Python Functions

The fundamentals of Python functions, including what they are, their syntax, their primary parts, return keywords, and major types, will be covered in this tutorial. Additionally, we'll examine several instances of Python function definitions.

What are Python Functions?

A function is a collection of related assertions that performs a mathematical, analytical, or evaluative operation. A collection of statements called Python Functions returns the particular task. Python functions are simple to define and essential to intermediate-level programming. The exact criteria hold to function names as they do to variable names. The goal is to group up certain often performed actions and define a function. We may call the function and reuse the code contained within it with different variables rather than repeatedly creating the same code block for different input variables.

User-defined and built-in functions are the two main categories of functions in Python. It helps maintain the programme concise, unique, and well-structured.

Advantages of Functions in Python

Python functions have the following Perks.

• By including functions, we can prevent repeating the same code block repeatedly in a program.
• Python functions, once defined, can be called many times and from anywhere in a program.
• If our Python program is large, it can be separated into numerous functions which is simple to track.
• The key accomplishment of Python functions is we can return as many outputs as we want with different arguments.

However, calling functions has always been overhead in a Python program.

Syntax of Python Function

The following elements make up to define a function, as seen above.

• The beginning of a function header is indicated by a keyword called def.
• function_name is the function's name that we can use to separate it from others. We will use this name to call the function later in the program. In Python, name functions must follow the same rules as naming variables.
• We pass arguments to the defined function using parameters. However, they are optional.
• The function header is terminated by a colon (:).
• We can use a documentation string called docstring in the short form to explain the purpose of the function.
• The body of the function is made up of several valid Python statements. The indentation depth of the whole code block must be the same (usually 4 spaces).
• We can use a return expression to return a value from a defined function.

Example of a User-Defined Function

We will define a function that when called will return the square of the number passed to it as an argument.

Code

Output:

The square of the given number is:  36

Calling a Function

A function is defined by using the def keyword and giving it a name, specifying the arguments that must be passed to the function, and structuring the code block.

After a function's fundamental framework is complete, we can call it from anywhere in the program. The following is an example of how to use the a_function function.

Code

Output:

Length of the string Functions is:  9
Length of the string Python is:  6

Pass by Reference vs. Pass by Value

All parameters in the Python programming language are provided by reference. It indicates that if we alter the value of an argument inside of a function, the calling function will likewise reflect the change. For example,

Code

Output:

Squares of the list are:  [289, 2704, 64]

Function Arguments

The following are the types of arguments that we can use to call a function:

1. Default arguments
2. Keyword arguments
3. Required arguments
4. Variable-length arguments

1) Default Arguments

A default argument is a kind of parameter that takes as input a default value if no value is supplied for the argument when the function is called. Default arguments are demonstrated in the following instance.

Code

Output:

Passing only one argument
number 1 is:  30
number 2 is:  20
Passing two arguments
number 1 is:  50
number 2 is:  30

2) Keyword Arguments

A function called's arguments are linked to keyword arguments. When invoking a function with keyword arguments, the user may tell whose parameter value it is by looking at the parameter label.

We can remove certain arguments or arrange them in a different order since the Python interpreter will connect the provided keywords to link the values with its parameters. Another way to use keywords to invoke the function() method is as follows:

Code

Output:

Without using keyword
number 1 is:  50
number 2 is:  30
With using keyword
number 1 is:  30
number 2 is:  50

3) Required Arguments

The arguments given to a function while calling in a pre-defined positional sequence are required arguments. The count of required arguments in the method call must be equal to the count of arguments provided while defining the function.

We must send two arguments to the function function() in the correct order, or it will return a syntax error, as seen below.

Code

Output:

Passing out of order arguments
number 1 is:  30
number 2 is:  20
Passing only one argument
Function needs two positional arguments

4) Variable-Length Arguments

We can use special characters in Python functions to pass as many arguments as we want in a function. There are two types of characters that we can use for this purpose:

1. *args -These are Non-Keyword Arguments
2. **kwargs -These are Keyword Arguments.

Here is an example to clarify Variable length arguments

Code

Output:

['PYTHON', 'FUNCTIONS', 'TUTORIAL']
[['First', 'Python'], ['Second', 'Functions'], ['Third', 'Tutorial']]

return Statement

We write a return statement in a function to leave a function and give the calculated value when a defined function is called.

Syntax:

The return statement, which is supplied as output when a particular job or function is finished, might take the form of an argument, a statement, or a value. A declared function will return a None object if no return statement is written.

Here is an example of a return statement in Python functions.

Code

Output:

With return statement
2704
Without return statement
None

The Anonymous Functions

These types of Python functions are anonymous since we do not declare them, as we declare usual functions, using the def keyword. We can use the lambda keyword to define the short, single output, anonymous functions.

Lambda expressions can accept an unlimited number of arguments; however, they only return one value as the result of the function. They can't have numerous expressions or instructions in them. Since lambda needs an expression, an anonymous function cannot be directly called to print.

Lambda functions contain their unique local domain, meaning they can only reference variables in their argument list and the global domain name.

Although lambda expressions seem to be a one-line representation of a function, they are not like inline expressions in C and C++, which pass function stack allocations at execution for efficiency concerns.

Syntax

Lambda functions have exactly one line in their syntax:

Below is an illustration of how to use the lambda function:

Code

Output:

Value of the function is :  50
Value of the function is :  90

Scope and Lifetime of Variables

The scope of a variable refers to the domain of a program wherever it is declared. A function's arguments and variables are not accessible outside the defined function. As a result, they only have a local domain.

The lifespan of a variable in RAM is how long it stays there. A function's lifespan is the same as that of its internal variables. They are taken away after we exit the function. Consequently, a function does not keep the value of a variable from previous executions.

Here's a simple example of a variable's scope within a function.

Code

Output:

Value of num inside the function:  50
Value of num outside the function: 10

Here, we can see that num starts out with a value of 10. The value of num outside of the function remained intact, even though the function number() changed the value of num to 50.

This is due to the fact that the function's internal variable num is different from the external variable (local to the function). Despite having the same variable name, they are two separate variables with separate scopes.

Variables beyond the function, on the contrary, are accessible within the function. These variables have a global reach. We can retrieve their values inside the function but cannot alter or change them. If we declare a variable global using the keyword global, we can also change the variable's value outside the function.

Python Function within Another Function

Functions are considered first-class objects in Python. In a programming language, first-class objects are treated the same wherever they are used. They can be used in conditional expressions, as arguments, and saved in built-in data structures. A programming language is considered to implement first-class functions if it treats functions as first-class objects. The concept of First Class functions is supported by Python.

Inner or nested function refers to a function defined within another defined function. Inner functions can access the parameters of the outer scope. Inner functions are constructed to cover them from the changes that happen outside the function. Many developers regard this process as encapsulation.

Code

Output:

Python functions tutorial
5