Re: [Tutor] constructing semi-arbitrary functions
On 18 February 2014 17:59, Peter Otten <__pete...@web.de> wrote: > > I don't know if the OP may use it, but there seems to be a version of minuit > that allows to override the function signature: > > """ > forced_parameters: tell Minuit not to do function signature detection and > use this argument instead. (Default None (automagically detect signature) > """ Interesting. I don't really understand why it works that way though. Looking here http://iminuit.github.io/iminuit/api.html#function-sig-label I find the suggestion to do instead: """ f = lambda x,m,c: m*x+c #the beauty here is that all you need to build #a Chi^2 is just your function and data class GenericChi2: def __init__(self, f, x, y): self.f = f args = describe(f)#extract function signature self.func_code = Struct( co_varnames = args[1:],#dock off independent param co_argcount = len(args)-1 ) def __call__(self, *arg): return sum((self.f(x,*arg)-y)**2 for x,y in zip(self.x, self.y)) m = Minuit(GenericChi2(f,x,y)) """ But that just seems a bit ridiculous to me. If it were my library I would probably be aiming to handle complex cases with a closure-based solution like this: def make_chisq(f, xdata, ydata): def chisq(m, c): return sum((self.f(x,m, c)-y)**2 for x,y in zip(xdata, ydata)) return chisq f = lambda x,m,c: m*x+c m = Minuit(make_chisq(xdata, ydata), names=['m', 'c']) At the least I don't understand why it needs both the argument names and the number of arguments as independent quantities. Surely len(names) would be the number of arguments... Or am I missing something? BTW to the OP the functions in scipy.optimize don't do any of this. You just pass in the function and an initial guess at the parameter values. It doesn't care about the names and infers the number of parameters from the initial guess. Also numpy has a polyfit function that you can just call with polyfit(xdata, ydata, deg) where deg is the degree of the polynomial you want to fit. Under the hood it solves the scaled Vandermonde matrix as I described earlier: https://github.com/numpy/numpy/blob/master/numpy/polynomial/polynomial.py#L1351 Oscar ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
On 02/19/2014 07:33 AM, Oscar Benjamin wrote: At the least I don't understand why it needs both the argument names and the number of arguments as independent quantities. Surely len(names) would be the number of arguments... Or am I missing something? In the standard library, the attributes are func_code.co_varnames and func_code.co_argcount Note that varnames will include all the locals, not just the formal parameters. So the count tells you how many of them are parameters. -- DaveA ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
On Wed, Feb 19, 2014 at 7:33 AM, Oscar Benjamin
wrote:
> I don't really understand why it works that way though.
> Looking here
>
>http://iminuit.github.io/iminuit/api.html#function-sig-label
This API is unusual, but co_argcount and co_varnames should be
available and defined as per the spec:
http://docs.python.org/2/reference/datamodel#index-59
CPython/PyPy Jython
=
co_name *
co_argcount *
co_nlocals*
co_varnames *
co_cellvars *
co_freevars *
co_filename *
co_firstlineno*
co_flags *
co_code
co_consts
co_names
co_lnotab
co_stacksize
The last few attributes aren't relevant to Jython since it's using the JVM.
To its credit, util.better_arg_spec does fall back on
inspect.getargspec. But then, its ultimate fallback is regex magic:
util.arguments_from_docstring. Wow. I guess it's convenient to specify
initial values, step size, limits, etc, as keyword arguments for named
parameters.
I haven't read this whole thread, but here are some source links if
the OP is using this iminuit package. The `describe` function is in
util.py.
https://github.com/iminuit/iminuit/blob/master/iminuit/util.py
https://github.com/iminuit/iminuit/blob/master/iminuit/_libiminuit.pyx
Some snippets from Minuit.__init__:
args = describe(fcn) if forced_parameters is None\
else forced_parameters
# ...
self.initialvalue = {x:maplookup(kwds,x,0.) for x in args}
self.initialerror = \
{x:maplookup(kwds,'error_'+x,1.) for x in args}
self.initiallimit = \
{x:maplookup(kwds,'limit_'+x,None) for x in args}
self.initialfix = \
{x:maplookup(kwds,'fix_'+x,False) for x in args}
# ...
self.parameters = args
self.args = tuple(self.initialvalue[k] for k in args)
self.values = {k:self.initialvalue[k] for k in args}
self.errors = {k:self.initialerror[k] for k in args}
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[Tutor] How to write Sikuli scripts using Python in Eclipse (Pydev Environment.)
