RPy (R from Python)

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[Rpy] A terrible experience with rpy2.

From: Bo Peng <ben.bob@gm...> - 2009-04-22 17:16

Dear all,

I have been a long time rpy user. rpy is *very simple* to use in that
you essentially only need to remember two things:

1. Call a R function using r.func(). The only exception is to use _
for . in case that there is a dot in the function name (r.R_Version()
for R.Version() and r.dev_off() for dev.off()).

2. Call a R function or a long script using r('blah blah').

Because rpy2 is said to be replacing rpy. I had a quick look at the
rpy2 manual (I admit that I am positively impressed) and tried to use
rpy2 today. In one of my scripts, the first call is to a R.Version
function to determine its revision number. This is where the nightmare
began.

Using rpy, this is simply int(r.R_Version()['svn rev']). Please allow
me to quote and comment on what I have done. Note that this is using
Python 2.4.3, rpy2.0.3 on a Redhat RHEL5 system.

% python
Python 2.4.3 (#1, Sep 17 2008, 16:07:08)
[GCC 4.1.2 20071124 (Red Hat 4.1.2-41)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from rpy2.robjects import *
>>> r.R_Version()
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "/usr/lib64/python2.4/site-packages/rpy2/robjects/__init__.py",
line 511, in __getattribute__
raise orig_ae
AttributeError: 'R' object has no attribute 'R_Version'
>>> r.R.Version()
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "/usr/lib64/python2.4/site-packages/rpy2/robjects/__init__.py",
line 511, in __getattribute__
raise orig_ae
AttributeError: 'R' object has no attribute 'R'

The _ to . conversion is gone! Then I read
http://rpy.sourceforge.net/rpy2/doc/html/robjects.html and notice
that, to use such functions, I have to use rpy_classic.

>>> from rpy2.rpy_classic import *
>>> r.R_Version()
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "/usr/lib64/python2.4/site-packages/rpy2/rpy_classic.py", line
254, in __getattr__
res = self.__getitem__(name)
File "/usr/lib64/python2.4/site-packages/rpy2/rpy_classic.py", line
261, in __getitem__
res = rpy2py(res)
File "/usr/lib64/python2.4/site-packages/rpy2/rpy_classic.py", line
176, in rpy2py
raise ValueError("Invalid default mode.")
ValueError: Invalid default mode.

Well, I remember there was a mode thing in rpy, but BASIC_CONVERSION
was set by default. Anyway,

>>> set_default_mode(BASIC_CONVERSION)
>>> r.R_Version()
[['x86_64-redhat-linux-gnu'], ['x86_64'], ['linux-gnu'], ['x86_64,
linux-gnu'], [''], ['2'], ['7.1'], ['2008'], ['06'], ['23'],
['45970'], ['R'], ['R version 2.7.1 (2008-06-23)']]

But where is the 'svn rev' key?

In R, this function returns something like

> R.Version()
$platform
[1] "x86_64-redhat-linux-gnu"

$arch
[1] "x86_64"

$os
[1] "linux-gnu"

and rpy returns a dictionary, as expected.

>>> r.R_Version()
{'status': '', 'major': '2', 'version.string': 'R version 2.7.1
(2008-06-23)', 'language': 'R', 'os': 'linux-gnu', 'svn rev': '45970',
'system': 'x86_64, linux-gnu', 'month': '06', 'platform':
'x86_64-redhat-linux-gnu', 'year': '2008', 'arch': 'x86_64', 'day':
'23', 'minor': '7.1'}

Maybe the raw R object has more information?

>>> set_default_mode(NO_CONVERSION)
>>> r.R_Version()
<rpy2.rpy_classic.Robj object at 0x2b3f5bda4810>
>>> r.R_Version()[0]
<rpy2.rpy_classic.Robj object at 0x2b3f5bda4b90>

What is this? I admit that I am completely lost and do not know how to proceed.

Now, what about the old faithful r('R.Version()')? In rpy, I could do
>>> r('R.Version()')
{'status': '', 'major': '2', 'version.string': 'R version 2.7.1
(2008-06-23)', 'language': 'R', 'os': 'linux-gnu', 'svn rev': '45970',
'system': 'x86_64, linux-gnu', 'month': '06', 'platform':
'x86_64-redhat-linux-gnu', 'year': '2008', 'arch': 'x86_64', 'day':
'23', 'minor': '7.1'}

In rpy2,

>>> from rpy2.rpy_classic import *
>>> set_default_mode(NO_CONVERSION)
>>> r('R.Version()')
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "/usr/lib64/python2.4/site-packages/rpy2/rpy_classic.py", line
265, in __call__
return self.eval(self.parse(text=s))
File "/usr/lib64/python2.4/site-packages/rpy2/rpy_classic.py", line
199, in __call__
a = a.getSexp()
AttributeError: 'Robj' object has no attribute 'getSexp'

What about the robject mode?

