<br><br><div class="gmail_quote">2012/10/25 <span dir="ltr"><<a href="mailto:ipython-user-request@scipy.org" target="_blank">ipython-user-request@scipy.org</a>></span><br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
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Today's Topics:<br>
<br>
1. Re: questions about IPython.parallel (MinRK)<br>
2. Re: questions about IPython.parallel (Francesco Montesano)<br>
3. Re: questions about IPython.parallel (Min RK)<br>
4. error of install ipython 0.10.0 (Jack Bryan)<br>
<br>
<br>
----------------------------------------------------------------------<br>
<br>
Message: 1<br>
Date: Wed, 24 Oct 2012 10:37:56 -0700<br>
From: MinRK <<a href="mailto:benjaminrk@gmail.com">benjaminrk@gmail.com</a>><br>
Subject: Re: [IPython-User] questions about IPython.parallel<br>
To: "Discussions about using IPython. <a href="http://ipython.org" target="_blank">http://ipython.org</a>"<br>
<<a href="mailto:ipython-user@scipy.org">ipython-user@scipy.org</a>><br>
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<br>
On Wed, Oct 24, 2012 at 3:36 AM, Francesco Montesano <<br>
<a href="mailto:franz.bergesund@gmail.com">franz.bergesund@gmail.com</a>> wrote:<br>
<br>
> Dear list,<br>
><br>
> I have a bunch of coded designed to repeat the same operation over a<br>
> (possibly large)<br>
> number of file. So after discovering Ipython.parallel not long ago, I<br>
> decided to<br>
> rewrite to give me the possibility to use a task scheduler (I use<br>
> load_balance_view) in order<br>
> to make the best use possible of my quad core machines.<br>
> Here is the typical structure of my code<br>
><br>
> ###### BEGIN example.py ######<br>
> #imports<br>
><br>
> def command_line_parsing( ... ):<br>
> "in my case argparse"<br>
><br>
> def do_some_operation( ... ):<br>
> "executes some mathematical operation"<br>
><br>
> def read_operate_save_file( file, ... ):<br>
> """reads the file, does operations and save to an output file"""<br>
> input = np.loadtxt( file )<br>
> [1] do_some_operation( )<br>
> np.savetxt( outfile, ..... )<br>
><br>
> if __name__ == "__main__":<br>
><br>
> args = command_line_parsing( )<br>
><br>
> #parallelisation can be can chosen or not<br>
> if args.parallel :<br>
> #checks that Ipython is there, that an ipcluster has been started<br>
> #initialises a Client and a load_balance_view. I can pass a string<br>
> or<br>
> #list of strings to be executed on all engines (I use it to<br>
> "import xxx as x" )<br>
> lview = IPp.start_load_balanced_view( to_execute )<br>
><br>
> if( args.parallel == False ): #for serial computation<br>
> [2] for fn in args.ifname: #file name loop<br>
> output = read_operate_save_file(fn, dis, **vars(args) )<br>
> else: #I want parallel computation<br>
> [3] runs = [ lview.apply( read_operate_save_file,<br>
> os.path.abspath(<a href="http://fn.name" target="_blank">fn.name</a>), ... ) for fn in args.ifname ]<br>
> results = [r.result for r in runs]<br>
><br>
> ###### END example.py ######<br>
><br>
> I have two questions:<br>
> [1] In function 'read_operate_save_file', I call 'do_some_operation'. When<br>
> I<br>
> work on serial mode, everything works fine, but in parallel mode I get<br>
> the error<br>
> "IPython.parallel.error.RemoteError: NameError(global name<br>
> 'do_some_operation' is not defined)"<br>
> I'm not surprised by this, as I imagine that each engine know only what<br>
> has been<br>
> executed or defined before and that lview.apply( func, ... ) just passes<br>
> the<br>
> "func" to the engines. A solution that I see is to run "from example import<br>
> do_some_operation" on the engines when initialising the load_balance_view.<br>
> Is<br>
> there any easier/safer way?<br>
><br>
<br>
<br>
This namespace issue is common, and I have explanations scattered about the<br>
internet:<br>
<br>
<a href="http://stackoverflow.com/a/12307741/938949" target="_blank">http://stackoverflow.com/a/12307741/938949</a><br>
<a href="http://stackoverflow.com/a/10859394/938949" target="_blank">http://stackoverflow.com/a/10859394/938949</a><br>