Hi, Could you please tell me how to write Sikuli scripts using Python in Eclipse (Pydev Environment.) For Example: I want to open Adobe Reader using Sikuli and wants to perform different action on it. I had already integrated Python in Eclipse and also provide path for Jython Interpreter. Please provide me steps to import Sikuli Api's or other extra things needed to do my assignment. Thanks a lot in advance. Nupur___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] How to write Sikuli scripts using Python in Eclipse (Pydev Environment.)
On 19/02/14 13:22, Nupur Goel wrote: Could you please tell me how to write *Sikuli* scripts using *Python in Eclipse (Pydev Environment.)* This list is for teaching the core Python language and its standard library. For support for third party libraries and tools you are usually better off asking on a dedicated forum or list. I want to open Adobe Reader using Sikuli and wants to perform different action on it. I had already integrated Python in Eclipse and also provide path for Jython Interpreter. Sikuli, Eclipse and Jython are all off topic for this list. You might be lucky enough to find somebody with some experience but I suspect you will be better off asking elsewhere, possibly even on the main python mailing list/newsgroup. -- Alan G Author of the Learn to Program web site http://www.alan-g.me.uk/ http://www.flickr.com/photos/alangauldphotos ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
Hi Oscar,
>> Is there a benefit to this method vs a standard linear least squares?
>
> It's the same except that you're using an analytic solution rather
> than a black box solver.
OK. Interesting. I usually construct the analytic solution by just
differentiating the chi^2, which sets up, I am guessing, a similar matrix
equation. When I solve with chi^2, I see clearly how to put the uncertainties
in, and use them for estimating the uncertainties on the coefficients. The
parameter uncertainties are simply related to the double-derrivatives of the
chi^2 for linear least squares. But it is not clear to me if knowing the
Vandermonde matrix automatically gives these parameter uncertainties as well.
>> The most common problem I am solving is fitting a sum of real exponentials
>> to noisy data, with the model function
>>
>> C(t) = sum_n A_n e^{- E_n t}
>>
>> the quantities of most interest are E_n, followed by A_n so I solve this
>> with non-linear regression.
>> To stabilize the fit, I usually do a linear-least squares for the A_n first,
>> solving as a function of the E_n, and then do a non-linear fit for the E_n.
>
> That doesn't sound optimal to me. Maybe I've misunderstood but fitting
> over one variable and then over another is not in any way guaranteed
> to produce an optimal fit.
I have not been precise enough.
The first solve for A_n is using an analytic linear-least squares algorithm, so
it is gauranteed to be correct. The solution will depend upon the E_n, but in
a known way.
The point is that the numerical minimization of sums of exponentials is a hard
problem. So why ask the numerical minimizer to do all the extra work of also
minimizing the coefficients? This can make it very unstable. So by first
applying the analytic linear-least squares to the coefficients, the numerical
minimization over the smaller set of E_n is more likely to converge. Usually,
in my cases, we have of order 2-10 times more A_n than E_n, as we really solve
a matrix
C_{ij}(t) = sum_n A^n_{ij} exp(-E_n t)
the linear least squares gives
A^n_{ij} = analytically solvable matrix function (E_n)
> Well it sounds like your approach so far is working for now but as I
> say the real fix is to improve or bypass the interface you're using.
> One limitation that you may at some point hit is that in Python you
> can't have an unbounded number of formal parameters for a function:
>
> $ python3 tmp2.py
> File "tmp2.py", line 1
>def f(x0, x1, x2, x3, x4, x5, x6, x7, x8, x9, x10, x11,
> x12, x13, x14,
> ^
> SyntaxError: more than 255 arguments
In my work, it is unlikely I will ever need to minimize in so many parameters.
