rdata 0.11.2

rdata
=====

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Read R datasets from Python.

..
Github does not support include in README for dubious security reasons, so
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The package rdata offers a lightweight way to import R datasets/objects stored
in the ".rda" and ".rds" formats into Python.
Its main advantages are:

- It is a pure Python implementation, with no dependencies on the R language or
related libraries.
Thus, it can be used anywhere where Python is supported, including the web
using `Pyodide <https://pyodide.org/>`__.
- It attempt to support all R objects that can be meaningfully translated.
As opposed to other solutions, you are no limited to import dataframes or
data with a particular structure.
- It allows users to easily customize the conversion of R classes to Python
ones.
Does your data use custom R classes?
Worry no longer, as it is possible to define custom conversions to the Python
classes of your choosing.
- It has a permissive license (MIT). As opposed to other packages that depend
on R libraries and thus need to adhere to the GPL license, you can use rdata
as a dependency on MIT, BSD or even closed source projects.

Installation
============

rdata is on PyPi and can be installed using :code:`pip`:

.. code::

pip install rdata

It is also available for :code:`conda` using the :code:`conda-forge` channel:

.. code::

conda install -c conda-forge rdata

Installing the develop version
------------------------------

The current version from the develop branch can be installed as

.. code::

pip install git+https://github.com/vnmabus/rdata.git@develop

Documentation
=============

The documentation of rdata is in
`ReadTheDocs <https://rdata.readthedocs.io/>`__.

Examples
========

Examples of use are available in
`ReadTheDocs <https://rdata.readthedocs.io/en/stable/auto_examples/>`__.

Simple usage
============

Read a R dataset
----------------

The common way of reading an R dataset is the following one:

.. code:: python

import rdata

converted = rdata.read_rda(rdata.TESTDATA_PATH / "test_vector.rda")
converted

which results in

.. code::

{'test_vector': array([1., 2., 3.])}

Under the hood, this is equivalent to the following code:

.. code:: python

import rdata

parsed = rdata.parser.parse_file(rdata.TESTDATA_PATH / "test_vector.rda")
converted = rdata.conversion.convert(parsed)
converted

This consists on two steps:

#. First, the file is parsed using the function
`rdata.parser.parse_file <https://rdata.readthedocs.io/en/latest/modules/rdata.parser.parse_file.html>`__.
This provides a literal description of the
file contents as a hierarchy of Python objects representing the basic R
objects. This step is unambiguous and always the same.
#. Then, each object must be converted to an appropriate Python object. In this
step there are several choices on which Python type is the most appropriate
as the conversion for a given R object. Thus, we provide a default
`rdata.conversion.convert <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.convert.html>`__
routine, which tries to select Python objects that preserve most information
of the original R object. For custom R classes, it is also possible to
specify conversion routines to Python objects.

Convert custom R classes
------------------------

The basic
`convert <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.convert.html>`__
routine only constructs a
`SimpleConverter <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.SimpleConverter.html>`__
object and calls its
`convert <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.SimpleConverter.html#rdata.conversion.SimpleConverter.convert>`__
method. All arguments of
`convert <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.convert.html>`__
are directly passed to the
`SimpleConverter <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.SimpleConverter.html>`__
initialization method.

It is possible, although not trivial, to make a custom
`Converter <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.Converter.html>`__
object to change the way in which the
basic R objects are transformed to Python objects. However, a more common
situation is that one does not want to change how basic R objects are
converted, but instead wants to provide conversions for specific R classes.
This can be done by passing a dictionary to the
`SimpleConverter <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.SimpleConverter.html>`__
initialization method, containing
as keys the names of R classes and as values, callables that convert a
R object of that class to a Python object. By default, the dictionary used
is
`DEFAULT_CLASS_MAP <https://rdata.readthedocs.io/en/latest/modules/rdata.conversion.DEFAULT_CLASS_MAP.html>`__,
which can convert commonly used R classes such as
`data.frame <https://www.rdocumentation.org/packages/base/topics/data.frame>`__
and `factor <https://www.rdocumentation.org/packages/base/topics/factor>`__.

As an example, here is how we would implement a conversion routine for the
factor class to
`bytes <https://docs.python.org/3/library/stdtypes.html#bytes>`__
objects, instead of the default conversion to
Pandas
`Categorical <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Categorical.html#pandas.Categorical>`__ objects:

.. code:: python

import rdata

def factor_constructor(obj, attrs):
values = [bytes(attrs['levels'][i - 1], 'utf8')
if i >= 0 else None for i in obj]

return values

new_dict = {
**rdata.conversion.DEFAULT_CLASS_MAP,
"factor": factor_constructor
}

converted = rdata.read_rda(
rdata.TESTDATA_PATH / "test_dataframe.rda",
constructor_dict=new_dict,
)
converted

which has the following result:

.. code::

{'test_dataframe': class value
1 b'a' 1
2 b'b' 2
3 b'b' 3}

Additional examples
===================

Additional examples illustrating the functionalities of this package can be
found in the
`ReadTheDocs documentation <https://rdata.readthedocs.io/en/latest/auto_examples/index.html>`__.


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