<a href="https://github.com/ipython/ipython/issues/2489" target="_blank">https://github.com/ipython/ipython/issues/2489</a><br>
<a href="http://ipython.org/ipython-doc/dev/parallel/index.html" target="_blank">http://ipython.org/ipython-doc/dev/parallel/index.html</a><br>
<br>
Which I really need to consolidate into a single thorough explanation with<br>
examples.<br>
<br>
But the gist:<br>
<br>
- If a function is importable (e.g. in a module available both locally and<br>
remotely), then it's no problem<br>
- If it is defined in __main__ (e.g. in a script), then any references will<br>
be resolved in the *engine* namespace<br>
<br>
I recommend conforming to the first case if feasible, because then there<br>
should be no surprises.<br>
Everything surprising happens when you have depend on references in<br>
`__main__` or the current working dir (e.g. locally imported modules),<br>
since `__main__` is not the same on the various machines, nor is the<br>
working dir (necessarily).<br>
<br>
That said, if the names you need to resolve are few, a simple import/push<br>
step with a DirectView to set up namespaces should be all you need prior to<br>
submitting tasks (assuming new engines are not arriving in mid-computation).<br>
<br>
e.g.:<br>
<br>
rc = Client()<br>
dv = rc[:]<br>
# push any locally defined functions that your task function uses:<br>
dv['do_some_operation'] = do_some_operation<br>
# perform any imports that are needed:<br>
dv.execute("import numpy as np...")<br>
# continue as before:<br>
lview = IPp.start_load_balanced_view( to_execute )<br>
...<br>
<br>
<br>
<br>
><br>
> [2] Because of the way I parse my command line arguments, args.ifname its a<br>
> list of already opened files. In serial mode, this is no problem, but when<br>
> I<br>
> assign the function to the scheduler passing the file, I get an error<br>
> saying<br>
> that the cannot work on a closed file. If I pass the file name with the<br>
> absolute path, numpy can read it without problem. Is this a behaviour to be<br>
> expected or a bug?<br>
><br>
<br>
I would expect a PickleError when you try to send an open file. Definitely<br>
send filenames, not open file objects.<br>
<br>
<br>
><br>
> Thanks for any help,<br>
><br>
> Cheers,<br>
> Francesco<br>
> _______________________________________________<br>
> IPython-User mailing list<br>
> <a href="mailto:IPython-User@scipy.org">IPython-User@scipy.org</a><br>
> <a href="http://mail.scipy.org/mailman/listinfo/ipython-user" target="_blank">http://mail.scipy.org/mailman/listinfo/ipython-user</a><br>
><br>
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Message: 2<br>
Date: Wed, 24 Oct 2012 22:07:37 +0200<br>
From: Francesco Montesano <<a href="mailto:franz.bergesund@gmail.com">franz.bergesund@gmail.com</a>><br>
Subject: Re: [IPython-User] questions about IPython.parallel<br>
To: "Discussions about using IPython. <a href="http://ipython.org" target="_blank">http://ipython.org</a>"<br>
<<a href="mailto:ipython-user@scipy.org">ipython-user@scipy.org</a>><br>
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<br>
Hi Min,<br>
<br>
thanks for the answer<br>
<br>
2012/10/24 MinRK <<a href="mailto:benjaminrk@gmail.com">benjaminrk@gmail.com</a>>:<br>
><br>
><br>
> On Wed, Oct 24, 2012 at 3:36 AM, Francesco Montesano<br>
> <<a href="mailto:franz.bergesund@gmail.com">franz.bergesund@gmail.com</a>> wrote:<br>
>><br>
>> Dear list,<br>
>><br>
>> I have a bunch of coded designed to repeat the same operation over a<br>
>> (possibly large)<br>
>> number of file. So after discovering Ipython.parallel not long ago, I<br>
>> decided to<br>
>> rewrite to give me the possibility to use a task scheduler (I use<br>
>> load_balance_view) in order<br>
>> to make the best use possible of my quad core machines.<br>
>> Here is the typical structure of my code<br>
>><br>
>> ###### BEGIN example.py ######<br>
>> #imports<br>
>><br>
>> def command_line_parsing( ... ):<br>
>> "in my case argparse"<br>
>><br>
>> def do_some_operation( ... ):<br>