I’ll worry about that when I run into it.
Thanks for the info.
Andre
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Re: [Tutor] constructing semi-arbitrary functions
Hi eryksun,
Indeed, I am using iminuit to interface with Minuit.
That is where I am learning to make my own classes to set up my functions to
pass into the minimizer. I also happened to get the string-hack to work (which
requires using global variables). Instead of just copying (since it works) I am
also trying to improve my programming knowledge at the same time - hence this
whole thread.
Minuit is a sophisticated minimizer, which means it is important to set initial
values, expected uncertainties on the parameters, etc. Minuit uses your
estimate of the parameter uncertainties to set up the grid step-size it uses to
search the parameter space. So sloppiness here can screw up the minimization
getting one stuck in a local min (to small error estimate) or spend too much
time wondering around (too large error estimate).
Cheers,
Andre
On Feb 19, 2014, at 10:17 AM, eryksun wrote:
> On Wed, Feb 19, 2014 at 7:33 AM, Oscar Benjamin
> wrote:
>> I don't really understand why it works that way though.
>> Looking here
>>
>> http://iminuit.github.io/iminuit/api.html#function-sig-label
>
> This API is unusual, but co_argcount and co_varnames should be
> available and defined as per the spec:
>
> http://docs.python.org/2/reference/datamodel#index-59
>
>CPython/PyPy Jython
>=
>co_name *
>co_argcount *
>co_nlocals*
>co_varnames *
>co_cellvars *
>co_freevars *
>co_filename *
>co_firstlineno*
>co_flags *
>co_code
>co_consts
>co_names
>co_lnotab
>co_stacksize
>
> The last few attributes aren't relevant to Jython since it's using the JVM.
>
> To its credit, util.better_arg_spec does fall back on
> inspect.getargspec. But then, its ultimate fallback is regex magic:
> util.arguments_from_docstring. Wow. I guess it's convenient to specify
> initial values, step size, limits, etc, as keyword arguments for named
> parameters.
>
> I haven't read this whole thread, but here are some source links if
> the OP is using this iminuit package. The `describe` function is in
> util.py.
>
> https://github.com/iminuit/iminuit/blob/master/iminuit/util.py
> https://github.com/iminuit/iminuit/blob/master/iminuit/_libiminuit.pyx
>
> Some snippets from Minuit.__init__:
>
>args = describe(fcn) if forced_parameters is None\
> else forced_parameters
>
># ...
>
>self.initialvalue = {x:maplookup(kwds,x,0.) for x in args}
>self.initialerror = \
>{x:maplookup(kwds,'error_'+x,1.) for x in args}
>self.initiallimit = \
>{x:maplookup(kwds,'limit_'+x,None) for x in args}
>self.initialfix = \
>{x:maplookup(kwds,'fix_'+x,False) for x in args}
>
># ...
>
>self.parameters = args
>self.args = tuple(self.initialvalue[k] for k in args)
>self.values = {k:self.initialvalue[k] for k in args}
>self.errors = {k:self.initialerror[k] for k in args}
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Re: [Tutor] constructing semi-arbitrary functions
On Wed, Feb 19, 2014 at 2:56 PM, "André Walker-Loud
" wrote:
>
> I also happened to get the string-hack to work (which requires
> using global variables).
