I am working on a python hangman game and have my graphics based on a variable, lives, so when you have 1 lives, the corresponding picture appears. i put my graphics into definitions and want to call them from that. Here's my code so far:
if life== 1:
graphics1()
if life==2:
graphics2()
if life==3:
graphics3()
if life==4:
graphics4()
if life==5:
graphics5()
if life==6:
graphics6()
if life==7:
graphics7()
if life==8:
graphics8()
if life==9:
graphics9()
if life==10:
graphics10()
and so on, so is there a command which would allow me to shorten this to one or two lines?
I highly discourage it, but it could be accomplished by doing:
globals()["graphics" + str(life)]()
However there's most definitely a better solution. Presuming that the contents of each graphics*() is similar to one another.
Well, multiple if branches can be expressed via lookup table as
lt = {"1":graphics1(), "2":graphics2()}
and so on.
Accès to if branch via (and provide a fallback function)
lt.get(life, graphics1())
If you want to create the dict dynamically use the dict comprehension and use the getattr to get the function.
Or, as stated above, generalize the function graphics passing the "ith" param to it.
Related
This is a question about a clean, pythonic way to juggle some different instance methods.
I have a class that operates a little differently depending on certain inputs. The differences didn't seem big enough to justify producing entirely new classes. I have to interface the class with one of several data "providers". I thought I was being smart when I introduced a dictionary:
self.interface_tools={'TYPE_A':{ ... various ..., 'data_supplier':self.current_data},
'TYPE_B':{ ... various ..., 'data_supplier':self.predicted_data} }
Then, as part of the class initialization, I have an input "source_name" and I do ...
# ... various ....
self.data_supplier = self.interface_tools[source_name]['data_supplier']
self.current_data and self.predicted_data need the same input parameter, so when it comes time to call the method, I don't have to distinguish them. I can just call
new_data = self.data_supplier(param1)
But now I need to interface with a new data source -- call it "TYPE_C" -- and it needs more input parameters. There are ways to do this, but nothing I can think of is very clean. For instance, I could just add the new parameters to the old data_suppliers and never use them, so then the call would look like
new_data = self.data_supplier(param1,param2,param3)
But I don't like that. I could add an if block
if self.data_source != 'TYPE_C':
new_data = self.data_supplie(param1)
else:
new_data = self.data_c_supplier(param1,param2,param3)
but avoiding if blocks like this was exactly what I was trying to do in the first place with that dictionary I came up with.
So the upshot is: I have a few "data_supplier" routines. Now that my project has expanded, they have different input lists. But I want my class to be able to treat them all the same to the extent possible. Any ideas? Thanks.
Sounds like your functions could be making use of variable length argument lists.
That said, you could also just make subclasses. They're fairly cheap to make, and would solve your problem here. This is pretty much the case they were designed for.
You could make all your data_suppliers accept a single argument and make it a dictionary or a list or even a NamedTuple.
so i know this is a bit of a workaround and theres probably a better way to do this, but heres the deal. Ive simplified the code from where tis gathering this info from and just given solid values.
curSel = nuke.selectedNodes()
knobToChange = "label"
codeIn = "[value in]"
kcPrefix = "x"
kcStart = "['"
kcEnd = "']"
changerString = kcPrefix+kcStart+knobToChange+kcEnd
for x in curSel:
changerString.setValue(codeIn)
But i get the error i figured i would - which is that a string has no attribute "setValue"
its because if i just type x['label'] instead of changerString, it works, but even though changer string says the exact same thing, its being read as a string instead of code.
Any ideas?
It looks like you're looking for something to evaluate the string into a python object based on your current namespace. One way to do that would be to use the globals dictionary:
globals()['x']['label'].setValue(...)
In other words, globals()['x']['label'] is the same thing as x['label'].
Or to spell it out explicitly for your case:
globals()[kcPrefix][knobToChange].setValue(codeIn)
Others might suggest eval:
eval('x["label"]').setValue(...) #insecure and inefficient
but globals is definitely a better idea here.
Finally, usually when you want to do something like this, you're better off using a dictionary or some other sort of data structure in the first place to keep your data more organized
Righto, there's two things you're falling afoul of. Firstly, in your original code where you are trying to do the setValue() call on a string you're right in that it won't work. Ideally use one of the two calls (x.knob('name_of_the_knob') or x['name_of_the_knob'], whichever is consistent with your project/facility/personal style) to get and set the value of the knob object.
From the comments, your code would look like this (my comments added for other people who aren't quite as au fait with Nuke):
# select all the nodes
curSel = nuke.selectedNodes()
# nuke.thisNode() returns the script's context
# i.e. the node from which the script was invoked
knobToChange = nuke.thisNode()['knobname'].getValue()
codeIn = nuke.thisNode()['codeinput'].getValue()
for x in curSel:
x.knob(knobToChange).setValue(codeIn)
Using this sample UI with the values in the two fields as shown and the button firing off the script...
