Changes in rpy2

Release 3.5.13

New features

  • R is setting a number of environment variables in a wrapper script. Those variables were not set by default by rpy2 and this could lead to issues (see issue #1033). The variables are now added to os.environ.

Bugs fixed

  • python -m rpy2.situation LD_LIBRARY_PATH could incorrectly truncate the value for LD_LIBRARY_PATH when the variable LD_LIBRARY_PATH is already defined.

Changes

  • The dependency on pytz, a deprecated package, was removed and replaced by a dependency to zoneinfo. If Python < 3.9 the package backports.zoneinfo is an added dependency.

  • The depency on tzlocal does no longer limit it to <5.0 (issue #1035).

  • Remove dependency on distutils in Python’s standard library. That package is deprecated and removed in Python 3.12 (see https://peps.python.org/pep-0632/ and issue #1040).

Release 3.5.12

New features

  • rpy2.rinterface.evalr_expr_with_visible() to evaluate an expression and return the visibility status of the value returned.

  • More events in the intialization and termination of an embedded R logged by rpy2.rinterface_lib.embedded.logger at INFO and DEBUG levels.

  • rpy2.robjects.R.__call__() has 2 named arguments “visible” and “print_r_warnings” to handle R “invisible” results and print R warnings at the end of the evaluation. Invisible results happen when doing rpy2.robjects.r(“x <- 1”). R will return the value of x “invisibly”. The default are invisible is True and print_r_warnings is True.

Bugs fixed

  • “R magic” cells are now show R warnings at the end of the evaluation of an R cell (#issue 226).

Changes

  • Evaluating a string as R code using rpy2.robjects.R.__call__() (e.g., rpy2.robjects.r(“1+2”)) now shows R warnings at the end of the evaluation by default.

  • rpy2.robjects.R.__call__() returns the results invisibly by default (see section “New features” for this release).

Release 3.5.11

New features

  • pandas.Categorical objects are now converted to R factor objects.

Bugs fixed

  • pandas 2.0 makes API-breaking changes that made conversion fail (issue #1013).

  • The default converter for R magic was dropping R factors to numpy arrays of integers rather than convert them to pandas Category (issue #1010).

Changes

  • The fix for issue #1010 (see above) changes the numpy conversion for R factors. It returns an arrays with the level factors rather than the integer codes for the levels.

  • rpy2.rojects.pandas2ri.py2rpy_categoryseries() raises a DeprecationWarning.

Release 3.5.10

New features

  • rpy2.situation reports cffi interface type information.

  • The ipython/jupyter R magic can now have jpeg as a default graphics format for static figures in addition to png and svg.

Bugs fixed

  • Building the path to the R shared library was incorrectly using the output of R CMD config LIBnn (issue #982).

  • R started raising warnings when calling formals on BUILTINSXP R objects. Internal functions in rpy.robjects.functions calling formals no longer propagate the warnings.

Release 3.5.9

New features

  • Type hints in rpy2 are now checked with mypy.

Bugs fixed

  • Building the path to the R shared library was incorrectly using the output of R CMD config LIBnn (issue #982).

  • R started raising warnings when calling formals on SPECIALSXP R objects. Internal functions rpy.robjects.functions calling formals no longer propagate the warnings.

  • The numpy converter was not turning NA_character_ into None (issue #979).

  • rpy2.situation included an eager import rpy2 that could cause a version

    mismatch error with some build/install toolchain (issue #984). The import is now lazy/delayed.

  • Installation targets pandas, all, and test now specify pandas>=1.2.0 (which should limit frequencies of issues like #998).

Changes

  • rpy2.robjects.conversion.Converter objects are no longer functioning context managers. An exception is now raised when trying to use it that way. The feature was introduced with rpy2-3.5.7 but it does not guarantee the locality of a context manager and can result in permanently changed conversion rules. The method rpy2.robjects.conversion.Converter.context() should be used instead.

Release 3.5.8

New features

  • Default value for the interactivity status of the embedded R as initialization is now a private variable _DEFAULT_R_INTERACTIVE in rpy2.rinterface_lib.embedded.

Bugs fixed

  • rpy2.rinterface.initr_checkenv() (aliased to rpy2.rinterface.initr()) did not include initialization parameters for interactive, _want_setcallbacks, and _c_stack_limit (issue #976).

  • The numpy converter was not listing R objects of type CHARSXP as vectors. This make R NA_character_ values wrapped in rpy2 Python objects to be passed as-is (issue #983).

Release 3.5.7

New features

  • rpy2.robjects.conversion.Converter objects are now also context managers. This makes the use of rpy2.robjects.conversion.localconverter() unnecessary as a converter can now be used directly with a Python with statement. The documentation was updated accordingly.

Bugs fixed

  • Building the C-extension could fail when the C compiler is not C99-compatible or requires to be specified C99 compatibility (issue #963).

  • With the “R magic”, converters in a local namespace were inadvertently skipped (the local namespace was not searched).

  • Calling rpy2.rinterface.rternalize() before the embedded R is initialized was ending with a segfault. It is now raising an rpy2.rinterface_lib/embedded/RNotReady (issue #971).

Changes

  • The default for the contextvars.ContextVar holding conversion rules (rpy2.robjects.conversion.converter) is now a dummy converter raising errors about missing conversion rules. This behavior helps with troubleshooting Python code using multithreading without fetching the context (see issue #965).

  • A warning is now issued when trying to convert a DataFrame with duplicate indexes (issue #811).

Release 3.5.6

Bugs fixed

  • rpy2.rlike.container.OrdDict objects were triggering an error when unpickled (PR #955).

  • Function signature mapping not longer assumes that all default values are R vectors mapped to a Vector instance (PR #954).

Release 3.5.5

New features

  • For ipython and Jupyter notebooks, R “magics” accepting optional input arguments (-i or –input) can now be of form <python-name> or <r-name>=<python-name>. The former is the way is has been working so far: the R object is given the name of the Python object. The latter allows to specify the name under which the input object will be known to R. In addition to that the python name can optionally be a path, that is a name nested in a sequence of namespaces. For example, -i module.varname. The magics concerned are %R, %%R, and %Rpush (issues #934 and #935).

  • For ipython and Jupyter notebooks, R “magics” accepting an optional conversion argument (-c/–converter) now also accepts names that are a path in Python, that is a name nested in a sequence of namespaces. For example, -c rpy2.robjects.default_converter (issue #934).

  • The “magic” %Rpush accepts an optional argument -c/–converter that is similar in nature to the argument of the same name in %R and %%R.

Bugs fixed

  • rpy2.rlike.container.TaggedList objects were triggering an error when unpickled (issue #947).

  • Converting pandas.Series of type “object” with a fallback to R strings no longer fails with an error (issue #916).

Changes

  • rpy2.robjects.help.Page.iteritems() is deprecated. Use the method items() instead.

  • Calling str() on rpy2 objects that are proxies of R objects is now using R’s print() whenever R’s show() results in an error (issue #908).

Release 3.5.4

New features

Bugs fixed

  • Better handling of timezone in rpy2.robjects.vectors.POSIXct (issue #917).

  • pandas conversion is now correctly handling R data frames with duplicated column names. They were dropped tbefore that (issue #925).

  • pandas conversion is now correctly handling R data frames with nested columns (issue #930).

  • Importing rpy2.ipython.rmagic while pandas is not installed resulted in an error.

Changes

  • rpy2.robjects.methods.getclassdef() is now explicitly naming the optional argument with the R package name when calling the underlying R function.

  • The %R line magic for ipython/jupyter was trying to substitute anything after a dolar ($) sign, which caused issue since this character is used to access by name elements in R containers. No substitution is happening anymore (issue #922).

Release 3.5.3

Bugs fixed

  • Pandas converter no longer fails with arrays of dtype pandas.BoolDtype or pandas.Float64Dtype.(issue #880).

  • Numpy and pandas conversion could fail an R object is a low-level wrapper for an R list (issue #890).

