I have a bunch of Objects from the same Class in Python.
I've decided to put each object in a different file since it's
easier to manage them (If I plan to add more objects or edit them individually)
However, I'm not sure how to run through all of them, they are in another Package
So if I look at Netbeans I have TopLevel... and there's also a Package named Shapes
in Shapes I have Ball.py, Circle.py, Triangle.py (inside the files is a call for a constructor with the details of the specific shape) and they are all from class GraphicalShape
That is configured in GraphicalShape.py in the TopLevel Package.
Now, I have also on my Toplevel Package a file named newpythonproject.py, which would start the
process of calling each shape and doing things with it, how do I run through all of the shapes?
also: Is it a good way to do this?
p.s. never mind the uppercase lowercase stuff...
Just to clarify, I added a picture of the Project Tree
http://i47.tinypic.com/2i1nomw.png
It seems that you're misunderstanding the Python jargon. The Python term "object" means an actual run-time instance of a class. As far as I can tell, you have "sub-classes" of the Shape class called ball, circle and triangle. Note that a sub-class is also a class. You are keeping the code for each such sub-class in a separate file, which is fine.
I think you're getting mixed up because you're focusing on the file layout of your project far too early. With Python it is often easier to start with just one file, writing everything you need in that file (functions, classes, etc.). Just get things working first. Later, when you've got working code and you just want to split a part of it into another file for organizational reasons, it will be much more obvious (to you!) how this should be done.
In Python, every class does not have to be defined in its own separate file. You can do this if you like, but it is not compulsory.
it's not clear what you mean when you say "run through them all".
If you mean "import them for use", then you should:
Make sure the parent folder of shapes is on the PYTHONPATH environment variable; then use
from shapes import ball.
Related
I really like how Microsoft.Extensions.Configuration works in .NET to manage and merge configuration. Now I'm starting a Python project and I would like to know if there's any package that gives comparable features there. What I especially like is the ability to add a series of JSON files that override one-another, and being able to specify some as optional.
On top of that, it gives the ability to override some values from environment variables using some environment variable name convention. That would be the cherry on top, but I can live without it.
Example: I have a default JSON config file (it would be called appsettings.json in .NET), and for deployments, I add another JSON file (would be called appsettings.Deployment.json). When the app starts, it looks for the first file (it's mandatory) and the second file (optionally) and combines the two by overriding values from the first file with values from the second file where it applies. The whole thing is deserialized to some object (I think I can easily handle that in Python).
If this is simply the wrong way of thinking about it in Python and there's some better way of doing mergeable configuration, I would also be glad to learn about that.
I have an application that dynamically generates a lot of Python modules with class factories to eliminate a lot of redundant boilerplate that makes the code hard to debug across similar implementations and it works well except that the dynamic generation of the classes across the modules (hundreds of them) takes more time to load than simply importing from a file. So I would like to find a way to save the modules to a file after generation (unless reset) then load from those files to cut down on bootstrap time for the platform.
Does anyone know how I can save/export auto-generated Python modules to a file for re-import later. I already know that pickling and exporting as a JSON object won't work because they make use of thread locks and other dynamic state variables and the classes must be defined before they can be pickled. I need to save the actual class definitions, not instances. The classes are defined with the type() function.
If you have ideas of knowledge on how to do this I would really appreciate your input.
You’re basically asking how to write a compiler whose input is a module object and whose output is a .pyc file. (One plausible strategy is of course to generate a .py and then byte-compile that in the usual fashion; the following could even be adapted to do so.) It’s fairly easy to do this for simple cases: the .pyc format is very simple (but note the comments there), and the marshal module does all of the heavy lifting for it. One point of warning that might be obvious: if you’ve already evaluated, say, os.getcwd() when you generate the code, that’s not at all the same as evaluating it when loading it in a new process.
The “only” other task is constructing the code objects for the module and each class: this requires concatenating a large number of boring values from the dis module, and will fail if any object encountered is non-trivial. These might be global/static variables/constants or default argument values: if you can alter your generator to produce modules directly, you can probably wrap all of these (along with anything else you want to defer) in function calls by compiling something like
my_global=(lambda: open(os.devnull,'w'))()
so that you actually emit the function and then a call to it. If you can’t so alter it, you’ll have to have rules to recognize values that need to be constructed in this fashion so that you can replace them with such calls.
