tests run against Python 3.6, 3.7, and 3.8. It is
    no longer checked against Python 3.5.
  + Bugs fixed
  * `aes` in :mod:`rpy2.robjects.lib.ggplot2` had stopped working with the
    R package ggplot2 reaching version 3.2.0..
  * Better handling of recent :mod:`pandas` arrays with missing values.
  * The mapping of the R operator `%in%` reachable through the attribute `ro`
    of R vectors was always returning `True`. It is now working properly.
  * R POSIXct vectors with `NA` dates were triggering an error when converted
    in a data frame converted to :mod:`pandas`.

- 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

- Update to 2.9.5
  * Missing values in pandas :class:`Category` series were creating
    invalid R factors when converted (issue #493).

- Remove unused dependencies on blas libraries
- Don't exclude post-build-checks

- Update to 2.9.4
  * Fallback for failure to import numpy or pandas is now dissociated from
    failure to import :mod:`numpy2ri` or :mod:`pandas2ri` (issue #463).
  * :func:`repr` for R POSIX date/time vectors is now showing a string
    representation of the date/time rather than the timestamp as a float
    (issue #467).
  * The HTML representation of R data frame (the default representation in the
    Jupyter notebook) was displaying an inconsistent number of rows
    (found while workin on issue #466).
  * Handle time zones in timezones in Pandas when converting to R data frames
    (issue #454).
  * When exiting the Python process, the R cleanup is now explicitly request
    to happen before Python's exit. This is preventing possible segfaults
    the process is terminating (issue #471).
  * dplyr method `ungroup()` was missing from
    :class:`rpy2.robjects.lib.dplyr.DataFrame` (issue #473).

- Ensure neutrality of description. Trim future goals from
  description.

- Fix license

- Use %license tag

- Update to version 2.9.3
  * Delegate finding where is local time zone file to either a user-specified
    module-level variable `default_timezone` or to the third-party
    module :mod:`tzlocal` (issue #448).
- Update to version 2.9.2
  + Changes
  * The pandas converter is converting :class:`pandas.Series` of `dtype` `"O"`
    to :class:`rpy2.robjects.vectors.StrVector` objects, issueing a warning
    about it (See issue #421).
  * The conversion of pandas data frame is now working with columns rather
    than rows (introduce in bug fix for issue #442 below) and this is expected
    to result in more efficient conversions.
  + Bugs fixed
  * Allow floats in figure sizes for R magic (Pull request #63)
  * Fixed pickling unpickling of robjects-level instances,
    regression introduced in fix for issue #432 with release 2.9.1 (issue #443).
  * Fixed broken unit test for columns of `dtype` `"O"` in `pandas` data frames.
  * Fixed incorrect conversion of R factors in data frames to columns of
    integers in pandas data frame (issue #442).
- Update to version 2.9.1
  + Changes
  * Fixing issue #432 (see Section Bugs fixed below) involved removed the method
    `__reduce__` previously provided for all rpy2 objects representing R objects.
  + Bugs fixed
  * An error when installing with an unsupported R version was fixed (issue #420).
  * The docstring for `rinterface.endr()` was improperly stating that the function was not taking
    any argument (issue #423).
  * Target version of dplyr and tidyr are now 0.7.4 and 0.7.2 respectively.
  * Fixed memory leak when pickling objects (issue #432). Fixing the leak caused a
    slight change in the API (see Section Changes above).
  * Conversion to :mod:`pandas` now handling R ordered factor (issue #398).
    :mod:`jinja2` was not listed as a dependency (issue #437).

