Python 3 - Loops

In general, statements are executed sequentially − The first statement in a function is executed first, followed by the second, and so on. There may be a situation when you need to execute a block of code several number of times.

Programming languages provide various control structures that allow more comppcated execution paths.

A loop statement allows us to execute a statement or group of statements multiple times. The following diagram illustrates a loop statement −

Python programming language provides the following types of loops to handle looping requirements.

Loop Control Statements

The Loop control statements change the execution from its normal sequence. When the execution leaves a scope, all automatic objects that were created in that scope are destroyed.

Python supports the following control statements.

Let us go through the loop control statements briefly.

Iterator and Generator

Iterator is an object which allows a programmer to traverse through all the elements of a collection, regardless of its specific implementation. In Python, an iterator object implements two methods, iter() and next().

String, List or Tuple objects can be used to create an Iterator.

#!/usr/bin/python3
import sys

pst = [1,2,3,4]
it = iter(pst) # this builds an iterator object
print (next(it)) #prints next available element in iterator
#Iterator object can be traversed using regular for statement
for x in it:
   print (x, end=" ")
#or using next() function
while True:
   try:
      print (next(it))
   except StopIteration:
      sys.exit()

A generator is a function that produces or yields a sequence of values using yield method.

When a generator function is called, it returns a generator object without even beginning execution of the function. When the next() method is called for the first time, the function starts executing until it reaches the yield statement, which returns the yielded value. The yield keeps track i.e. remembers the last execution and the second next() call continues from previous value.

Example

The following example defines a generator, which generates an iterator for all the Fibonacci numbers.

#!usr/bin/python3

import sys
def fibonacci(n): #generator function
   a, b, counter = 0, 1, 0
   while True:
      if (counter > n): 
         return
      yield a
      a, b = b, a + b
      counter += 1
f = fibonacci(5) #f is iterator object

while True:
   try:
      print (next(f), end=" ")
   except StopIteration:
      sys.exit()