>>> from rpy2.robjects import *
>>> r('R.Version()')
<RVector - Python:0x2b74072e0830 / R:0x20256eb8>
>>> r('R.Version()')[0]
<RVector - Python:0x2b740af211b8 / R:0x20a4db48>
>>> r('R.Version()')[0][0]
'x86_64-redhat-linux-gnu'

Looks better, it is a vector, but why the first element is [0][0], not [0]?

>>> print r('R.Version()')
$platform
[1] "x86_64-redhat-linux-gnu"

..

Great, the information is there, but how can I get 'svn rev'???

>>> print r('R.Version()').getnames()
[1] "platform" "arch" "os" "system"
[5] "status" "major" "minor" "year"
[9] "month" "day" "svn rev" "language"
[13] "version.string"
>>> print r('R.Version()')['svn rev']
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "/usr/lib64/python2.4/site-packages/rpy2/robjects/__init__.py",
line 266, in __getitem__
res = super(RVector, self).__getitem__(i)
TypeError: an integer is required

Finally, I found the subset function,

>>> r('R.Version()').subset('svn rev')
<RVector - Python:0x2b740af231b8 / R:0x20556ec8>
>>> print r('R.Version()').subset('svn rev')
$`svn rev`
[1] "45970"

but the only way to get the revision number seems to be

>>> r('R.Version()').subset('svn rev')[0][0]
'45970'

If the correct answer is r('R.Version()').subset('svn rev')[0][0], I
have to say that rpy2 is not for me. I can see that a lot of energy
has been devoted to make Python and R integrate better, but I do not
see any benefit from such an effort. In summary,

1. rpy_classic is not the same as rpy.
2. The R vector etc are too complicated to use, and I do not see any
benefit of using them.
3. The rpy_object stuff is almost useless without support for the . to
_ conversion, because there are so many functions in R with .
(dev.off(), as.xxxx()...).

I apologize if all these were due to my incorrect use of rpy2.
Bo

Thread View

Thread	Author	Date
[Rpy] A terrible experience with rpy2.	Bo Peng <ben.bob@gm...>

Re: [Rpy] rpy2 memory leak

From: Denham Robert <Robert.Denham@nr...> - 2009-04-23 02:53

I know this was raised before, and I saw a suggestion that using
gc.collect seemed to fix things, but I am getting I think a memory leak
in rpy2 which doesn't seem to occur in rpy. This could be how I am
coding things of course. Here is an example:

import rpy2.robjects as robjects
from numpy import *
import rpy2.robjects.numpy2ri
import gc

robjects.r('set.seed(99813)')
aa = array(robjects.r.runif(205))
bb = arange(0,1,step=1/205.0)robjects.r('library(locfit)')
lfraw = robjects.globalEnv.get("locfit.raw")

##and try this many times:
for i in range(90000):
if i%1000==0:
gc.collect()
print i
res = lfraw(bb,aa)

If I monitor this using top, the memory use steadily increases. This
does not happen with the equivalent code in rpy. We would like to use
some R functions many times, so the memory leak is of concern. Does
anyone have any insight to this problem -- perhaps I can modify my code
to avoid it, or should we go back to rpy?

I am using rpy2 2.0.3 on linux on 64bit suse running R-2.8.0

Thanks
Robert

As of 26 March 2009 the Department of Natural Resources and Water/Environmental Protection Agency integrated to form the Department of Environment and Resource Management

Queensland celebrates its 150th anniversary in 2009. Check out what's on today at http://www.q150.qld.gov.au

************************************************************************
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Re: [Rpy] A terrible experience with rpy2.

From: laurent <lgautier@gm...> - 2009-04-23 03:35

On Wed, 2009-04-22 at 12:16 -0500, Bo Peng wrote:
(...)

> If the correct answer is r('R.Version()').subset('svn rev')[0][0], I
> have to say that rpy2 is not for me.