Another detail that may be important is closures: if your generator uses local functions/classes, you’ll need to create the cell objects, perhaps via “fake” closures of your own:
def cell(x): return (lambda: x).__closure__[0]
I am a beginner in Python, and I am trying to learn by making a simple game. I started by having everything in one big file (let's call it main.py), but it is getting to the point where it has so many classes and functions that I would like to split this code into more manageable components.
I have some experience with LaTeX (although certainly not an expert either) and, in LaTeX there is a function called \input which allows one to write part of the code in a different file. For example, if I have files main.tex and sub.tex which look like:
main.tex:
Some code here.
\input{sub}
Lastly, some other stuff.
and
sub.tex:
Some more code here
then, when I execute main.tex, it will execute:
Some code here.
Some more code here
Lastly, some other stuff.
I wonder, is there a similar thing in Python?
Note 1: From what I have seen, the most commonly suggested way to go about splitting your code is to use modules. I have found this a bit uncomfortable for a few reasons, which I will list below (of course, I understand that I find them uncomfortable because I am a inexperienced, and not because this is the wrong way to do things).
Reasons why I find modules uncomfortable:
My main.py file imports some other modules, like Pygame, which need to be imported into all the new modules I create. If for some reason I wanted to import a new module into main.py later in the process I would then need to import it on every other module I create.
My main.py file has some global variables that are used in the different classes; for example, I have a global variable CITY_SIZE that controls the size of all City instances on the screen. Naturally, CITY_SIZE is used in the definition of the class City. If I were to move the class City to a module classes.py, then I need to define CITY_SIZE on classes.py as well, and if I ever wanted to change the value of CITY_SIZE I would need to change its value on classes.py as well.
Again, suppose that I add a classes.py module where I store all my classes, like City. Then in main.py I need to write classes.City in my code instead of City. I understand this can be overcome by using from classes import City but then I need to add a line of code every time I add a new class to classes.py.
Note 2: I would very much appreciate any comments about how to use modules comfortably in Python, but please note that because this is not my question I would not be able to accept those as valid answers (but, again, they would be appreciated!).
If you have all of your modules in the same directory, you can simply use:
import <name of submodule without .py>
For example, if a submodule file was named sub.py, you would import it like this:
import sub
Does anyone know how pydev determines what to use for code completion? I'm trying to define a set of classes specifically to enable code completion. I've tried using __new__ to set __dict__ and also __slots__, but neither seems to get listed in pydev autocomplete.
I've got a set of enums I want to list in autocomplete, but I'd like to set them in a generator, not hardcode them all for each class.
So rather than
class TypeA(object):
ValOk = 1
ValSomethingSpecificToThisClassWentWrong = 4
def __call__(self):
return 42
I'd like do something like
def TYPE_GEN(name, val, enums={}):
def call(self):
return val
dct = {}
dct["__call__"] = call
dct['__slots__'] = enums.keys()
for k, v in enums.items():
dct[k] = v
return type(name, (), dct)
TypeA = TYPE_GEN("TypeA",42,{"ValOk":1,"ValSomethingSpecificToThisClassWentWrong":4})
What can I do to help the processing out?
edit:
The comments seem to be about questioning what I am doing. Again, a big part of what I'm after is code completion. I'm using python binding to a protocol to talk to various microcontrollers. Each parameter I can change (there are hundreds) has a name conceptually, but over the protocol I need to use its ID, which is effectively random. Many of the parameters accept values that are conceptually named, but are again represented by integers. Thus the enum.
I'm trying to autogenerate a python module for the library, so the group can specify what they want to change using the names instead of the error prone numbers. The __call__ property will return the id of the parameter, the enums are the allowable values for the parameter.
Yes, I can generate the verbose version of each class. One line for each type seemed clearer to me, since the point is autocomplete, not viewing these classes.
Ok, as pointed, your code is too dynamic for this... PyDev will only analyze your own code statically (i.e.: code that lives inside your project).
Still, there are some alternatives there:
Option 1:
You can force PyDev to analyze code that's in your library (i.e.: in site-packages) dynamically, in which case it could get that information dynamically through a shell.
To do that, you'd have to create a module in site-packages and in your interpreter configuration you'd need to add it to the 'forced builtins'. See: http://pydev.org/manual_101_interpreter.html for details on that.
