Readings: Pythonisms Summary:

Dunders

• Dunder or magic methods in Python are the methods having two prefix and suffix underscores in the method name. Dunder here means “Double Under (Underscores)”. These are commonly used for operator overloading. Few examples for magic methods are: init, add, len, repr etc. __len__ returns a length for the class. Here’s an example

class LenSupport:
    def __len__(self):
        return 42

>>> obj = LenSupport()
>>> len(obj)
42

__init__ is the method that lets us build constructors inside of a class.

class Account:
    """A simple account class"""

    def __init__(self, owner, amount=0):
        """
        This is the constructor that lets us create
        objects from this class
        """
        self.owner = owner
        self.amount = amount
        self._transactions = []

__str__ formats the string neatly for the enduser.

__repr__ is the official string representation of an object and the goal of it is to be ambiguous.

class Account:
    # ... (see above)

    def __repr__(self):
        return 'Account({!r}, {!r})'.format(self.owner, self.amount)

    def __str__(self):
        return 'Account of {} with starting amount: {}'.format(
            self.owner, self.amount)

__getitem__ iterates through the object.

__eq__ means equal. __lt__ means less than.

from functools import total_ordering

@total_ordering
class Account:
    # ... (see above)

    def __eq__(self, other):
        return self.balance == other.balance

    def __lt__(self, other):
        return self.balance < other.balance

and now we can compare other objects:

>>> acc2 > acc
True

>>> acc2 < acc
False

>>> acc == acc2
False

__add__ merges two objects together.

__call__ makes the object callable.

__enter__ and __exit__ are context managers.

Iterators

• Iterators provide a sequence interface to Python objects that’s memory efficient and considered Pythonic. Behold the beauty of the for-in loop!
• To support iteration an object needs to implement the iterator protocol by providing the iter and next dunder methods.
• Class-based iterators are only one way to write iterable objects in Python. Also consider generators and generator expressions.

Generators

Generators use yield statements instead of return. Local variables and the execution state of the generator function are only stashed away temporarily and not thrown out completely. Generators start raising StopIteration exceptions after control flow leaves the generator function by any means other than a yield statement.