>> "executes some mathematical operation"<br>
>><br>
>> def read_operate_save_file( file, ... ):<br>
>> """reads the file, does operations and save to an output file"""<br>
>> input = np.loadtxt( file )<br>
>> [1] do_some_operation( )<br>
>> np.savetxt( outfile, ..... )<br>
>><br>
>> if __name__ == "__main__":<br>
>><br>
>> args = command_line_parsing( )<br>
>><br>
>> #parallelisation can be can chosen or not<br>
>> if args.parallel :<br>
>> #checks that Ipython is there, that an ipcluster has been started<br>
>> #initialises a Client and a load_balance_view. I can pass a string<br>
>> or<br>
>> #list of strings to be executed on all engines (I use it to<br>
>> "import xxx as x" )<br>
>> lview = IPp.start_load_balanced_view( to_execute )<br>
>><br>
>> if( args.parallel == False ): #for serial computation<br>
>> [2] for fn in args.ifname: #file name loop<br>
>> output = read_operate_save_file(fn, dis, **vars(args) )<br>
>> else: #I want parallel computation<br>
>> [3] runs = [ lview.apply( read_operate_save_file,<br>
>> os.path.abspath(<a href="http://fn.name" target="_blank">fn.name</a>), ... ) for fn in args.ifname ]<br>
>> results = [r.result for r in runs]<br>
>><br>
>> ###### END example.py ######<br>
>><br>
>> I have two questions:<br>
>> [1] In function 'read_operate_save_file', I call 'do_some_operation'. When<br>
>> I<br>
>> work on serial mode, everything works fine, but in parallel mode I get<br>
>> the error<br>
>> "IPython.parallel.error.RemoteError: NameError(global name<br>
>> 'do_some_operation' is not defined)"<br>
>> I'm not surprised by this, as I imagine that each engine know only what<br>
>> has been<br>
>> executed or defined before and that lview.apply( func, ... ) just passes<br>
>> the<br>
>> "func" to the engines. A solution that I see is to run "from example<br>
>> import<br>
>> do_some_operation" on the engines when initialising the load_balance_view.<br>
>> Is<br>
>> there any easier/safer way?<br>
><br>
><br>
><br>
> This namespace issue is common, and I have explanations scattered about the<br>
> internet:<br>
><br>
> <a href="http://stackoverflow.com/a/12307741/938949" target="_blank">http://stackoverflow.com/a/12307741/938949</a><br>
> <a href="http://stackoverflow.com/a/10859394/938949" target="_blank">http://stackoverflow.com/a/10859394/938949</a><br>
> <a href="https://github.com/ipython/ipython/issues/2489" target="_blank">https://github.com/ipython/ipython/issues/2489</a><br>
> <a href="http://ipython.org/ipython-doc/dev/parallel/index.html" target="_blank">http://ipython.org/ipython-doc/dev/parallel/index.html</a><br>
><br>
> Which I really need to consolidate into a single thorough explanation with<br>
> examples.<br>
><br>
> But the gist:<br>
><br>
> - If a function is importable (e.g. in a module available both locally and<br>
> remotely), then it's no problem<br>
> - If it is defined in __main__ (e.g. in a script), then any references will<br>
> be resolved in the *engine* namespace<br>
><br>
> I recommend conforming to the first case if feasible, because then there<br>
> should be no surprises.<br>
> Everything surprising happens when you have depend on references in<br>
> `__main__` or the current working dir (e.g. locally imported modules), since<br>
> `__main__` is not the same on the various machines, nor is the working dir<br>
> (necessarily).<br>
><br>
> That said, if the names you need to resolve are few, a simple import/push<br>
> step with a DirectView to set up namespaces should be all you need prior to<br>
> submitting tasks (assuming new engines are not arriving in mid-computation).<br>
><br>
> e.g.:<br>
><br>
> rc = Client()<br>
> dv = rc[:]<br>
> # push any locally defined functions that your task function uses:<br>
> dv['do_some_operation'] = do_some_operation<br>
I ended up doing the following when initialising the load_balance_view<br>
dv.execute( 'import sys' )<br>
dv.execute( 'sys.path.append("path_to_example.py")' )<br>
dv.execute( 'from example import do_some_operation' )<br>
Your suggestion looks much neater, just a couple of questions.<br>
