Iterators & Generators

Iterators & Generators

Definitions

-   Lazy evaluation : delays evaluation of an expression until its value is needed

-   Iterable : an ovject capable of returning its members one at a time. examples include all sequences ( string, list )and some non-sequence types ( dictionaries )

-   Iterator : an object that provide sequenctial access to values, one by one

 ( all iterators are iterables. not all iterables are iterators. )

-   Metaphor : iterables are books & iterators are bookmarks

Iterators

How do we create iterators ?

iter ( iterable ) : return an iterator over the elements of an iterable values

- this method creates a bookmark from a book starting at the front

next ( iterator ) : return the nect element in an iterator

- returns the current page and moves the bookmark to the next page

- the iterator remembers when you left off. If the current apge is the end of the book, error

Check your understanding : Fibonacci

Define a function that returns an iterator that outputs up to the nth value in the Fibonacci sequence. You can assume n will always be 2 or greater

( remember, iter ( iterable ) creates an iterator. Lists are iterables )

def fib_iter(n):

   prev, curr = 0, 1

   list = [prev, curr]

   index = 2

   while index < n :

      print(prev, curr)

      prev, curr = curr, prev + curr

      list += [curr]

      index += 1

   print(list)

   return iter(list) 

Exceptions / Errors

: sometimes, computer programs behave in non-standard ways

Raise Exceptions

: exceptions are raised with a raise statement

raise < expression >

< expression > must be exceptions

Back to Iterators _ The FOR statement

1. evaluate the header <expression>, which must evaluate to an iterable object.

2. for each element in that sequence, in order:

 a. bind <name> to that element in the first frame of the current environment

 b. execute the <suite>

Generators

generator : an iterator created automatically by calling a generator function

generator function : a function that contains the keyword yield anywhre in the body

when a geneartor function is called, it returns a generator instead of going into the body of the function. The only way to go into the body of a generator function is by calling next on the returned generator

Generators and Generator functions

- we are allowed to call next on generators because generators are a type of iterator

- calling next on a generator goes into the function and evaluates to the first yield statement. the next time we call next on that generator, it resumes where it left off ( just like calling next on any iterator )

- once the generator hits a return statement, it raises a StopIteration

Generators can Yield from Iterators

: a yield from statement yields all values from an iterable