...this code is going to give you an error message of 'Nothing is named "foo"' when you execute it because the .getValue() call is actually returning you the evaluated result of the knob - which is the error message as it tries to execute the TCL [value foo], and finds that there isn't any object named foo.
What you should ideally do is instead invoke .toScript() which returns the raw text.
# select all the nodes
curSel = nuke.selectedNodes()
# nuke.thisNode() returns the script's context
# i.e. the node from which the script was invoked
knobToChange = nuke.thisNode()['knobname'].toScript()
codeIn = nuke.thisNode()['codeinput'].toScript()
for x in curSel:
x.knob(knobToChange).setValue(codeIn)
You can sidestep this problem as you've noted by building up a string, adding in square brackets etc etc as per your original code, but yes, it's a pain, a maintenance nightmare, and starting to go down that route of building objects up from strings (which #mgilson explains how to do in both a globals() or eval() method)
For those who haven't had the joy of working with Nuke, here's a small screencap that may (or may not..) provide more context:
Is it better not to name list variables "list"? Since it's conflicted with the python reserved keyword. Then, what's the better naming? "input_list" sounds kinda awkward.
I know it can be problem-specific, but, say I have a quick sort function, then quick_sort(unsorted_list) is still kinda lengthy, since list passed to sorting function is clearly unsorted by context.
Any idea?
I like to name it with the plural of whatever's in it. So, for example, if I have a list of names, I call it names, and then I can write:
for name in names:
which I think looks pretty nice. But generally for your own sanity you should name your variables so that you can know what they are just from the name. This convention has the added benefit of being type-agnostic, just like Python itself, because names can be any iterable object such as a tuple, a dict, or your very own custom (iterable) object. You can use for name in names on any of those, and if you had a tuple called names_list that would just be weird.
(Added from a comment below:) There are a few situations where you don't have to do this. Using a canonical variable like i to index a short loop is OK because i is usually used that way. If your variable is used on more than one page worth of code, so that you can't see its entire lifetime at once, you should give it a sensible name.
goats
Variable names should refer what they are not just what type they are.
Python stands for readability. So basically you should name variables that promote readability. See PEP20.You should only have a general rule of consistency and should break this consistency in the following situations:
When applying the rule would make the code less readable, even for
someone who is used to reading code that follows the rules.
To be consistent with surrounding code that also breaks it (maybe for
historic reasons) -- although this is also an opportunity to clean up
someone else's mess (in true XP style)
Also, use the function naming rules: lowercase with words separated by underscores as necessary to improve readability.
All this is taken from PEP 8
Just use lst, or seq (for sequence)
I use a naming convention based on descriptive name and type. (I think I learned this from a Jeff Atwood blog post but I can't find it.)
goats_list
for goat in goats_list :
goat.bleat()
cow_hash = {}
etc.
Anything more complicated (list_list_hash_list) I make a class.
What about L?
Why not just use unsorted? I prefer to have names, which communicate ideas, not data types. There are special cases, where the type of a variable is important. But in most cases, it's obvious from the context - like in your case. Quick sort is obviously working on a list.
I prefer to use long identifiers to keep my code semantically clear, but in the case of repeated references to the same identifier, I'd like for it to "get out of the way" in the current scope. Take this example in Python:
def define_many_mappings_1(self):
self.define_bidirectional_parameter_mapping("status", "current_status")
self.define_bidirectional_parameter_mapping("id", "unique_id")
self.define_bidirectional_parameter_mapping("location", "coordinates")
#etc...
Let's assume that I really want to stick with this long method name, and that these arguments are always going to be hard-coded.
Implementation 1 feels wrong because most of each line is taken up with a repetition of characters. The lines are also rather long in general, and will exceed 80 characters easily when nested inside of a class definition and/or a try/except block, resulting in ugly line wrapping. Let's try using a for loop:
def define_many_mappings_2(self):
mappings = [("status", "current_status"),
("id", "unique_id"),
("location", "coordinates")]
for mapping in mappings:
self.define_parameter_mapping(*mapping)
I'm going to lump together all similar iterative techniques under the umbrella of Implementation 2, which has the improvement of separating the "unique" arguments from the "repeated" method name. However, I dislike that this has the effect of placing the arguments before the method they're being passed into, which is confusing. I would prefer to retain the "verb followed by direct object" syntax.
I've found myself using the following as a compromise:
def define_many_mappings_3(self):
d = self.define_bidirectional_parameter_mapping
d("status", "current_status")
d("id", "unique_id")
d("location", "coordinates")
In Implementation 3, the long method is aliased by an extremely short "abbreviation" variable. I like this approach because it is immediately recognizable as a set of repeated method calls on first glance while having less redundant characters and much shorter lines. The drawback is the usage of an extremely short and semantically unclear identifier "d".
What is the most readable solution? Is the usage of an "abbreviation variable" acceptable if it is explicitly assigned from an unabbreviated version in the local scope?
itertools to the rescue again! Try using starmap - here's a simple demo:
list(itertools.starmap(min,[(1,2),(2,2),(3,2)]))
prints
[1,2,2]
starmap is a generator, so to actually invoke the methods, you have to consume the generator with a list.
import itertools
def define_many_mappings_4(self):
list(itertools.starmap(
self.define_parameter_mapping,
[
("status", "current_status"),
("id", "unique_id"),
("location", "coordinates"),
] ))
Normally I'm not a fan of using a dummy list construction to invoke a sequence of functions, but this arrangement seems to address most of your concerns.
