# 11.10. Functional Filter

• filter(callable, *iterables)

• Select elements from sequence

• Generator (lazy evaluated)

• required callable - Function

• required iterables - 1 or many sequence or iterator objects

The filter function in Python is a built-in function that allows you to filter out elements from a given iterable based on a specified condition. It takes two arguments: a function that returns a Boolean value and an iterable (such as a list, tuple, or set) that you want to filter.

The function is applied to each element in the iterable, and only those elements for which the function returns True are included in the result. The filtered elements are returned as an iterator, which can be converted to a list or other iterable if desired.

Here's an example of using the filter function to filter out even numbers from a list:

>>> data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>>
>>> def is_odd(n):
...     return n % 2 != 0
>>>
>>> result = filter(is_odd, data)
>>> list(result)
[1, 3, 5, 7, 9]


In this example, the is_odd function returns True for odd numbers and False for even numbers. The filter function is used to apply this function to each element in the numbers list and return only those elements for which is_odd returns True. The resulting list contains only the odd numbers from the original list.

>>> def even(x):
...     return x % 2 == 0
>>>
>>> result = (x for x in range(0,5) if even(x))
>>> result = filter(even, range(0,5))
>>>
>>> result = (x for x in range(0,5) if x%2==0)
>>> result = filter(lambda x: x%2==0, range(0,5))

>>> from inspect import isgeneratorfunction, isgenerator
>>>
>>>
>>> def even(x):
...     return x % 2 == 0
>>>
>>>
>>> isgeneratorfunction(filter)
False
>>>
>>> result = filter(even, [1,2,3])
>>> isgenerator(result)
False


## 11.10.1. Problem

Plain code:

>>> def even(x):
...     return x % 2 == 0
>>>
>>>
>>> DATA = [1, 2, 3, 4, 5, 6]
>>> result = []
>>>
>>> for x in DATA:
...     if even(x):
...         result.append(x)
>>>
>>> print(result)
[2, 4, 6]


Comprehension:

>>> def even(x):
...     return x % 2 == 0
>>>
>>>
>>> DATA = [1, 2, 3, 4, 5, 6]
>>> result = [x for x in DATA if even(x)]
>>>
>>> print(result)
[2, 4, 6]


## 11.10.2. Solution

>>> def even(x):
...     return x % 2 == 0
>>>
>>>
>>> DATA = [1, 2, 3, 4, 5, 6]
>>> result = filter(even, DATA)
>>>
>>> list(result)
[2, 4, 6]


## 11.10.3. Lazy Evaluation

>>> def even(x):
...     return x % 2 == 0
>>>
>>>
>>> DATA = [1, 2, 3, 4, 5, 6]
>>> result = filter(even, DATA)
>>>
>>> next(result)
2
>>> next(result)
4
>>> next(result)
6
>>> next(result)
Traceback (most recent call last):
StopIteration


## 11.10.4. Performance

>>> def even(x):
...     return x % 2 == 0
>>>
>>>
>>> data = [1, 2, 3, 4, 5, 6]

>>>
... %%timeit -r 1000 -n 1000
... result = [x for x in data if even(x)]
1.11 µs ± 139 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)

>>>
... %%timeit -r 1000 -n 1000
... result = list(filter(even, data))
921 ns ± 112 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)


## 11.10.5. Use Case - 0x01

>>> users = [
... ]

>>> def above40(person):
...     return person['age'] >= 40
>>>
>>> def under40(person):
...     return person['age'] < 40

>>> result = filter(above40, users)
>>> list(result)

>>> result = filter(under40, users)
>>> list(result)


## 11.10.6. Use Case - 0x02

>>> users = [
... ]
>>>
>>>
...     return user['is_staff']
>>>
>>>
>>> list(staff)


## 11.10.7. Use Case - 0x03

>>> users = [
...     'mwatney',
...     'mlewis',
...     'rmartinez',
...     'avogel',
...     'bjohanssen',
...     'cbeck',
... ]
>>>
>>> staff = [
...     'mwatney',
...     'mlewis',
...     'ptwardowski',
...     'jjimenez',
... ]
>>>
>>>