# Python – codewindow.in

## Python Programing

#### The syntax of a list comprehension in Python looks like this:

``````new_list = [expression for item in iterable if condition]
``````

#### For example, suppose you have a list of integers and you want to create a new list containing only the even numbers from the original list. You could use a list comprehension like this:

``````original_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
new_list = [x for x in original_list if x % 2 == 0]
``````

#### The general syntax of a list comprehension in Python is as follows:

``````new_list = [expression for item in iterable if condition]
``````

#### Example 1: Squaring elements of a list using a list comprehension

``````original_list = [1, 2, 3, 4, 5]
squared_list = [x**2 for x in original_list]
print(squared_list)
``````

#### Output:

``````[1, 4, 9, 16, 25]
``````

#### Example 2: Filtering odd numbers from a list using a list comprehension

``````original_list = [1, 2, 3, 4, 5]
even_list = [x for x in original_list if x % 2 == 0]
print(even_list)
``````

#### Output:

``````[2, 4]
``````

#### The basic syntax for a nested list comprehension is as follows:

``````new_list = [[expression for item in iterable] for item in iterable]
``````

#### Example 1: Creating a matrix using nested list comprehensions

``````matrix = [[i + j for j in range(3)] for i in range(3)]
print(matrix)
``````

#### Output:

``````[[0, 1, 2], [1, 2, 3], [2, 3, 4]]
``````

#### Example 2: Flattening a nested list using nested list comprehensions

``````nested_list = [[1, 2], [3, 4], [5, 6]]
flat_list = [item for sublist in nested_list for item in sublist]
print(flat_list)
``````

#### Output:

``````[1, 2, 3, 4, 5, 6]
``````

#### The `map()` function in Python is used to apply a given function to each item of an iterable (such as a list) and return a new iterable with the transformed values. The basic syntax of the `map()` function is as follows:

``````map(function, iterable)
``````

#### One common use of `map()` is in conjunction with list comprehensions to create a new list with the transformed values. Here’s an example:

``````numbers = [1, 2, 3, 4, 5]
squares = list(map(lambda x: x**2, numbers))
print(squares)
``````

#### Output:

``````[1, 4, 9, 16, 25]
``````

#### The basic syntax for creating a generator expression is similar to that of a list comprehension, but with parentheses instead of square brackets:

``````(expression for item in iterable)
``````

#### Here, `expression` is the value to be generated for each item in the iterable, and `item` is the current item in the iterable. Like list comprehensions, generator expressions can also include conditional statements to filter the values to be generated:

``````(expression for item in iterable if condition)
``````

#### Once a generator expression has been defined, it can be used in a for loop just like any other iterable object, such as a list or tuple:

``````gen_expr = (x**2 for x in range(10) if x % 2 == 0)
for val in gen_expr:
print(val)
``````

#### Output:

``````0
4
16
36
64
``````

#### 1. Using `count()`:

``````from itertools import count

for i in count(1, 2):
print(i)
if i > 10:
break
``````

#### 2. Using `cycle()`:

``````from itertools import cycle

colors = ['red', 'green', 'blue']

for color in cycle(colors):
print(color)
if color == 'blue':
break
``````

#### 3. Using `repeat()`:

``````from itertools import repeat

for i in repeat('hello', 3):
print(i)
``````

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