How to use classes derived from a Python list class

Question

This is a question to question 912526 - How to pass many variables to and from a function in Python? .

In the program I am writing, I need to pass all the variables, and from my previous question I understand that I have to put these variables in classes, and then bypass the classes.

Some of these variables are included in repeating sets - to calculate a thin film I need to track the optical properties (refractive index, absorption, thickness, etc.) for several layers.

Is the best way to store variables like this to create a class derived from a Python list, to store a set of classes, each of which contains variables for a single layer? And then put the functions that are associated with the set of layers in the class obtained from the list, and the functions that belong to a specific layer in this class? Is there a better way to do this with a single class?

Using the two-class approach in the following example, I can configure everything so that I can access variables using statuses such as

n1 = layers[5].n 

This is the best way to do this, right?

 #Test passing values to and from functions class Layers(list): def add(self,n,k,comment): self.append( OneLayer(n,k,comment) ) def input_string(self): input_string = [] for layer in self: vars = layer.input_string() for var in vars: input_string.append( var ) return input_string def set_layers(self,results): for layer,i in enumerate(self): j = i*layer.num_var layer.set_layer( *results[j:j+2] ) class OneLayer(object): def __init__(self,n,k,comment): self.n = n self.k = k self.comment = comment def input_string(self): return [['f','Index of Refraction',self.n], ['f','Absorption',self.k],['s','Comment',self.comment]] def set_layer(self,n,k,comment): self.n = n; self.k=k; self.comment = comment def num_var(self): return 3 if __name__ == '__main__': layers = Layers() layers.add(1.0,0.0,'This vacuum sucks') layers.add(1.5,0.0,'BK 7 Glass') print layers[0].n print layers.input_string() layers[1].set_layer(1.77,0.0,'Sapphire') print layers.input_string() 

I get the following result from this test program:

 1.0 [['f', 'Index of Refraction', 1.0], ['f', 'Absorption', 0.0], ['s', 'Comment', 'This vacuum sucks'], ['f', 'Index of Refraction', 1.5], ['f', 'Absorption', 0.0], ['s', 'Comment', 'BK 7 Glass']] [['f', 'Index of Refraction', 1.0], ['f', 'Absorption', 0.0], ['s', 'Comment', 'This vacuum sucks'], ['f', 'Index of Refraction', 1.77], ['f', 'Absorption', 0.0], ['s', 'Comment', 'Sapphire']] 

Answer 1

There are several problems in the code:

1. If you are performing a list operation, the result will be your own list:

 layers1 = Layers() layers2 = Layers() layers1 + layers2 -> the result will be a native list 

2.Why define input_string when you can override __repr__ or __str__

3. What should you extract from the list in this case? You only need to remove it from the list if you want your class to behave exactly the same as the list. But in your case, you seem to be looking for a container. All you need to do to make your class behave similar to a list is to override some special python methods http://docs.python.org/reference/datamodel.html#emulating-container-types

 class Layers(object): def __init__(self, container=None): if container is None: container = [] self.container = container def add(self,n,k,comment): self.container.append([n,k,comment]) def __str__(self): return str(self.container) def __repr__(self): return str(self.container) def __getitem__(self, key): return Layers(self.container[key]) def __len__(self): return len(self.container) >>> l = Layers() >>> l.add(1, 2, 'test') >>> l.add(1, 2, 'test') >>> l [[1, 2, 'test'], [1, 2, 'test']] >>> l[0] [1, 2, 'test'] >>> len(l) 2