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Understanding Python super() with __init__() methods super() lets you avoid referring to the base class explicitly, which can be nice But the main advantage comes with multiple inheritance, where all sorts of fun stuff can happen
How does Pythons super () work with multiple inheritance? In fact, multiple inheritance is the only case where super() is of any use I would not recommend using it with classes using linear inheritance, where it's just useless overhead
node. js - Why is npm install really slow? - Stack Overflow npm install I get the following which can take hours to fully setup: This is not a general computing or hardware issue Comparative speeds are below : Run haversine to calculate all distances on over 1 million records in a non-index mysql table takes significantly less time (computational) Download a full install of Linux (Dual Layer DVD ISO) in significantly less time (bandwidth) I suspect
java - Meaning of Super Keyword - Stack Overflow The super keyword refers to the instance of the parent class (Object, implicitly) of the current object This is useful when you override a method in a subclass but still wants to call the method defined in the parent class
python - Super init vs. parent. __init__ - Stack Overflow super has a lesser benefit of reducing requires changes if you rename or change the base class In python 3, the arguments to super are optional, so you can just do super() __init__()
Python super and setting parent class property from subclasses The property refers to a mutable object, and you are making changes (setting new keys) in that object All the property mechanism get in a line like super() data['aws_lambda'] = new_value is a read access to super() data - Python resolves that part of the expression and returns a dictionary - then you set the dictionary key