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| Name: python312-rpy2 | Distribution: openSUSE Tumbleweed |
| Version: 3.4.4 | Vendor: openSUSE |
| Release: 1.19 | Build date: Tue Apr 27 06:21:14 2021 |
| Group: Unspecified | Build host: reproducible |
| Size: 2456236 | Source RPM: python-rpy2-3.4.4-1.19.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: https://bitbucket.org/rpy2/rpy2 | |
| Summary: A Python interface to the R Programming Language | |
RPy is a Python interface to the R Programming Language. It can manage all kinds of R objects and can execute arbitrary R functions (including the graphic functions). All errors from the R language are converted to Python exceptions. Any module installed for the R system can be used from Python. This code is inspired by RSPython from the Omegahat project.
GPL-2.0-or-later
* Tue Apr 27 2021 Steve Kowalik <steven.kowalik@suse.com>
- Update to 3.4.4:
* `RRuntimeError` exceptions raised while evaluating R code
an R magic (ipython/jupyter) are now propagated (issue #792).
* :mod:`rpy2.robjects.lib.ggplot2` maps more functions in the
R package (issue #767)
* Utility function :func:`rpy2.robjects.lib.ggplot2.dict2rvec`
to convert a Python `Dict[str, str]` into an R named vector
of strings.
* Converting pandas series with the older numpy types could result
in an error (issue #781)
* Numpy converter was not properly turing R integer or float arrays
into their numpy equivalent (issue #785)
* Multithreading during the initialization of the embedded R no longer
triggers a fatal error (issue #729)
* The mapping of the R C API now includes `Rf_isSymbol()`.
* Singleton class :class:`rpy2.rinterface_lib.sexp.RVersion` to report
the R version for the embedded R.
* :func:`rpy2.rinterface.local_context` to create a context manager
to evaluate R code within a local environment.
* The `staticmethod` :meth:`rpy2.robjects.vectors.DateVector.isrinstance`
will tell whether an R objects is an R `Date` array.
* The functions :func:`rpy2.robjects.numpy.activate()` and
:func:`rpy2.robjects.pandas.activate()` are deprecated and will
be removed in rpy2*3.5.0.
* :meth:`rpy2.robjects.lib.ggplot2.vars` to map the R function
`ggplot2::vars` (issue #742).
* Report correctly the class of R matrix objects with R>=4.0: it is
now `('matrix', 'array')`. With R<4.0 `('matrix')` is still reported.
* The conversion `rpy2py` is now working with any Python object inheriting
from `_rinterface_capi.SupportsSEXP`.
* More complete and correct mapping of R class names in
:func:`rpy2.rinterface_lib.sexp.rclass_get`.
* The conversion of R string arrays to `numpy` arrays was leaving
R's `NA` value as R NA objects. NAs in this type of arrays are now
turned to `None` in the resulting `numpy` array (issue #751).
* `rpy2.situation.get_rlib_path()` was returning an environment variable
with an invalid separator on Windows (mentioned in issue #754).
* R strings encoded with something else than 'utf-8' could result in
errors when trying to convert to Python strings (issue #754).
* R `Date` arrays/vectors were not wrapped into
:class:`rpy2.robjects.vectors.DateVector` objects but left as
R arrays of floats (which they are at the C level).
* The :meth:`__repr__` of `robjects`-level objects was not displaying
the rpy2 class the R object is mapped to.
* The unit tests for importing R packages with `lib_loc` were
broken (issue #720).
* Fix the constructor of metaclass
:class:`rpy2.robjects.methods.RS4Auto_Type`.
* Fix call to end the embedded R in :class:`rpy2.robjects.R.__cleanup__`
(issue #734).
- Do not build on Python 3.6, due to no NumPy.
* Wed Jul 15 2020 Todd R <toddrme2178@gmail.com>
- Update to 3.3.5
* Trying to import an R package that it not installed will now raise an
exception :class:`rpy2.robjects.packages.PackageNotInstalledError`.
* The R C API functions `void SET_FRAME(SEXP x, SEXP v)`,
`void SET_ENCLOS(SEXP x, SEXP v)` and `void SET_HASHTAB(SEXP x, SEXP v)`
are now accessible through rpy2.
* When calling R C-API's `R_ParseVector` and a error occurs, the
exception message now contains the parsing status.
* Mon Feb 10 2020 Todd R <toddrme2178@gmail.com>
- 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.
* Thu Jan 30 2020 Todd R <toddrme2178@gmail.com>
- 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.
* Wed Nov 27 2019 Todd R <toddrme2178@gmail.com>
- 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`.
* Thu Jul 25 2019 Todd R <toddrme2178@gmail.com>
- 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
* Mon Dec 03 2018 Todd R <toddrme2178@gmail.com>
- Update to 2.9.5
* Missing values in pandas :class:`Category` series were creating
invalid R factors when converted (issue #493).
* Tue Aug 14 2018 schwab@suse.de
- Remove unused dependencies on blas libraries
- Don't exclude post-build-checks
* Wed Aug 08 2018 toddrme2178@gmail.com
- 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).
* Fri May 18 2018 jengelh@inai.de
- Ensure neutrality of description. Trim future goals from
description.
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