- Implement single-spec version
- Update to version 2.9.0
  * See changes at https://bitbucket.org/rpy2/rpy2/src/33ae1887a9cf3b624ea03b389835cd7a91cb815a/NEWS?at=RELEASE_2_9_0&fileviewer=file-view-default

- Update to version 2.7.9
  * Python objects exposed to R could lead to segfault when the Python process is
    exiting (issue #331)
- specfile:
  * updated source url to files.pythonhosted.org
- update to version 2.7.8:
  * New class :class:`rpy2.robjects.SourceCode`. The class extends
    Python's :class:`str` and is meant to represent R source code. An
    HTML renderer for the ipython notebook (syntax highlighting using
    :mod:`pygment` is also added).
  * New module :mod:`rpy2.robjects.lib.tidyr` providing a custom
    wrapper for the R library `tidyr`
  * The long-deprecated functions
    :func:`rpy2.rinterface.set_writeconsole` and
    :func:`rpy2.rinterface.get_writeconsole` are no longer
    available. One of :func:`rpy2.rinterface.set_writeconsole_regular`
    / :func:`rpy2.rinterface.set_writeconsole_warnerror` or
    :func:`rpy2.rinterface.get_writeconsole_regular` /
    :func:`rpy2.rinterface.get_writeconsole_warnerror` respectively
    should be used instead.
  * The attribute :attr:`rpy2.robjects.RObject.slots` can now be
    implictly interated on (the method :meth:`__iter__` is now an
    alias for :meth:`keys`).
- specfile:
  * update copyright year
- update to version 2.7.7:
  * Pickling `robjects`-level objects resulted in `rinterface`-level
    objects when unpickled (issue #324).
- changes from version 2.7.6:
  * :mod:`rpy2.robjects.lib.ggplot2` was modified to match the newly
    released ggplot2-2.0.0. This is introducing API-breaking changes,
    which breaks the promise to keep the API stable through bugfix
    releases within series, but without it 2.7.x will not a work with
    new default installation of the R package ggplot2.
- changes from version 2.7.5:
  * Division and floordivision through the delegator `.ro` provided
    with R vectors wrapped by `robjects`. (issue #320)
  * Memory leak when unserializing (unpickling) R objects bundled in
    Python objects (issue #321)
- update to version 2.7.4:
  * Python 3.5 highlighted slightly incorrect C-level flags in rpy2
    objects declarations, and :mod:`rpy2.robjects` could not be
    imported.
  * Fixed unit tests for rmagic when :mod:`numpy` is not installed,
    and for :mod:`numpy` is installed by :mod:`pandas` in missing.
- update to version 2.7.3:
  * method :meth:`DataFrame.collect` in :mod:`rpy2.robjects.lib.dplyr`
    was not functioning.
  * Applied patch by Matthias Klose to fix implict pointer
    conversions.
  * :mod:`pandas2ri.ri2py_dataframe` is now propagating the row names
    in the R data frame into an index in the pandas data frame (issue
    [#285])
  * methods `union`, `intersect`, `setdiff`, `ungroup` defined in the
    R package `dplyr` were missing from the `DataFrame` definition in
    :mod:`rpy2.robjects.lib.dplyr`
- update to version 2.7.2:
  * methods `distinct`, `sample_n`, and `sample_frac` defined in the R
    package `rplyr` were missing from the `DataFrame` definition in
    :mod:`rpy2.robjects.lib.dplyr`
  * The fix for the inheritance problem with
    :mod:`rpy2.robjects.lib.dplyr.DataFrame` introduced a regression
    whenever `group_by` is used.
  * The methods to perform joins on dplyr `DataFrame` objects where
    not working properly.
- update to version 2.7.1:
  * The :meth:`__repr__` for :mod:`robjects`-level vectors was broken
    for vectors of length 1 (issue #306)
  * The ipython notebook-based sections of the documentation
    were not building
  * Classes inheriting from :mod:`dplyr.DataFrame` had dplyr methods
    returning objects of their parent class.
- specfile:
  * check for R-version >= 3.2
- update to version 2.7.0:
  * New exception :class:`rpy2.rinterface.RParsingError`. Errors
    occurring when parsing R code through
    :func:`rpy2.rinterface.parse` raise this exception (previously
    :class:`rpy2.rinterface.RRuntimeError`).
  * New class :class:`rpy2.robjects.conversion.Converter` to replace
    the `namedtuple` of the same name
  * New class :class:`rpy2.robjects.converter.ConversionContext`. This
    is a context manager allowing an easy setting of local conversion
    rules.  The constructor has an alias called
    :meth:`rpy2.robjects.constructor.localconverter`.
  * New module :mod:`rpy2.robjects.lib.dplyr` providing a custom
    wrapper for the R library `dplyr`
  * Method :method:`Environment.items()` to iterate through the
    symbols and associated objects in an R environment.
  * Exception :class:`rpy2.rinterface.ParsingIncompleError`, a child
    class of :class:`rpy2.rinterface.ParsingError`, raised when
    calling :meth:`rpy2.rinteface.parse` results in R's C-level status
    to be `PARSE_INCOMPLETE`. This can make the Python implementation
    of an IDE for R easier.
  * Attribute :attr:`slots` for :mod:`rpy2.robjects`-level
