When should you use getters and setters? Getters and setters are great for configuring or determining the configuration of a class, or retrieving data from a model Getting the price of an item is an entirely reasonable use of a getter. That is data that needs to be available and may involve special considerations to … Read more
Encapsulation helps in isolating implementation details from the behavior exposed to clients of a class (other classes/functions that are using this class), and gives you more control over coupling in your code. Consider this example, similar to the one in Robert Martin’s book Clean Code: public class Car { //… public float GetFuelPercentage() { /* … Read more
I received the error “A suitable constructor for type ‘<type>’ could not be located.” after accidentally generating a protected constructor instead of public constructor. Marking it back to public fixed it.
The problem you describe could be solved using the Visitor pattern (everything can be solved using the Visitor pattern, so beware! ) The visitor pattern lets you move the implementation logic towards a new class. That way you do not need a base class, and a visitor works extremely well over different inheritance trees. To … Read more
This is the way I create modules: myModule.js var MyObject = function() { // This is private because it is not being return var _privateFunction = function(param1, param2) { … return; } var function1 = function(param1, callback) { … callback(err, results); } var function2 = function(param1, param2, callback) { … callback(err, results); } return { … Read more
From here: Adapter provides a different interface to its subject. Proxy provides the same interface. You might think of an Adapter as something that should make one thing fit to another that is incompatible if connected directly. When you travel abroad, for example, and need an electrical outlet adapter. Now a Proxy is an object … Read more
What about just using __fields__: from pydantic import BaseModel class AdaptedModel(BaseModel): parent_attr: str class TestClass(AdaptedModel): child_attr: str TestClass.__fields__ Output: {‘parent_attr’: ModelField(name=”parent_attr”, type=str, required=True), ‘child_attr’: ModelField(name=”child_attr”, type=str, required=True)} This is just a dict and you could get only the field names simply by: TestClass.__fields__.keys() See model properties: https://pydantic-docs.helpmanual.io/usage/models/#model-properties
The problem in your initial definition of the class is that you’ve written: class name(object, name): This means that the class inherits the base class called “object”, and the base class called “name”. However, there is no base class called “name”, so it fails. Instead, all you need to do is have the variable in … Read more