Which loop to select when we know the number of iteration write their program

Numeric Range Loop

The most basic

for  in :
    

for i = 1 to 10
    

Here, the body of the loop is executed ten times. The variable

for  in :
    

for  in :
    

for  in :
    

for  in :
    

Three-Expression Loop

Another form of

for  in :
    

• An initialization
• An expression specifying an ending condition
• An action to be performed at the end of each iteration.

This type of loop has the following form:

for [i = 1; i >> a = ['foo', 'bar', 'baz']
>>> for i in a:
...     print[i]
...
foo
bar
baz

for  in :
    

>>> a = ['foo', 'bar', 'baz']
>>> for i in a:
...     print[i]
...
foo
bar
baz

This loop is interpreted as follows:

• Initialize

  for  in :
      
  

  7 to

  for  in :
      
  

  8.
• Continue looping as long as

  >>> a = ['foo', 'bar', 'baz']
  >>> for i in a:
  ...     print[i]
  ...
  foo
  bar
  baz
  

  7.
• Increment

  for  in :
      
  

  7 by

  for  in :
      
  

  8 after each loop iteration.

Three-expression

for  in :
    

for  in :
    

Collection-Based or Iterator-Based Loop

This type of loop iterates over a collection of objects, rather than specifying numeric values or conditions:

for i in 
    

Each time through the loop, the variable

for  in :
    

>>> iter['foobar']                             # String


>>> iter[['foo', 'bar', 'baz']]                # List


>>> iter[['foo', 'bar', 'baz']]                # Tuple


>>> iter[{'foo', 'bar', 'baz'}]                # Set


>>> iter[{'foo': 1, 'bar': 2, 'baz': 3}]       # Dict

for  in :
    

>>> iter['foobar']                             # String


>>> iter[['foo', 'bar', 'baz']]                # List


>>> iter[['foo', 'bar', 'baz']]                # Tuple


>>> iter[{'foo', 'bar', 'baz'}]                # Set


>>> iter[{'foo': 1, 'bar': 2, 'baz': 3}]       # Dict

for  in :
    

Further Reading: See the For loop Wikipedia page for an in-depth look at the implementation of definite iteration across programming languages.

Iterables

In Python, iterable means an object can be used in iteration. The term is used as:

• An adjective: An object may be described as iterable.
• A noun: An object may be characterized as an iterable.

If an object is iterable, it can be passed to the built-in Python function

>>> a = ['foo', 'bar', 'baz']

>>> itr = iter[a]
>>> itr


>>> next[itr]
'foo'
>>> next[itr]
'bar'
>>> next[itr]
'baz'

Each of the objects in the following example is an iterable and returns some type of iterator when passed to

>>> a = ['foo', 'bar', 'baz']

>>> itr = iter[a]
>>> itr


>>> next[itr]
'foo'
>>> next[itr]
'bar'
>>> next[itr]
'baz'

>>>

>>> iter['foobar']                             # String


>>> iter[['foo', 'bar', 'baz']]                # List


>>> iter[['foo', 'bar', 'baz']]                # Tuple


>>> iter[{'foo', 'bar', 'baz'}]                # Set


>>> iter[{'foo': 1, 'bar': 2, 'baz': 3}]       # Dict

These object types, on the other hand, aren’t iterable:

>>>

>>> iter[42]                                   # Integer
Traceback [most recent call last]:
  File "", line 1, in 
    iter[42]
TypeError: 'int' object is not iterable

>>> iter[3.1]                                  # Float
Traceback [most recent call last]:
  File "", line 1, in 
    iter[3.1]
TypeError: 'float' object is not iterable

>>> iter[len]                                  # Built-in function
Traceback [most recent call last]:
  File "", line 1, in 
    iter[len]
TypeError: 'builtin_function_or_method' object is not iterable

All the data types you have encountered so far that are collection or container types are iterable. These include the string, list, tuple, dict, set, and frozenset types.

