# 3.4. FuncProg Pure Functions¶

• Pure functions have no side effects (i.e. memory, state, I/O)

• Calling the pure function again with the same arguments returns the same result (this can enable caching optimizations such as memoization)

• If the result of a pure expression is not used, it can be removed without affecting other expressions

• If there is no data dependency between two pure expressions, their order can be reversed, or they can be performed in parallel and they cannot interfere with one another (the evaluation of any pure expression is thread-safe) 1

>>> def add(a, b):
...     return a + b


## 3.4.1. Pure Function¶

>>> def add(a, b):
...     return a + b
>>>
>>>
3
3
3


## 3.4.2. Impure Function¶

>>> def add(a, b):
...     return a + b + c
>>>
>>>
>>> c = 0
>>>
3
3
3
>>>
>>>
>>> c = 1
>>>
4
4
4


## 3.4.3. Impure to Pure Function¶

>>> def add(a, b, c):
...     return a + b + c
>>>
>>>
>>> c = 0
>>>
>>> add(1, 2, c)
3
>>> add(1, 2, c)
3
>>> add(1, 2, c)
3
>>>
>>>
>>> c = 1
>>>
>>> add(1, 2, c)
4
>>> add(1, 2, c)
4
>>> add(1, 2, c)
4


## 3.4.4. Side Effects¶

• I/O - Input Output

• Looks like a pure function

• File content can change by other process

>>> def read(filename):
...     with open(filename) as file:


Each of those variables can have different value as of the read() function depends on file content, which can be modified by other process in the meantime between reading a and reading b.

>>> a = read('myfile.txt')
>>> b = read('myfile.txt')


## 3.4.5. Use Case - 0x01¶

• Math Functions

• Mathematical functions are pure in general

>>> def add(a, b):
...     return a + b

>>> def odd(x):
...     return x % 2

>>> def cube(x):
...     return x ** 3


## 3.4.6. Use Case - 0x01¶

• Select

Pure:

>>> DATA = [
...     (5.8, 2.7, 5.1, 1.9, 'virginica'),
...     (5.1, 3.5, 1.4, 0.2, 'setosa'),
...     (5.7, 2.8, 4.1, 1.3, 'versicolor'),
...     (6.3, 2.9, 5.6, 1.8, 'virginica'),
...     (6.4, 3.2, 4.5, 1.5, 'versicolor'),
...     (4.7, 3.2, 1.3, 0.2, 'setosa')]
>>>
>>>
>>> def function(data, species):
...     result = []
...     for *features, label in data:
...         if label == species:
...             result.append(features)
...     return result


Impure:

>>> DATA = [
...     (5.8, 2.7, 5.1, 1.9, 'virginica'),
...     (5.1, 3.5, 1.4, 0.2, 'setosa'),
...     (5.7, 2.8, 4.1, 1.3, 'versicolor'),
...     (6.3, 2.9, 5.6, 1.8, 'virginica'),
...     (6.4, 3.2, 4.5, 1.5, 'versicolor'),
...     (4.7, 3.2, 1.3, 0.2, 'setosa')]
>>>
>>>
>>> def function(species):
...     result = []
...     for *features, label in DATA:
...         if label == species:
...             result.append(features)
...     return result


## 3.4.7. References¶

1

Functional programming. Retrieved: 2020-10-09. URL: https://en.wikipedia.org/wiki/Functional_programming