  • Fixed detection of the R install path on Windows (issues #875 and #885).

  • Fixed error with dynamic docstring generation for functions without arguments (issue #903).

  • Fixed error with dynamic docstring generation when R functions are missing the section ‘Details’ (isue #902).

Release 3.5.2

New features

  • The string representation for rpy2.robjects.conversion.Converter objects lists classes the converter will dispatch on.

Bugs fixed

  • rpy2.robjects.vectors.FactorVector.iter_labels() was failing if any element is NA (issue #879).

  • The definition of converters was not thread-safe. The fix deprecates the use of rpy2.robjects.conversion.converter and replaces it with rpy2.robjects.conversion.get_conversion().

Release 3.5.1

Bugs fixed

  • Fix __setitem__ on R list when the value is a simple Python object with a default low-level conversion (issue #864).

  • The default converter for the rmagic could fail with a RecursionError (issue #866).

Release 3.5.0

New features

  • rpy2.rinterface.NULL can be refererenced in code before the embedded R is initialized.

  • LD_LIBRARY_PATH is obtained from the executable RScript and set prior to initializing R at the rpy2.rinterface level (issue #833).

  • The package is now fully typed with type hints.

  • The rpy2.rinterface.evalr() accepts the named parameters envir and enclos, mirroring better the signature of the R function eval.

  • New function rpy2.rinterface.evalr_expr() to evaluate R expressions.

  • rpy2.situation is now using a module-level (called logger) to facilitate troubleshooting. When the module is run as an executable the flag –verbose can take the possible values DEBUG, INFO, WARNING, ERROR.

Changes

  • Better customizablity of conversion rules from R objects with typeof INTSXP (array of integers), VECSEXP (R list), and LGLSXP (array of booleans) pandas.

  • The representation of R integer is no longer using a comma separator for thousands (issue #797).

  • Requirement is now Python>=3.7. rpy2 is no longer tested with Python 3.6.

  • rpy2.robject.lib.grid was refactored to fix the conversion. This fixes issue #804. A classes now have a classmethod r for the R constructor (the __init__ is the Python constructor).

  • rpy2.robjects.vectors.__all__ is removed.

  • Cleaner class design by having rpy2.rinterface.NumpyArrayMixin removed and replaced by rpy2.rinterface.SexpVectorWithNumpyInterface.

  • With Python < 3.8 the module typing_extensions is now a requirement.

  • Initialization and update steps for rpy2.robjects.conversion.NameClassMap were updated to ensure type hints are correct. This probably solved cryptic bugs with conversion system.

  • rpy2.rinterface.LangSexpVector.from_string() was at the robject level (class method of rpy2.robjects.language.LangVector) but is now at the interface level.

  • rpy2.rinterface.get_evaluation_context() is deprecated. The module level context variable evaluation_context should be used instead. The use of the context variable should address issues when using nested rpy2.rinterface.local_context().

  • Added recommendation to try pandas.DataFrame.infer_objects() when the converion to R data frames fails because of mixed types (issue #794).

  • No longer implicit dependency on numpy for memory views. The Python API has an unresolved issue around handling FORTRAN-ordered arrays without going to C-level (https://bugs.python.org/issue34778), and C-extension as added to rpy2 to cut the dependency on numpy for just this (PR #856).

Bugs fixed

  • R warning about partial argument name matching is now cleared (issue #821).

  • Setting a slice for a StrSexpVector where some of the elements are not strings no longer fails.

  • Assigning items to an R array of strings using a slice of more than one element was likely to fail.

  • The rpy2.rinterface-level conversion of Python integers to R integers is now checking that integers are not larger than what R can handle.

  • Trying to access items in an R environment before R is initialized is no longer ending with a segfault (issue #842).

Release 3.4.6

  • Added a class and an alias to map ggplot2’s element_line (issue #822).

Release 3.4.5

Changes

  • The deprecation warning when using rpy2.robjects.lib.grid.activate() was missing (indirectly revealed through issue #804).

  • The named argument LINPACK in rpy2.robjects.vectors.Matrix.svd() is no longer present in R.

Bugs fixed

  • SIGPIPE sent to a process running Python+rpy2 could result in a segfault. This was caused by an incorrect setting of R signal handlers (issue #809).

Release 3.4.4

Changes

  • RRuntimeError exceptions raised while evaluating R code an R magic (ipython/jupyter) are now propagated (issue #792).

Release 3.4.3

New features

  • rpy2.robjects.lib.ggplot2 maps more functions in the R package (issue #767)

  • Utility function rpy2.robjects.lib.ggplot2.dict2rvec() to convert a Python Dict[str, str] into an R named vector of strings.

Bugs fixed

  • Calling mod:rpy2.situation to report on the environment no longer stops with an uncaught exception when no R home can be determined (issue #774)

  • 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)

  • The HTML representation of R list without named element was incorrect (issue #787)

  • Fix for when R is installed in a user home directory on Windows (PR #788)

Release 3.4.2

Bugs fixed

  • Multithreading during the initialization of the embedded R no longer triggers a fatal error (issue #729)

Changes

  • pytest is now an optional package. Optional sets of packages are numpy, pandas, test, and all (all optional packages). They can be specified during the installation. For example pip install rpy2[test]. (issue #670)

Release 3.4.1

Bugs fixed

  • The file requirements.txt was missing from the source distribution on pypi (issue #764).

Release 3.4.0

New Features

  • The mapping of the R C API now includes Rf_isSymbol().

  • Singleton class rpy2.rinterface_lib.sexp.RVersion to report the R version for the embedded R.

  • rpy2.rinterface.local_context() to create a context manager to evaluate R code within a local environment.

  • The staticmethod rpy2.robjects.vectors.DateVector.isrinstance() will tell whether an R objects is an R Date array.

Changes

  • The dynamic generation of docstrings for R man pages is now using R’s Rd2txt.

  • The rpy2.rinterface_lib._rinterface_capi._findVarInFrame() is replaced by the function rpy2.rinterface_lib._rinterface_capi._findvar_in_frame() (see fix to issue #710).

  • The functions rpy2.robjects.numpy.activate() and rpy2.robjects.pandas.activate() are deprecated and will be removed in rpy2-3.5.0.

  • rpy2.rinterface_lib.embedded.setinitialized() was renamed to rpy2.rinterface_lib.embedded._setinitialized() to indicate that one should not use it.

  • 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 of R/rpy2 objects to python objects using R class name mapping is extended to more classes. The documentation about conversion covers the topic.

  • If R_NilValue is not null when the initialization of the embedded R is attempted, it is now assumed that R was initialized through other means (e.g., an other C library in the same process) and the C-level initialization is be skipped.

  • The conversion rpy2py is now working with any Python object inheriting from _rinterface_capi.SupportsSEXP.

Bugs fixed

  • The C function Rf_findVarInFrame() in the R API can trigger in an R-level error, and while this is rare, when it does when embedded in Python it creates a segfault. Calls are now wrapped in R_ToplevelExec() to limit the propagation of R exceptions. This solved issue #710.

  • More complete and correct mapping of R class names in rpy2.rinterface_lib.sexp.rclass_get().

  • Initializing the embedded R caused the loss of ability to use Ctrl-C to send SIGINT to a Python process (issue #723)

  • rpy2.sitation is now working when the environment variable R_HOME is set even though R is not in the PATH or in the Windows registry (issue #744).

  • Handling an R language objects could result in a segfault when its R class was queried (issue #749).

  • 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).

  • Extracting documentation pages for R objects in packages could generate spurious warnings when several “section” tags are present.

  • R Date arrays/vectors were not wrapped into rpy2.robjects.vectors.DateVector objects but left as R arrays of floats (which they are at the C level).

  • The HTML representation of short R lists without names could fail with an error.

  • The __repr__() of robjects-level objects was not displaying the rpy2 class the R object is mapped to.

Release 3.3.6

Bugs fixed

  • The unit tests for importing R packages with lib_loc were broken (issue #720).