Functions load unassigned names from the global/builtins scopes, so
there's no need to declare the g* variables global in chisq_mn. Also,
implicit string concatenation and string formatting will make the
definition easier to read, IMO:
def make_chisq_mn(pars, x, y, dy):
global _gx, _gy, _gdy
_gx, _gy, _gdy = x, y, dy
names = ['c_%d' % i for i in xrange(len(pars))]
src = ('def chisq_mn(%(p)s):\n'
'return chisq([%(p)s], _gx, _gy, _gdy)' %
{'p': ', '.join(names)})
print 'funcdef=\n', src
exec src in globals()
You can use a custom dict with exec to avoid contaminating the
module's global namespace:
def make_chisq_mn(pars, x, y, dy):
ns = {'x': x, 'y': y, 'dy': dy, 'chisq': chisq}
names = ['c_%d' % i for i in xrange(len(pars))]
src = ('def chisq_mn(%(p)s):\n'
'return chisq([%(p)s], x, y, dy)' %
{'p': ', '.join(names)})
print 'funcdef=\n', src
exec src in ns
return ns['chisq_mn']
This version of chisq_mn uses the ns dict as its func_globals:
>>> chisq = lambda *a: None # dummy
>>> chisq_mn = make_chisq_mn([1,2,3], 10, 20, 30)
funcdef=
def chisq_mn(c_0, c_1, c_2):
return chisq([c_0, c_1, c_2], x, y, dy)
>>> sorted(chisq_mn.func_globals)
['__builtins__', 'chisq', 'chisq_mn', 'dy', 'x', 'y']
>>> dis.dis(chisq_mn)
2 0 LOAD_GLOBAL 0 (chisq)
3 LOAD_FAST0 (c_0)
6 LOAD_FAST1 (c_1)
9 LOAD_FAST2 (c_2)
12 BUILD_LIST 3
15 LOAD_GLOBAL 1 (x)
18 LOAD_GLOBAL 2 (y)
21 LOAD_GLOBAL 3 (dy)
24 CALL_FUNCTION4
27 RETURN_VALUE
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Re: [Tutor] constructing semi-arbitrary functions
Hi eryksun,
Thanks - this is great.
Also, since you are chiming in, do you have an opinion in general about which
approach you prefer? The string hacking vs class method (for lack of better
way to describe them)?
Cheers,
Andre
On Feb 19, 2014, at 4:56 PM, eryksun wrote:
> On Wed, Feb 19, 2014 at 2:56 PM, "André Walker-Loud
> " wrote:
>>
>> I also happened to get the string-hack to work (which requires
>> using global variables).
>
> Functions load unassigned names from the global/builtins scopes, so
> there's no need to declare the g* variables global in chisq_mn. Also,
> implicit string concatenation and string formatting will make the
> definition easier to read, IMO:
>
>def make_chisq_mn(pars, x, y, dy):
>global _gx, _gy, _gdy
>_gx, _gy, _gdy = x, y, dy
>names = ['c_%d' % i for i in xrange(len(pars))]
>src = ('def chisq_mn(%(p)s):\n'
> 'return chisq([%(p)s], _gx, _gy, _gdy)' %
> {'p': ', '.join(names)})
>print 'funcdef=\n', src
>exec src in globals()
>
>
> You can use a custom dict with exec to avoid contaminating the
> module's global namespace:
>
>def make_chisq_mn(pars, x, y, dy):
>ns = {'x': x, 'y': y, 'dy': dy, 'chisq': chisq}
>names = ['c_%d' % i for i in xrange(len(pars))]
>src = ('def chisq_mn(%(p)s):\n'
> 'return chisq([%(p)s], x, y, dy)' %
> {'p': ', '.join(names)})
>print 'funcdef=\n', src
>exec src in ns
>return ns['chisq_mn']
>
>
> This version of chisq_mn uses the ns dict as its func_globals:
>
chisq = lambda *a: None # dummy
chisq_mn = make_chisq_mn([1,2,3], 10, 20, 30)
>funcdef=
>def chisq_mn(c_0, c_1, c_2):
>return chisq([c_0, c_1, c_2], x, y, dy)
>
sorted(chisq_mn.func_globals)
>['__builtins__', 'chisq', 'chisq_mn', 'dy', 'x', 'y']
>
dis.dis(chisq_mn)
> 2 0 LOAD_GLOBAL 0 (chisq)
> 3 LOAD_FAST0 (c_0)
> 6 LOAD_FAST1 (c_1)
> 9 LOAD_FAST2 (c_2)
> 12 BUILD_LIST 3
> 15 LOAD_GLOBAL 1 (x)
> 18 LOAD_GLOBAL 2 (y)
> 21 LOAD_GLOBAL 3 (dy)
> 24 CALL_FUNCTION4
> 27 RETURN_VALUE
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Re: [Tutor] How to write Sikuli scripts using Python in Eclipse (Pydev Environment.)
