pitrou commented on a change in pull request #11679: URL: https://github.com/apache/arrow/pull/11679#discussion_r755122630
########## File path: docs/source/python/integration/python_r.rst ########## @@ -0,0 +1,312 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +Integrating PyArrow with R +========================== + +Arrow supports exchanging data within the same process through the +:ref:`c-data-interface`. + +This can be used to exchange data between Python and R functions and +methods so that the two languages can interact without any cost of +marshaling and unmarshaling data. + +.. note:: + + The article takes for granted that you have a ``Python`` environment + with ``pyarrow`` correctly installed and an ``R`` environment with + ``arrow`` library correctly installed. + +Invoking R functions from Python +-------------------------------- + +Suppose we have a simple R function receiving an Arrow Array to +add ``3`` to all its elements: + +.. code-block:: R + + library(arrow) + + addthree <- function(arr) { + return(arr + 3) + } + +We could save such function in a ``addthree.R`` file so that we can +make it available for reuse. + +Once the ``addthree.R`` is created we can invoke any of its functions +from Python using the +`rpy2 <https://rpy2.github.io/doc/latest/html/index.html>`_ library which +enables a R runtime within the Python interpreter. + +``rpy2`` can be installed using ``pip`` like most python libraries + +.. code-block:: bash + + $ pip install rpy2 + +The most basic thing we can do with our ``addthree`` function is to +invoke it from Python with a number and see how it will return the result. + +To do so we can create an ``addthree.py`` file which uses ``rpy2`` to +import the ``addthree`` function from ``addthree.R`` file and invoke it: + +.. code-block:: python + + import rpy2.robjects as robjects + + # Load the addthree.R file + r_source = robjects.r["source"] + r_source("addthree.R") + + # Get a reference to the addthree function + addthree = robjects.r["addthree"] + + # Invoke the function + r = addthree(3) + + # Access the returned value + value = r[0] + print(value) + +Running the ``addthree.py`` file will show how our Python code is able +to access the ``R`` function and print the expected result: + +.. code-block:: bash + + $ python addthree.py + 6.0 + +If instead of passing around basic data types we want to pass around +Arrow Arrays, we can do so relying on the ``rpy2-arrow`` module which +implements rpy2 support for Arrow types. + +``rpy2`` can be installed through ``pip``: + +.. code-block:: bash + + $ pip install rpy2-arrow + +``rpy2-arrow`` implements converters from pyarrow objects to r arrow objects, +this is done without occurring into any data copy cost as it relies on the +C Data interface. + +To pass to ``addthree`` a pyarrow array our ``addthree.py`` needs to be modified +to enable ``rpy2-arrow`` converters and then pass the pyarrow array: + +.. code-block:: python + + import rpy2.robjects as robjects + from rpy2_arrow.pyarrow_rarrow import (rarrow_to_py_array, + converter as arrowconverter) + from rpy2.robjects.conversion import localconverter + + r_source = robjects.r["source"] + r_source("addthree.R") + + addthree = robjects.r["addthree"] + + import pyarrow + + array = pyarrow.array((1, 2, 3)) + + # Enable rpy2-arrow converter so that R can receive the array. + with localconverter(arrowconverter): + r_result = addthree(array) + + # The result of the R function will be an R Environment + # we can convert back the Environment to a pyarrow Array + # using the rarrow_to_py_array function + py_result = rarrow_to_py_array(r_result) + print("RESULT", type(py_result), py_result) + +Running the newly modified ``addthree.py`` should now properly execute +the R function and print the resulting pyarrow Array: + +.. code-block:: bash + + $ python addthree.py + RESULT <class 'pyarrow.lib.DoubleArray'> [ + 4, + 5, + 6 + ] + +.. note:: + + Even though we sent an ``Int64Array`` to R, we end up with a + result as a ``DoubleArray``. That's due to the lack of native + support for 64 bits numbers in R and thus its use of doubles + to represent those. + +For additional information you can refer to +`rpy2 Documentation <https://rpy2.github.io/doc/latest/html/index.html>`_ +and `rpy2-arrow Documentation <https://rpy2.github.io/rpy2-arrow/version/main/html/index.html>`_ + +Invoking Python functions from R +-------------------------------- + +Exposing Python functions to R can be done through the ``reticulate`` +library. For example if we want to invoke :func:`pyarrow.compute.add` from +R on an