High-Performance Open-Source Archive
Internal updates to avoid R_NamespaceRegistry and
R_UnboundValue in compiled code on R-devel (4.6)
(#1894).
Internal updates to remove Rf_findVar* calls in
compiled code on R-devel (4.6) (#1892).
Internal updates for Rcpp compatibility around
Rf_error handling (#1887).
Fixed py_list_packages() for uv-managed
environments. (#1890, #1891)
Positron now supports F1 help for reticulate Python objects (#1866).
Reticulate now supports pandas 3.0 (#1874, #1875).
py_require() now allows action = "add"
for already-required packages after Python initialization, while still
erroring on true version conflicts (@JBGruber, #1872, #1878).
py_to_r() now converts direct pandas categorical
objects (for example, pd$Categorical(...)) for pandas 2.x
and 3.x (#1883).
Positron now handles reticulate-backed UI actions, such as restarting or creating a new session, more reliably (#1869, #1871).
Reticulate now avoids spurious
Error: ignoring SIGPIPE signal messages on Unix when
embedded Python writes to a closed pipe (#1868).
Reticulate no longer triggers a CRAN NOTE on R-devel (4.6) for relative vignette URLs (#1882).
virtualenv_starter() now excludes free-threaded
CPython builds, which are not supported by reticulate (#1883).
The default Python version in install_python() and
conda_create() is now 3.12 (#1862).
Fix error in
virtualenv_create()/virtualenv_starter()
(#1861).
Fix display of Python variables in the Positron Variables Pane (#1859).
Reticulate now clears its cache automatically every 120 days.
Configure the interval in .Rprofile with:
options(reticulate.max_cache_age = as.difftime(30, units = "days")).
install_miniconda() now installs miniforge instead
of miniconda (#1800, #1820).
New helpers for reading and writing requirements files,
py_write_requirements() and
py_read_requirements() (#1846).
Adds support for requesting Python versions with a wildcard
pattern x.x.* such as ==3.12.* in
virtualenv_starter(), py_require(), and
related functions (#1825)
Restored compatability with uv versions >= 0.8.0
(#1818).
virtualenv_starter() now discovers Python
installations managed by external uv installations
(#1849).
py_require() now gives a better message when a user
erroneously declares a module from the Python standard library as a
required package (@lazappi, #1788)
Positron’s reticulate integration will now be automatically enabled when the reticulate package is loaded in Positron (#1822).
with() now forwards errors to Python context manager
exit handlers (e.g., so database transactions can roll back cleanly)
(#1840, #1841)
Fixed !! in string literals being wrongly expanded
to a %system magic in repl_python(). Added
support for assigning %system command output to multiple
variables via unpacking (#1844).
reticulate now warns when py_require()d packages are
not found in the selected Python virtual environment. This behavior can
be disabled by setting the environment variable
RETICULATE_CHECK_REQUIRED_PACKAGES=0 (#1850).
Fixed usage of micromamba and mamba, next-generation conda environment management tools. reticulate now prefers to use micromamba, mamba, then conda when managing environments (@gdevenyi, #1771).
Added str(), dim(), and
t() S3 methods for NumPy Arrays.
Fixed a segfault observed on R session exit (#1785, #1786).
Added check in install_miniconda() if existing files
will be overwritten. (#1794, #1796)
Fixed error in install_python() under R 4.5 when the
requested Python version has a ":latest" suffix, as it does
by default. (#1792, #1797)
Fixed error in get_python_conda_info() when conda
not found through conda-meta/history and NULL
is passed to normalizePath (#1184)
Hotfix to pin uv version resolved by reticulate to
<0.8.0. (#1812)
Python discovery by uv is much faster now. The
internal utility uv_python_list() searches only for managed
python environments by default. Users can request discovery of system
pythons by setting UV_PYTHON_PREFERENCE. Also,
uv_python_list() will now discover pyenv pythons and python
binaries installed by install_python() if a system python
is requested. (#1810)
Fixed an issue in RStudio on Windows where interrupts were ignored while Python code was executing (#1753).
Updates for Positron to fix issues with
repl_python() and Variables Pane (#1755).
Fixed an issue where [ received Python objects as
slice arguments. e.g., x[start:end] when start
or end were Python objects (#1731).
The [ method will now translate symbol
.. to a Python Ellipsis .... (#1763)
The [ method can now accept index values greater
than 2^31 (#1769)
Reticulate-managed uv can now resolve
system-installed Pythons, supporting platforms where pre-built binaries
are unavailable, such as musl-based Alpine Linux (#1751,
#1752).
uv_run_tool() gains an exclude_newer
argument (#1748).
py_register_load_hook() is now exported to enable
usage described in the “Using reticulate in an R package vignette”
(#1754).
https://rstudio.github.io/reticulate/articles/package.html
Internal changes to support R-devel (4.5) and R API updates (#1747, #1774).
Internal fixes to prevent reticulate-managed uv from
writing outside reticulates cache directory (#1745).
Fixed an issue with pointing reticulate at a pyenv shim python (#1758)
New py_require() function for declaring Python
requirements for the current R session. For details, see updated
vignettes and help:
py_require() help:
https://rstudio.github.io/reticulate/dev/reference/py_require.htmlNew uv_run_tool() function for running command line
tools distributed via Python packages.
Raw R arrays and NumPy arrays with dtype “V1” (“void8”) now
convert between each other. Use r_to_py(as.array(x)) to
efficiently convert raw vectors to NumPy arrays, and
py_to_r(array$view("V1")) to efficiently convert NumPy
arrays to raw vectors. (#1734)
Fixed an issue with using Python 3.12 on Linux (#1712, #1714).
Fixed an issue where virtualenv_starter() would not
discover a custom built Python (#1704).
The S3 classes for some (rarely encountered) Python objects have
changed. Only Python objects with non-standard __module__
values are affected. If a Python object’s parent class’s
__module__ attribute does not resolve to a string,
reticulate:
__name__. (See #1686 for more context)Added support for Python 3.13. Note that Python 3.13 removed
support for classmethod descriptors, which may affect the
S3 class of some Python objects that use metaclass properties to resolve
a class’s __module__ or __name__ attribute.
(#1686, #1698)
py_is_null_xptr() and [[ now load
delayed modules (#1688).
Fixed error when attempting to use a python venv created with
uv (#1678)
Resolved an issue where py_discover_config()
attempted to detect Windows App Store Python installations. These are
now excluded from discovery by both py_discover_config()
and virtualenv_starter() (#1656, #1673).
Fixed an error when converting an empty NumPy char array to R (#1662).
Fixed an error when using reticulate with radian (#1668, #1670).
Fixed a segfault encountered when running the Python session finalizer (#1663, #1664).
Resolved a segfault in RStudio when rapidly switching between R and Python chunks in a Quarto document (#1665).
Improved behavior when the conda binary used to create an environment cannot be resolved (contributed by @tl-hbk, #1654, #1659).