On 19/02/14 17:34, Alan Gauld wrote: Sikuli, Eclipse and Jython are all off topic for this list. Correcting myself. Jython is not off topic if it's about how to program with Jython. It's the details of using Jython in the context of Eclipse etc that is off topic for tutor. I don't want to scare away any Jython lurkers out there. :-) -- Alan G Author of the Learn to Program web site http://www.alan-g.me.uk/ http://www.flickr.com/photos/alangauldphotos ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
[Tutor] Looking for IAC solutions in Python
Hi, I am looking for IAC - Intelligent Adaptive Curiosity solutions in Python. Have you got any idea of project / algorithm / source code based on that type of things ? Best regards -- Aurélien DESBRIÈRES Run Free - Run GNU.org ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] Looking for IAC solutions in Python
On 19/02/2014 19:53, Aurélien DESBRIÈRES wrote: Hi, I am looking for IAC - Intelligent Adaptive Curiosity solutions in Python. Have you got any idea of project / algorithm / source code based on that type of things ? Best regards Haven't a clue to be quite blunt, I suggest that you try the main Python mailing list/newsgroup rather than this tutor list. -- My fellow Pythonistas, ask not what our language can do for you, ask what you can do for our language. Mark Lawrence --- This email is free from viruses and malware because avast! Antivirus protection is active. http://www.avast.com ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
On Wed, Feb 19, 2014 at 6:59 PM, "André Walker-Loud " wrote: > > Also, since you are chiming in, do you have an opinion in general about > which approach you prefer? The string hacking vs class method (for lack > of better way to describe them)? I've never used iminuit before. I'd ask on a support forum to see what other people are doing. That said, if possible I'd use a closure like Peter showed: def make_chisq_mn(x, y, dy): def chisq_mn(*args): return chisq(args, x, y, dy) return chisq_mn Then combine that with the forced_parameters option that Peter mentioned. This seems simplest to me. ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
OK - I have not seen an email from Peter. So I looked up the thread online, and see I did not receive half the emails on this thread :O My first inclination was to blame my mac mavericks mail gmail syncing problem. but logging into gmail, I see no record of the emails there either. I currently receive the tutor emails in the digest mode - thought I was paying attention to all the digests - but I seems to have missed many. I apologize to all those who offered input whose emails I missed - I certainly wasn’t ignoring them. Andre On Feb 19, 2014, at 7:21 PM, eryksun wrote: > On Wed, Feb 19, 2014 at 6:59 PM, "André Walker-Loud > " wrote: >> >> Also, since you are chiming in, do you have an opinion in general about >> which approach you prefer? The string hacking vs class method (for lack >> of better way to describe them)? > > I've never used iminuit before. I'd ask on a support forum to see what > other people are doing. That said, if possible I'd use a closure like > Peter showed: > >def make_chisq_mn(x, y, dy): >def chisq_mn(*args): >return chisq(args, x, y, dy) >return chisq_mn > > Then combine that with the forced_parameters option that Peter > mentioned. This seems simplest to me. ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
On Feb 19, 2014, at 7:45 PM, André Walker-Loud wrote: > OK - I have not seen an email from Peter. > So I looked up the thread online, and see I did not receive half the emails > on this thread :O > > My first inclination was to blame my mac mavericks mail gmail syncing > problem. but logging into gmail, I see no record of the emails there either. > > I currently receive the tutor emails in the digest mode - thought I was > paying attention to all the digests - but I seems to have missed many. > > I apologize to all those who offered input whose emails I missed - I > certainly wasn’t ignoring them. and as a follow up - is there a way to download a thread from the tutor archive? I am guessing the answers are one of 1) write a python script to grab the emails associated with the threads from the web 2) download the whole gzip’d text and use python to grab only the parts I want but 1) I haven’t done that before and unfortunately don’t have time to learn now 2) some combination of being too busy and lazy prevents me from this option… cheers, andre ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
