[Tutor] Python tutoring
Hello, my name is Marcus Douglas and I'm a student at College of Central Florida, I'm contacting you because this is my first year programming and I'm seriously seeking some HELP...ASAP...ThanksMarcus Douglas ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
[Tutor] When is = a copy and when is it an alias
Running python 2.7 in linux Below are two extremes. Can I get some guidance on this? Thanks, -Denis H >>> a=zeros((2,3),dtype=int) >>> b=a >>> a[:,0]=[1,2] >>> a array([[1, 0, 0], [2, 0, 0]]) >>> b array([[1, 0, 0], [2, 0, 0]]) >>> a=2 >>> a 2 >>> b array([[1, 0, 0], [2, 0, 0]]) ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] Python tutoring
On Sun, Jan 26, 2014 at 10:44:56PM -0500, marcus douglas wrote: > Hello, my name is Marcus Douglas and I'm a student at College of > Central Florida, I'm contacting you because this is my first year > programming and I'm seriously seeking some HELP...ASAP... Hello Marcus, and welcome! We hope that we can help you, but only if you ask us questions! What are you having trouble with? Please don't say "everything" :-) Remember, we're not here to do your work for you, and your College almost certainly has rules about plagiarism and collaboration, so please try to ask generic questions about the language rather than specific questions about homework questions. If you must ask homework questions, expect that we'll only give you round-about answers that hint at a solution. Good questions: "What's a variable?" "Can you explain exceptions? I don't understand them." "I have a for-loop, and I want to exit it early. What should I do?" "How do I look for an item in a list? I tried "find(my_list, item) but it printed NameError." "What's the best way to read a file with items separated by tabs?" "Here is my code. I tried running it, expecting this result, but got this different result instead. What did I do wrong?" Bad questions: "Help!?" "Here's a project I have to do for my course. Solve it for me. Urgently. Because I forgot to do my project for the last three weeks and it's due tomorrow." "Here's some code. It doesn't work. Fix it for me." Good luck, and happy programming! -- Steven ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When is = a copy and when is it an alias
Hi Denis, and welcome! On Sun, Jan 26, 2014 at 10:16:25PM -0800, Denis Heidtmann wrote: > Running python 2.7 in linux > > Below are two extremes. Can I get some guidance on this? In Python, = is ALWAYS an alias, never a copy, unless you explicitly do something to make a copy. For example, with dicts, there is a `copy` method: newdict = olddict.copy() But it's not always *obvious* that you're just aliasing the same object. For example, this is obvious: py> a = [] py> b = a # b is now a new name for a py> a.append(42) # modifies the list in place py> b [42] but this is not: py> a = 23 py> b = a # b is now a new name for a py> a = a + 1 py> b 23 In this second case, b is unchanged because `a = a + 1` doesn't *modify* a, it makes a new value (23 + 1 => 24) and assigns that new value to a, leaving b unchanged. In your example below, I take it you are using numpy. You should say so, in case it is unclear. > >>> a=zeros((2,3),dtype=int) > >>> b=a > >>> a[:,0]=[1,2] > >>> a > array([[1, 0, 0], >[2, 0, 0]]) > >>> b > array([[1, 0, 0], >[2, 0, 0]]) In this example, you bind the name "a" to an array of zeroes, then bind the name "b" to the same array. "Name binding" is another term for assignment in Python. So a and b are two names for the same array. When you modify the array via the name "a", b sees the same changes because they are the same array. Even though the line a[:,0] = [1, 2] looks like an assignment, it's not actually a name binding, because you're only assigning to a slice of the array, not the name. That makes it an in-place modification, just like appending to a list. But this code that follows: > >>> a=2 > >>> a > 2 > >>> b > array([[1, 0, 0], >[2, 0, 0]]) is different. Here, the line `a = 2` is an actual name binding. It makes the name `a` refer to the value 2, instead of the array it used to refer to. But that doesn't change the array in any way, nor does it change `b`, so b is unaffected. Hope this helps, -- Steven ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When is = a copy and when is it an alias
On 01/27/2014 07:16 AM, Denis Heidtmann wrote: Running python 2.7 in linux Below are two extremes. Can I get some guidance on this? Thanks, -Denis H a=zeros((2,3),dtype=int) b=a a[:,0]=[1,2] a array([[1, 0, 0], [2, 0, 0]]) b array([[1, 0, 0], [2, 0, 0]]) a=2 a 2 b array([[1, 0, 0], [2, 0, 0]]) Note: your example is strongly obscured by using weird and rare features that don't bring any helpful point to the actual problematic concepts you apparently want to deal with. It seems you are confusing 2 issues: relation (reference) between values (objects) and relations between symbols (variables). The last part of your example implies that you expect that, maybe, symbol 'b' may now magically point to 2 just because it were corelated with 'a', which was set to point to 2. Correct? If so, you are wrong: there is no relation between symbols in python (nore