Added Positron support for the Variables Pane and
repl_python() (#1692, #1641, #1648, #1658, #1681,
#1687).
Python background threads can now run in parallel with the R session (#1641).
py_main_thread_func() is deprecated; every R
function can now safely be called from background Python threads
(#1648).
Calls from Python threads into R now notify the main thread using R’s native event loop, ensuring that these calls are handled even when the main thread is engaged in non-Python tasks (#1648).
The knitr engine now avoids overwriting Altair’s default chart
dimensions with the values of ut.width.px and
ut.height.px. Use altair.fig.height,
altair.fig.width, or Altair’s width and
height parameters to adjust chart dimensions (contributed
by @joelostblom,
#1646).
New as.character() method for
python.builtin.str with support for handling embedded NULs
in strings (#1653).
New as.raw() method for
python.builtin.bytes (#1649, #1652).
as.character() method for
python.builtin.bytes gains a nul argument,
allowing for convenient handling of embedded NULs in the string
(#1652).
Reticulate now uses the RETICULATE_VIRTUALENV_ROOT
environment variable when determining where to resolve virtual
environments (#1657).
conda_run2() is now exported (contributed by @dramanica,
#1637).
The Python session is now finalized when the R session exits (#1648).
Internal updates for NumPy 2.1 (#1651).
Fixed error when importing a module named config
(#1628).
Fixes for CRAN check failures on macOS-oldrel (#1645).
Fixed an error where opening a Python subprocess in Positron on Windows resulted in “OSError: [WinError 6] The handle is invalid.” (#1658, posit-dev/positron#4457).
Python Exceptions converted to R conditions are now R lists instead of R environments, for compatability with {rlang} and {purrr}. (tidyverse/purrr#1104, r-lib/rlang#1664, #1617)
Internal updates for NumPy 2.0 (#1621)
Added support for converting NumPy StringDType arrays to R character arrays. (#1623)
Internal updates for compliance with R’s upcoming formalized C API. (#1625)
Fixed an issue where attempting to convert a NumPy array with a non-simple dtype to R would signal an error. (#1613, fixed in #1614).
Interrupting Python no longer leads to segfaults. (#1601, fixed in #1602)
Print method for Python callables now includes the callable’s signature. (#1605, #1607)
Reticulate now installs successfully on Windows ARM64. (#1609, contributed by @andrjohns)
virtualenv_starter() no longer warns when
encountering broken symlinks. (#1598)
Fixed an issue where configuration for reticulate
conda_* functions to use the executable mamba
instead of conda was ignored. (#1608, contributed by @AlexandreGuinaudeau)
Fix issue where py_to_r() method for Pandas
DataFrames would error if py_to_r() S3 methods were defined
for Pandas subtypes, (as done by {anndata}) (#1591).
“Python Dependencies” vignette edits (@salim-b, #1586)
Added an option for extra command-line arguments in
conda_create() and conda_install()
(#1585).
Fixed issue where conda_install() would ignore
user-specified channels during Python installation (#1594).
Internal refactoring and optimizations now give a faster
experience, especially for workflows that frequently access Python
objects from R. For example, simple attribute access like
sys$path is ~2.5x times faster, and a sample workload of
py_to_r(np_array(1:3) + np_array(1:3)) benchmarks ~3.5x
faster when compared to the previous CRAN release.
Fixed issue where callable python objects created with
convert = FALSE would not be wrapped in an R function
(#1522).
Fixed issue where py_to_r() S3 methods would not be
called on arguments supplied to R functions being called from Python
(#1522).
install_python() will now build optimized versions
of Python on macOS and Linux (#1567)
Default Python version installed by install_python()
is now 3.10 (was 3.9) (#1574).
Output of reticulate::py_last_error() now includes a
hint, showing how to access the full R call stack (#1572).
Fixed an issue where nested py_capture_output()
calls result in a lost reference to the original sys.stdout
and sys.stderr, resulting in no further visible output from
Python, and eventually, a segfault. (#1564)
Fixed issues reported by rchk, as requested by CRAN (#1581).
py_to_r(x) now returns x unmodified if
x is not a Python object, instead of signaling an
error.
New as.data.frame() method exported for Python
Polars DataFrames (#1568)
Fixed an issue where printing a delayed module
(import("foo", delay_load = TRUE)) would output
<pointer: 0x0>.
py_validate_xptr() will now attempt to resolve
delayed modules before signaling an error (#1561).
R packages can now express multiple preferred Python environments
to search for and use if they exist, by supplying a character vector to
import():
import("foo", delay_load = list(environment = c("r-foo", "r-bar")))
(#1559)
Reticulate will no longer warn about ignored
use_python(,required = FALSE) calls (#1562).
reticulate now prefers using the agg matplotlib
backend when the R session is non-interactive. The backend can also be
overridden via the MPLBACKEND or
RETICULATE_MPLBACKEND environment variables when necessary
(#1556).
attr(x, "tzone") attributes are (better) preserved
when converting POSIXt to Python. POSIXt types with a non-empty
tzone attr convert to a datetime.datetime,
otherwise they convert to NumPy datetime64[ns]
arrays.
Fixed an issue where calling py_set_item() on a
subclassed dict would not invoke a custom __setitem__
method.
py_del_attr(x, name) now returns x
invisibly
source_python() no longer exports the r
symbol to the R global environment. (the “R Interface Object” that is
used by Python code get a reference to the R
globalenv())
Fixed hang encountered (sometimes) when attempting to call
iterate() on an exhausted py_iterator() object
multiple times (#1539).
iterate(simplify=TRUE) rewritten in C for speed
improvements (#1539).
Update for Pandas 2.2 deprecation of Index.format()
(#1537, #1538).
Updates for CRAN R-devel (R 4.4) (#1554).
Fixed an issue where py_discover_config() would
discover python (v2) on the PATH in preference of
python3 on the PATH. (#1547)
Fixed an issue where reticulate would error when using conda
environments created with the (new) conda env create
command. (#1535, #1543)
Fixed an issue where reticulate would error when using a conda environment where the original conda binary that was used to create the environment is no longer available (#1555)
Fixed an issue where a user would be unable to accept the prompt to create the default “r-reticulate” venv (#1557).
is_py_object() is now exported (#1573).
Subclassed Python list and dict objects are no longer
automatically converted to R vectors. Additionally, the S3 R
class attribute for Python objects is now constructed using
the Python type(object) directly, rather than from the
object.__class__ attribute. See #1531 for details and
context.
R external pointers (EXTPTRSXP objects) now round-trip through
py_to_r(r_to_py(x)) successfully. (reported in #1511, fixed
in #1519, contributed by @llaniewski).
Fixed issue where virtualenv_create() would error on
Ubuntu 22.04 when using the system python as a base. (#1495, fixed in
#1496).
Fixed issue where csc_matrix objects with unsorted
indices could not be converted to a dgCMatrix. (related to #727, fixed
in #1524, contributed by @rcannood).
