# Python Map, Filter, and Reduce

Python provides several functional programming tools that allow you to process data efficiently. Three of the most common are `map()`, `filter()`, and `reduce()`.

## `map()`

The `map()` function applies a given function to each item of an iterable (list, tuple, etc.) and returns a map object (which is an iterator).

### Syntax

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

### Example

```python
def square(n):
    return n * n

numbers = [1, 2, 3, 4]
result = map(square, numbers)
print(list(result)) # Output: [1, 4, 9, 16]
```

## `filter()`

The `filter()` function filters elements from an iterable based on a function that returns True or False.

### Syntax

```python
filter(function, iterable)
```

### Example

```python
def check_even(n):
    return n % 2 == 0

numbers = [1, 2, 3, 4, 5, 6]
result = filter(check_even, numbers)
print(list(result)) # Output: [2, 4, 6]
```

## `reduce()`

The `reduce()` function applies a rolling computation to sequential pairs of values in a list. It is defined in the `functools` module.

### Example

```python
from functools import reduce

numbers = [1, 2, 3, 4]
result = reduce(lambda x, y: x + y, numbers)
print(result) # Output: 10
```

[[programming/python/python]]