# Python – codewindow.in

## Related Topics ## 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)
``````

#### Overall, `itertools` functions can be very useful for generating and manipulating sequences in Python, and can often be combined with other language constructs (like for loops or list comprehensions) to accomplish complex tasks efficiently and elegantly. #### Top Company Questions  #### Automata Fixing And More  ## We Loveto Support you

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