🌐 Mailman 3 July 2010 - Python-list - python.org

Re: default behavior
by Steven D'Aprano Aug. 7, 2010

Aug. 7, 2010

On Fri, 30 Jul 2010 08:34:52 -0400, wheres pythonmonks wrote: > Sorry, doesn't the following make a copy? > >>>>> from collections import defaultdict as dd x = dd(int) >>>>> x[1] = 'a' >>>>> x >> defaultdict(<type 'int'>, {1: 'a'}) >>>>> dict(x) >> {1: 'a'} >> >> >> > > I was hoping not to do that -- e.g., actually reuse the same underlying > data. It does re-use the same underlying data. >>> from collections import defaultdict as dd >>> x = dd(list) >>> x[1].append(1) >>> x defaultdict(<type 'list'>, {1: [1]}) >>> y = dict(x) >>> x[1].append(42) >>> y {1: [1, 42]} Both the defaultdict and the dict are referring to the same underlying key:value pairs. The data itself isn't duplicated. If they are mutable items, a change to one will affect the other (because they are the same item). An analogy for C programmers would be that creating dict y from dict y merely copies the pointers to the keys and values, it doesn't copy the data being pointed to. (That's pretty much what the CPython implementation does. Other implementations may do differently, so long as the visible behaviour remains the same.) > Maybe dict(x), where x is a defaultdict is smart? I agree that a > defaultdict is safe to pass to most routines, but I guess I could > imagine that a try/except block is used in a bit of code where on the > key exception (when the value is absent) populates the value with a > random number. In that application, a defaultdict would have no random > values. If you want a defaultdict with a random default value, it is easy to provide: >>> import random >>> z = dd(random.random) >>> z[2] += 0 >>> z defaultdict(<built-in method random of Random object at 0xa01e4ac>, {2: 0.30707092626033605}) The point which I tried to make, but obviously failed, is that any piece of code has certain expectations about the data it accepts. If take a function that expects an int between -2 and 99, and instead decide to pass a Decimal between 100 and 150, then you'll have problems: if you're lucky, you'll get an exception, if you're unlucky, it will silently give the wrong results. Changing a dict to a defaultdict is no different. If you have code that *relies* on getting a KeyError for missing keys: def who_is_missing(adict): for person in ("Fred", "Barney", "Wilma", "Betty"): try: adict[person] except KeyError: print person, "is missing" then changing adict to a defaultdict will cause the function to misbehave. That's not unique to dicts and defaultdicts. > Besides a slightly different favor, does the following have applications > not covered by defaultdict? > > m.setdefault('key', []).append(1) defaultdict calls a function of no arguments to provide a default value. That means, in practice, it almost always uses the same default value for any specific dict. setdefault takes an argument when you call the function. So you can provide anything you like at runtime. > I think I am unclear on the difference between that and: > > m['key'] = m.get('key',[]).append(1) Have you tried it? I guess you haven't, or you wouldn't have thought they did the same thing. Hint -- what does [].append(1) return? -- Steven

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Re: Easy questions from a python beginner
by Steven D'Aprano Aug. 6, 2010

Aug. 6, 2010

On Thu, 22 Jul 2010 21:23:05 -0700, Stephen Hansen wrote: > On 7/22/10 7:47 PM, wheres pythonmonks wrote: [...] >> The truth is that I don't intend to use these approaches in anything >> serious. However, I've been known to do some metaprogramming from time >> to time. > > Depending on how you define "metaprogramming", Python is pretty > notoriously ill-suited towards the task (more, its basically considered > a feature it doesn't let you go there) -- or, it allows you to do vast > amounts of stuff with its few dark magic hooks. I've never had a > satisfying definition of metaprogramming that more then 50% of any group > agree with, so I'm not sure which you're looking for. :) I disagree strongly at your characterisation that Python is notorious for being ill-suited towards metaprogramming. I'd say the complete opposite -- what is considered dark and scary metaprogramming tasks in other languages is considered too ordinary to even mention in Python. If you have a class that defines a single member (or attribute in Python terminology) "spam", and you want to add a second "ham" to a specific instance, such a thing is either deep, dark metaprogramming in some languages, if not outright impossible. In Python it is not even noteworthy: instance.ham = "something" # *yawns* Recently there was a thread started by some Java or C++ refugee who was distressed about attribute access in Python, because it made metaprogramming frighteningly easy: http://mail.python.org/pipermail/python-list/2010-June/1248029.html My response at the time was: Python makes metaprogramming *easy*: http://mail.python.org/pipermail/python-list/2010-June/1248053.html I can't imagine how he would have reacted if we had showed him how easy it is to monkey-patch built-in functions... [...] > But! What it doesn't let you do is get clever with syntax and write a > sort of "simplified" or domain specific language to achieve certain > sorts of repetitive tasks quickly. You always end up writing normal > Python that looks like all other Python. Exactly... 90% of the time that you think you want a DSL, Python beat you to it. It is true that other languages (like Lisp, or Forth) allow you to write your own syntax. That's incredibly powerful, but it also has serious costs. If you can define your own syntax, that means every piece of code you look at is potentially a different language. -- Steven

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Checking that 2 pdf are identical (md5 a solution?)
by rlevesque Aug. 6, 2010

Aug. 6, 2010

Hi I am working on a program that generates various pdf files in the / results folder. "scenario1.pdf" results from scenario1 "scenario2.pdf" results from scenario2 etc Once I am happy with scenario1.pdf and scenario2.pdf files, I would like to save them in the /check folder. Now after having developed/modified the program to produce scenario3.pdf, I would like to be able to re-generate files /results/scenario1.pdf /results/scenario2.pdf and compare them with /check/scenario1.pdf /check/scenario2.pdf I tried using the md5 module to compare these files but md5 reports differences even though the code has *not* changed at all. Is there a way to compare 2 pdf files generated at different time but identical in every other respect and validate by program that the files are identical (for all practical purposes)?