    objects. The attribute is a :class:`rpy2.robjects.Rslots` which
    behaves like a Python mapping to provide access to R-attributes
    for the object (see issue #275).
  * The R "magic" for ipython `%%R` can be passed a local converter
    (see new features above) by using `-c`.
  * Conversion  rules were  not  applied when  parsing and  evaluating
    string as R with :class:`rpy2.robjects.R`.
  * Calling the constructor for
    :class:`rpy2.robjects.vectors.FactorVector` with an R factor is no
    longer making a copy, loosing the associated R attributes if any
    (fixes issue #299).
  * `rpy2` could crash when R was unable to dynamically load the C
    extension for one of its packages (noticed with issue #303).
  * :func:`rpy2.rinterface.is_initialized` is now a function.
  * :meth:`rpy2.robjects.R.__call__` is now calling R's
    `base::parse()` to parse the string rather the parser through R's
    C-API. The workaround let's us retrieve R's error message in case
    of failure (see issue #300)
- changes from version 2.6.3:
  * Metaclass `RS4Auto_Type` facilitating the creation of Python
    classes from R S4 classes was not handling classes without methods
    (issue #301)
- update to version 2.6.2:
  * Check that R >= 3.2 is used at build time (issue #291)
  * Conversion rules were not applied when parsing and evaluating
    string as R code with :class:`rpy2.robjects.R`.
- update to version 2.6.1:
  * Because of their long names, the classes
    :class:`SignatureTranslatedAnonymousPackage`,
    :class:`SignatureTranslatedPackage`, and
    :class:`SignatureTranslatedFunction` in
    :mod:`rpy2.robjects.packages` have now the aliases :class:`STAP`,
    :class:`STP`, and :class:`STF` respectively.
  * Typo in function name emitting warnings at build time (issue #283)
  * The conversion of `TaggedList` instances is now handling the names
    of items in the list (issue #286)
  * Loading the `ipython` extension in the absence of `pandas` or
    `numpy` is now issuing a warning (issue #279)
- update to version 2.6.0:
  * Report the existence during build time of a file `.Renviron`, or
    the definition of the environment variables `R_ENVIRON' or
    `R_ENVIRON_USER` with a warning. (issue #204)
  * Moved console writting callback to use `ptr_R_WriteConsoleEx`
    rather than `ptr_R_WriteConsole`. This allows callbacks for
    warnings and messages. `get/set_writeconsole` is now replaced by
    `get/set_writeconsole_regular` (regular output) and
    `get/set_writeconsole_warnerror` (warning and error).  In order to
    conserve backward compatibility an alias for
    `get/set_writeconsole_regular` called `get/set_writeconsole` is
    provided.
  * Added callback for `ptr_R_ResetConsole`.
  * `pandas` :class:`Categorical` objects are automatically handled in
    the pandas converter.
  * The translation of R symbols into Python symbols used in `importr`
    and underlying classes and methods can be customized with a
    callback.  The default translation turning `.` into `_` is
    `default_symbol_r2python`.
  * Translation of named arguments in R function is now sharing code
    with the translation of R symbols (see point above), providing a
    consistent way to perform translations.
  * Utility function `sequence_to_vector` in `robjects` to convert
    Python sequences (e.g., `list` or `tuple`) to R vector without
    having to specify the type (the type is inferred from the list).
  * `robjects.vectors` object have a property :attr:`NAvalue`
    that contains the `NA` value for the vector, allowing generic code
    on R vectors.  For example, testing whether any vector contains
    `NA` can be written as `any(x is myvector.NAvalue for x in
    myvector)`. Making numpy /masked/ array is an other application.
  * Changes
    + The automatic name translation from R to Python used in
    `importr` is now slightly more complex. It will not only
    translate `.` to `_` but should a conflict arise from the
    existence in R of both the `.` and `_` versions the `.` version
    will be appended a `_` (in accordance with :pep:0008). The
    change was discussed in issue #274).
    + The ipython 'R magic' is now starting with a default conversion
    mode that is `pandas2ri` if it can find it, then `numpy2ri` if
    it can find it, and then the basic conversion.
    + R vectors are now typed at the C level (IntSexpVector,
    FloatSexpVector, ListSexpVector, etc...) whenever retrieving
    them from the embedded R with the low-level `rinterface`. This
    is facilitating dispatch on vector type (e.g., with
    `singledispatch` now used for the conversion system).
  * Bugs fixed
    + The evaluation of R code through R's C-level function `tryEval`
    caused console output whenever an error occurred. Moving to the
    seemingly experimental `tryEvalSilent` makes evaluations less
    verbose.
    + Multiple plots in one ipython cell (pull request #44)
- changes from version 2.5.7:
  * "simplegeneric" was moved of ipython 4.0.0 (pull request #43)