  • Trying to create a memoryview for an R array with complex values was failing with an attribute error.

  • Fix the constructor of metaclass rpy2.robjects.methods.RS4Auto_Type.

  • Fix call to end the embedded R in rpy2.robjects.R.__cleanup__ (issue #734).

Release 3.3.5

Bugs fixed

  • The callback handler to read input to R returned an invalid result, leading to R asking for input without ever acknowledging it received it.

Release 3.3.4

Bugs fixed

  • Creating an R vector object from a Python object implementing the buffer protocol could give incorrect results as C-level incompatibilities could be missed (issue #702).

  • rpy2.robjects.packages.importr() could fail when lib_loc was specified (issue #705).

Release 3.3.3

Bugs fixed

  • Fallback for when str2lang is missing (R < 3.6)

  • Fix segfault with PairListSexpVector.__getitem__() when elements of the R pairlist have a NILSXP name (issue #700)

Release 3.3.2

Bugs fixed

  • Initial fixes to have rpy2 running in ABI mode on Windows. Few tests are not passing (many in callbacks for R’s C API).

  • System detection is now checking for FreeBSD.

Release 3.3.1

Bugs fixed

  • rpy2.robjects.conversion.NameClassMap.update() can update the mapping (dict) or the default class.

Changes

  • Adding local converters was overwriting the base NameClassMap.

Release 3.3.0

New features

  • Trying to import an R package that is not installed will now raise an exception 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.

  • The module rpy2.situation can now return LD_LIBRARY_PATH information about R. For example with python -m rpy2.situation LD_LIBRARY_PATH

  • rpy2.robjects.methods.RS4.extends() lists the class names in the inheritance line.

  • The conversion of R objects to Python allows much more flexibility and better allow the use of independent code converting different classes. This is currently limited to R objects that are lists, environments, or S4 objects. The Sphinx documentation contains an example. While this is still work in progress this should already address concerns at the origin of issue #539 about S4 classes.

  • rpy2.robjects.language.LangVector to map R language objects at the robjects level.

  • rpy2.robjects.vectors.PairlistVector to map R pairlist objects at the robjects level.

  • An alternative function to display the output of R cells can be specified using -d or –display in the magic arguments (in rpy2.ipython.rmagic).

  • Python classes representing underlying R objects no longer have to exclusively rely on inheritance from rpy2.rinterface objects`. An abstract class rpy2.rinterface_lib.sexp.SupportsSEXP is added to identify objects supporting a __sexp__ protocol, and that abstract class can also be used with type hints.

  • rpy2.robjects.functions.wrap_r_functions() can create Python functions with matching signature from R functions

  • rpy2.robjects.functions.wrap_r_functions() can create Python functions with matching signature from R functions.

  • New class rpy2.rinterface_lib._rinterface_capi.UninitializedRCapsule to allow the instanciation of “placeholder” rpy2 objects before the embedded R is initialized. This facilitate the use of static typing checks such as mypy, mocking for tests that do not involve the execution of R code, and allow cleaner implementations of module-level globals that are R objects.

  • New class rpy2.robjects.vectors.DateVector to represent R dates.

  • pandas.Series containing date objects can now be converted to R Date vectors.

Changes

  • When calling R C-API’s R_ParseVector and a error occurs, the exception message now contains the parsing status.

  • rpy2.rinterface_lib.embedded has a module-level “constant” DEFAULT_C_STACK_LIMIT used when initializing the embedded R.

  • When creating a rpy2.robjects.vectors.DataFrame from (name, vector) pairs, the names are no longer transformed to syntactically valid R symbols (issue #660).

  • The value nan in pandas Series with strings is now converted to R NA (issue #668).

  • Initial support for pandas.NA (still experimental in pandas at the time of writing, and rpy2 support is limited to arrays of strings).

  • pandas series of dtype pandas.StringDType, experimental in pandas 1.0, are now supported by the converted (in the pandas-to-R direction) (issue #669)

  • Version checking for the mapping of R packages in rpy2.robjects.lib is now more permissive (check that version prefixes are matching).

Bugs fixed

  • Building ABI only mode could require an API build environment (and fail with an error when not present).

  • SVG output for the R magic were incorrectly bytes objects.

  • rpy2.rinterface_lib.sexp.StrSexpVector.__getitem__() was returning the string ‘NA’ when an R NA value. Not it returns rpy2.rinterface_lib.na_values.NA_Character.

Release 3.2.7

Bugs fixed

  • An f-string in _rinterface_cffi_build.py prevented installation on Python 3.5 (issue #654).

Release 3.2.6

Bugs fixed

  • The conversion of date/time object with specified timezones was wrong when different than the local time zone (issue #634)

  • Iterating over rpy2.situation.iter_info() could result in a error because of a typo in the code.

Changes

  • pandas 1.0.0 breaks the conversion layer. A warning is now emitted whenever trying to use pandas >= 1.0.

Release 3.2.5

Bugs fixed

  • Latest release for R package rlang broke import through importr(). A workaround for rpy2.robjects.lib.ggplot2 is to rename the offending R object (issue #631).

Changes

  • f-string requiring Python >= 3.6 removed.

Release 3.2.4

Bugs fixed

  • An incomplete backport of the bug fixed in 3.2.3 broke the ABI mode.

Release 3.2.3

Bugs fixed

  • Error when parsing strings as R codes could result in a segfault.

Release 3.2.2

Bugs fixed

  • Python format error when trying to report that the system is not reported on Windows (issue #597).

  • The setup script would error on build if R is not installed. It is now printing an error message.

Release 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 Sexp.names() to fail (issue #587).

  • Whenever the pandas conversion was activated FloatSexpVector instances with the R class POSIXct attached where not corrected mapped back to pandas datetime arrays. (issue #594).

  • Fix installation when an installation when a prefix without write access is used (issue #588).

Release 3.2.0

New features

  • rpy2 can built and used with 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 TypeError or a ValueError depending on the issue (rather than always ValueError before.

Bugs fixed

  • setup.py is now again compatible with Python2 (issue #580).

  • Unit tests were failing if numpy is not installed.

  • 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 (issue #537).

Release 3.1.0

New features

  • Python matrix multiplication (__matmul__ / @) added to R Matrix objects.

  • An threading.RLock is added to rpy2.rinterface_lib.openrlib and is used by the context manager 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 rpy2.rinterface_lib.embedded (set to None until R is initialized).

  • Unit tests are included in a subpackage rpy2.tests as was the case before release 3.0.0 (issue #528).

  • Experimental initialization for Microsoft Windows.

  • rpy2.situation is now also reporting the rpy2 version.

  • rpy2.robjecs.package_utils.default_symbol_check_after() was renamed rpy2.robjecs.package_utils.default_symbol_resolve(). The named parameters default_symbol_check_after present in few methods in rpy2.robjects.packages and rpy2.robjects.functions were modified to keep a consistent naming.

  • Trying to instantiate an rpy2.rlike.container.OrdDict with a a dict will result in a TypeError rather than a ValueError.

  • Methods of rpy2.rlike.container.OrdDict now raises a NotImplementedError when not implemented.

  • The creation of R vectors from Python sequences is now relying on a method _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 rpy2.robjects.lib.ggplot2 had stopped working with the R package ggplot2 reaching version 3.2.0. (issue #562).

  • Better handling of recent pandas arrays with missing values (related to issue #544).

  • 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 pandas (issue #561).

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 (issue #565).

Release 3.0.4

Bugs fixed

  • Fixed conversion of pandas Series of dtype pandas.Int32Dtype, or pandas.Int64Dtype (issue #544).

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 (issue #543).

  • Fixed conversion of pandas.Series of dtype “object” when all items are either all of the same type or are None (issue #540).

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” (issue #533).

  • Callback for console reset was not set during R initialization.

  • Fixed rternalized function returning rpy2 objects (issue #538).

  • –vanilla is no longer among the default options used to initialize R (issue #534).

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 (issue #524).