in any other language I know, for the matter). Symbols 'a' and 'b' are independant, whatever the possible relations between their values. If you *replace* a's value, this has no effect on b, even if they previously held the very same, unique, value. Python 3.3.2+ (default, Oct 9 2013, 14:50:09) [GCC 4.8.1] on linux Type "help", "copyright", "credits" or "license" for more information. a = [1,2,3] b = a a is b True a = (1,2) # replacement b [1, 2, 3] Now, there are 2 ways to change a symbol's value: to *replace* it globally as above, or to *modify* it partly a = [1,2,3] b = a a is b True a[1] = 0# modification a [1, 0, 3] b [1, 0, 3] a is b True A misleading point is exemplified by "a is b": it does not mean that both symbols actually are the same one (unique), but that _their value objects_ are the same one (unique). This is the role of symbols: once defined, they are used for whatever they represent. Here symbols a & b just play their normal role of symbols, right? The above example of modification is only possible if the value is complex (and mutable). Simple values like numbers or strings obviously cannot be modified, only replaced. Thus, such simple values just behave like "plain old values" in static or historical languages (in which there aren't symbols & values are runtime, instead plain adresses & raw data). In such languages there is systematic copy on assignment, unless one explicitely uses pointers. Maybe you are used to that, and expect such behaviour in python. Quite the opposite, in python "symbolic assignment" (where the right side also is a symbol) never copies, in fact never creates a new value, but bind the left symbol to the same, unique value, as the right symbol. Note: such are the semantics (the meaning) of the language. But since as said above this does not make any difference in practice for simple values, the language implementation is in fact free to copy under the hood, if this is simpler or more efficient to do so: the language's semantics are preserved nevertheless. However, python's standard implementation does not appear to do so: a = -12.345 b = a a is b True# a & b are bound to the same value, there's only one -12.345 d ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When is = a copy and when is it an alias
Denis Heidtmann wrote: > Running python 2.7 in linux > > Below are two extremes. Can I get some guidance on this? a=zeros((2,3),dtype=int) b=a a[:,0]=[1,2] a > array([[1, 0, 0], >[2, 0, 0]]) b > array([[1, 0, 0], >[2, 0, 0]]) a=2 a > 2 b > array([[1, 0, 0], >[2, 0, 0]]) In short: x = ... binds a name, it never copies. On the other side x[whatever] = ... or x.attr = ... can run arbitrary code that may or may not alter the object bound to x inplace. You have to know the type of x to know what happens. ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] Multi Layered Graphs
On 01/26/2014 11:23 PM, Ankit Arora wrote: I'm working on a project which involves network graphs. Is there a library that can help me do this: I want to create multi-layered graphs i.e. graphs which contain a set number of vertices but multiple 'layers' of edges i.e. same set of vertices representing two or more properties in the same data structure. One rather hacky solution can be to form a complete graph in igraph and deal with the layers as if they were igraph edge attributes, though when dealing with tens of thousands of vertices on a complete graph it will be inefficient. Any clue if something proper exists? If not, any more intelligent solutions using existing libraries such as igraph/networkx? Just a personal point of view: I usually end up implementing custom graphs or trees because it is rather simple [*] and because of the variety of structures and features. (Maybe that's why there are no general purpose node/tree/graph libs, only highly specialised one, as for XML parsing.) If you take this route and need help or advice on given points or features, we can probably be of some use. Denis [*] compared the overall app: if a graph is complex, then the app it is a component of is even more complex ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When is = a copy and when is it an alias
On 27/01/2014 09:53, spir wrote: On 01/27/2014 07:16 AM, Denis Heidtmann wrote: Running python 2.7 in linux Below are two extremes. Can I get some guidance on this? Thanks, -Denis H a=zeros((2,3),dtype=int) b=a a[:,0]=[1,2] a array([[1, 0, 0], [2, 0, 0]]) b array([[1, 0, 0], [2, 0, 0]]) a=2 a 2 b array([[1, 0, 0], [2, 0, 0]]) Note: your example is strongly obscured by using weird and rare features that don't bring any helpful point to the actual problematic concepts you apparently want to deal with. Nothing weird and rare about it, just something from the numpy maths library and not pure Python. -- My fellow Pythonistas, ask not what our language can do for you, ask what you can do for our language. Mark Lawrence ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When is = a copy and when is it an alias