Added support for partially unexpanded variables like
$USER in XDG_DATA_HOME and similar (#1513,
#1514)
The knitr python engine now formats captured python exceptions to
include the exception type and any exception notes when chunk options
error = TRUE is set (reported in #1520, fixed in
#1527).
Fixed an issue where the knitr python engine would fail to
include figures from python chunks if a custom root.dir
chunk option was set. (reported in #1526, fixed in #1529)
knitr engine gains the ability to save chunk figures in multiple files/formats (Contributed by @Rumengol in #1507)
Fixed an issue where matplotlib figures generated in the initial chunk where matplotlib was first imported would be the wrong size (reported in #1523, fixed in #1530)
Fixed an issue where the knitr engine would not correctly display altair compound charts if more than one were present in a document (#1500, #1532).
Fixed issue where asyncio, (and modules that use
asyncio), would error on Windows when running under RStudio
(#1478, #1479).
Added compatability with Python 3.12.
condaenv_exists() is now exported.
reticulate now supports casting R data.frames to Pandas
data.frames using nullable data types, allowing users to preserve NA’s
from R atomic vectors. This feature is opt-in and can be enabled by
setting the R option reticulate.pandas_use_nullable_dtypes
to TRUE. (#1439)
reticulate now exports a chooseOpsMethod() method,
allowing for Ops dispatch to more specialized Ops methods defined for
Python objects.
py_discover_config() will now warn instead of error
upon encountering a broken Python installation. (#1441, #1459)
Fixed issue where Python would raise exception “OSError: [WinError 6] The handle is invalid” when opening a subprocess while running in Rstudio on Windows. (#1448, #518)
Fixed issue where the multiprocessing Python module would crash
or hang when spawning a Process() on Windows. (#1430,
#1346, fixed in #1461)
Fixed issue where virtualenv_create() would fail to
discover a ‘virtualenv’ module in the system Python installation on
Ubuntu. Reticulate will no longer discover and attempt to use the
venv module stub present on Ubuntu systems where the
python3-venv apt package has not been installed.
(mlverse/pysparklyr#11, #1437, #1455)
Fixed issue where the user was prompted to create an ‘r-reticulate’ venv in the RStudio IDE before reticulate was requested to initialize Python. (#1450, #1456)
Improved error message when reticulate attempts to initialize a virtual environment after the Python installation it was created from is no longer available. (#1149, #1457)
Improved error message on Fedora when attempting to create a
virtual environment from the system python before running
dnf install python3-pip.
Fixed issue where install_python() on macOS in the
RStudio IDE would fail to discover and use brew for Python build
dependencies.
Fixed error with
virtualenv_create(python = "/usr/bin/python") on centos7.
(#1467)
reticulate will no longer prompt users to install miniconda.
Instead, reticulate will now prompt users to create a default
r-reticulate venv.
The search that reticulate conducts to select which Python
installation to load has changed. See the updated Python “Order of
Discover” in the “versions” vignette.
vignette("versions", package = "reticulate").
Updated recommendations in the “python_dependencies” vignette for
how R packages can approach Python dependency management.
vignette("python_dependencies", package = "reticulate")
New function virtualenv_starter(), which can be used
to find a suitable python binary for creating a virtual environment.
This is now the default method for finding the python binary when
calling
virtualenv_create(version = <version>).
virtualenv_create() and
virtualenv_install() gain a requirements
argument, accepting a filepath to a python requirements file.
virtualenv_create() gains a force
argument.
virtualenv_install() gains a
python_version argument, allowing users to customize which
python version is used when bootstrapping a new virtual
environment.
Fixed an issue where the list of available python versions used
by install_python() would be out-of-date.
install_python() now gives a better error message if
git is not installed.
install_python() on macOS will now will use brew, if
it’s available, to install build dependencies, substantially speeding up
python build times.
New function conda_search(), contributed by @mkoohafkan in PR
#1364.
New [ and [<- methods that invoke
Python __getitem__, __setitem__ and
__delitem__. The R generics [ and
[<- now accept python-style slice syntax like
x[1:2:3]. See examples in
?py_get_item.
py_iterator() gains a prefetch
argument, primarily to avoid deadlocks where the main thread is blocked,
waiting for the iterator, which is waiting to run on the main thread, as
encountered in TensorFlow/Keras. (#1405).
String columns from Pandas data frames containing
None, pd.NA or np.nan are now
simplified into character vectors and missing values replaced by
NA (#1428).
Converting from Pandas data frames containing columns with Pandas nullable data types are now correctly converted into R data.frames preserving the missing values (#1427).
The knitr engine gains a jupyter_compat option,
enabling reticulate to better match the behavior of Jupyter. When this
chunk option is set to TRUE, only the return value from the
last expression in a chunk is auto-printed. (#1391, #1394, contributed
by @matthew-brett)
The knitr engine now more reliably detects and displays
matplotlib pending plots, without the need for a matplotlib artist
object to be returned as a top-level expression. E.g., the knitr engine
will now display plots when the matplotlib api returns something other
than an artist object, (plt.bar()), or the matplotlib
return value is not auto-printed due to being assigned,
(x = plt.plot()), or suppressed with a ;,
(plt.plot();). (#1391, #1401, contributed by @matthew-brett)
Fixed an issue where knitr engine would not respect chunk options
fig.width / fig.height when rendering
matplotlib plots. (#1398)
Fixed an issue where the reticulate knitr engine would not capture output printed from python. (PR #1412, fixing #1378, #331)
Reticulate now periodically flushes python stdout
and stderr buffers even while the main thread is blocked
executing Python code. Streaming output from a long-running Python
function call will now appear in the R console while the Python function
is still executing. (Previously, output might not appear until the
Python function had finished and control of the main thread had returned
to R).
Updated sparse matrix conversion routines for compatibility with scipy 1.11.0.
Fixed an issue where a py capsule finalizer could access the R API from a background thread. (#1406)
Fixed issue where R would segfault (crash) in long-lived R sessions where both rpy2 and reticulate were in use (#1236).
Fixed an issue where exceptions from reticulate would not be formatted properly when running tests under testthat (r-lib/rlang#1637, #1413).
Fixed an issue where py_get_attr(silent = TRUE)
would not return an R NULL, if the attribute was missing,
as documented. (#1413)
Fixed an issue where py_get_attr(silent = TRUE)
would leave a python global exception set if the attribute was missing,
resulting in fatal errors when running python under debug mode.
(#1396)
R error information (call, message, other attributes) is now preserved as an R error condition traverses the R <-> Python boundary.
Python Exceptions now inherit from error and
condition, and can be passed directly to
base::stop() to signal an error in R and raise an exception
in Python.
Raised Python Exceptions are now used directly to signal an R
error. For example, in the following code, e is now an
object that inherits from python.builtin.Exception as well
as error and condition:
r e <- tryCatch(py_func_that_raises_exception(), error = function(e) e)
Use base::conditionCall() and
base::conditionMessage() to access the original R call and
error message.
py_last_error() return object contains
r_call, r_trace and/or r_class if
the Python Exception was raised by an R function called from
Python.