On 20/02/2014 00:56, "André Walker-Loud " wrote: On Feb 19, 2014, at 7:45 PM, André Walker-Loud wrote: OK - I have not seen an email from Peter. So I looked up the thread online, and see I did not receive half the emails on this thread :O My first inclination was to blame my mac mavericks mail gmail syncing problem. but logging into gmail, I see no record of the emails there either. I currently receive the tutor emails in the digest mode - thought I was paying attention to all the digests - but I seems to have missed many. I apologize to all those who offered input whose emails I missed - I certainly wasn’t ignoring them. and as a follow up - is there a way to download a thread from the tutor archive? I am guessing the answers are one of 1) write a python script to grab the emails associated with the threads from the web 2) download the whole gzip’d text and use python to grab only the parts I want but 1) I haven’t done that before and unfortunately don’t have time to learn now 2) some combination of being too busy and lazy prevents me from this option… cheers, andre See here for where this list is archived https://mail.python.org/mailman/listinfo/tutor, looks as if your choices are activestate or gmane, I'm unsure as to whether or not you can grab gzip'd text. -- My fellow Pythonistas, ask not what our language can do for you, ask what you can do for our language. Mark Lawrence --- This email is free from viruses and malware because avast! Antivirus protection is active. http://www.avast.com ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] constructing semi-arbitrary functions
On 20 February 2014 00:56, "André Walker-Loud " wrote: > On Feb 19, 2014, at 7:45 PM, André Walker-Loud wrote: > >> OK - I have not seen an email from Peter. >> So I looked up the thread online, and see I did not receive half the emails >> on this thread :O >> >> My first inclination was to blame my mac mavericks mail gmail syncing >> problem. but logging into gmail, I see no record of the emails there either. >> >> I currently receive the tutor emails in the digest mode - thought I was >> paying attention to all the digests - but I seems to have missed many. >> >> I apologize to all those who offered input whose emails I missed - I >> certainly wasn't ignoring them. > > and as a follow up - is there a way to download a thread from the tutor > archive? > I am guessing the answers are one of > 1) write a python script to grab the emails associated with the threads from > the web > 2) download the whole gzip'd text and use python to grab only the parts I want > > but 1) I haven't done that before and unfortunately don't have time to learn > now > 2) some combination of being too busy and lazy prevents me from this option... I'm sure there is a way to do it (I don't know how exactly) but for now you have the archive here: https://mail.python.org/pipermail/tutor/2014-February/100213.html I would suggest not to receive the digest. Peter's messages were sent to the list and not CC'ed to you (which is often considered the correct way) so you would only have seen them in the digest but it's not so easy to follow a thread that way. I also use gmail and what I do is to set a filter that sends all the tutor emails into a particular folder (skip inbox, don't mark as read) and then there's no problem with the emails cluttering up my inbox and no need to receive a digest. When I feel like looking at tutor emails they're in a particular folder for me to look at. When I feel like processing work-related emails etc. then they're in different folders. When I do look at the messages they are threaded by gmail so I don't miss anything in a particular thread. Oscar ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
[Tutor] Programmatic access to email archives (was: constructing semi-arbitrary functions)
"André Walker-Loud " writes: > and as a follow up - is there a way to download a thread from the > tutor archive? You've indicated you know this, but for other readers: The mailing list archives are available https://mail.python.org/pipermail/tutor/> in compressed “mbox” format, by month. > 2) download the whole gzip’d text and use python to grab only the > parts I want A decent email client (such as Mutt, Gnus, Thunderbird, etc.) will be able to open an mbox-format archive as a folder, and from there you can filter and reply to messages as normal. For programmatic access, the Python standard library ‘mailbox’ module http://docs.python.org/3/library/mailbox.html> supports reading “mbox”, and you then have all the Mailbox methods to select and extract messages. -- \“Human reason is snatching everything to itself, leaving | `\ nothing for faith.” —Saint Bernard, 1090–1153 | _o__) | Ben Finney ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
