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# List Comprehension
Creating lists concisely and expressively is what list comprehension in Python does. You can generate lists from already existing iterables like lists, tuples or strings with a short form.
This boosts the readability of code and reduces necessity of using explicit looping constructs.
## Syntax :
### Basic syntax
```python
new_list = [expression for item in iterable]
```
- **new_list**: This is the name given to the list that will be created using the list comprehension.
- **expression**: This is the expression that defines how each element of the new list will be generated or transformed.
- **item**: This variable represents each individual element from the iterable. It takes on the value of each element in the iterable during each iteration.
- **iterable**: This is the sequence-like object over which the iteration will take place. It provides the elements that will be processed by the expression.
This list comprehension syntax `[expression for item in iterable]` allows you to generate a new list by applying a specific expression to each element in an iterable.
### Syntax including condition
```python
new_list = [expression for item in iterable if condition]
```
- **new_list**: This is the name given to the list that will be created using the list comprehension.
- **expression**: This is the expression that defines how each element of the new list will be generated or transformed.
- **item**: This variable represents each individual element from the iterable. It takes on the value of each element in the iterable during each iteration.
- **iterable**: This is the sequence-like object over which the iteration will take place. It provides the elements that will be processed by the expression.
- **if condition**: This is an optional part of the syntax. It allows for conditional filtering of elements from the iterable. Only items that satisfy the condition
will be included in the new list.
## Examples:
1. Generating a list of squares of numbers from 1 to 5:
```python
squares = [x ** 2 for x in range(1, 6)]
print(squares)
```
- **Output** :
```python
[1, 4, 9, 16, 25]
```
2. Filtering even numbers from a list:
```python
nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even = [x for x in nums if x % 2 == 0]
print(even)
```
- **Output** :
```python
[2, 4, 6, 8, 10]
```
3. Flattening a list of lists:
```python
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flat = [x for sublist in matrix for x in sublist]
print(flat)
```
- **Output** :
```python
[1, 2, 3, 4, 5, 6, 7, 8, 9]
```
List comprehension is a powerful feature in Python for creating lists based on existing iterables with a concise syntax.
By mastering list comprehension, developers can write cleaner, more expressive code and leverage Python's functional programming capabilities effectively.