The hint to run reticulate::py_last_error() after an
exception is now clickable in the RStudio IDE.
Filepaths to Python files in the print output from
py_last_error() are now clickable links in the RStudio
IDE.
Python exceptions encountered in repl_python() are
now printed with the full Python traceback by default. In the RStudio
IDE, filepaths in the tracebacks are rendered as clickable links.
(#1240)
Converted Python callables gain support for dynamic dots from the rlang package. New features:
fn(!!!kwargs)nm <- "key"; fn("{nm}" := value)fn(a, ) identical to fn(a)New Ops group generics for Python objects: +,
-, *, /, ^,
%%, %/%, &, |,
!, %*%. Methods for all the Ops group generics
are now defined for Python objects. (#1187, #1363) E.g., this now
works:
np <- reticulate::import("numpy", convert = FALSE)
x <- np$array(1:5)
y <- np$array(6:10)
x + yFixed two issues with R comparison operator methods
(==, !=, <,
<=, >=, >):
==,
may now no long return an R scalar logical if one of the Python object
being compared was created with convert = FALSE. Wrap the
result of the comparison with py_bool() to restore the
previous behavior. (#1187, #1363)R functions wrapping Python callables now have formals matching those of the Python callable signature, enabling better autocompletion in more contexts (#1361).
new nameOfClass() S3 method for Python types,
enabling usage:
base::inherits(x, <python-type-object>) (requires R
>= 4.3.0)
py_run_file() and source_python() now
prepend the script directory to the Python module search path,
sys.path, while the requested script is executing. This
allows the Python scripts to resolve imports of modules defined in the
script directory, matching the behavior of
python <script> at the command line. (#1347)
The knitr engine now suppresses warnings from Python code if
warning=FALSE is set in the chunk options.
(quarto-dev/quarto#125, #1358)
Fixed issue where reticulate’s knitr engine would attach comments in a code chunk to the wrong code chunk (requires Python>=3.8) (#1223).
The knitr Python engine now respects the strip.white
option (#1273).
Fixed issue where the knitr engine would show an additional plot
from a chunk if the user called matplotlib.pyplot.show()
(#1380, #1383)
py_to_r() now succeeds when converting subtypes of
the built-in types (e.g. list, dict,
str). (#1352, #1348, #1226, #1354, #1366)
New pillar::type_sum() method now exported for
Python objects. That ensures the full object class name is printing in R
tracebacks and tibbles containing Python objects.
py_load_object() gains a convert
argument. If convert = FALSE, the returned Python object
will not be converted to an R object.
Fixed error r_to_py() with Pandas>=2.0 and R
data.frames with a factor column containing levels with
NA.
r_to_py() now succeeds for many additional types of
R objects. Objects that reticulate doesn’t know how to convert are
presented to the Python runtime as a pycapsule (an opaque pointer to the
underlying R object). Previously this would error. This allows for R
code to pass R objects that cannot be safely converted to Python through
the Python runtime to other R code. (e.g, to an R function called by
Python code). (#1304)
reticulate gains the ability to bind to micromamba Python installations (#1378, #1176, #1382, #1379, thanks to Zia Khan, @zia1138)
Default Python version used by install_miniconda()
and friends is now 3.9 (was 3.8).
Fixed issue where source_python() (and likely many
other entrypoints) would error if reticulate was built with Rcpp 1.0.10.
Exception and error handling has been updated to accommodate usage of
R_ProtectUnwind(). (#1328, #1329).
Fixed issue where reticulate failed to discover Python 3.11 on Windows. (#1325)
Fixed issue where reticulate would error by attempting to bind to a cygwin/msys2 installation of Python on Windows (#1325).
py_run_file() now ensures the __file__
dunder is visible to the executing python code. (#1283, #1284)
Fixed errors with install_miniconda() and
conda_install(), on Windows (#1286, #1287,
conda/conda#11795, #1312, #1297), and on Linux and macOS (#1306,
conda/conda#10431)
Fixed error when activating a conda env from a UNC drive on Windows (#1303).
Fixed issue where reticulate failed to bind to python2. (#1241, #1229)
A warning is now issued when reticulate binds to python2 that python2 support will be removed in an upcoming reticulate release.
py_id() now returns a character string, instead of
an R integer (#1216).
Fixed an issue where py_to_r() would not convert
elements of a dictionary (#1221).
Fixed an issue where setting RETICULATE_PYTHON or
RETICULATE_PYTHON_FALLBACK on Windows to the pyenv-win
python.bat shim would result in an error (#1263).
Fixed an issue where datetime.datetime objects with
a tzinfo attribute was not getting converted to R correctly
(#1266).
Fixed an issue where pandas
pandas.Categorical(,ordered=True) Series were not correctly
converted to an R ordered factor (#1234).
The reticulate Python engine no longer halts on
error for Python chunks containing parse errors when the
error=TRUE chunk option is set. (#583)
install_python() now leverages brew for python build
dependencies like openssl@1.1 if brew is already installed and on the
PATH, substantially speeding up install_python() on macOS
systems with brew configured.
Fixed an issue where reticulate would fail to bind to a conda environment on macOS or linux if conda installed a non-POSIX compliant activation script into the conda environment. (#1255)
Fixed an issue where the python knitr engine would error when
printing to HTML a constructor of class instances with a
_repr_html_ or to_html method (e.g.,
pandas.DataFrame; #1249, #1250).
Fixed an issue where the python knitr engine would error when printing a plotly figure to an HTML document in some (head-less) linux environments (#1250).
Fixed an issue where conda_install(pip=TRUE) would
install packages into a user Python library instead of the conda env if
the environment variable PIP_USER=true was set.
py_install(), virtualenv_install(), and
conda_install() now always specify --no-user
when invoking pip install. (#1209)
Fixed issue where py_last_error() would return
unconverted Python objects (#1233)
The Knitr engine now supports printing Python objects with
_repr_markdown_ methods. (via
quarto-dev/quarto-cli#1501)
sys.executable on Windows now correctly reports the
path to the Python executable instead of the launching R executable.
(#1258)
The sys module is no longer automatically imported
in __main__ by reticulate.
Fixed an issue on Windows where reticulate would fail to find Python installations from pyenv installed via scoop.
Fixed an issue where configure_environment() would
error on Windows. (#1247)
Updated docs for compatibility with HTML5 / R 4.2.
Updated r_to_py.sparseMatrix() method for compatibility with Matrix 1.4-2.
Fixed an issue where reticulate would fail if R was running embedded under rpy2. reticulate now ensures the Python GIL is acquired before calling into Python. (#1188, #1203)
Fixed an issue where reticulate would fail to bind to an ArcGIS Pro conda environment (#1200, @philiporlando).
Fixed an issue where reticulate would fail to bind to an Anaconda base environment on Windows.