If define_parameter_mapping returns None, then you can replace list with any, and then all of the function calls will get made, and you won't have to construct that dummy list.
I would go with Implementation 2, but it is a close call.
I think #2 and #3 are equally readable. Imagine if you had 100s of mappings... Either way, I cannot tell what the code at the bottom is doing without scrolling to the top. In #2 you are giving a name to the data; in #3, you are giving a name to the function. It's basically a wash.
Changing the data is also a wash, since either way you just add one line in the same pattern as what is already there.
The difference comes if you want to change what you are doing to the data. For example, say you decide to add a debug message for each mapping you define. With #2, you add a statement to the loop, and it is still easy to read. With #3, you have to create a lambda or something. Nothing wrong with lambdas -- I love Lisp as much as anybody -- but I think I would still find #2 easier to read and modify.
But it is a close call, and your taste might be different.
I think #3 is not bad although I might pick a slightly longer identifier than d, but often this type of thing becomes data driven, so then you would find yourself using a variation of #2 where you are looping over the result of a database query or something from a config file
There's no right answer, so you'll get opinions on all sides here, but I would by far prefer to see #2 in any code I was responsible for maintaining.
#1 is verbose, repetitive, and difficult to change (e.g. say you need to call two methods on each pair or add logging -- then you must change every line). But this is often how code evolves, and it is a fairly familiar and harmless pattern.
#3 suffers the same problem as #1, but is slightly more concise at the cost of requiring what is basically a macro and thus new and slightly unfamiliar terms.
#2 is simple and clear. It lays out your mappings in data form, and then iterates them using basic language constructs. To add new mappings, you only need add a line to the array. You might end up loading your mappings from an external file or URL down the line, and that would be an easy change. To change what is done with them, you only need change the body of your for loop (which itself could be made into a separate function if the need arose).
Your complaint of #2 of "object before verb" doesn't bother me at all. In scanning that function, I would basically first assume the verb does what it's supposed to do and focus on the object, which is now clear and immediately visible and maintainable. Only if there were problems would I look at the verb, and it would be immediately evident what it is doing.
I'm coding a poker hand evaluator as my first programming project. I've made it through three classes, each of which accomplishes its narrowly-defined task very well:
HandRange = a string-like object (e.g. "AA"). getHands() returns a list of tuples for each specific hand within the string:
[(Ad,Ac),(Ad,Ah),(Ad,As),(Ac,Ah),(Ac,As),(Ah,As)]
Translation = a dictionary that maps the return list from getHands to values that are useful for a given evaluator (yes, this can probably be refactored into another class).
{'As':52, 'Ad':51, ...}
Evaluator = takes a list from HandRange (as translated by Translator), enumerates all possible hand matchups and provides win % for each.
My question: what should my "domain" class for using all these classes look like, given that I may want to connect to it via either a shell UI or a GUI? Right now, it looks like an assembly line process:
user_input = HandRange()
x = Translation.translateList(user_input)
y = Evaluator.getEquities(x)
This smells funny in that it feels like it's procedural when I ought to be using OO.
In a more general way: if I've spent so much time ensuring that my classes are well defined, narrowly focused, orthogonal, whatever ... how do I actually manage work flow in my program when I need to use all of them in a row?
Thanks,
Mike
Don't make a fetish of object orientation -- Python supports multiple paradigms, after all! Think of your user-defined types, AKA classes, as building blocks that gradually give you a "language" that's closer to your domain rather than to general purpose language / library primitives.
At some point you'll want to code "verbs" (actions) that use your building blocks to perform something (under command from whatever interface you'll supply -- command line, RPC, web, GUI, ...) -- and those may be module-level functions as well as methods within some encompassing class. You'll surely want a class if you need multiple instances, and most likely also if the actions involve updating "state" (instance variables of a class being much nicer than globals) or if inheritance and/or polomorphism come into play; but, there is no a priori reason to prefer classes to functions otherwise.
If you find yourself writing static methods, yearning for a singleton (or Borg) design pattern, writing a class with no state (just methods) -- these are all "code smells" that should prompt you to check whether you really need a class for that subset of your code, or rather whether you may be overcomplicating things and should use a module with functions for that part of your code. (Sometimes after due consideration you'll unearth some different reason for preferring a class, and that's allright too, but the point is, don't just pick a class over a module w/functions "by reflex", without critically thinking about it!).
You could create a Poker class that ties these all together and intialize all of that stuff in the __init__() method:
class Poker(object):
def __init__(self, user_input=HandRange()):
self.user_input = user_input
self.translation = Translation.translateList(user_input)
self.evaluator = Evaluator.getEquities(x)
# and so on...
p = Poker()
# etc, etc...