-
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.frame
s with non-ASCII column names could not be converted to Pandas DataFrames. (#834) -
Fixed an issue where the
pip_ignore_installed
argument inconda_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 setsLD_LIBRARY_PATH
when discovering Python. (#836) -
reticulate
is now better at capturing Python logger streams (those that write to stdout or stderr) whenpy_capture_output()
is set. (#825) -
reticulate
no longer callsutils::loadhistory()
after each REPL iteration. -
reticulate
now better detects when Python modules are loaded. -
reticulate::import_from_path()
now accepts thedelay_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 viasetHook("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 topy_install()
. This should fix use cases where Conda environments are placed outside of the Conda installation itself. -
reticulate
now setsPYTHONPATH
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 wherereticulate
was unable to bind to a Python virtual environment in some cases. -
reticulate::virtualenv_create()
gains thepackages
argument, allowing one to choose a set of packages to be installed (viapip install
) after the virtual environment has been created. -
reticulate::virtualenv_create()
gains thesystem_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 toFALSE
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()
andREprintf()
. -
reticulate::py_install()
better respects themethod
argument, whenpy_install()
is called without an explicit environment name. (#777) -
reticulate:::pip_freeze()
now better handlespip
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 withtthread::
, to avoid issues with symbol conflicts during compilation. (#773) -
reticulate
will now prefer an existing Miniconda installation over aconda
binary on the PATH, when looking for Conda. (#790)
-
TinyThread now calls
Rf_error()
rather thanstd::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 ofpip
. (#757) -
conda_create()
gains theforge
andchannel
arguments, analogous to those already inconda_install()
. (#752, @jtilly)
-
reticulate
now ensures SciPycsr_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 byreticulate
can now be configured using an R option. Useoptions(reticulate.conda_binary = <...>)
to forcereticulate
to use a particularconda
executable. -
reticulate::use_condaenv()
better handles cases where no matching environment could be found. (#687) -
reticulate
gains thepy_ellipsis()
function, used to access the PythonEllipsis
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. Usereticulate::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 byaddTaskCallback()
. This behavior is controlled with theoptions(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 thechannel
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 whenknit_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 thanpython
, when no other version of Python has been explicitly requested by e.g.use_python()
. -
reticulate now provides R hooks for Python's
input()
andraw_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 bypy_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 theConfig/reticulate
field in theirDESCRIPTION
file. Currently, this only activated when using Miniconda; as the assumption is that users will otherwise prefer to manually manage their Python environments. Please seevignette("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 whenvenv
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 whenconvert = 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 acceptspython_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 theRETICULATE_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()
andpy_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()
andpy_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 a failing virtual environment test on CRAN.
-
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 Pythonvenv
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 Pythondatetime
objects. Note that these conversions can be inefficient -- if you would prefer conversion to NumPydatetime64
objects / arrays, you should convert your date toPOSIXct
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 inwith()
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()
andvirtualenv_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 thatprint()
-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()
, andpy_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 andScipy
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 fromimport_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 satsified when usingeng_python()
-
Forward
required
argument fromuse_virtualenv()
anduse_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
, andinclude
knitr chunk options for Python engine
- Bugfix: ensure single-line Python chunks that produce no output still have source code emitted.
-
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
inuse_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 S3length()
method for Python lists (already hadlength()
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()
andpy_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
andlength
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 toconda_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 foriter_next()
toNULL
(wasNA
) -
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()
amdpy_function_wrapper()
utility functions for scaffolding R wrappers for Python functions. -
Add
py_last_error()
function for retreiving 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 topy_run_string()
andpy_run_file()
. Modify behavior to return local execution dictionary (rather than a reference to the main module). -
Use
PyImport_Import
rather thanPyImport_ImportModule
forimport()
-
Added ability to customize mapping of Python classes to R classes via the
as
argument toimport()
and theregister_class_filter()
function -
Added separate
on_load
andon_error
functions fordelay_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 defaultstr
method) -
Use
grepl()
rather thanendsWith()
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 converstion 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 withdelay_load
- Initial CRAN release