With the push that you suggest, do I simply call the<br>
'do_some_operation' as in my example or do I need some different<br>
syntax?<br>
Do you think that one or the other way is more optimal when the<br>
function is called and executed?<br>
<br>
> # perform any imports that are needed:<br>
> dv.execute("import numpy as np...")<br>
> # continue as before:<br>
> lview = IPp.start_load_balanced_view( to_execute )<br>
> ...<br>
><br>
><br>
>><br>
>><br>
>> [2] Because of the way I parse my command line arguments, args.ifname its<br>
>> a<br>
>> list of already opened files. In serial mode, this is no problem, but when<br>
>> I<br>
>> assign the function to the scheduler passing the file, I get an error<br>
>> saying<br>
>> that the cannot work on a closed file. If I pass the file name with the<br>
>> absolute path, numpy can read it without problem. Is this a behaviour to<br>
>> be<br>
>> expected or a bug?<br>
><br>
><br>
> I would expect a PickleError when you try to send an open file. Definitely<br>
> send filenames, not open file objects.<br>
Just a curiosity: what is the working directory of the engines? Is the<br>
one where the ipcluster is started or where the profile is stored?<br>
(While fixing my code, I ended up passing the filename with the full path)<br>
<br>
Thanks again,<br>
<br>
Francesco<br>
<br>
><br>
>><br>
>><br>
>> Thanks for any help,<br>
>><br>
>> Cheers,<br>
>> Francesco<br>
>> _______________________________________________<br>
>> IPython-User mailing list<br>
>> <a href="mailto:IPython-User@scipy.org">IPython-User@scipy.org</a><br>
>> <a href="http://mail.scipy.org/mailman/listinfo/ipython-user" target="_blank">http://mail.scipy.org/mailman/listinfo/ipython-user</a><br>
><br>
><br>
><br>
> _______________________________________________<br>
> IPython-User mailing list<br>
> <a href="mailto:IPython-User@scipy.org">IPython-User@scipy.org</a><br>
> <a href="http://mail.scipy.org/mailman/listinfo/ipython-user" target="_blank">http://mail.scipy.org/mailman/listinfo/ipython-user</a><br>
><br>
<br>
<br>
------------------------------<br>
<br>
Message: 3<br>
Date: Wed, 24 Oct 2012 13:51:22 -0700<br>
From: Min RK <<a href="mailto:benjaminrk@gmail.com">benjaminrk@gmail.com</a>><br>
Subject: Re: [IPython-User] questions about IPython.parallel<br>
To: "Discussions about using IPython. <a href="http://ipython.org" target="_blank">http://ipython.org</a>"<br>
<<a href="mailto:ipython-user@scipy.org">ipython-user@scipy.org</a>><br>
Message-ID: <<a href="mailto:CCF626CE-650C-4029-A7FA-B7DCDA8A6F30@gmail.com">CCF626CE-650C-4029-A7FA-B7DCDA8A6F30@gmail.com</a>><br>
Content-Type: text/plain; charset=us-ascii<br>
<br>
<br>
<br>
On Oct 24, 2012, at 13:07, Francesco Montesano <<a href="mailto:franz.bergesund@gmail.com">franz.bergesund@gmail.com</a>> wrote:<br>
<br>
> Hi Min,<br>
><br>
> thanks for the answer<br>
><br>
> 2012/10/24 MinRK <<a href="mailto:benjaminrk@gmail.com">benjaminrk@gmail.com</a>>:<br>
>><br>
>><br>
>> On Wed, Oct 24, 2012 at 3:36 AM, Francesco Montesano<br>
>> <<a href="mailto:franz.bergesund@gmail.com">franz.bergesund@gmail.com</a>> wrote:<br>
>>><br>
>>> Dear list,<br>
>>><br>
>>> I have a bunch of coded designed to repeat the same operation over a<br>
>>> (possibly large)<br>
>>> number of file. So after discovering Ipython.parallel not long ago, I<br>
>>> decided to<br>
>>> rewrite to give me the possibility to use a task scheduler (I use<br>
>>> load_balance_view) in order<br>
>>> to make the best use possible of my quad core machines.<br>
>>> Here is the typical structure of my code<br>
>>><br>
>>> ###### BEGIN example.py ######<br>
>>> #imports<br>
>>><br>
>>> def command_line_parsing( ... ):<br>
>>> "in my case argparse"<br>
>>><br>
>>> def do_some_operation( ... ):<br>
>>> "executes some mathematical operation"<br>
>>><br>
>>> def read_operate_save_file( file, ... ):<br>
>>> """reads the file, does operations and save to an output file"""<br>
>>> input = np.loadtxt( file )<br>
>>> [1] do_some_operation( )<br>