Option 2:
Another option would be putting it into your predefined completions (but in this case it also needs to be in the interpreter configuration, not in your code -- and you'd have to make the completions explicit there anyways). See the link above for how to do this too.
Option 3:
Generate the actual code. I believe that Cog (http://nedbatchelder.com/code/cog/) is the best alternative for this as you can write python code to output the contents of the file and you can later change the code/rerun cog to update what's needed (if you want proper completions without having to put your code as it was a library in PyDev, I believe that'd be the best alternative -- and you'd be able to grasp better what you have as your structure would be explicit there).
Note that cog also works if you're in other languages such as Java/C++, etc. So, it's something I'd recommend adding to your tool set regardless of this particular issue.
Fully general code completion for Python isn't actually possible in an "offline" editor (as opposed to in an interactive Python shell).
The reason is that Python is too dynamic; basically anything can change at any time. If I type TypeA.Val and ask for completions, the system had to know what object TypeA is bound to, what its class is, and what the attributes of both are. All 3 of those facts can change (and do; TypeA starts undefined and is only bound to an object at some specific point during program execution).
So the system would have to know st what point in the program run do you want the completions from? And even if there were some unambiguous way of specifying that, there's no general way to know what the state of everything in the program is like at that point without actually running it to that point, which you probably don't want your editor to do!
So what pydev does instead is guess, when it's pretty obvious. If you have a class block in a module foo defining class Bar, then it's a safe bet that the name Bar imported from foo is going to refer to that class. And so you know something about what names are accessible under Bar., or on an object created by obj = Bar(). Sure, the program could be rebinding foo.Bar (or altering its set of attributes) at runtime, or could be run in an environment where import foo is hitting some other file. But that sort of thing happens rarely, and the completions are useful in the common case.
What that means though is that you basically lose completions whenever you use "too much" of Python's dynamic language flexibility. Defining a class by calling a function is one of those cases. It's not ready to guess that TypeA has names ValOk and ValSomethingSpecificToThisClassWentWrong; after all, there's presumably lots of other objects that result from calls to TYPE_GEN, but they all have different names.
So if your main goal is to have completions, I think you'll have to make it easy for pydev and write these classes out in full. Of course, you could use similar code to generate the python files (textually) if you wanted. It looks though like there's actually more "syntactic overhead" of defining these with dictionaries than as a class, though; you're writing "a": b, per item rather than a = b. Unless you can generate these more systematically or parse existing definition files or something, I think I'd find the static class definition easier to read and write than the dictionary driving TYPE_GEN.
The simpler your code, the more likely completion is to work. Would it be reasonable to have this as a separate tool that generates Python code files containing the class definitions like you have above? This would essentially be the best of both worlds. You could even put the name/value pairs in a JSON or INI file or what have you, eliminating the clutter of the methods call among the name/value pairs. The only downside is needing to run the tool to regenerate the code files when the codes change, but at least that's an automated, simple process.
Personally, I would just go with making things more verbose and writing out the classes manually, but that's just my opinion.
On a side note, I don't see much benefit in making the classes callable vs. just having an id class variable. Both require knowing what to type: TypeA() vs TypeA.id. If you want to prevent instantiation, I think throwing an exception in __init__ would be a bit more clear about your intentions.
I am working on my program, GarlicSim, in which a user creates a simulation, then he is able to manipulate it as he desires, and then he can save it to file.
I recently tried implementing the saving feature. The natural thing that occured to me is to pickle the Project object, which contains the entire simulation.
Problem is, the Project object also includes a module-- That is the "simulation package", which is a package/module that contains several critical objects, mostly functions, that define the simulation. I need to save them together with the simulation, but it seems that it is impossible to pickle a module, as I witnessed when I tried to pickle the Project object and an exception was raised.
What would be a good way to work around that limitation?
(I should also note that the simulation package gets imported dynamically in the program.)
If the project somehow has a reference to a module with stuff you need, it sounds like you might want to refactor the use of that module into a class within the module. This is often better anyway, because the use of a module for stuff smells of a big fat global. In my experience, such an application structure will only lead to trouble.
(Of course the quick way out is to save the module's dict instead of the module itself.)
If you have the original code for the simulation package modules, which I presume are dynamically generated, then I would suggest serializing that and reconstructing the modules when loaded. You would do this in the Project.__getstate__() and Project.__setstate__() methods.