1- There is not "one correct answer". There are several ways to achieve
it. Other options are :

import rpy2.robjects as ro

ro.r('R.Version()[["svn rev"]]')[0]
ro.r('R.Version()').r["svn rev"][0][0]

2- rpy is still around.

> I can see that a lot of energy
> has been devoted to make Python and R integrate better, but I do not
> see any benefit from such an effort.

> In summary,
>
> 1. rpy_classic is not the same as rpy.

This is not a complete implementation of the rpy API because of:
- limited resources
- apparently a limited demand
Contributions have not been many.

> 2. The R vector etc are too complicated to use, and I do not see any
> benefit of using them.

Watch closer, I'd like to say.

> 3. The rpy_object stuff is almost useless without support for the . to
> _ conversion, because there are so many functions in R with .
> (dev.off(), as.xxxx()...).
>

It's straightforward to implement for yourself. Where is the/your
problem ?

> I apologize if all these were due to my incorrect use of rpy2.

Shouldn't that though come first ?

> Bo
>
> ------------------------------------------------------------------------------
> Stay on top of everything new and different, both inside and
> around Java (TM) technology - register by April 22, and save
> $200 on the JavaOne (SM) conference, June 2-5, 2009, San Francisco.
> 300 plus technical and hands-on sessions. Register today.
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> _______________________________________________
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> rpy-list@li...
> https://lists.sourceforge.net/lists/listinfo/rpy-list

Re: [Rpy] rpy2 memory leak

From: laurent <lgautier@gm...> - 2009-04-23 03:35

Thanks,
I'll look into that ASAP.

L.

On Thu, 2009-04-23 at 12:29 +1000, Denham Robert wrote:
> I know this was raised before, and I saw a suggestion that using
> gc.collect seemed to fix things, but I am getting I think a memory leak
> in rpy2 which doesn't seem to occur in rpy. This could be how I am
> coding things of course. Here is an example:
>
> import rpy2.robjects as robjects
> from numpy import *
> import rpy2.robjects.numpy2ri
> import gc
>
> robjects.r('set.seed(99813)')
> aa = array(robjects.r.runif(205))
> bb = arange(0,1,step=1/205.0)robjects.r('library(locfit)')
> lfraw = robjects.globalEnv.get("locfit.raw")
>
> ##and try this many times:
> for i in range(90000):
> if i%1000==0:
> gc.collect()
> print i
> res = lfraw(bb,aa)
>
>
> If I monitor this using top, the memory use steadily increases. This
> does not happen with the equivalent code in rpy. We would like to use
> some R functions many times, so the memory leak is of concern. Does
> anyone have any insight to this problem -- perhaps I can modify my code
> to avoid it, or should we go back to rpy?
>
> I am using rpy2 2.0.3 on linux on 64bit suse running R-2.8.0
>
>
>
>
> Thanks
> Robert
>
>
> As of 26 March 2009 the Department of Natural Resources and Water/Environmental Protection Agency integrated to form the Department of Environment and Resource Management
>
> Queensland celebrates its 150th anniversary in 2009. Check out what's on today at http://www.q150.qld.gov.au
>
> ************************************************************************
> The information in this email together with any attachments is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material.
> Any form of review, disclosure, modification, distribution and/or publication of this email message is prohibited, unless as a necessary part of Departmental business.
> If you have received this message in error, you are asked to inform the sender as quickly as possible and delete this message and any copies of this message from your computer and/or your computer system network.
> ************************************************************************
>
>
>
>
> ------------------------------------------------------------------------------
> Stay on top of everything new and different, both inside and
> around Java (TM) technology - register by April 22, and save
> $200 on the JavaOne (SM) conference, June 2-5, 2009, San Francisco.
> 300 plus technical and hands-on sessions. Register today.
> Use priority code J9JMT32. http://p.sf.net/sfu/p
> _______________________________________________
> rpy-list mailing list
> rpy-list@li...
> https://lists.sourceforge.net/lists/listinfo/rpy-list

Re: [Rpy] A terrible experience with rpy2.

From: Bo Peng <ben.bob@gm...> - 2009-04-23 04:53

On Wed, Apr 22, 2009 at 10:33 PM, laurent <lgautier@gm...> wrote:
> On Wed, 2009-04-22 at 12:16 -0500, Bo Peng wrote:
> (...)

I apologize for the wording of my previous email, which was sent, less
than politely, out of my extreme frustration over a software I had
high expectation. However, if you consider all the frustrations
misuses of rpy2 and do not see bugs or feature requests there, I will
not bother you again with them.

