Functions

Functions#

A function in Python is a reusable block of code that performs a specific task. It can be executed with different sets of arguments, allowing for code abstraction and modularity by encapsulating operations into a single, callable unit.

Parameters#

A named entity in a function (or method) definition that specifies an argument (or in some cases, arguments) that the function can accept.

Find out more:

There are such types of parameters in python:

Name

Description

Syntax

Positional-only

Parameters that can be specified only positionally.

Parameters before the symbol /

Positional-or-keyword

Can be specified positionally as well as through keyword arguments.

Default parameters of the function

Var-positional

Parameter that takes values of all positional arguments that don’t correspond to the positional-only or positional-or-keyword parameters.

Parameter name begins with the * symbol; typical option is *args

Keyword-only

Can be specified only through keyword arguments.

Parameters that follow the Var-positional argument or just *

Var-keyword

Parameter that takes values of all keyword arguments that don’t correspond to the positional-or-keyword or keyword-only parameters.

Parameter name begins with **; typical option is **kwargs

You can define default values for parameters just by using syntax <parameter>=<default value>. But of you have defined default values for positional-only or for positional-or-keyword parameter all following parameters of these groups should have default values.

The following cell shows the definition of a function that contains all types of parameters, with default values defined for some of them, arranged in a way that forms a valid Python expression.

def some_function(
    positional_only1,
    positional_only2,
    /,
    positional1,
    positional2=None,
    *args,
    keyword_only1=None,
    keyword_only2,
    **kwargs 
):
    pass

Built in functions#

Python includes a set of built-in functions that are available directly in the interpreter without requiring any imports. This section provides an overview of these functions.

Sorted#

Function for sorting in python. Which takes an object and returns a new object with the elements sorted. You can pass any sortable object, such as a list, and receive the sorted result.

The following cell demonstrates how to sort a Python list.

sorted([8, 2, 3, 1, 4, 2])

[1, 2, 2, 3, 4, 8]

Key argument#

The key argument allows you to specify a callable that, for each element of the original array, returns a value used to determine the order of the elements during sorting.

Consider the list [4, 5, 7, 12, 15]. If we want to treat odd numbers as halves when sorting, the code to achieve this is shown below:

ans = [4, 5, 7, 12, 15]
sorted(ans, key=lambda x: (x/2 if x%2 else x))

[5, 7, 4, 15, 12]

Consider the following example: for each element of the original array, if the number is odd, it is transformed to half of its value; if it is even, it remains unchanged. For the list [4, 5, 7, 12, 15], this results in the pairs: 4 → 4, 5 → 2.5, 7 → 3.5, 12 → 12, and 15 → 7.5. Sorting based on these transformed values gives the order: 5 → 2.5, 7 → 3.5, 4 → 4, 15 → 7.5, and 12 → 12, which corresponds to the original list order of [5, 7, 4, 15, 12].

One useful example is sorting dictionary keys based on their corresponding values. By passing a function that retrieves the value for each key, you can obtain a list of keys sorted according to their values.

sort_dict = {
    "mazda": 32,
    "audi": 50,
    "mercedes": 43,
    "bmw": 38,
    "toyota": 45,
    "ford": 29
}
sorted(sort_dict, key=lambda key: sort_dict[key])

['ford', 'mazda', 'bmw', 'mercedes', 'toyota', 'audi']
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