Release 3.0.0

New features

  • rpy2 can be installed without a development environment.

  • Unit tests are now relying on the Python module pytest.

  • rpy2.rinterface.NA_Integer is now only defined when the embedded R is initialized.

Changes

Bugs fixed

  • Row names in R data frames were lost when converting to pandas data frames (issue #484).

Known issues

  • Mismatch between R’s POSIXlt wday and Python time struct_time’s tm_wday (issue #523).

Release 2.9.6

Bugs fixed

  • Latest release of pandas deprecated DataFrame.from_items(). (issue #514).

  • Latest release of 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

Release 2.9.5

Bugs fixed

  • Missing values in pandas Category series were creating invalid R factors when converted (issue #493).

Release 2.9.4

Bugs fixed

  • Fallback for failure to import numpy or pandas is now dissociated from failure to import numpy2ri or pandas2ri (issue #463).

  • 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 rpy2.robjects.lib.dplyr.DataFrame (issue #473).

Release 2.9.3

Bugs fixed

  • Delegate finding where is local time zone file to either a user-specified module-level variable default_timezone or to the third-party module tzlocal (issue #448).

Release 2.9.2

Changes

  • The pandas converter is converting pandas.Series of dtype “O” to 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).

Release 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 pandas now handling R ordered factor (issue #398).

  • jinja2 was not listed as a dependency (issue #437).

Release 2.9.0

New features

  • New module rpy2.situation to extract and report informations about the environment, such as where is the R HOME, what is the version of R, what is the version of R rpy2 was built with, etc… The module is also designed to be run directly and provide diagnostics: python -m rpy2.situation.

  • Environment.values(), Environment.pop(), Environment.popitems(), Environment.clear() to match dict.values(), dict.pop(), dict.popitems(), dict.clear().

  • VectorOperationsDelegator now has a method __matmul__ to implement Python’s matrix multiplication operator (PEP-0645).

  • A rule to convert R POSIXct vectors to pandas Timestamp vectors was added (issue #418).

  • method _repr_html_() for R vectors to display HTML in jupyter.

Changes

  • Starting several times the singleton EventProcessor longer results in a RuntimeError. This is now only a warning, addressing issue #182.

  • The target version for the R package dplyr mapped is now 0.7.1, and rpy2.robjects.lib.dplyr.src_dt() (issue #357) and rpy2.robjects.lib.dplyr.src_desc() are no longer present.

  • Environment.keys() is now a iterator to match dict.keys(), also an interator in Python 3.

  • Target version of ggplot2 library is 2.2.1.

  • Option stringsasfactors in the constructor for the class DataFrame. If False, the strings are no longer converted to factors. When converting from pandas data frames the default is to no longer convert columns of strings to factors.

  • The R “magic” for jupyter is now more consistently using the conversion system, and the use of custom converters through the magic argument -c will work as expected.

  • Docker-related files moved to directory docker/ (where variants image for rpy2 are available)

Bugs fixed

  • numpy.float128() is not available on all platforms. The unit test for it is now skipped on systems where it is not present (issue #347)

  • R pairlist objects can now be sliced (and issue #380 is resolved).

  • Passing parameters names that are empty string to R function was causing a segfault (issue #409).

  • Trying to build an atomic R vector from a Python object that has a length, but it not a sequence nor an iterator was causing a segfault (issue #407).

Release 2.8.6

Bugs fixed

  • Trying to build an atomic R vector from a Python object that has a length, but it not a sequence nor an iterator was causing a segfault (issue #407 - backport from rpy2-2.9.0).

Release 2.8.5

Bugs fixed

  • The defintion of the method rpy2.rlike.container.OrdDict.items was incorrect, and so was the documentation for rcall (issue #383)

  • Giving an empty sequence to robjects.sequence_to_vector() is now raising a ValueError rather than fail with an UnboundLocalError (see issue #388).

  • robjects.robject.RSlots.items() is now working (see pull request #57).

Release 2.8.4

Bugs fixed

  • The context manager rpy2.robjects.lib.grdevices.render_to_file() is no longer trying to impose a file name generated by tempfile (issue #371)

  • The symbol LISTSXP (corresponding to R pairlist objects) was not imported from the C module in rpy2.

  • The functions scale_linetype_discrete and scale_linetype_continuous in ggplot2 were not wrapped by rpy2.robjects.lib.ggplot2 (issue #381)

Release 2.8.3

Bugs fixed

  • Fixed the error when the transformation of R “man” pages into Python docstrings was failing when the section “arguments” was missing (issue #368)

  • Failing to find R in the PATH during the installation of rpy2 is now printing an error message instead of a warning (issue #366)

Release 2.8.2

Bugs fixed

  • R’s dplyr::src_dt was moved to dtdplyr::src_dt with dplyr release 0.5.0. To address this, src_dt will become a None if the R package dplyr is discovered to be of version >= 0.5.0 at runtime. (issue #357)

  • Conversion issue when R symbols were accessed as attribute of the singleton rpy2.robjects.R. (issue #334)

  • The rmagic extension for ipython was no longer loading with the latest ipython (version 5.0.0). (issue #359)

Changes

  • The fix to issue #357 (see bugs fixed above) was expanded to cover all R packages wrapped in rpy2.robjects.lib and ensure that the respective Python modules can loaded even if symbols are no longer defined in future versions of the corresponding R packages.

Release 2.8.1

New features

Bugs Fixed

  • Trying to install rpy2 while R is not in the PATH resulted in an error in setup.py.

Release 2.8.0

New features

  • New class rpy2.robjects.SourceCode. The class extends Python’s str and is meant to represent R source code. An HTML renderer for the ipython notebook (syntax highlighting using pygment is also added).

  • New module rpy2.robjects.lib.tidyr providing a custom wrapper for the R library tidyr

  • The long-deprecated functions rpy2.rinterface.set_writeconsole() and rpy2.rinterface.get_writeconsole() are no longer available. One of rpy2.rinterface.set_writeconsole_regular() / rpy2.rinterface.set_writeconsole_warnerror() or rpy2.rinterface.get_writeconsole_regular() / rpy2.rinterface.get_writeconsole_warnerror() respectively should be used instead.

  • The attribute rpy2.robjects.RObject.slots can now be implictly interated on (the method __iter__() is now an alias for keys()).

  • The default Python-R conversion is now handling functions. This means that Python function can directly be used as parameters to R functions (when relevant).

  • Ipython display hook display_png for ggplot2 graphics.

  • pandas “category” vectors are better handled by the pandas conversion.

  • New module rpy2.robjects.lib.grdevices providing a custom wrapper for the R library ‘grDevices’, exposing few key functions in the package and providing context managers (render_to_file and render_to_bytesio) designed to simplify the handling of static plots (e.g., webserver producing graphics on the fly or figure embedded in a Jupyter notebook).

  • Numpy conversion is handling better arrays with dtype equal to “O” when all objects are either all inheriting from str or from bytes. Such arrays are now producing StrSexpVector or BytesSexpVector objects respectively.

  • R’s own printing of warnings if now transformed to warnings of type rinterface.RRuntimeWarning (it used to be a regular UserWarning)

  • The family of functions src_* and the function tbl in the R package dplyr have aliases in the module rpy2.robjects.lib.dplyr, and a class DataSource has been added for convenience.

  • rpy2.robjects.vectors.DataFrame has a method head corresponding to R’s method of the same name. The method takes the n first row of a data frame.

  • dplyr’s functions count_ and tally are now exposed as methods for the class dplyr.DataFrame.

Changes

  • Building/installing rpy2 with a development version of R does not require the use of option –ignore-check-rversion any longer. A warning is simply issue when the R version is “development”.

  • On MSWindows, the dependency on pywin32 was removed (issue #315)

  • GroupedDataFrame in the dplyr interface module is now inheriting from the definition of DataFrame in that same module (it was previously inheriting from robjects.vectors.DataFrame).

  • The default repr() for R objects is now printing the R classes (as suggested in issue #349).