>> If the correct answer is r('R.Version()').subset('svn rev')[0][0], I
>> have to say that rpy2 is not for me.
>
> 1- There is not "one correct answer". There are several ways to achieve
> it. Other options are :
>
> ro.r('R.Version()[["svn rev"]]')[0]
> ro.r('R.Version()').r["svn rev"][0][0]

These look as ugly as r('R.Version()').subset('svn rev')[0][0]. I do
not want to go into all the technical complexities here because they
are irrelevant in terms of user expectation. Essentially speaking,
R.Version() returns a list of strings identifiable by keys so users
expect something like a dictionary, even if it is something wrapped
around a R object.

-- If R.Version()[["svn rev"]] returns '12345' in R, users will expect
'12345' in rpy. The [0] part is simply redundant and makes me wonder
what is [1].

-- If r('R.Version()') returns the whole dictionary-like object, it is
natural to expect r('R.Version()')['svn rev']. Users will have to know
a lot about rpy2 to write something like r["svn rev"][0][0].

Compared to r('R.Version()')['svn rev'] in rpy, the syntax in rpy2 is
extremely difficult to understand.

> 2- rpy is still around.

I hope that it will continue to be maintained for future versions of
Python and R.

>> 1. rpy_classic is not the same as rpy.
>
> This is not a complete implementation of the rpy API because of:
> - limited resources
> - apparently a limited demand
> Contributions have not been many.

As the maintainer of another open source object, I do understand all
these but please indicate clearly the differences between rpy_classic
and rpy in the documentation.

>> 2. The R vector etc are too complicated to use, and I do not see any
>> benefit of using them.
>
> Watch closer, I'd like to say.

I looked through the rpy2 documentation and I could not find an answer
to questions such as what is lacking in rpy, what problems rpy2 is
trying to address, what are the advantages of rpy2 over rpy, and in
which way users will benefit from rpy2. Instead, I saw you were
motivated by some alternative implementation (??) of rpy. My guess is
that this implementation allows rpy2 to expose internal R objects as
native Python objects. These are of course not a bad thing but I would
like to know how exactly normal users would benefit from this
approach, at the cost of all the syntax complexities/oddities.

>> 3. The rpy_object stuff is almost useless without support for the . to
>> _ conversion, because there are so many functions in R with .
>> (dev.off(), as.xxxx()...).

> It's straightforward to implement for yourself. Where is the/your
> problem ?

I had contributed to rpy before and I am still listed as one of the
developers. However, I need to be persuaded that rpy2 is better than
rpy to invest my time on it. Right now, I am afraid that rpy2 might be
designed around technical possibilities, not users' need.

Cheers,
Bo

Re: [Rpy] rpy2 memory leak

From: Réjean Ducharme <ducharme@ap...> - 2009-04-23 14:46

There are many posts concerning a memory leak in rpy2, and I have to say
that it's also affecting me.
But fortunately, after losing a couple of days on this problem, I found
this webpage that kind of solve my problem:

http://code.activestate.com/recipes/511474/

The solution is to wrap the work done by rpy2 in a function, and to run
it in a seperate process.
When this process finish, you can be sure that all ressources used by
rpy2 are released!

I know that it is a hack, but at least it worked for me!
I hope this could help some of you who have the same problem.

Réjean

> Thanks,
> I'll look into that ASAP.
>
>
>
> L.
>
>
>
> On Thu, 2009-04-23 at 12:29 +1000, Denham Robert wrote:
>
>> I know this was raised before, and I saw a suggestion that using
>> gc.collect seemed to fix things, but I am getting I think a memory leak
>> in rpy2 which doesn't seem to occur in rpy. This could be how I am
>> coding things of course. Here is an example:
>>
>> import rpy2.robjects as robjects
>> from numpy import *
>> import rpy2.robjects.numpy2ri
>> import gc
>>
>> robjects.r('set.seed(99813)')
>> aa = array(robjects.r.runif(205))
>> bb = arange(0,1,step=1/205.0)robjects.r('library(locfit)')
>> lfraw = robjects.globalEnv.get("locfit.raw")
>>
>> ##and try this many times:
>> for i in range(90000):
>> if i%1000==0:
>> gc.collect()
>> print i
>> res = lfraw(bb,aa)
>>
>>
>> If I monitor this using top, the memory use steadily increases. This
>> does not happen with the equivalent code in rpy. We would like to use
>> some R functions many times, so the memory leak is of concern. Does
>> anyone have any insight to this problem -- perhaps I can modify my code
>> to avoid it, or should we go back to rpy?
>>
>> I am using rpy2 2.0.3 on linux on 64bit suse running R-2.8.0
>>
>>
>>
>>
>> Thanks
>> Robert