- Update to version 2.5.6
  - Detection of the R version during setup on Win8 (issues #255 and #258)
  - Segmentation fault when converting :mod:`pandas` :class:`Series` with
    elements of type object (issue #264)
  - The default converter from Python (non-rpy2) objects to rinterface-level
    objects was producing robjects-level objects whenever the input was of
    type :class:`list` (discovered while fixing issue #264)
  - Implemented suggested fix for issue with unlinking files on Windows
    (issue #191)
  - Testing rpy2 in the absence of ipython no longer stops with an error
    (issue #266)
- Update to version 2.5.5
  - Crash (segfault) when querying an R object in an R environment triggers an
    error (symbol exists, but associated values resolves to an error - issue #251)
  - Change in the signature of `rcall` was not updated in the documentation
    (issue #259)
  - Minor update to the documentation (issue #257)

- specfile:
  * update copyright year
  * README -> README.md
- update to version 2.5.4:
  * Filter PNG files on size, preventing empty files causing trouble
    to be ipython notebook rendering of graphics later on (slight
    modification of the pull request #39)
  * Fix installation left unresolved with rpy2-2.5.3 (issue #248)
  * Possible segfault with Python 3.4 (issue #249)
- changes to version 2.5.3:
  * 'setup.py' has 'install_requires' in addition to 'requires' in the
    hope to fix the missing dependency with Python 2
    ('singledispatch' is required but not installed).
  * Extracting configuration information from should now work when R
    is emitting a warning (issue #247)
  * On OS X the library discovery step can yield nothing (see issue
    [#246]). A tentative fix is to issue a warning and keep moving.
- changes to version 2.5.2:
  * String representation of 'robjects.R' (issue #238)
  * Check during 'build_ext' if unsupported version of R (pull request
    [#32])
  * HTMl display of columns of factors in a DataFrame (issue #236)
  * HTML display of factors (issue #242)
- changes to version 2.5.1:
  * Require singledispatch if Python 3.3 (issue #232)
  * Fixed bug when R spits out a warning when asked configuration
    information (issue #233)
  * Restored printing of compilation information when running
    'setup.py'
  * Fixed installation issue on some systems (issue #234)
  * Workaround obscure failure message from unittest if Python < 3.4
    and 'singledispatch' cannot be imported (issue #235)
- changes to version 2.5.0:
  * Experimental alternative way to preserve R objects from garbage
    collection.  This can be activated with
    'rinterface.initr(r_preservehash=True)' (default is 'False'.
  * 'GGPlot' object getting a method 'save' mirroring R's
    'ggplot2::ggsave()'.
  * The conversion system is now using generics/single dispatch.
  * New module 'rpy2.ipython.html' with HTML display for rpy2 objects
  * [Experimental] New function 'robjects.methods.rs4instance_factory'
    to type RS4 objects with more specificity.
  * The script 'setup.py' was rewritten for clarity and ease of
    maintenance.  Now it only uses 'setuptools'.
- changes to version 2.4.4:
  * Use 'input' rather than 'raw_input' in the default console
    callback with Python 3 (fixes issue #222)
  * Issues with conversions, pandas, and rmagic (fixes issue #218 and
    more)
- changes to version 2.4.3:
  * 'geom_raster' was missing from 'rpy2.robjects.lib.ggplot2' (pull
    request #30)
  * Fixed issue with SVG rendering in ipython notebook (issue #217)
  * Regression with 'rx2()' introduced with new conversion (issue
