NEWS.md
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 satsified 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 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 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 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 with delay_load