Array created in R we can do so importing ``pyarrow`` in R +through ``reticulate``. + +A basic ``addthree.R`` script that invokes ``add`` to add ``3`` to +an R array would look like: + +.. code-block:: R + + # Load arrow and reticulate libraries + library(arrow) + library(reticulate) + + # Create a new array in R + a <- Array$create(c(1, 2, 3)) + + # Make pyarrow.compute available to R + pc <- import("pyarrow.compute") + + # Invoke pyarrow.compute.add with the array and 3 + # This will add 3 to all elements of the array and return a new Array + result <- pc$add(a, 3) + + # Print the result to confirm it's what we expect + print(result) + +Invoking the ``addthree.R`` script will print the outcome of adding +``3`` to all the elements of the original ``Array$create(c(1, 2, 3))`` array: + +.. code-block:: bash + + $ R --slave -f addthree.R + Array + <double> + [ + 4, + 5, + 6 + ] + +For additional information you can refer to +`Reticulate Documentation <https://rstudio.github.io/reticulate/>`_ + +R to Python communication using C Data Interface +------------------------------------------------ + +Both the solutions described in previous chapters use the Arrow C Data +interface under the hood. + +In case we want to extend the previous ``addthree`` example to switch +from using ``rpy2-arrow`` to using the plain C Data interface we can +do so by introducing some modifications to our codebase. + +To enable importing the Arrow Array from the C Data interface we have to +wrap our ``addthree`` function in a function that does the extra work +necessary to import an Arrow Array in R from the C Data interface. + +That work will be done by the ``addthree_cdata`` function which invokes the +``addthree`` function once the Array is imported. + +Our ``addthree.R`` will thus have both the ``addthree_cdata`` and the +``addthree`` functions: + +.. code-block:: R + + library(arrow) + + addthree_cdata <- function(array_ptr_s, schema_ptr_s) { + array_ptr <- as.numeric(array_ptr_s) + schema_ptr <- as.numeric(schema_ptr_s) + + a <- Array$import_from_c(array_ptr, schema_ptr) + + return(addthree(a)) + } + + addthree <- function(arr) { + return(arr + 3) + } + +We can now provide to R the array and its schema from Python through the +``array_ptr_s`` and ``schema_ptr_s`` arguments so that R can build back +an ``Array`` from them and then invoke ``addthree`` with the array. + +Invoking ``addthree_cdata`` from Python involves building the Array we +want to pass to ``R``, exporting it to the C Data interface and then +passing the exported references to the ``R`` function. + +Our ``addthree.py`` will thus become: + +.. code-block:: python + + # Get a reference to the addthree_cdata R function + import rpy2.robjects as robjects + r_source = robjects.r["source"] + r_source("addthree.R") + addthree_cdata = robjects.r["addthree_cdata"] + + # Create the pyarrow array we want to pass to R + import pyarrow + array = pyarrow.array((1, 2, 3)) + + # Import the pyarrow module that provides access to the C Data interface + from pyarrow.cffi import ffi as arrow_c + + # Allocate structures where we will export the Array data + # and the Array schema. They will be released when we exit the with block. + with arrow_c.new("struct ArrowArray*") as c_array, \ + arrow_c.new("struct ArrowSchema*") as c_schema: + # Get the references to the C Data structures. + c_array_ptr = int(arrow_c.cast("uintptr_t", c_array)) + c_schema_ptr = int(arrow_c.cast("uintptr_t", c_schema)) + + # Export the Array and its schema to the C Data structures. + array._export_to_c(c_array_ptr) + array.type._export_to_c(c_schema_ptr) + + # Invoke the R addthree_cdata function passing the references + # to the array and schema C Data structures. + # Those references are passed as strings as R doesn't have + # native support for 64bit integers, so the integers are + # converted to their string representation for R to convert it back. + r_result_array = addthree_cdata(str(c_array_ptr), str(c_schema_ptr)) + + # r_result will be an Environment variable that contains the + # arrow Array built from R as the return value of addthree. + # To make it available as a Python pyarrow array we need to export + # it as a C Data structure invoking the Array$export_to_c R method + r_result_array["export_to_c"](float(c_array_ptr), float(c_schema_ptr)) Review comment: What does it change to call `as.numeric`? You would still get a floating-point number with not enough precision, right? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: github-unsubscr...@arrow.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
