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****************
Related projects
****************
Bioinformatics
==============
Cloud computing
---------------
`rpy2` is among the many bioinformatics-oriented packages
provided with `CloudBioLinux <http://cloudbiolinux.org/>`_. Check it out if
you are considering a project involving cloud computing.
Bioconductor
------------
Bioconductor is a popular set of R packages for bioinformatics.
A number of classes defined within that project are exposed as Python
classes through rpy2,
in the project `rpy2-bioconductor-extensions <http://pypi.python.org/pypi/rpy2-bioconductor-extensions/0.2-dev>`_. The bioconductor project is evolving quite rapidely the mapping might not longer be working.
The `blog of Brad Chapman <http://bcbio.wordpress.com/>`_ also has good examples about how to use `rpy2` for bioinformatics tasks (or Python for bioinformatics
in general).
.. _interactive-sessions:
Interactive consoles
====================
Data analysts often like to work interactively, that is going through short
cycles like:
* write a bit of code, which can be mostly involving a call to an existing function
* run that code
* inspect the results, often using plots and figures
R users will be particularly familiar with this sort of approach, and will likely
want it when working with :mod:`rpy2`.
Obviously the Python console can be used, but there exist improvements to it, making
the user experience more pleasant with features such as history and autocompletion.
Other interactive environments
------------------------------
* bpython: curse-based enhancement to the Python console
* emacs: the Emacs text editor can be used to host a python session,
or an ipython session
Embeddeding an R console
------------------------
Python can be used to develop full-fledged applications, including applications with
a graphical user interface.
:mod:`rpy2` can be used to provide an R console embedded in such applications,
or build an alternative R GUI.
When offering an R console, the developer(s) may want to retain control on the
the way interaction with R is handled, at the level of the console and for the
base R functions targetting interactivity (see Section :ref:`rinterface-callbacks`).
The `RPyGTK project <http://code.google.com/p/rpygtk/>`_ demonstrates how
:mod:`rpy2` can be used to implement a full-blown GUI for R using python.
Alternative interfaces
=======================
The `rtools <http://pypi.python.org/pypi/rtools>`_ package proposes additions / customizations of the higher-level
interface in rpy2.
The `pandas <http://pypi.python.org/pypi/pandas>` package proposes an interpretation of data frames in Python,
tied to numpy structures. A custom interfacing with rpy2 is mentioned, but it appears not as much developed as
the rest of the project.
R-like data strucutures
=======================
R's data frames are extremely convient when manipulating data.
In :mod:`rpy2` the original R `data.frame` is represented by
:class:`rpy2.robjects.vectors.DataFrame`, but the
`pydataframe <http://code.google.com/p/pydataframe/>`_ project
has a pure Python implementation of them (with a compatibility
layer with :mod:`rpy2` providing a seamless transition
whenever needed.
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