Skip to content

Latest commit

 

History

History
75 lines (39 loc) · 2.75 KB

iterator_generator.md

File metadata and controls

75 lines (39 loc) · 2.75 KB
Raw

Iterators

Iterator is an object which allows a programmer to traverse through all the elements of a collection, regardless of its specific implementation. Iterators provide a sequence interface to Python objects that’s memory efficient and considered Pythonic.

  • Iterators are objects that contain countable values(but not finite).
  • An interator is an object that can be iterated upon.
  • Iterators must implement the iterator protocols, namely the methods __iter__() and __next__()

Iterators have several advantages:

  • Cleaner code
  • Iterators can work with infinite sequences
  • Iterators save resources
    • when working with iterators, we can get the next element in a sequence without keeping the entire dataset in memory(example reading files with open).

Iterators vs Iterable

Lists, tuples, dictionaries, sets, strings are all iterable objects. They are iterable containers which you can get an iterator from.

  • iter() method takes an iterable and returns an iterator. Iterable objects call the method iter() in them.
mytuple = ("apple", "banana", "cherry")
myit = iter(mytuple)

# If there are no more elements on using next() a StopIteration Exception is raised. The StopIteration exception will cease the for loop and in user defined iterators within [next](http://zetcode.com/lang/python/itergener/).

print(next(myit))
print(next(myit))
print(next(myit))
  • To create a User Defined iterator. Look at example here

Generators

Generators simplifies creation of iterators and are special routines which return iterators.

  • Are defined with the def keyword just like functions
  • Use the yield keyword
  • May use several yield keywords

Example.

The yield keyword exits the generator and returns a value. To reach the first and successive yield lines one has to use the next function. When there is nothing left to yield, a StopIteration exception is raised.

Generator Expressions

Generator expression is similar to a list comprehension. The difference is that a generator expression returns a generator, not a list and used () instead of [] as outer most braces.

n = (e for e in range(50000000) if not e % 3)

Creating a list comprehension in this case would be very inefficient because the example would occupy a lot of memory unnecessarily. Insted of this, we create a generator expression, which generates values lazily on demand.

Itertools

The itertools module in the standard library provides lot of intersting tools to work with iterators.

  • itertools.chain() : to chain multiple iterators, i.e. append one after the other.
  • izip : iterable version of zip