Bugs Fixed

  • Parameter names to R function that are in UTF-8 are no longer causing a segfault (issue #332)

  • Looking for a missing key in an R environment (using __getitem__ or [) could raise a LookupError instead of a KeyError.

  • R environment can now handle unicode keys as UTF-8 (was previously trying Latin1)

  • rpy2 is interrupting attempts to install with Python < 2.7 with an informative error message (issue #338)

  • Setting the R class can be done by using a simple Python string (issue #341)

  • rpy2.robjects.lib.grid.viewport is now returning an instance of class Viewport (defined in the same module) (issue #350)

Release 2.7.9

Bug fixed

  • Python objects exposed to R could lead to segfault when the Python process is exiting (issue #331)

Release 2.7.8

Bugs fixed

  • American English spelling was missing for some of the function names to specify colour (color) scales.

  • Fix for printing R objects on Windows (pull request #47)

Release 2.7.7

Bugs fixed

  • Pickling robjects-level objects resulted in rinterface-level objects when unpickled (issue #324).

Release 2.7.6

Changes

  • 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.

Release 2.7.5

Bugs fixed

  • 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)

Release 2.7.4

Bugs fixed

  • Python 3.5 highlighted slightly incorrect C-level flags in rpy2 objects declarations, and rpy2.robjects could not be imported.

  • Fixed unit tests for rmagic when numpy is not installed, and for numpy is installed by pandas in missing.

Release 2.7.3

Bugs fixed

  • method DataFrame.collect() in rpy2.robjects.lib.dplyr was not functioning.

  • Applied patch by Matthias Klose to fix implict pointer conversions.

  • 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 rpy2.robjects.lib.dplyr

Release 2.7.2

Bugs fixed

  • methods distinct, sample_n, and sample_frac defined in the R package dplyr were missing from the DataFrame definition in rpy2.robjects.lib.dplyr

  • The fix for the inheritance problem with 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.

Release 2.7.1

Bugs fixed

  • The __repr__() for 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 dplyr.DataFrame had dplyr methods returning objects of their parent class.

Release 2.7.0

New features

  • New exception rpy2.rinterface.RParsingError. Errors occurring when parsing R code through rpy2.rinterface.parse() raise this exception (previously rpy2.rinterface.RRuntimeError).

  • New class rpy2.robjects.conversion.Converter to replace the namedtuple of the same name

  • New class rpy2.robjects.converter.ConversionContext. This is a context manager allowing an easy setting of local conversion rules. The constructor has an alias called rpy2.robjects.constructor.localconverter().

  • New module rpy2.robjects.lib.dplyr providing a custom wrapper for the R library dplyr

  • Method Environment.items() to iterate through the symbols and associated objects in an R environment.

  • Exception rpy2.rinterface.ParsingIncompleError, a child class of rpy2.rinterface.ParsingError, raised when calling 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 slots for rpy2.robjects-level objects. The attribute is a 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.

Bugs fixed

  • Conversion rules were not applied when parsing and evaluating string as R with rpy2.robjects.R.

  • Calling the constructor for 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).

Changes

  • rpy2.rinterface.is_initialized() is now a function.

  • 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)

Release 2.6.3

Bug fixed

  • Metaclass RS4Auto_Type facilitating the creation of Python classes from R S4 classes was not handling classes without methods (issue #301)

Release 2.6.2

Bugs fixed

  • 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 rpy2.robjects.R.

Release 2.6.1

New features

  • Because of their long names, the classes SignatureTranslatedAnonymousPackage, SignatureTranslatedPackage, and SignatureTranslatedFunction in rpy2.robjects.packages have now the aliases STAP, STP, and STF respectively.

Bugs fixed

  • 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)

Changes

  • Loading the ipython extension in the absence of pandas or numpy is now issuing a warning (issue #279)

Release 2.6.0

New features

  • 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 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 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)

Release 2.5.7

  • simplegeneric was moved of ipython 4.0.0 (pull request #43)

Release 2.5.6

Bugs fixed

  • Detection of the R version during setup on Win8 (issues #255 and #258)

  • Segmentation fault when converting pandas 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 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)

Release 2.5.5

Bugs fixed

  • 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)

Release 2.5.4

Bugs fixed

  • 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)

Release 2.5.3

Changes

  • 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).

Bugs fixed

  • 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.

Release 2.5.2

Bugs fixed

  • 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)

Release 2.5.1

Bugs fixed

  • 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)

Release 2.5.0

New features

  • 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.

Changes

  • The script setup.py was rewritten for clarity and ease of maintenance. Now it only uses setuptools.

Release 2.4.4

Bugs fixed

  • 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)

Release 2.4.3

Bugs fixed

  • 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

Release 2.4.0

Changes

  • Conversion system slightly changed, with the optional conversions for numpy and 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’).

  • 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 rpy2.robjects.Function, the __doc__ is now a property fetching information about the parameters in the R signature.

  • Convenience function rpy2.robjects.packages.data() to extract the datasets in an R pacakges

  • ipython’s rmagic is now part of rpy. To use, %load_ext rpy2.ipython from within IPython.

  • new method rpy2.rinterface.SexpEnvironment.keys(), returnings the names in the environment as a tuple of Python strings.

  • convenience class robjects.packages.InstalledPackages, with a companion function robjects.packages.isinstalled().

  • new class rinterface.SexpSymbol to represent R symbols

Bugs fixed

Release 2.3.10

Bugs fixed

  • setup.py build was broken when new R compiled with OpenMP (Issue #183)

Release 2.3.9

  • Changes in pandas 0.13.0 broke the rpy2 conversion layer (Issue #173)

Release 2.3.8

Bugs fixed

  • 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)

Release 2.3.7

Bugs fixed

  • ggplot2’s “guides” were missing

  • ggplot2’s “theme_classic” was missing (PR #143)

  • ggplot2’s “element_rect” was missing (PR #144)

  • rpy2.interactive.packages() was broken (PR #142)

Release 2.3.6

Bugs fixed

  • Several reports of segfault on OS X (since rpy2-2.3.1 - PR #109)

  • More fixes in converting DataFrames with dates from pandas

Relase 2.3.5

Bugs fixed

  • Missing mapping to ggplot2’s scale_shape_discrete function

  • Better handling of dates in Pandas

  • Constructor for POSIXct improved (and fixed)

Changes

  • The attribute rclass is no longer read-only and can be set (since R allows it)

  • Importing the module rpy2.interactive no longer activates event processing by default (triggering concurrency errors when used with ipython).

New features

  • New module rpy2.interactive.ipython (so far plotting automatically a ggplot2 figure in the iPython’s console)

  • It is now possible to set the rclass.

Relase 2.3.4

Bugs fixed

  • Spurious error when running unit tests with Python 3 and numpy installed

  • Missing mapping to ggplot2’s geom_dotplot function

  • Warnings are not longer printed (see Changes below)

Changes

  • Bumped target version of ggplot2 to 0.9.3.1

  • Warnings are not longer printed. The C-level function in R became hidden in R-3.0, and the cost of an R-level check/print is relatively high if the R code called is very short. This might evolve into printing warnings only if interactive mode in Python (if this can be checked reliably).

Release 2.3.3

Bugs fixed

  • Some of the data.frames converted from pandas were triggering a TypeError when calling repr()

  • In rpy2.robjects.lib.ggplot2, a mapping to coord_fixed was missing (PR #120)

  • Using the parameter lib_loc in a call to rpy2.robjects.packages.importr() was resulting in an error (PR #119)

  • Creating a layer through the rpy2.robjects.lib.ggplot2 interface did not accept parameters (PR #122)

  • Testing the Python version was crashing of a number of unsupported Python versions (<= 2.6) (PR #117)

New features

  • New module pandas2ri to convert from mod:pandas DataFrame objects

  • New classes rpy2.robjects.lib.grid.Unit and rpy2.robjects.lib.grid.Gpar to model their counterparts in R’s grid package as they were previously missing from rpy2.