Re: [Rpy] rpy2 memory leak

From: laurent <lgautier@gm...> - 2009-04-26 13:02

Hi Robert,

I looked at it a little closer, and the problem was a nasty missing
Py_DECREF() in rinterface.c's newSEXP(). People mostly creating their
vectors/arrays with R were not much subject to the problem, which may
explain why there were only sporadic complains about a process growing
in size.

The fix is already in bitbucket's 2.1-dev, as well as backported to the
2.0.x branch.

The bug is serious enough to trigger a bugfix release 2.0.4 soon (within
a week, I think).

L.

On Thu, 2009-04-23 at 12:29 +1000, Denham Robert wrote:
> I know this was raised before, and I saw a suggestion that using
> gc.collect seemed to fix things, but I am getting I think a memory leak
> in rpy2 which doesn't seem to occur in rpy. This could be how I am
> coding things of course. Here is an example:
>
> import rpy2.robjects as robjects
> from numpy import *
> import rpy2.robjects.numpy2ri
> import gc
>
> robjects.r('set.seed(99813)')
> aa = array(robjects.r.runif(205))
> bb = arange(0,1,step=1/205.0)robjects.r('library(locfit)')
> lfraw = robjects.globalEnv.get("locfit.raw")
>
> ##and try this many times:
> for i in range(90000):
> if i%1000==0:
> gc.collect()
> print i
> res = lfraw(bb,aa)
>
>
> If I monitor this using top, the memory use steadily increases. This
> does not happen with the equivalent code in rpy. We would like to use
> some R functions many times, so the memory leak is of concern. Does
> anyone have any insight to this problem -- perhaps I can modify my code
> to avoid it, or should we go back to rpy?
>
> I am using rpy2 2.0.3 on linux on 64bit suse running R-2.8.0
>
>
>
>
> Thanks
> Robert
>
>
> As of 26 March 2009 the Department of Natural Resources and Water/Environmental Protection Agency integrated to form the Department of Environment and Resource Management
>
> Queensland celebrates its 150th anniversary in 2009. Check out what's on today at http://www.q150.qld.gov.au
>
> ************************************************************************
> The information in this email together with any attachments is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material.
> Any form of review, disclosure, modification, distribution and/or publication of this email message is prohibited, unless as a necessary part of Departmental business.
> If you have received this message in error, you are asked to inform the sender as quickly as possible and delete this message and any copies of this message from your computer and/or your computer system network.
> ************************************************************************
>
>
>
>
> ------------------------------------------------------------------------------
> Stay on top of everything new and different, both inside and
> around Java (TM) technology - register by April 22, and save
> $200 on the JavaOne (SM) conference, June 2-5, 2009, San Francisco.
> 300 plus technical and hands-on sessions. Register today.
> Use priority code J9JMT32. http://p.sf.net/sfu/p
> _______________________________________________
> rpy-list mailing list
> rpy-list@li...
> https://lists.sourceforge.net/lists/listinfo/rpy-list

Re: [Rpy] A terrible experience with rpy2.

From: laurent <lgautier@gm...> - 2009-04-29 04:53

On Wed, 2009-04-22 at 23:53 -0500, Bo Peng wrote:
> On Wed, Apr 22, 2009 at 10:33 PM, laurent <lgautier@gm...> wrote:
> > On Wed, 2009-04-22 at 12:16 -0500, Bo Peng wrote:
> > (...)
>
> I apologize for the wording of my previous email, which was sent, less
> than politely, out of my extreme frustration over a software I had
> high expectation. However, if you consider all the frustrations
> misuses of rpy2 and do not see bugs or feature requests there, I will
> not bother you again with them.

I am sorry to have to say that what seems mostly like unstructured and
public venting of frustration (or 無的放矢 if you prefer) might not meet
lengthy diplomatic answers, if any.