All commands that create, modify, or delete a Python environment now echo the system command about to be executed. Affected: virtualenv_{create,install,remove} conda_{create,clone,remove,install,update} py_install
install_python() and
create_virtualenv() gain the ability to automatically
select the latest patch of a requested Python version. e.g.:
install_python("3.9:latest"),
create_virtualenv("my-env", version = "3.9:latest")
install_python() version arg gains
default value of "3.9:latest".
install_python() can now be called with no
arguments.
Fixed an issue where reticulate would fail to bind to a conda python if the user didn’t have write permissions to the conda installation (#1156).
Fixed an issue where reticulate would fail to bind to a conda python if spaces were present in the file path to the associated conda binary (#1154).
use_python(, required = TRUE) now issues a warning
if the request will be ignored (#1150).
New function py_repr() (#1157)
print() and related changes (#1148, #1157):
print() method for Python objects now
invokes py_repr() instead of str().format() method that
invokes py_str().py_str() default method no longer strips the object
memory address.print() now returns the printed object invisibly, for
composability with %>%.Exception handling changes (#1142, @t-kalinowski):
R error messages from Python exceptions are now truncated
differently to satisfy getOption("warning.length"). A hint
to call reticulate::py_last_error() is shown if the
exception message was truncated.
Python buffers sys.stderr and
sys.stdout are now flushed when Python exceptions are
raised.
-py_last_error():
Return object is now an S3 object ‘py_error’, includes a default print method.
The python Exception object (‘python.builtin.Exception’) is available as an R attribute.
Gains the ability to restore a previous exception if provided in
a call py_last_error(previous_error)
Python traceback objects gain a default format() S3
method.
Fixed py_to_r() for scipy matrices when scipy >=
1.8.0, since sparse matrices are now deprecated.
Fixed r_to_py() for small scipy matrices.
New maintainer: Tomasz Kalinowski
reticulate would fail to bind to
the system version of Python on macOS if command line tools were
installed, but Xcode was not.use_condaenv() gains the ability to accept an
absolute path to a python binary for envname.
All python objects gain a length() method, that
returns either py_len(x), or if that fails,
as.integer(py_bool(x)).
conda_create() default for
python_version changed from NULL to
miniconda_python_version() (presently, 3.8).
New function py_bool(), for evaluating Python
“truthiness” of an object.
reticulate gains the function
py_list_packages(), and can be used to list the Python
modules available and installed in a particular Python environment.
(#933)
reticulate now supports conversion of Python datatable objects.
(#1081)
repl_python() gains support for invoking select
magic and system commands like !ls and
%cd <dir>. See ?repl_python() for
details and examples.
The development branch for reticulate has moved to
the “main” branch.
reticulate gains
reticulate::conda_update(), for updating the version of
conda in a particular conda
installation.
reticulate gains
reticulate::miniconda_uninstall(), for uninstalling the
reticulate-managed version of Miniconda. (#1077)
reticulate::use_python() and friends now assume
required = TRUE by default. For backwards compatibility,
when use_python() is called as part of a package load hook,
the default value will instead be FALSE.
reticulate now provides support for Python
environments managed by poetry.
For projects containing a pyproject.toml file,
reticulate will attempt to find and use the virtual
environment managed by Poetry for that project. (#1031)
The default version of Python used for the
r-reticulate Miniconda environment installed via
reticulate::install_miniconda() has changed from 3.6 to
3.8.
reticulate::install_miniconda() now prefers
installing the latest arm64 builds of miniforge. See
https://conda-forge.org/blog/posts/2020-10-29-macos-arm64/ for more
details.
reticulate::conda_create() gains the
environment argument, used when creating a new conda
environment based on an exported environment definition
(e.g. environment.yml or
environment.json).
reticulate gains the function,
conda_export(), for exporting a conda environment
definition as YAML. Environments are exported as via the
conda env export command. (#779)
reticulate::find_conda() will now locate miniforge
Conda installations located within the default install
locations.
Fixed an issue that caused
reticulate::conda_install(pip = TRUE) to fail on windows.
(#1053, @t-kalinowski)
reticulate::conda_install(pip = TRUE) to fail. (#1052)use_condaenv("base") can now be used to activate the
base Anaconda environment.
reticulate will now execute any hooks registered via
setHook("reticulate.onPyInit", <...>) after Python
has been initialized. This can be useful for packages that need to take
some action after reticulate has initialized
Python.
Further refined interrupt handling.
Fixed an issue where attempting to bind reticulate
to /usr/bin/python3 on macOS could fail if Xcode was not
installed. (#1017)
The reticulate Python REPL no longer exits when a
top-level interrupt is sent (e.g. via Ctrl + C).
The miniconda auto-installer now supports aarch64 Linux machines. (#1012)
Fixed an issue where matplotlib plots were incorrectly overwritten when multiple Python chunks in the same R Markdown document included plot output. (#1010)
reticulate can now use the version of Python
configured in projects using pipenv. If the project
contains a Pipfile at the root directory (as understood by
here::here()), then reticulate will invoke
pipenv --venv to determine the path to the Python virtual
environment associated with the project. Note that the
RETICULATE_PYTHON environment variable, as well as usages
of use_python(..., force = TRUE), will still take
precedence. (#1006)
Fixed an issue where
reticulate::py_run_string(..., local = TRUE) failed to
return the dictionary of defined Python objects in some cases.
Fixed an issue where reticulate’s interrupt handlers
could cause issues with newer versions of Python.
reticulate now better handles Pandas categorical
variables containing NA values. (#942)
reticulate now supports converting
pandas.NA objects into R NA objects.
(#950)
reticulate now sets the
PYTHONIOENCODING environment variable to UTF-8 when running
within RStudio. This should allow UTF-8 input and output to be handled
more appropriately.
reticulate gains the install_python()
function, used to install different versions of Python via pyenv (pyenv-windows on
Windows).
Interrupt signals (e.g. those generated by Ctrl + C)
are now better handled by reticulate. In particular, when
repl_python() is active, Ctrl + C can be used
to interrupt a pending Python computation.
virtualenv_create() gains the
pip_version and setuptools_version arguments,
allowing users to control the versions of pip and
setuptools used when initializing the virtual environment.
The extra argument can also now be used to pass arbitrary
command line arguments when necessary.
virtualenv_create() gains the module
argument, used to control whether virtualenv or
venv is used to create the requested virtual
environment.
py_to_r.datetime.datetime no longer errs when
tzname is NULL, and instead assumes the time
is formatted for UTC. (#876)
reticulate now supports the rendering of plotly plots and Altair charts in rendered R
Markdown documents. (#711)
reticulate now avoids invoking property methods when
inferring the type for Python class members, for auto-completion
systems. (#907)
reticulate now attempts to set the
QT_QPA_PLATFORM_PLUGIN_PATH environment variable when
initializing a Conda installation of Python, when that associated
plugins directory exists. (#586)
The reticulate Python engine now supports the
results = "hold" knitr chunk option. When set, any
generated outputs are “held” and then displayed after the associated
chunk’s source code. (#530)
conda_create() gains the python_version
argument, making it easier to request that Conda environments are
created with a pre-specified version of Python. (#766)
Fixed an issue where reticulate::conda_install()
would attempt to re-install the default Python package, potentially
upgrading or downgrading the version of Python used in an
environment.