    [#219])
  * Fixed documentation (missing 'import') (issue #213)
- Release 2.4.2
  * Bugs fixed
  - Assigning an R `DataFrame` into an environment was failing if
    the conversion for Pandas was activated. (Issue #207)
- Release 2.4.1
  * Bugs fixed
  - :meth:`rpy2.ipython` fixed spurious output to notebook cells.
- Release 2.4.0
  * Changes
  - Conversion system slightly changed, with the optional
    conversions for :mod:`numpy` and :mod:`pandas` modified
    accordingly. The changes should only matter if using
    third-party conversion functions.
  - The Python 3 version is now a first class citizen. `2to3`
    is no longer used, and the code base is made directly
    compatible with Python. This lowers significantly the
    installation time with Python 3
    (which matters when developping rpy2).
  - The default options to initialize R (`rpy2.rinterface.initoptions') are no longer
    `('rpy2', '--quiet', '--vanilla', '--no-save')` but now
    `('rpy2', '--quiet', '--no-save')`.
  - :class:`robjects.vectors.ListVector` can be instanciated from
    any objects with a method `items()` with the expectation that the method
    returns an iterable of (name, value) tuples, or even be an iterable
    of (name, value) tuples.
  * New features
  - For instances of :class:`rpy2.robjects.Function`,
    the `__doc__` is now a property fetching information
    about the parameters in the R signature.
  - Convenience function :func:`rpy2.robjects.packages.data`
    to extract the datasets in an R pacakges
  - :mod:`ipython`'s `rmagic` is now part of :mod:`rpy`. To use, `%load_ext
    rpy2.ipython` from within IPython.
  - new method :meth:`rpy2.rinterface.SexpEnvironment.keys`, returnings
    the names in the environment as a tuple of Python strings.
  - convenience class :class:`robjects.packages.InstalledPackages`, with a companion function
    :func:`robjects.packages.isinstalled`.
  - new class :class:`rinterface.SexpSymbol` to represent R symbols
  * Bugs fixed
  - :meth:`rpy2.rinterface.Sexp.do_slot` was crashing when
    the parameter was an empty string (PR #155)
- Release 2.3.10
  * Bugs fixed
  - `setup.py build` was broken when new R compiled with OpenMP (Issue #183)
- Release 2.3.9
  * Bugs fixed
  - Changes in pandas 0.13.0 broke the rpy2 conversion layer (Issue #173)

- Update to version 2.3.8
  + Fix crash with R-3.0.2. Changes in R-3.0.2's C API coupled to a
    strange behaviour with R promises caused the problem. (PR #150)
- Changes from version 2.3.7
  + ggplot2's "guides" were missing
  + ggplot2's "theme_classic" was missing (PR #143)
  + ggplot2's "element_rect" was missing (PR #144)
  + :func:`rpy2.interactive.packages` was broken (PR #142)
- Changes from version 2.3.6
  + Several reports of segfault on OS X (since rpy2-2.3.1 - PR #109)
  + More fixes in converting `DataFrames` with dates from `pandas`
- Remove redundant %clean section
- Fix license; rpy2 is released under the MOZILLA PUBLIC LICENSE 1.1
  and can be used under this one or under GNU General Public License
  version 2 or GNU Lesser General Public License version 2.1
- Add licenses files in package documentation

- update to new version 2.3.5
- update to new URL
- add buildrequires: R-base, which is needed for openSUSE:Factory

- Add python 3 package
- Clean up spec file formatting

- Update BuildRequires in keeping with lapack package naming
  changes.

- fix build for SLE-11

- Clean up spec file

- update to version 2.2.4
- add readline as BuildRequires

- update new version 2.1.9

- update new version 2.1.7