> >> If the correct answer is r('R.Version()').subset('svn rev')[0][0], I
> >> have to say that rpy2 is not for me.
> >
> > 1- There is not "one correct answer". There are several ways to achieve
> > it. Other options are :
> >
> > ro.r('R.Version()[["svn rev"]]')[0]
> > ro.r('R.Version()').r["svn rev"][0][0]
>
> These look as ugly as r('R.Version()').subset('svn rev')[0][0]. I do
> not want to go into all the technical complexities here because they
> are irrelevant in terms of user expectation. Essentially speaking,
> R.Version() returns a list of strings identifiable by keys so users
> expect something like a dictionary, even if it is something wrapped
> around a R object.

An R list is not a dictionary and cannot be reliably represented as such
for a) it is ordered, b) names do not have to be unique.
Spending time on the archives for this list could have been an
alternative to writing the above:
http://www.mail-archive.com/rpy-list@li.../msg01337.html

Otherwise, customization is straightforward:
http://rpy.sourceforge.net/rpy2/doc/html/robjects_convert.html#a-simple-example

> -- If R.Version()[["svn rev"]] returns '12345' in R, users will expect
> '12345' in rpy. The [0] part is simply redundant and makes me wonder
> what is [1].
>
> -- If r('R.Version()') returns the whole dictionary-like object, it is
> natural to expect r('R.Version()')['svn rev']. Users will have to know
> a lot about rpy2 to write something like r["svn rev"][0][0].
>
> Compared to r('R.Version()')['svn rev'] in rpy, the syntax in rpy2 is
> extremely difficult to understand.

I do not think so. The choice made is the one of consistency for the
python __getitem__/"["; R lists are recursive structures (having two
ways to be subset "[", and "[[").

A short section in the documentation describing particularities
about a list is what I mostly see missing in the short term.

"robjects" is otherwise still evolving and likely getting better.
It is one high-level interface, and there is one known alternative to it
(rnumpy).

> > 2- rpy is still around.
>
> I hope that it will continue to be maintained for future versions of
> Python and R.
>
> >> 1. rpy_classic is not the same as rpy.
> >
> > This is not a complete implementation of the rpy API because of:
> > - limited resources
> > - apparently a limited demand
> > Contributions have not been many.
>
> As the maintainer of another open source object, I do understand all
> these but please indicate clearly the differences between rpy_classic
> and rpy in the documentation.

The first sentence at
http://rpy.sourceforge.net/rpy2/doc/html/rpy_classic.html
appears to be:
"This module provides an API similar to the one in RPy-1.x (rpy)."

"Similar" is used here for "some of the same characteristics".

> >> 2. The R vector etc are too complicated to use, and I do not see any
> >> benefit of using them.
> >
> > Watch closer, I'd like to say.
>
> I looked through the rpy2 documentation and I could not find an answer
> to questions such as what is lacking in rpy, what problems rpy2 is
> trying to address, what are the advantages of rpy2 over rpy, and in
> which way users will benefit from rpy2. Instead, I saw you were
> motivated by some alternative implementation (??) of rpy. My guess is
> that this implementation allows rpy2 to expose internal R objects as
> native Python objects. These are of course not a bad thing but I would
> like to know how exactly normal users would benefit from this
> approach, at the cost of all the syntax complexities/oddities.

Read more, guess less.

- A low-level interface upon which high-level interface can be built
http://rpy.sourceforge.net/rpy2/doc/html/overview.html#design-notes
http://rpy.sourceforge.net/rpy2/doc/html/robjects.html#overview

- Better similarity between R and rpy code:
http://rpy.sourceforge.net/rpy2/doc/html/introduction.html#principal-component-analysis

- No more CONVERSION/NO_CONVERSION poking.
http://rpy.sourceforge.net/rpy2/doc/html/robjects.html#overview

> >> 3. The rpy_object stuff is almost useless without support for the . to
> >> _ conversion, because there are so many functions in R with .
> >> (dev.off(), as.xxxx()...).
>
> > It's straightforward to implement for yourself. Where is the/your
> > problem ?
>
> I had contributed to rpy before and I am still listed as one of the
> developers. However, I need to be persuaded that rpy2 is better than
> rpy to invest my time on it. Right now, I am afraid that rpy2 might be
> designed around technical possibilities, not users' need.

Thanks for sharing this with us, but whether rpy or rpy2 suits best your
needs is mostly for yourself to decide.

Also, since "users' needs" seems to be used in place of "my needs", may
be you can tell us a little more about what you are doing ?

L.

> Cheers,
> Bo
>
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