Fixed an issue where reticulate invoked its
reticulate.initialized hook too early.
Fixed an issue where Python modules loaded on a separate thread could cause a crash. (#885)
conda_install() now allows version specifications
for the python_version argument;
e.g. conda_install(python_version = ">=3.6").
(#880)
Fixed an issue where conda_install() failed to pass
along forge and channel in calls to
conda_create(). (#878)
Fixed an issue where Python’s auto-loader hooks could fail when binding to a Python 2.7 installation.
python_config() could throw an
error when attempting to query information about a Python 2.6
installation.reticulate now checks for and disallows installation
of Python packages during R CMD check.
reticulate no longer injects the r
helper object into the main module if another variable called
r has already been defined.
The function py_help_handler() has now been
exported, to be used by front-ends and other tools which need to provide
help for Python objects in different contexts. (#864)
Fixed an issue where timezone information could be lost when converting Python datetime objects to R. (#829)
Fixed an issue where numeric (rather than integer) dimensions could cause issues when converting SciPy sparse matrices to their R counterparts. (#844)
Fixed an issue where R data.frames with non-ASCII
column names could not be converted to Pandas DataFrames.
(#834)
Fixed an issue where the pip_ignore_installed
argument in conda_install() was silently being
ignored.
Fixed an issue where reticulate::conda_install()
could re-install Python into an environment when not explicitly
requested by the user.
reticulate now sets LD_LIBRARY_PATH
when discovering Python. (#836)
reticulate is now better at capturing Python logger
streams (those that write to stdout or stderr) when
py_capture_output() is set. (#825)
reticulate no longer calls
utils::loadhistory() after each REPL iteration.
reticulate now better detects when Python modules
are loaded.
reticulate::import_from_path() now accepts the
delay_load parameter, allowing modules which should be
loaded from a pre-specified path to be lazy-loaded.
Fixed an issue where reticulate load hooks (normally
defined via
setHook("reticulate::<module>::load", ...)) would
segfault if those hooks attempted to load the hooked module.
reticulate now attempts to resolve the conda binary
used to create the associated Conda environment in calls to
py_install(). This should fix use cases where Conda
environments are placed outside of the Conda installation
itself.
reticulate now sets PYTHONPATH before
loading Python, to ensure modules are looked up in the same locations
where a regular Python interpreter would find them on load. This should
fix issues where reticulate was unable to bind to a Python
virtual environment in some cases.
reticulate::virtualenv_create() gains the
packages argument, allowing one to choose a set of packages
to be installed (via pip install) after the virtual
environment has been created.
reticulate::virtualenv_create() gains the
system_site_packages argument, allowing one to control
whether the --system-site-packages flag is passed along
when creating a new virtual environment. The default value can be
customized via the
"reticulate.virtualenv.system_site_packages" option and now
defaults to FALSE when unset.
Fixed an issue where
reticulate::configure_environment() would fail when
attempting to configure an Anaconda environment. (#794)
reticulate now avoids presenting a Miniconda prompt
for interactive sessions during R session initialization.
Fixed unsafe usages of Rprintf() and
REprintf().
reticulate::py_install() better respects the
method argument, when py_install() is called
without an explicit environment name. (#777)
reticulate:::pip_freeze() now better handles
pip direct references. (#775)
Fixed an issue where output generated from
repl_python() would be buffered until the whole submitted
command had completed. (#739, @randy3k)
reticulate now explicitly qualifies symbols used
from TinyThread with tthread::, to avoid issues with symbol
conflicts during compilation. (#773)
reticulate will now prefer an existing Miniconda
installation over a conda binary on the PATH, when looking
for Conda. (#790)
TinyThread now calls Rf_error() rather than
std::terminate() when an internal error occurs.
Conversion of Pandas DataFrames to R no longer emits deprecation warnings with pandas >= 0.25.0. (#762)
reticulate now properly handles the version strings
returned by beta versions of pip. (#757)
conda_create() gains the forge and
channel arguments, analogous to those already in
conda_install(). (#752, @jtilly)
reticulate now ensures SciPy csr_matrix
objects are sorted before attempting to convert them to their R
equivalent. (#738, @paulofelipe)
Fixed an issue where calling input() from Python
with no prompt would fail. (#728)
Lines ending with a semi-colon are no longer auto-printed in the
reticulate REPL. (#717, @jsfalk)
reticulate now searches for Conda binaries in
/opt/anaconda and /opt/miniconda. (#713)
The conda executable used by reticulate
can now be configured using an R option. Use
options(reticulate.conda_binary = <...>) to force
reticulate to use a particular conda
executable.
reticulate::use_condaenv() better handles cases
where no matching environment could be found. (#687)
reticulate gains the py_ellipsis()
function, used to access the Python Ellipsis builtin.
(#700, @skeydan)
reticulate::configure_environment() now only allows
environment configuration within interactive R sessions, and ensures
that the version of Python that has been initialized by Python is indeed
associated with a virtual environment or Conda environment. Use
reticulate::configure_environment(force = TRUE) to force
environment configuration within non-interactive R sessions.
reticulate now automatically flushes output written
to Python’s stdout / stderr, as a top-level task added by
addTaskCallback(). This behavior is controlled with the
options(reticulate.autoflush) option. (#685)
reticulate::install_miniconda() no longer attempts
to modify the system PATH or registry when installing Miniconda.
(#681)
reticulate::conda_install() gains the
channel argument, allowing custom Conda channels to be used
when installing Python packages. (#443)
reticulate::configure_environment() can now be used
to configure a non-Miniconda Python environment. (#682; @skeydan)
Fixed an issue where matplotlib plots would be included using absolute paths, which fails in non-standalone documents rendered to HTML. (#669)
Fixed an issue where reticulate would attempt to
flush a non-existent stdout / stderr stream. (#584)
Fixed an issue where rmarkdown::render() could fail
when including matplotlib plots when knit_root_dir is set.
(#645)
reticulate now scans for Conda installations within
the ~/opt folder, as per the updated installers distributed for macOS.
(#661)
Python classes can now be defined directly from R using the
PyClass() function. (#635; @dfalbel)
reticulate is now compatible with Python 3.9. (#630, @skeydan)
Pandas DataFrames with a large number of columns should now be converted to R data.frames more quickly. (#620, @skeydan)
Python loggers are now better behaved in the Python chunks of R Markdown documents. (#386)
reticulate will now attempt to bind to python3
rather than python, when no other version of Python has
been explicitly requested by e.g. use_python().
reticulate now provides R hooks for Python’s input()
and raw_input() functions. It should now be possible to
read user input from Python scripts loaded by reticulate.