Thanks for the responses. The distinction between replacement and modification seems to capture the essential aspect and helps to clarify the issue for me. spir: Quite the opposite, in python "symbolic assignment" (where the right side also is a symbol) never copies, in fact never creates a new value, but bind the left symbol to the same, unique value, as the right symbol. If this is accurate, I can see crazy bugs in my future until I internalize it. Python 2.7.3 (default, Sep 26 2013, 20:03:06) [GCC 4.6.3] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> a=[2,3] >>> b=[10,20] >>> a[0]=b[0] >>> a [10, 3] >>> b[0]=100 >>> a [10, 3] Apparently a[0]=b[0] does not qualify as "symbolic assignment" in this case. a[0] is not a reference to b[0]. I think I see the essential distinction. Experience will complete the picture for me. -DH ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] Multi Layered Graphs
-- On Sun, Jan 26, 2014 11:23 PM CET Ankit Arora wrote: >I'm working on a project which involves network graphs. Is there a library >that can help me do this: > >I want to create multi-layered graphs i.e. graphs which contain a set >number of vertices but multiple 'layers' of edges i.e. same set of vertices >representing two or more properties in the same data structure. > >One rather hacky solution can be to form a complete graph in igraph and >deal with the layers as if they were igraph edge attributes, though when >dealing with tens of thousands of vertices on a complete graph it will be >inefficient. > >Any clue if something proper exists? If not, any more intelligent solutions >using existing libraries such as igraph/networkx? Maybe D3py, a Python wrapper for D3.js. No experience with it but it looks great. ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When is = a copy and when is it an alias
> Apparently a[0]=b[0] does not qualify as "symbolic assignment" in this case. > a[0] is not a reference to b[0]. I think I see the essential distinction. > Experience will complete the picture for me. Yes. The distinction is something that is blurred by Python's syntax. The "=" is a conceptually different thing, based on what's on the "left hand side" of the "=". It can means "variable binding" or "structure mutation", and those concepts are similar, but not the same thing. And variable binding itself can even have a slightly different meaning, depending on whether the surrounding context is a function definition or not, establishing a local or global variable binding. Whew! Assignment can be tricky. It's at the heart of one of the things that makes programming "hard": it is very much about change, about dynamics, about having to reason what the world looks like "before" and "after" a change. (And hence why some customized programming languages for beginners outright prohibit the assignment operator.) ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
Re: [Tutor] When is = a copy and when is it an alias
On Mon, Jan 27, 2014 at 2:01 PM, Danny Yoo wrote:
> And variable binding itself can even have a slightly
> different meaning, depending on whether the surrounding context is a
> function definition or not, establishing a local or global variable
> binding. Whew!
Name binding is local unless you tell Python otherwise by declaring a
name to be global (also nonlocal in 3.x). CPython, for example,
compiles top-level module code to use the STORE_NAME instruction,
which stores to the locals mapping of the current frame. If the name
is declared global, it instead uses STORE_GLOBAL.
Module-level code is flagged to create a frame for which locals and
globals are the same dict. You could, however, exec code using
separate dicts for locals and globals:
src = r'''
global x
x = 0
y = 1
'''
gvars, lvars = {}, {}
exec src in gvars, lvars
>>> sorted(gvars)
['__builtins__', 'x']
>>> sorted(lvars)
['y']
CPython bytecode:
>>> code = compile(src, '', 'exec')
>>> dis.dis(code)
3 0 LOAD_CONST 0 (0)
3 STORE_GLOBAL 0 (x)
4 6 LOAD_CONST 1 (1)
9 STORE_NAME 1 (y)
12 LOAD_CONST 2 (None)
15 RETURN_VALUE
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Re: [Tutor] When is = a copy and when is it an alias
On Mon, Jan 27, 2014 at 9:07 AM, Mark Lawrence wrote: > On 27/01/2014 09:53, spir wrote: >> >> Note: your example is strongly obscured by using weird and rare features >> that don't bring any helpful point to the actual problematic concepts >> you apparently want to deal with. >> > > Nothing weird and rare about it, just something from the numpy maths library > and not pure Python. NumPy arrays may seem weird to someone who expects a slice to create a shallow copy of the data, in the way that slicing a `list` creates a shallow copy: >>> a = [0, 2, 4] >>> b = a[:] `b` is a copy of list `a`, so modifying `b` has no effect on `a`: >>> b[:] = [1, 3, 5] >>> a [0, 2, 4] Slicing a NumPy array returns a new view on the data: a = np.array([0, 2, 4], dtype=object) b = a[:] >>> b.base is a True >>> b.flags.owndata False The view shares the underlying data array, so modifying it also changes the original: >>> b[:] = [1, 3, 5] >>> a array([1, 3, 5], dtype=object) You have to ask for a `copy`: a = np.array([0, 2, 4], dtype=object) b = a.copy() >>> b.base is None True >>> b.flags.owndata True >>> b[:] = [1, 3, 5] >>> a array([0, 2, 4], dtype=object) ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