But these are by no means the only types that you can iterate over. Many objects that are built into Python or defined in modules are designed to be iterable. For example, open files in Python are iterable. As you will see soon in the tutorial on file I/O, iterating over an open file object reads data from the file.

In fact, almost any object in Python can be made iterable. Even user-defined objects can be designed in such a way that they can be iterated over. [You will find out how that is done in the upcoming article on object-oriented programming.]

Iterators

Okay, now you know what it means for an object to be iterable, and you know how to use

>>> a = ['foo', 'bar', 'baz']

>>> itr = iter[a]
>>> itr


>>> next[itr]
'foo'
>>> next[itr]
'bar'
>>> next[itr]
'baz'

An iterator is essentially a value producer that yields successive values from its associated iterable object. The built-in function

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

Here is an example using the same list as above:

>>>

>>> a = ['foo', 'bar', 'baz']

>>> itr = iter[a]
>>> itr


>>> next[itr]
'foo'
>>> next[itr]
'bar'
>>> next[itr]
'baz'

In this example,

>>> iter[42]                                   # Integer
Traceback [most recent call last]:
  File "", line 1, in 
    iter[42]
TypeError: 'int' object is not iterable

>>> iter[3.1]                                  # Float
Traceback [most recent call last]:
  File "", line 1, in 
    iter[3.1]
TypeError: 'float' object is not iterable

>>> iter[len]                                  # Built-in function
Traceback [most recent call last]:
  File "", line 1, in 
    iter[len]
TypeError: 'builtin_function_or_method' object is not iterable

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

>>> a = ['foo', 'bar', 'baz']

>>> itr = iter[a]
>>> itr


>>> next[itr]
'foo'
>>> next[itr]
'bar'
>>> next[itr]
'baz'

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

Notice how an iterator retains its state internally. It knows which values have been obtained already, so when you call

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

What happens when the iterator runs out of values? Let’s make one more

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

>>>

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

If all the values from an iterator have been returned already, a subsequent

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

You can only obtain values from an iterator in one direction. You can’t go backward. There is no

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

>>>

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

Even when iterator

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

If you want to grab all the values from an iterator at once, you can use the built-in

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

>>>

for [i = 1; i >> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

>>>

for [i = 1; i >> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

When you use

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

>>> a
['foo', 'bar', 'baz']

>>> itr1 = iter[a]
>>> itr2 = iter[a]

>>> next[itr1]
'foo'
>>> next[itr1]
'bar'
>>> next[itr1]
'baz'

>>> next[itr2]
'foo'

In fact, it is possible to create an iterator in Python that returns an endless series of objects using generator functions and

for [i = 1; i >> a = ['foo', 'bar', 'baz']

>>> itr = iter[a]
>>> itr


>>> next[itr]
'foo'
>>> next[itr]
'bar'
>>> next[itr]
'baz'

Now, consider again the simple

for  in :
    

>>>

>>> a = ['foo', 'bar', 'baz']
>>> for i in a:
...     print[i]
...
foo
bar
baz

This loop can be described entirely in terms of the concepts you have just learned about. To carry out the iteration this

for  in :
    

• Calls

  >>> a = ['foo', 'bar', 'baz']
  
  >>> itr = iter[a]
  >>> itr
  
  
  >>> next[itr]
  'foo'
  >>> next[itr]
  'bar'
  >>> next[itr]
  'baz'
  

  7 to obtain an iterator for

  >>> iter[42]                                   # Integer
  Traceback [most recent call last]:
    File "", line 1, in 
      iter[42]
  TypeError: 'int' object is not iterable
  
  >>> iter[3.1]                                  # Float
  Traceback [most recent call last]:
    File "", line 1, in 
      iter[3.1]
  TypeError: 'float' object is not iterable
  
  >>> iter[len]                                  # Built-in function
  Traceback [most recent call last]:
    File "", line 1, in 
      iter[len]
  TypeError: 'builtin_function_or_method' object is not iterable
  