Release 2.3.2

Bug fixed

  • Building on Win64 (pull request #6)

  • Fetching data from an R package through importr was masking any R object called data in that package. The data are now under the attribute name __rdata__. This is not completely safe either, although much less likely, a warning will be issued if still masking anything.

Changes

  • More informative error message when failing to build because R CMD config does not return what is expected

Release 2.3.1

Bugs fixed

  • default console print callback with Python (issue #112 linked to it)

  • deprecation warnings with ggplot2 (issue #111 and contributed patch)

Release 2.3.0

New Features

rpy2.rinterface:

  • C-level API, allowing other C-level modules to make use of utilities without going through the Python level. The exact definition of the API is not yet fixed. For now there is PyRinteractive_IsInitialized() to assess whether R was initialized (through rpy2.rinterface or not).

  • C-module _rpy_device, allowing one to implement R graphical devices in Python [(very) experimental]

  • Tracking of R objects kept protected from garbage collection by rpy2 is now possible.

  • New method Sexp.rid() to return the identifier of the R object represented by a Python/rpy2 object

rpy2.rinteractive:

  • Dynamic build of Python docstrings out of the R manual pages

rpy2.robjects.help:

  • Build dynamic help

rpy2.robjects.packages:

  • Build anonymous R packages from strings

  • When using importr(), the datasets are added as an attribute data, itself an instance of a new class PackageData. It no longer possible to access datasets are regular objects from a code package (because of changes in R), and the new system is more robust against quirks.

Changes

rpy2.rinterface:

  • SexpClosure.env to replace the method closureenv.

Release 2.2.6

Bugs fixed

  • Newest R-2.15 and ggplot2 0.9 broke the ggplot2 interaface in rpy2.robjects.lib.ggplot2

Release 2.2.5

Bugs fixed

  • install process: Library location for some of the R installations

  • should compile on win32 (thanks to a patch from Evgeny Cherkashin),

    a work to a limited extend

Release 2.2.4

Bugs fixed

  • Memory leak when creating R vectors from Python (issue #82)

Release 2.2.3

Bugs fixed

  • Dynamic construction of S4 classes was looking for R help as ‘class.<class>’ rather than ‘<class>-class’

  • The cleanup of temporary directories created by R was not happening if the Python process terminated without calline rpy2.rinterface.endr() (issue #68, and proof-of-principle fix by chrish42)

Release 2.2.2

Bugs fixed

  • With the robjects layer, repr() on a list containing non-vector elements was failing

Release 2.2.1

Bugs fixed

  • MANIFEST.in was missing from MANIFEST.in, required with Python 3

Release 2.2.0

New Features

  • Support for Python 3, and for some of its features ported to Python 2.7

rpy2.robjects:

rpy2.rinterface:

  • NA_Complex and NAComplexType for missing complex values.

  • SexpExtPtr to represent R objects of type EXTPTR (external pointers).

  • rpy2.rinterface.parse() to parse a string a R code

  • rpy2.rinterface.rternalise() to wrap Python function as SexpClosure that can be called by R just as it was a function of its own.

  • rpy2.rinterface.RNULLType for R’s C-level NULL value and rpy2.rinterface.UnboundValueType for R’s C-level R_UnboundValue (both singletons).

  • rinterface.SexpVector.index(), of similar behaviour to list.index().

  • rpy2.rinterface.Sexp.list_attrs() to list the names of all R attributes for a given object.

  • rpy2.rinterface.ByteSexpVector to represent R ‘raw’ vectors.

  • constant R_LEN_T_MAX to store what is the maximum length for a vector in R.

  • tuple R_VERSION_BUILD to store the version of R rpy2 was built against

  • getter Sexp.rclass to return the R class associated with an object

rpy2.rlike:

  • container.OrdDict get proper methods keys() and get

rpy2.interactive:

  • A new sub-package to provide utilities for interactive work, either for handling R interactive events or use Python for interactive programming (as often done with the R console)

Changes

rpy2.robjects:

  • NA_bool, NA_real, NA_integer, NA_character and NA_complex are now deprecated (and removed). NA_Logical, NA_Real, NA_Integer, NA_Character, NA_Complex should be used.

  • rpy2.robjects.packages.Package now inherits from types.ModuleType

  • classes representing R vector also inherit their type-specific rinterface-level counterpart.

  • Importing the rpy2.robjects.numpy2ri is no longer sufficient to active the conversion. Explicit activation is now needed; the function activate can do that.

rpy2.rinterface:

  • IntSexpVector, FloatSexpVector, StrSexpVector, BoolSexpVector, ComplexSexpVector are now defined at the C level, improving performances and memory footprint whenever a lot of instances are created.

Bugs fixed

  • Better and more explicit detection system for needed libraries when compiling rpy2 (ported to release 2.1.6)

  • Long-standing issue with readline fixed (issue #10)

Release 2.1.9

Bugs fixed

  • The R class in rpy2.robjects is now truly a singleton

  • When using numpy 1.5 and Python >= 2.7, the exposed buffer for R numerical (double) vectors or arrays was wrong.

Release 2.1.8

Bugs fixed

  • Fixed issue with R arrays with more than 2 dimensions and numpy arrays (issue #47 - backported from the branch 2.2.x).

Release 2.1.7

Bugs fixed

  • More fixes for the automated detection of include and libraries at build time.

Release 2.1.6

Bugs fixed

  • Further fixes in the automatic detection of includes and libraries needed to compile rpy2 against R. The detection code has been refactored (backport from the 2.2.x branch)

Release 2.1.5

Bugs fixed

  • fixes the automatic detection of R_HOME/lib during building/compiling when R_HOME/lib is not in lib/ (issue #54)

Release 2.1.4

New features

  • rpy2.robjects.lib.ggplot2 now has the functions limits(), xlim(), ylim() exposed (patch contributed anonymously)

Bugs fixed

  • Install script when the BLAS library used by R is specified as a library file (patch by Michael Kuhn)

Release 2.1.3

Bugs fixed

  • Spurious error message when using DataFrame.from_csvfile() without specifying col_names or row_names

  • Patch to finally compile with Python < 2.6 (contribDuted by Denis Barbier)

Release 2.1.2

New Features

rpy2.robjects:

  • NA_Logical, NA_Real, NA_Integer, NA_Character from rpy2.rinterface are imported by robjects.

Changes

rpy2.robjects:

  • NA_bool, NA_real, NA_integer, NA_character and NA_complex are now robjects-level vectors (they were rinterface-level vectors). Consider using the rinterface-defined NAs instead of them.

Bugs fixed

  • Missing conditional C definition to compile with Python 2.4 # issue 38

  • Fixed error when calling robjects.vectors.Vector.iteritems() on an R vector without names

  • Fixed automatic conversion issues (issue #41)

Release 2.1.1

Bugs fixed

  • Issues with NA values # issue 37

  • Missing manual scale functions in rpy2.robjects.lib.ggplot2 # issue 39

Release 2.1.0

New Features

rpy2.robjects:

  • Method formals() for Function (formerly RFunction)

  • Methods slotnames(), isclass(), and validobject() for RS4

  • Vector-like objects now in a module rpy2.robjects.vectors

  • set_accessors() for adding simply accessors to a class inheriting from RS4

  • RS4_Type for metaclass-declared accessors

  • Delegating classes ExtractDelegator and DoubleExtractDelegator for extracting the R-way

  • DataFrame (formerly RDataFrame) can now be created from :rlike.container.OrdDict instances, or any other object inheriting from dict.

  • FactorVector to represent R factors

  • the conversion is now returning subclasses of robjects.vectors.Vector -formerly RVector- (such as IntVector, FloatVector, etc…) rather than only return Vector

  • StrVector has a method factor() to turn a vector of strings into an R factor

  • Matrix was added the methods: dot(), svd(), crossprod(), tcrossprod(), transpose().