>>> np.savetxt( outfile, ..... )<br>
>>><br>
>>> if __name__ == "__main__":<br>
>>><br>
>>> args = command_line_parsing( )<br>
>>><br>
>>> #parallelisation can be can chosen or not<br>
>>> if args.parallel :<br>
>>> #checks that Ipython is there, that an ipcluster has been started<br>
>>> #initialises a Client and a load_balance_view. I can pass a string<br>
>>> or<br>
>>> #list of strings to be executed on all engines (I use it to<br>
>>> "import xxx as x" )<br>
>>> lview = IPp.start_load_balanced_view( to_execute )<br>
>>><br>
>>> if( args.parallel == False ): #for serial computation<br>
>>> [2] for fn in args.ifname: #file name loop<br>
>>> output = read_operate_save_file(fn, dis, **vars(args) )<br>
>>> else: #I want parallel computation<br>
>>> [3] runs = [ lview.apply( read_operate_save_file,<br>
>>> os.path.abspath(<a href="http://fn.name" target="_blank">fn.name</a>), ... ) for fn in args.ifname ]<br>
>>> results = [r.result for r in runs]<br>
>>><br>
>>> ###### END example.py ######<br>
>>><br>
>>> I have two questions:<br>
>>> [1] In function 'read_operate_save_file', I call 'do_some_operation'. When<br>
>>> I<br>
>>> work on serial mode, everything works fine, but in parallel mode I get<br>
>>> the error<br>
>>> "IPython.parallel.error.RemoteError: NameError(global name<br>
>>> 'do_some_operation' is not defined)"<br>
>>> I'm not surprised by this, as I imagine that each engine know only what<br>
>>> has been<br>
>>> executed or defined before and that lview.apply( func, ... ) just passes<br>
>>> the<br>
>>> "func" to the engines. A solution that I see is to run "from example<br>
>>> import<br>
>>> do_some_operation" on the engines when initialising the load_balance_view.<br>
>>> Is<br>
>>> there any easier/safer way?<br>
>><br>
>><br>
>><br>
>> This namespace issue is common, and I have explanations scattered about the<br>
>> internet:<br>
>><br>
>> <a href="http://stackoverflow.com/a/12307741/938949" target="_blank">http://stackoverflow.com/a/12307741/938949</a><br>
>> <a href="http://stackoverflow.com/a/10859394/938949" target="_blank">http://stackoverflow.com/a/10859394/938949</a><br>
>> <a href="https://github.com/ipython/ipython/issues/2489" target="_blank">https://github.com/ipython/ipython/issues/2489</a><br>
>> <a href="http://ipython.org/ipython-doc/dev/parallel/index.html" target="_blank">http://ipython.org/ipython-doc/dev/parallel/index.html</a><br>
>><br>
>> Which I really need to consolidate into a single thorough explanation with<br>
>> examples.<br>
>><br>
>> But the gist:<br>
>><br>
>> - If a function is importable (e.g. in a module available both locally and<br>
>> remotely), then it's no problem<br>
>> - If it is defined in __main__ (e.g. in a script), then any references will<br>
>> be resolved in the *engine* namespace<br>
>><br>
>> I recommend conforming to the first case if feasible, because then there<br>
>> should be no surprises.<br>
>> Everything surprising happens when you have depend on references in<br>
>> `__main__` or the current working dir (e.g. locally imported modules), since<br>
>> `__main__` is not the same on the various machines, nor is the working dir<br>
>> (necessarily).<br>
>><br>
>> That said, if the names you need to resolve are few, a simple import/push<br>
>> step with a DirectView to set up namespaces should be all you need prior to<br>
>> submitting tasks (assuming new engines are not arriving in mid-computation).<br>
>><br>
>> e.g.:<br>
>><br>
>> rc = Client()<br>
>> dv = rc[:]<br>
>> # push any locally defined functions that your task function uses:<br>
>> dv['do_some_operation'] = do_some_operation<br>
> I ended up doing the following when initialising the load_balance_view<br>
> dv.execute( 'import sys' )<br>
> dv.execute( 'sys.path.append("path_to_example.py")' )<br>
> dv.execute( 'from example import do_some_operation' )<br>
> Your suggestion looks much neater, just a couple of questions.<br>
> With the push that you suggest, do I simply call the<br>
> 'do_some_operation' as in my example or do I need some different<br>