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A portable LISP interpreter that includes all the major list-processing functions is described. A complete, annotated listing of the program's code, written in PASCAL, is included.
by Emmy Noether Aug. 5, 2010

Aug. 5, 2010

Title Portable LISP interpreter Creator/Author Cox, L.A. Jr. ; Taylor, W.P. Publication Date 1978 May 31 OSTI Identifier OSTI ID: 7017786 Report Number(s) UCRL-52417 DOE Contract Number W-7405-ENG-48 Resource Type Technical Report Research Org California Univ., Livermore (USA). Lawrence Livermore Lab. Subject 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; COMPUTER CODES; L CODES; COMPUTERS; PROGRAMMING; PROGRAMMING LANGUAGES Description/Abstract A portable LISP interpreter that includes all the major list-processing functions is described. A complete, annotated listing of the program's code, written in PASCAL, is included. Country of Publication United States Language English Format Medium: X; Size: Pages: 21 Availability Dep. NTIS, PC A02/MF A01. System Entry Date 2008 Feb 12

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Fascinating interview by Richard Stallman on Russia TV
by bolega Aug. 5, 2010

Aug. 5, 2010

"Democracy is sick in the US, government monitors your Internet" http://www.youtube.com/watch?v=2BfCJq_zIdk&feature=fvsr Enjoy .....

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Nice way to cast a homogeneous tuple
by wheres pythonmonks Aug. 5, 2010

Aug. 5, 2010

A new python convert is now looking for a replacement for another perl idiom. In particular, since Perl is weakly typed, I used to be able to use unpack to unpack sequences from a string, that I could then use immediately as integers. In python, I find that when I use struct.unpack I tend to get strings. (Maybe I am using it wrong?) def f(x,y,z): print x+y+z; f( *struct.unpack('2s2s2s','123456')) 123456 (the plus concatenates the strings returned by unpack) But what I want is: f( *map(lambda x: int(x), struct.unpack('2s2s2s','123456'))) 102 But this seems too complicated. I see two resolutions: 1. There is a way using unpack to get out string-formatted ints? 2. There is something like map(lambda x: int(x).... without all the lambda function call overhead. (e.g., cast tuple)? [And yes: I know I can write my own "cast_tuple" function -- that's not my point. My point is that I want a super-native python inline solution like (hopefully shorter than) my "map" version above. I don't like defining trivial functions.] W

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Re: Nice way to cast a homogeneous tuple
by Ulrich Eckhardt Aug. 5, 2010

Aug. 5, 2010

wheres pythonmonks wrote: > Thanks ... I thought int was a type-cast (like in C++) so I assumed I > couldn't reference it. Hopefully somebody correct me if I explain this badly, but I'll take a shot... Firstly, "int" is a class. Python doesn't make a distinction between builtin types and class types like C++, where you e.g. can't derive from builtin types. Secondly, the class is callable like a function. When called, it creates an instance of that class. Therefore, when you create an object it has a similar syntax as when calling a function. Lastly, classes are not special. Like any variable or function they can be referenced by a name or by multiple names, and thus be passed as parameters to a function. Cheers! Uli -- Sator Laser GmbH Geschäftsführer: Thorsten Föcking, Amtsgericht Hamburg HR B62 932

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Re: Unicode error
by Nobody Aug. 4, 2010

Aug. 4, 2010

On Fri, 23 Jul 2010 18:27:50 -0400, Terry Reedy wrote: > But in the > meanwhile, once you get an error, you know what it is. You can > intentionally feed code bad data and see what you get. And then maybe > add a test to make sure your code traps such errors. That doesn't really help with exceptions which are triggered by external factors rather than explicit inputs. Also, if you're writing libraries (rather than self-contained programs), you have no control over the arguments. Coupled with the fact that duck typing is quite widely advocated in Python circles, you're stuck with the possibility that any method call on any argument can raise any exception. This is even true for calls to standard library functions or methods of standard classes if you're passing caller-supplied objects as arguments.

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Urrlib2 IncompleteRead error
by dirknbr Aug. 4, 2010

Aug. 4, 2010

I am running urllib2.request and get this response when I do the read. Any ideas what causes this? return response.read() File "C:\Python26\lib\socket.py", line 329, in read data = self._sock.recv(rbufsize) File "C:\Python26\lib\httplib.py", line 518, in read return self._read_chunked(amt) File "C:\Python26\lib\httplib.py", line 561, in _read_chunked raise IncompleteRead(''.join(value)) IncompleteRead: IncompleteRead(3235 bytes read) Dirk

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Re: The untimely dimise of a weak-reference
by Gregory Ewing Aug. 3, 2010

Aug. 3, 2010

Vincent van Beveren wrote: > I was working with weak references in Python, and noticed that it > was impossible to create a weak-reference of bound methods. > is there anything I can do about it? You can create your own wrapper that keeps a weak reference to the underlying object. Here's an example. import weakref class weakmethod(object): def __init__(self, bm): self.ref = weakref.ref(bm.im_self) self.func = bm.im_func def __call__(self, *args, **kwds): obj = self.ref() if obj is None: raise ValueError("Calling dead weak method") self.func(obj, *args, **kwds) if __name__ == "__main__": class A(object): def foo(self): print "foo method called on", self a = A() m = weakmethod(a.foo) m() del a m()

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