(#610)
reticulate now more consistently normalizes the
paths reported by py_config(). (#609)
reticulate now provides a mechanism for allowing
client packages to declare their Python package dependencies. Packages
should declare the Python packages they require as part of the
Config/reticulate field in their DESCRIPTION
file. Currently, this only activated when using Miniconda; as the
assumption is that users will otherwise prefer to manually manage their
Python environments. Please see
vignette("python_dependencies") for more details.
reticulate will now prompt the user to create and
use a Miniconda
environment when no other suitable Python environment has already been
requested. This should help ease some of the trouble in setting up a
Python environment on different platforms. The installer code was
contributed by @hafen,
from the rminiconda
package.
Fixed an issue where
virtualenv_create(..., python = "<python>") could
fail to use the requested version of Python when venv is
not installed. (#399)
Fixed an issue where iterable Python objects could not be
iterated with iter_next() due to a missing class.
(#603)
Fixed an issue where Conda environments could be mis-detected as virtual environments.
R functions wrapping Python functions now inherit the formal arguments as specified by Python, making autocompletion more reliable. (#573, @flying-sheep)
Fixed an issue where attempts to query Conda for environments could fail on Windows. (#576; #575; @dfalbel)
Properly check for NULL keyword arguments in
call_r_function(). (#562, @dfalbel)
Fixed an issue where subsetting with
[.python.builtin.object could fail when
convert = TRUE is set on the associated Python object.
(#554)
Fixed an issue where the wrong definition of
[[.python.builtin.object was being exported.
(#554)
py_install() now accepts
python_version, and can be used if a particular version of
Python is required for a Conda environment. (This argument is ignored
for virtual environments.) (#549)
Fixed an issue where reticulate could segfault in some cases
(e.g. when using the iterate() function). (#551)
It is now possible to compile reticulate with
support for debug versions of Python by setting the
RETICULATE_PYTHON_DEBUG preprocessor define during
compilation. (#548)
reticulate now warns if it did not honor the user’s request to
load a particular version of Python, as through
e.g. reticulate::use_python(). (#545)
py_save_object() and py_load_object()
now accept ... arguments. (#542)
py_install() has been revamped, and now better
detects available Python tooling (virtualenv vs. venv vs. Conda).
(#544)
reticulate now flushes stdout / stderr after calls to
py_run_file() and py_run_string().
Python tuples are now converted recursively, in the same way that Python lists are. This means that the sub-elements of the tuple will be converted to R objects when possible. (#525, @skeydan)
Python OrderedDict objects with non-string keys are now properly converted to R. (#516)
Fixed an issue where reticulate could crash after a failed attempt to load NumPy. (#497, @ecoughlan)
Fixed an issue where Python objects within Python lists would not be converted to R objects as expected.
Fixed an issue where single-row data.frames with row names could not be converted. (#468)
Fixed an issue where reticulate could fail to query
Anaconda environment names with Anaconda 3.7.
Fixed an issue where vectors of R Dates were not converted correctly. (#454)
Fixed an issue where R Dates could not be passed to Python functions. (#458)
Fixed an issue where attempts to activate virtual environments created with virtualenv 16.4.1 would fail. (#437)
Fixed an issue where conversion of Pandas Categorical variables to R objects would fail. (#389)
Textual output generated when adding items to a matplotlib plot object are now suppressed.
If the last statement in a Python chunk returns a matplotlib plot object, the plot will now be auto-shown as in other environments.
The reticulate function help handler now returns function arguments for Python builtin functions.
Top-level Python statements can now include leading indent when
submitted with repl_python().
The current matplotlib figure is now cleared as each
Python chunk in an R Markdown document is run.
The r helper object (used for evaluating R code from
Python) now better handles conversion of R functions. (#383)
The use_virtualenv() function now understands how to
bind to virtual environments created by the Python venv
module.
Reticulate better handles conversions of R lists to Python, and
similarly, Python lists to R. We now call r_to_py() on each
sub-element of an R list, and similarly, py_to_r() on each
sub-element of a Python list.
Reticulate now always converts R Date objects into
Python datetime objects. Note that these conversions can be
inefficient – if you would prefer conversion to NumPy
datetime64 objects / arrays, you should convert your date
to POSIXct first.
Python chunks containing errors will cause execution to halt if ‘error=FALSE’ during render, conforming with the default knitr behavior for R chunks.
The output of bare statements (e.g. 1 + 1) is now
emitted as output when using the reticulate Python engine.
Remapping of Python output streams to be R can now be explicitly
enabled by setting the environment variable
RETICULATE_REMAP_OUTPUT_STREAMS to 1. (#335)
Allow syntax errors in Python chunks with ‘eval = FALSE’ (#343)
Avoid dropping blank lines in Python chunks (#328)
Use “agg” matplotlib backend when running under RStudio Desktop (avoids crashes when attempting to generate Python plots)
Add as.character() S3 method for Python bytes
(defaults to converting using UTF-8 encoding)
Add py_main_thread_func() for providing R callbacks
to Python libraries that may invoke the function on a Python background
thread.
Add py_to_r S3 methods for Scipy sparse matrices:
CSR to dgRMatrix, COO to dgTMatrix, and for all other sparse matrices,
conversion via CSC/dgCMatrix.
Output is now properly displayed when using the
reticulate REPL with Windows + Python 2.7.
Address memory protection issues identified by rchk
Make variables defined using %as% operator in
with() available after execution of the with block (same
behavior as Python).
Check for presence of “module” property before
reading in as_r_class()
Only update pip in virtualenv_install() when version
is < 8.1
Support converting Python OrderedDict to R
Support for iterating all types of Python iterable
Add conda_python() and
virtualenv_python() functions for finding the python binary
associated with an environment.
Detect python 3 in environments where there is no python 2 (e.g. Ubuntu 18.04)
Always call r_to_py S3 method when converting objects from Python to R
Handle NULL module name when determining R class for Python objects
Convert RAW vectors to Python bytearray; Convert Python bytearray to RAW
Use importlib for detecting modules (rather than imp) for Python >= 3.4
Close text connection used for reading Python configuration probe
source_python() now flushes stdout and stderr after
running the associated Python script, to ensure that
print()-ed output is output to the console. (#284)
Fixed an issue where logical R matrices would not be converted correctly to their NumPy counterpart. (#280)
Fixed an issue where Python chunks containing multiple statements on the same line would be evaluated and printed multiple times.
Added py_get_item(), py_set_item(), and
py_del_item() as lower-level APIs for directly accessing
the items of e.g. a Python dictionary or a Pandas DataFrame.
Fix issue with Pandas column names that clash with built in methods (e.g. ‘pop’)
Improve default str() output for Python objects
(print __dict__ if available)
Improved filtering of non-numeric characters in Python / NumPy versions.
Added py_func() to wrap an R function in a Python
function with the same signature as that of the original R
function.
Added support for conversion between
Matrix::dgCMatrix objects in R and Scipy CSC
matrices in Python.
source_python() can now source a Python script from
a URL into R environments.