  6
• Calls

  >>> next[itr]
  Traceback [most recent call last]:
    File "", line 1, in 
      next[itr]
  StopIteration
  

  0 repeatedly to obtain each item from the iterator in turn
• Terminates the loop when

  >>> next[itr]
  Traceback [most recent call last]:
    File "", line 1, in 
      next[itr]
  StopIteration
  

  0 raises the

  >>> next[itr]
  Traceback [most recent call last]:
    File "", line 1, in 
      next[itr]
  StopIteration
  

  9 exception

The loop body is executed once for each item

>>> next[itr]
Traceback [most recent call last]:
  File "", line 1, in 
    next[itr]
StopIteration

for  in :
    

This sequence of events is summarized in the following diagram:

Perhaps this seems like a lot of unnecessary monkey business, but the benefit is substantial. Python treats looping over all iterables in exactly this way, and in Python, iterables and iterators abound:

• Many built-in and library objects are iterable.

• There is a Standard Library module called

  for [i = 1; i >> a = ['foo', 'bar', 'baz']
  
  >>> itr = iter[a]
  >>> itr
  
  
  >>> next[itr]
  'foo'
  >>> next[itr]
  'bar'
  >>> next[itr]
  'baz'
  

  7, so you know dictionaries must be iterable. What happens when you loop through a dictionary? Let’s see:

  >>>

  for [i = 1; i >>
  for [i = 1; i >
  for [i = 1; i >>
  for [i = 1; i >
  for [i = 1; i >>
  for [i = 1; i  a
  ['foo', 'bar', 'baz']
  
  >>> itr1 = iter[a]
  >>> itr2 = iter[a]
  
  >>> next[itr1]
  'foo'
  >>> next[itr1]
  'bar'
  >>> next[itr1]
  'baz'
  
  >>> next[itr2]
  'foo'
  3 or 
  >>> a
  ['foo', 'bar', 'baz']
  
  >>> itr1 = iter[a]
  >>> itr2 = iter[a]
  
  >>> next[itr1]
  'foo'
  >>> next[itr1]
  'bar'
  >>> next[itr1]
  'baz'
  
  >>> next[itr2]
  'foo'
  5. In a REPL session, that can be a convenient way to quickly display what the values are:
  >>>
  for i in 
      
  2
  However, when 
  for [i = 1; i >> a
  ['foo', 'bar', 'baz']
  
  >>> itr1 = iter[a]
  >>> itr2 = iter[a]
  
  >>> next[itr1]
  'foo'
  >>> next[itr1]
  'bar'
  >>> next[itr1]
  'baz'
  
  >>> next[itr2]
  'foo'
  3 or 
  >>> a
  ['foo', 'bar', 'baz']
  
  >>> itr1 = iter[a]
  >>> itr2 = iter[a]
  
  >>> next[itr1]
  'foo'
  >>> next[itr1]
  'bar'
  >>> next[itr1]
  'baz'
  
  >>> next[itr2]
  'foo'
  5 in this way. Like iterators, 
  for [i = 1; i >> a
  ['foo', 'bar', 'baz']
  
  >>> itr1 = iter[a]
  >>> itr2 = iter[a]
  
  >>> next[itr1]
  'foo'
  >>> next[itr1]
  'bar'
  >>> next[itr1]
  'baz'
  
  >>> next[itr2]
  'foo'
  3 or 
  >>> a
  ['foo', 'bar', 'baz']
  
  >>> itr1 = iter[a]
  >>> itr2 = iter[a]
  
  >>> next[itr1]
  'foo'
  >>> next[itr1]
  'bar'
  >>> next[itr1]
  'baz'
  
  >>> next[itr2]
  'foo'
  5 on a 
  for [i = 1; i 
  for i in 
      
  4
  All the parameters specified to 
  for [i = 1; i