> syntax?<br>
> Do you think that one or the other way is more optimal when the<br>
> function is called and executed?<br>
><br>
>> # perform any imports that are needed:<br>
>> dv.execute("import numpy as np...")<br>
>> # continue as before:<br>
>> lview = IPp.start_load_balanced_view( to_execute )<br>
>> ...<br>
>><br>
>><br>
>>><br>
>>><br>
>>> [2] Because of the way I parse my command line arguments, args.ifname its<br>
>>> a<br>
>>> list of already opened files. In serial mode, this is no problem, but when<br>
>>> I<br>
>>> assign the function to the scheduler passing the file, I get an error<br>
>>> saying<br>
>>> that the cannot work on a closed file. If I pass the file name with the<br>
>>> absolute path, numpy can read it without problem. Is this a behaviour to<br>
>>> be<br>
>>> expected or a bug?<br>
>><br>
>><br>
>> I would expect a PickleError when you try to send an open file. Definitely<br>
>> send filenames, not open file objects.<br>
> Just a curiosity: what is the working directory of the engines? Is the<br>
> one where the ipcluster is started or where the profile is stored?<br>
> (While fixing my code, I ended up passing the filename with the full path)<br>
<br>
It depends on configuration and how you start the engines. You can set this with your config files (look for work_dir), and you can view the current working dir with:<br>
<br>
rc[:].apply_sync(os.getcwdu)<br>
<br>
><br>
> Thanks again,<br>
><br>
> Francesco<br>
><br>
>><br>
>>><br>
>>><br>
>>> Thanks for any help,<br>
>>><br>
>>> Cheers,<br>
>>> Francesco<br>
>>> _______________________________________________<br>
>>> IPython-User mailing list<br>
>>> <a href="mailto:IPython-User@scipy.org">IPython-User@scipy.org</a><br>
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>><br>
>><br>
>><br>
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------------------------------<br>
<br>
Message: 4<br>
Date: Wed, 24 Oct 2012 19:52:01 -0600<br>
From: Jack Bryan <<a href="mailto:dtustudy68@hotmail.com">dtustudy68@hotmail.com</a>><br>
Subject: [IPython-User] error of install ipython 0.10.0<br>
To: <<a href="mailto:ipython-user@scipy.org">ipython-user@scipy.org</a>><br>
Message-ID: <BLU154-W3ED81D8D80D5A75D5A862CB7F0@phx.gbl><br>
Content-Type: text/plain; charset="iso-8859-1"<br>
<br>
<br>
Hi,<br>
I am trying to install ipython 0.10.0 on Linux Red Hat 4.4.4-17.<br>
I use instructions on:<br>
$ tar -xzf ipython.tar.gz<br>
$ cd ipython<br>
$ python setup.py installhttp://<a href="http://ipython.org/ipython-doc/stable/install/install.html" target="_blank">ipython.org/ipython-doc/stable/install/install.html</a><br>
but, I got:<br>
import pkg_resources Zope.Interface: yes Twisted: Not found (required for parallel computing capabilities) Foolscap: Not found (required for parallel computing capabilities) OpenSSL: 0.10 sphinx: Not found (required for building documentation) pygments: Not found (required for syntax highlighting documentation) nose: Not found (required for running the test suite) pexpect: no (required for running standalone doctests)running installrunning buildrunning build_pyrunning build_scriptsrunning install_librunning install_scriptschanging mode of /home/user/usr/bin/ipengine to 755changing mode of /home/user/usr/bin/ipcontroller to 755changing mode of /home/user/usr/bin/ipcluster to 755changing mode of /home/user/usr/bin/ipython to 755changing mode of /home/user/usr/bin/ipythonx to 755changing mode of /home/user<br>
/usr/bin/ipython-wx to 755changing mode of /home/user/usr/bin/pycolor to 755changing mode of /home/user/usr/bin/irunner to 755changing mode of /home/user/usr/bin/iptest to 755running install_datarunning install_egg_infoRemoving /home/user/usr/lib/python2.6/site-packages/ipython-0.10.1-py2.6.egg-infoWriting /home/user/usr/lib/python2.6/site-packages/ipython-0.10.1-py2.6.egg-info<br>
I have used easy_install to install nose, sphinx, pexpect, pygments.<br>
Why do I still have this error ?<br>
Thanks<br>
<br>
<br>
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