Always run source_python() in the main Python
module.
py_install() function for installing Python packages
into virtualenvs and conda envs
Automatically create conda environment for
conda_install()
Removed delay_load parameter from
import_from_path()
repl_python() function implementing a lightweight
Python REPL in R.
Support for converting Pandas objects (Index,
Series, DataFrame)
Support for converting Python datetime
objects.
py_dict() function to enable creation of
dictionaries based on lists of keys and values.
Provide default base directory (e.g. ‘~/.virtualenvs’) for
environments specified by name in
use_virtualenv().
Fail when environment not found with
use_condaenv(..., required = TRUE)
Ensure that use_* python version is satisfied when
using eng_python()
Forward required argument from
use_virtualenv() and use_condaenv()
Fix leak which occurred when assigning R objects into Python containers
Add support for Conda Forge (enabled by default) to
conda_install()
Added functions for managing Python virtual environments (virtualenv)
Remove implicit documentation extraction for Python classes
Add Library\bin to PATH on Windows to ensure
Anaconda can find MKL
New source_python() function for sourcing Python
scripts into R environments.
Support for RETICULATE_DUMP_STACK_TRACE environment
variable which can be set to the number of milliseconds in which to
output into stderr the call stacks from all running threads.
Provide hook to change target module when delay loading
Scan for conda environments in system-level installations
Support for miniconda environments
Implement eval, echo, and
include knitr chunk options for Python engine
Use existing instance of Python when reticulate is loaded within an embedded Python environment (e.g. rpy2, rice, etc.)
Force use of Python specified in PYTHON_SESSION_INITIALIZED (defined by rpy2)
Define R_SESSION_INITIALIZED (used by rpy2)
Force use of Python when required = TRUE in
use_python functions
Force use of Python specified by RETICULATE_PYTHON
dict: Don’t scan parent frame for Python objects if
a single unnamed list is passed.
Wait as long as required for scheduling generator calls on the main thread
Refine stripping of object addresses from output of
py_str() method
Added py_id() function to get globally unique ids
for Python objects
Added py_len() function and S3 length()
method for Python lists (already had length() methods for
dicts, tuples, and NumPy arrays).
Exported py object (reference to Python main
module)
Added eng_python() (knitr engine for Python
chunks)
Improved compatibility with strings containing high unicode characters when running under Python 2
Remove dim methods for NumPy arrays (semantics of
NumPy reshaping are different from R reshaping)
Added array_reshape function for reshaping R arrays
using NumPy (row-major) semantics.
Provide mechanism for custom R wrapper objects for Python objects
Added interface to pickle (py_save_object() and
py_load_object())
Catch and print errors which occur in generator functions
Write using Rprintf when providing custom Python output streams (enables correct handling of terminal control characters)
Implement isatty when providing custom Python output
streams
Add np_array function for creating NumPy arrays and
converting the data type, dimensions, and in-memory ordering of existing
NumPy arrays.
Add dim and length functions for NumPy
arrays
Add py_set_seed function for setting Python and
NumPy random seeds.
Search in additional locations for Anaconda on Linux/Mac
Improved support for UTF-8 conversions (always use UTF-8 when converting from Python to R)
Ignore private (“_” prefixed) attributes of dictionaries for .DollarNames
Provide “`function`” rather than “function” in completions.
Fail gracefully if call to conda in conda_list
results in an error
Add pip_ignore_installed option to
conda_install function.
Allow dict() function to accept keys with mixed
alpha/numeric characters
Use conda_list() to discover conda environments on
Windows (slower but much more reliable than scanning the
filesystem)
Add interface for registering F1 help handlers for Python modules
Provide virtual/conda env hint mechanism for delay loaded imports
Search WORKON_HOME (used by virtualenv_wrapper) for Python environments
Support priority field for delay loaded
modules.
Use json output from conda_list (handle spaces in path of conda env)
Look for callable before iterable when converting Python objects to R
Correct propagation of errors in R functions called from Python
Support for generators (creating Python iterators from R functions)
Changed default completed value for
iter_next() to NULL (was
NA)
Support for converting 16-bit floats (NPY_HALF) to R
Don’t throw error when probing Python <= 2.6
Copy Python dictionary before converting to R named list (fixes issue with dictionaries that are mutated during iteration, e.g. sys.modules)
Ensure that existing warning filters aren’t reset by py_suppress_warnings
Detect older versions of Anaconda during registry scanning.
Don’t probe python versions on windows when no executable is found
Poll for interrupts every 500ms rather than 100ms
Provide sys.stdout and sys.stderr when they are None (e.g. in R GUI)
Add Scripts directory to PATH on Windows
Add iter_next function for element-by-element access to iterators
Eliminate special print method for iterators/generators
Added py_help() function for printing documentation
on Python objects
Added conda_version() function.
Search dict() parent frames for symbols; only use
symbols which inherit from python.builtin.object as keys.
Add import_from_path() function for importing Python
modules from the filesystem.
Add py_discover_config() function to determine which
versions of Python will be discovered and which one will be used by
reticulate.
Add py_function_docs() amd
py_function_wrapper() utility functions for scaffolding R
wrappers for Python functions.
Add py_last_error() function for retrieving last
Python error.
Convert 0-dimension NumPy arrays (scalars) to single element R vectors
Convert “callable” Python objects to R functions
Automatically add Python bin directory to system PATH for consistent version usage in reticulate and calls to system
Added length() method for tuple objects
Enable specification of __name__ for R functions
converted to Python functions.
Give priority to the first registered delay load module (previously the last registered module was given priority)
Add additional safety checks to detect use of NULL xptr objects (i.e. objects from a previous session). This should mean that S3 methods no longer need to check whether they are handling an xptr.
Added py_eval() function for evaluating simple
Python statements.
Add local option to py_run_string() and
py_run_file(). Modify behavior to return local execution
dictionary (rather than a reference to the main module).
Use PyImport_Import rather than
PyImport_ImportModule for import()
Added ability to customize mapping of Python classes to R classes
via the as argument to import() and the
register_class_filter() function
Added separate on_load and on_error
functions for delay_load
Scan customary root directories for virtualenv installations
Allow calling __getitem__ via [[
operator (zero-based to match Python style indexing)
Added conda_* family of functions for using conda
utilities from within R.
Implement comparison operators (e.g. ==,
>=, etc.) for Python objects
Implement names() generic for Python
objects
Improve performance for marshalling of large Python dictionaries and iterators that return large numbers of items.
Implement str methods for Python List, Dict, and
Tuple (to prevent printing of very large collections via default
str method)
Use grepl() rather than endsWith() for
compatibility with R <= 3.2
Use inspect.getmro rather than
__bases__ for enumerating the base classes of Python
objects.
Fix PROTECT/UNPROTECT issue detected by
CRAN
Correct conversion of strings with Unicode characters on Windows
Fix incompatibility with system-wide Python installations on Windows
Fix issue with Python dictionary keys that shared names with primitive R functions (don’t check environment inheritance chain when looking for dictionary key objects by name).
Propagate convert parameter for modules with
delay_load
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