  • IntVector.tabulate() to count the number of times a value is found in the vector

  • Vector.sample() to draw a (random) sample of arbitrary size from a vector

  • NA_Bool, NA_Real, NA_Integer, NA_Character, NA_Complex as aliases for R’s missing values.

  • ComplexVector for vectors of complex (real + imaginary) elements

  • packages to provide utility functions to handle R packages (import of R packages)

  • functions to provide classes related to R functions, with the new class SignatureTranslatedFunction

  • DataFrame.iter_row() and DataFrame.iter_column(), iterating through rows and columns respectively.

  • DataFrame.cbind() and DataFrame.rbind() for binding columns or rows to a DataFrame.

  • Vector.iteritems() to iterate on pairs of names and values.

  • Robject.__rname__ to store the “R name”

rpy2.rinterface:

  • New functions for specifying callback functions for R’s front-ends: set_showmessage(), set_flushconsole(), set_choosefile(), set_showfiles()

  • New object MissingArg, exposing R’s special object for representing a “missing” parameter in a function call. (#this was first a patch by Nathaniel Smith with a function getMissingArgSexp)

  • Initial commit of a callback-based implementation of an R graphical device (this is for the moment very experimental - and not fully working)

  • SexpClosure.rcall() is now taking 2 parameters, a tuple with the parameters and an SexpEnvironment in which the call is to be evaluated.

  • Sexp.__sexp__ now has a setter method. This permits the rebinding of the underlying R SEXP, and allows to expose foo<- type of R methods as Python function/methods with side effects.

  • Objects of R type RAWSXP are now exposed as instances of class SexpVector.

  • Factory function unserialize() to build Sexp* instances from byte string serialized with R’s own ‘serialize’.

  • Method Sexp.__reduce__() for pickling/unpickling

  • Ability to specify a callback function for R_CleanUp (called upon exiting R) through get_cleanup() and set_cleanup() [very experimental]

  • Class ListSexpVector for creating R lists easily (complementing IntSexpVector, StrSexpVector, and friends)

  • colnames(), rownames() for Array (formerly RArray) are now property-style getters

  • Pairlists (LISTSXP) now handled

  • Experimental function set_interactive() to set whether R is in interactive mode or not (#following an issue reported by Yaroslav Halchenko)

  • New object R_NilValue, exposing R’s special object for representing a “NULL”.

  • ComplexSexpVector for vectors of complex (real + imaginary) elements

  • Scalar Python parameters of type int, long, double, bool, and None in a call (using SexpClosure) are now automatically converted to length-one R vectors (at the exception of None, converted to R_NilValue).

  • Python slices can now be used on R vector-like objects

  • Better handling of R’s missing values NA, NA_integer_, NA_real_, and NA_character_.

rpy2.rlike:

  • iteritems() for OrdDict (formerly:class:ArgDict) and TaggedList

  • static method from_iteritems() for TaggedList, for creating a TaggedList from any object having a method iteritems()

Changes

  • The setup.py script is now taking command-line arguments when specifying R library-related paths are wished. python setup.py –help build_ext will list them

rpy2.robjects:

  • RS4 no longer makes R’s slots as Python attributes through __attr__()

  • The package is split into modules

  • The broken variables NA_STRING, NA_INTEGER, NA_LOGICAL, and NA_REAL are removed. The documentation on missing values was revised.

  • globalEnv and baseNameSpaceEnv were renamed to globalenv and baseenv respectively

  • The parameter wantFun in Environment.get() (formerly REnvironment.get()) is now wantfun

  • Vector.r does not have a __getitem__ method any longer (see in .rx and .rx2 in the new features)

  • colnames(), rownames(), nrow(), ncol() for DataFrame are now property-style getters

  • nrow(), ncol() for Array are now property-style getters

  • static method from_csvfile() and instance method to_csvfile() for DataFrame

  • module lib to store modules representing R packages

  • module lib.ggplot2 for the CRAN package ggplot2.

  • renaming of few classes, the R prefix: Formula (from RFormula), DataFrame (from RDataFrame), Array (from RArray), Matrix (from RMatrix), Environment (from REnvironment), Function (from RFunction), Vector (from RVector).

  • robjects.vectors.Vector lost the (now redundant) methods subset and assign. Those operations were just aliases to the ExtractDelegator

rpy2.rinterface:

  • globalEnv, baseNameSpaceEnv, and emptyEnv were renamed to globalenv, baseenv and emptyenv respectively

  • The parameter wantFun in SexpEnvironment.get() is now wantfun

  • The call-back getters and setters are now get_readconsole(), set_readconsole(), get_writeconsole(), set_writeconsole(), get_flushconsole(), and set_flushconsole().

  • Functions also accept named parameters equal to Py_None, and transform them to R NULL (previously only accepted parameters inheriting from Sexp).

rpy2.rlike:

  • ArgDict becomes OrdDict.

  • tags() of TaggedList is now a property (with a getter and a setter)

rpy2.rpy_classic:

  • R named lists are returned as Python dict, like rpy-1.x does it, with the notable difference that duplicate names are not silently overwritten: an exception of class ValueError is thrown whenever happening

Bugs fixed

  • REnvironment.get() now accepts a named parameter wantFun (like rinterface.SexpEnvironment() does)

  • rinterface.SexpVector will now properly raise an exception when trying to create vector-like object of impossible type

  • Crash when trying to create a SexpVector of a non-vector type

  • R objects of class matrix are now properly converted into RMatrix (instead of Array)

  • Robj.as_py() was not working at all (and now it does to some extent)

Release 2.0.7

Bugs fixed

  • On win32, printing an object was leaving an open file handle behind each time, leading to an error and the impossibility to print (# bug report and fix by Christopher Gutierrez)

Release 2.0.6

No user-visible change. Win32-specific additions to the C module were made to compile it.

Release 2.0.5

Bugs fixed

  • Crash when calling SexpEnvironment.get() with an empty string #bug report by Walter Moreira

  • SexpEnvironment.__getitem__() called with an empty string caused unpredictable (and bad) things

Release 2.0.4

Bugs fixed

  • Added missing named parameter wantfun to method REnvironment.get() (making it similar to SexpEnvironment.get())

  • Leak in reference counting when creating SexpVector objects fixed (the symptom was a process growing in size when creating R vector from Python list or numpy arrays)

  • R CMD config LAPACK_LIBS could return an empty string when R was compiled with the veclib framework, causing the setup.py script to raise an exception. setup.py now only print a message about an empty string returned from R CMD config

  • Numpy arrays with complex elements are no longer causing segfaults

  • Calls to SexpClosure.rcall() with something else that the expected kind of tuple could cause a segfault

Release 2.0.3

New Features

rpy2.rinterface:

  • process_revents(), a Wrapper for R_ProcessEvents (# suggested by June Kim to help with issues related to interactive display on win32), and for R_RunHandlers on UNIX-like systems (# patch by Nathaniel Smith).

  • All callbacks are getting a get<callback> to complement the set<callback>. (# Patch by Nathaniel Smith)

  • Sexp.__deepcopy__() to copy an object (calling Rf_Duplicate)

    (# from a patch by Nathaniel Smith)

Changes

  • the default for reading and writing the console are now using sys.stdin and sys.stdout (# patch submitted by Nathaniel Smith)

  • console IO callbacks (reading and writing) are complemented by one to flush the console

  • Sexp.do_slot_assign() now creates the slot if missing (design-fix - # patch by Nathaniel Smith)

Bugs fixed

  • fixed problem of numpy interface with R boolean vectors. They are now presented as ‘i’ rather than ‘b’ to numpy (# patch submitted by Nathaniel Smith)

  • The mechanism for setting arbitrary callaback functions for console I/O now ensures that a traceback is printed to stderr whenever an error occurs during the evalutation of the callback (the raised exception used to be silently propagated to the next python call, leading to problems).

