This is quick write-up about python iterators and generators.

Iterator objects Link to heading

docs defines iter functions

""" Return an iterator object. The first argument is interpreted very differently depending on the presence of the second argument. Without a second argument, object must be a collection object which supports the iteration protocol (the iter() method) """

This is an example of built-in iterators where iter() and next() are called to get iterator object and get next element in the list.

mlist = [100,200,300]

iter_obj = iter(mlist)

print(next(iter_obj))
for i in iter_obj:
    print(i)

user-defined iter Link to heading

To define iterator protocol, we need at least iter and next

• iter: initializes the iteration and returns class object
• next: returns the iter-able elements. at the end of iteration, next returns StopIteration which caller catches and end the iteration.

class custome_itertor:
    def __iter__(self):
        self.o = ["a","b"]
        self.count = 0
        return self
    def __next__(self):
        if  self.count < len(self.o):
            x = self.o[self.count]
            self.count = self.count + 1
            return x
        else:
            raise StopIteration
# Thee object
myclass = custome_itertor()

# Get iterator object
myiter = iter(myclass)

# loop over 
for i in iter(myiter):
    print(i)

Generator function Link to heading

pep defines the generator function as functions with yield. it also describes gene

""" When a generator function is called, the actual arguments are bound to function-local formal argument names in the usual way, but no code in the body of the function is executed. Instead a generator-iterator object is returned; this conforms to the iterator protocol [6], so in particular can be used in for-loops in a natural way. Note that when the intent is clear from context, the unqualified name “generator” may be used to refer either to a generator-function or a generator-iterator. """

In the example, the call to function returns iterator object which we can call next on it. in the first call, function yields to caller and returns 0. and on the second call, the second print is executed.

def gen():
    x = 0
    print("Before first yield")
    yield x

    x = 1
    print("Before sencond yield")
    yield x


itero = gen()

print("calling 1st yield")
print(next(itero))
print("calling 2nd yield")
print(next(itero))

Iteration with Generator function Link to heading

Now, that iter and generator are explained. we can combine them to write simpler iter-able class. the iter is a generator function that returns iterator object on the first call and elements from the list on every next() call.

so, the class object can be used in for or any place iterator object can be used.

class iter_class:
    def __init__(self):
        self.arr= [1,2,3]

    def __iter__(self):
        for x in self.arr:
            yield x


ic = iter_class()
for  i in ic:
    print(i)