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.
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