Release 2.0.2

Bugs fixed

  • Fix installation bug when the include directories contain either ‘-’ or ‘I’ #spotted by James Yoo

  • Failing to initialize R now throws a RuntimeError

  • Copying an R “NA” into Python returns a None (and no longer a True) (#fixes a bug reported by Jeff Gentry)

Release 2.0.1

New features

rpy2.robjects:

  • Property names for the RVector methods getnames() and setnames() (this was likely forgotten for Release 2.0.0).

  • Property rclass for RObjectMixin

Changes

rpy2.robjects:

  • rclass() becomes getrclass()

Bugs fixed

  • Having the environment variable R_HOME specified resulted in an error when importing rpy2.rinterface # root of the problem spotted by Peter

  • Setup.py has no longer a (possibly outdated) static hardcoded version number for rpy2

  • Testing no longer stops with an error in the absence of the third-party module numpy

  • rpy2.rlike.container.TaggedList.pop() is now returning the element matching the given index

Release 2.0.0

New features

  • New module rpy2.robjects.conversion.

  • New module rpy2.robjects.numpy2ri to convert numpy objects into rpy2 objects. # adapted from a patch contributed by Nathaniel Smith

Changes

  • RObject.__repr__() moved to RObject.r_repr()

Bugs fixed

  • Informative message returned as RuntimeError when failing to find R’s HOME

  • Use the registry to find the R’s HOME on win32 # snatched from Peter’s earlier contribution to rpy-1.x

Release 2.0.0rc1

rpy2.rpy_classic:

  • rpy_classic.RObj.getSexp() moved to a property rpy_classic.Robj.sexp.

rpy2.robjects:

  • RObject.__repr__() moved to RObject.r_repr()

  • ri2py(), ro2py(), and py2ri() moved to the new module conversion. Adding the prefix conversion. to calls to those functions will be enough to update existing code

Bugs fixed

  • Informative message returned as RuntimeError when failing to find R’s HOME

  • Use the registry to find the R’s HOME on win32 # snatched from Peter’s earlier contribution to rpy-1.x

Release 2.0.0rc1

New features

  • added __version__ to rpy2/__init__.py

rpy2.robjects:

  • added classes StrVector, IntVector, FloatVector, BoolVector

rpy2.rinterface:

  • added missing class BoolSexpVector.

Changes

rpy2.robjects:

  • does not alias rinterface.StrSexpVector, rinterface.IntSexpVector, rinterface.FloatSexpVector anymore

  • Constructor for rpy2.robjects.RDataFrame checks that R lists are data.frames (not all lists are data.frame)

  • Formerly new attribute _dotter for R is now gone. The documentaion now points to rpy2.rpy_classic for this sort of things.

Bugs fixed

  • conditional typedef in rinterface.c to compile under win32 # reported and initial proposed fix from Paul Harrington

  • __pow__ was missing from the delegator object for robjects.RVector (while the documentation was claiming it was there) # bug report by Robert Nuske

  • Earlier change from Sexp.typeof() to getter Sexp.typeof was not reflected in rpy2.rpy_classic # bug report by Robert Denham

Release 2.0.0b1

New features

rpy2.robjects:

  • added setenvironment() for RFormula, and defined environment as a property

  • defined names as a property for RVector

rpy2.rinterface:

  • added functions get_initoptions() and set_initoptions().

  • new attribute _dotter for R singleton. Setting it to True will translate ‘_’ into ‘.’ if the attribute is not found

Changes

rpy2.robjects:

  • constructor for RDataFrame now now accepts either rlike.container.TaggedList or rinterface.SexpVector

rpy2.rinterface:

  • sexpTypeEmbeddedR() is now called str_typeint().

  • initOptions is now called initoptions. Changes of options can only be done through set_initoptions().

Bugs fixed

  • crash of Sexp.enclos() when R not yet initialized (bug report #2078176)

  • potential crash of Sexp.frame() when R not yet initialized

  • proper reference counting when handling, and deleting, Sexp.__sexp__ generated CObjects

  • setup.py: get properly the include directories (no matter where they are) #bug report and fix adapted from Robert Nuske

  • setup.py: link to external lapack or blas library when relevant

  • added a MANIFEST.in ensuring that headers get included in the source distribution #missing headers reported by Nicholas Lewin-Koh

  • rinterface.str_typeint() was causing segfault when called with 99

  • fixed subsetting for LANGSXP objects

Release 2.0.0a3

New features

rpy2.rinterface:

  • setReadConsole(): specify Python callback for console input

  • R string vectors can now be built from Python unicode objects

  • getter __sexp__ to return an opaque C pointer to the underlying R object

  • method rsame() to test if the underlying R objects for two Sexp are the same.

  • added emptyEnv (R’s C-level R_EmptyEnv)

  • added method Sexp.do_slot_assign()

rpy2.robjects:

  • R string vectors can now be built from Python unicode objects

rpy2.rlike:

  • module functional with the functions tapply(), listify(), iterify().

  • module indexing with the function order()

  • method TaggedList.sort() now implemented

Changes

rpy2.rinterface:

  • initEmbeddedR() is only initializing if R is not started (no effect otherwise, and no exception thrown anymore)

  • the method Sexp.typeof() was replaced by a Python getter typeof.

  • the method Sexp.named() was replaced by a Python getter named.

  • R objects of type LANGSXP are now one kind of vector (… but this may change again)

  • R objects of type EXPRSXP are now handled as vectors (… but this may change again)

  • initEmbeddedR() renamed to initr()

  • endEmbeddedR() renamed to endr()

rpy2.robjects:

  • R remains a singleton, but does not throw an exception when multiple instances are requested

Bugs fixed

  • unable to compile on Python2.4 (definition of aliases to Python2.5-specific were not where they should be).

  • overflow issues on Python 2.4/64 bits when indexing R vector with very large integers.

  • handling of negative indexes for SexpVector’s __getitem__() and __setitem__() was missing

  • trying to create an instance of SexpVector before initializing R raises a RuntimeException (used to segfault)

  • experimental method enclos() was not properly exported

  • setup.py was exiting prematurely when R was compiled against an existing BLAS library

  • complex vectors should now be handled properly by rpy2.rinterface.robjects.

  • methods rownames() and colnames() for RDataFrame were incorrect.

Release 2.0.0a2

New features

rpy2.rlike:

rpy2.rinterface:

  • method named(), corresponding to R’s C-level NAMED

  • experimental methods frame() and enclos() for SexpEnvironment corresponding to R’s C-level FRAME and ENCLOS

  • method rcall() for ClosureSexp

  • new experimental class SexpLang for R language objects.

Bugs fixed

  • R stack checking is disabled (no longer crashes when multithreading)

  • fixed missing R_PreserveObject for vectors (causing R part of the object to sometimes vanish during garbage collection)

  • prevents calling an R function when R has been ended (raise RuntimeException).

Release 2.0.0a1

New features

rpy2.robjects:

  • method getnames() for RVector

  • experimental methods __setitem__() and setnames() for RVector

  • method ‘getnames’ for RArray

  • new class RFormula

  • new helper class RVectorDelegator (see below)

  • indexing RVector the “R way” with subset is now possible through a delegating attribute (e.g., myvec.r[True] rather than myvec.subset(True)). #suggested by Michael Sorich

  • new class RDataFrame. The constructor __init__() is still experimental (need for an ordered dictionnary, that will be in before the beta

  • filled documentation about mapping between objects

Changes

  • many fixes and additions to the documentation

  • improved GTK console in the demos

  • changed the major version number to 2 in order to avoid confusion with rpy 1.x # Suggested by Peter and Gregory Warnes

  • moved test.py to demos/example01.py

rpy2.robjects:

  • changed method name getNames to getnames where available (all lower-case names for methods seems to be the accepted norm in Python).

Bugs fixed

rpy2.robjects:

  • fixed string representation of R object on Microsoft Windows (using fifo, not available on win32)

  • __getattr__() for RS4 is now using ri2py()

rpy2.rinterface:

  • fixed context of evaluation for R functions (now R_GlobalEnv)

Release 1.0a0

  • first public release