How do I design a class in Python?

Question

I've had some really awesome help on my previous questions for detecting paws and toes within a paw, but all these solutions only work for one measurement at a time.

Now I have data that consists off:

• about 30 dogs;
• each has 24 measurements (divided into several subgroups);
• each measurement has at least 4 contacts (one for each paw) and
  • each contact is divided into 5 parts and
  • has several parameters, like contact time, location, total force etc.

Obviously sticking everything into one big object isn't going to cut it, so I figured I needed to use classes instead of the current slew of functions. But even though I've read Learning Python's chapter about classes, I fail to apply it to my own code (GitHub link)

I also feel like it's rather strange to process all the data every time I want to get out some information. Once I know the locations of each paw, there's no reason for me to calculate this again. Furthermore, I want to compare all the paws of the same dog to determine which contact belongs to which paw (front/hind, left/right). This would become a mess if I continue using only functions.

So now I'm looking for advice on how to create classes that will let me process my data (link to the zipped data of one dog) in a sensible fashion.

Answer 1

How to design a class.

1. Write down the words. You started to do this. Some people don't and wonder why they have problems.

2. Expand your set of words into simple statements about what these objects will be doing. That is to say, write down the various calculations you'll be doing on these things. Your short list of 30 dogs, 24 measurements, 4 contacts, and several "parameters" per contact is interesting, but only part of the story. Your "locations of each paw" and "compare all the paws of the same dog to determine which contact belongs to which paw" are the next step in object design.

3. Underline the nouns. Seriously. Some folks debate the value of this, but I find that for first-time OO developers it helps. Underline the nouns.

4. Review the nouns. Generic nouns like "parameter" and "measurement" need to be replaced with specific, concrete nouns that apply to your problem in your problem domain. Specifics help clarify the problem. Generics simply elide details.

5. For each noun ("contact", "paw", "dog", etc.) write down the attributes of that noun and the actions in which that object engages. Don't short-cut this. Every attribute. "Data Set contains 30 Dogs" for example is important.

6. For each attribute, identify if this is a relationship to a defined noun, or some other kind of "primitive" or "atomic" data like a string or a float or something irreducible.

7. For each action or operation, you have to identify which noun has the responsibility, and which nouns merely participate. It's a question of "mutability". Some objects get updated, others don't. Mutable objects must own total responsibility for their mutations.

8. At this point, you can start to transform nouns into class definitions. Some collective nouns are lists, dictionaries, tuples, sets or namedtuples, and you don't need to do very much work. Other classes are more complex, either because of complex derived data or because of some update/mutation which is performed.

Don't forget to test each class in isolation using unittest.

Also, there's no law that says classes must be mutable. In your case, for example, you have almost no mutable data. What you have is derived data, created by transformation functions from the source dataset.