Python Global, Local and Nonlocal variables

Global Variables

In Python, a variable declared outside of the function or in global scope is known as a global variable. This means that a global variable can be accessed inside or outside of the function.

Let's see an example of how a global variable is created in Python.

Example 1: Create a Global Variable

x = "global"

def foo():
    print("x inside:", x)


foo()
print("x outside:", x)

x inside: global
x outside: global
In the above code, we created x as a global variable and defined a foo() to print the global variable x. Finally, we call the foo() which will print the value of x.
What if you want to change the value of x inside a function?
x = "global"

def foo():
    x = x * 2
    print(x)

foo(Output
UnboundLocalError: local variable 'x' referenced before assignment
The output shows an error because Python treats x as a local variable and x is also not defined inside foo().
To make this work, we use the global keyword. Visit Python Global Keyword to learn more.
Local Variables
A variable declared inside the function's body or in the local scope is known as a local variable.
Example 2: Accessing local variable outside the scope
def foo():
    y = "local"


foo()
print(y)
Output
NameError: name 'y' is not defined
The output shows an error because we are trying to access a local variable y in a global scope whereas the local variable only works inside foo() or local scope.
Let's see an example on how a local variable is created in Python.
Example 3: Create a Local Variable
Normally, we declare a variable inside the function to create a local variable.
def foo():
    y = "local"
    print(y)

foo()
Output
local
Let's take a look at the earlier problem where x was a global variable and we wanted to modify x inside foo().

Here, we will show how to use global variables and local variables in the same code.
Example 4: Using Global and Local variables in the same code

x = "global "

def foo():
    global x
    y = "local"
    x = x * 2
    print(x)
    print(y)

foo()

Python Anonymous/Lambda Function

What are lambda functions in Python?

In Python, an anonymous function is a function that is defined without a name.

While normal functions are defined using the def keyword in Python, anonymous functions are defined using the lambda keyword.

Hence, anonymous functions are also called lambda functions.

How to use lambda Functions in Python?

Syntax of Lambda Function in python

lambda arguments: expression

Lambda functions can have any number of arguments but only one expression. The expression is evaluated and returned. Lambda functions can be used wherever function objects are required.

---

Example of Lambda Function in python

Here is an example of lambda function that doubles the input value.

# Program to show the use of lambda functions
double = lambda x: x * 2

print(double(5)Output

10

In the above program, lambda x: x * 2 is the lambda function. Here x is the argument and x * 2 is the expression that gets evaluated and returned.
This function has no name. It returns a function object which is assigned to the identifier double. We can now call it as a normal function. The statement
double = lambda x: x * 2
is nearly the same as:
def double(x):
Use of Lambda Function in python

We use lambda functions when we require a nameless function for a short period of time.
In Python, we generally use it as an argument to a higher-order function (a function that takes in other functions as arguments). Lambda functions are used along with built-in functions like filter(), map() etc.
Example use with filter()
The filter() function in Python takes in a function and a list as arguments.
The function is called with all the items in the list and a new list is returned which contains items for which the function evaluates to True.
Here is an example use of filter() function to filter out only even numbers from a list.
# Program to filter out only the even items from a list
my_list = [1, 5, 4, 6, 8, 11, 3, 12]

new_list = list(filter(lambda x: (x%2 == 0) , my_list))

print(new_list)

Python Recursion

What is recursion?

Recursion is the process of defining something in terms of itself.

A physical world example would be to place two parallel mirrors facing each other. Any object in between them would be reflected recursively.

Python Recursive Function

In Python, we know that a function can call other functions. It is even possible for the function to call itself. These types of construct are termed as recursive functions.

The following image shows the working of a recursive function called recurse.

Recursive Function in Python

Following is an example of a recursive function to find the factorial of an integer.

Factorial of a number is the product of all the integers from 1 to that number. For example, the factorial of 6 (denoted as 6!) is 1*2*3*4*5*6 = 720.

Example of a recursive function

def factorial(x):
    """This is a recursive function
    to find the factorial of an integer"""

    if x == 1:
        return 1
    else:
        return (x * factorial(x-1))


num = 3
print("The factorial of", num, "is", factorial(num))

Output
The factorial of 3 is 6
In the above example, factorial() is a recursive function as it calls itself.
When we call this function with a positive integer, it will recursively call itself by decreasing the number.
Each function multiplies the number with the factorial of the number below it until it is equal to one. This recursive call can be explained in the following steps.
factorial(3)          # 1st call with 3
3 * factorial(2)      # 2nd call with 2
3 * 2 * factorial(1)  # 3rd call with 1
3 * 2 * 1             # return from 3rd call as number=1
3 * 2                 # return from 2nd call
6                     # return from 1st call
Let's look at an image that shows a step-by-step process of what is going on:
Working of a recursive factorial function
Our recursion ends when the number reduces to 1. This is called the base condition.
Every recursive function must have a base condition that stops the recursion or else the function calls itself infinitely.
The Python interpreter limits the depths of recursion to help avoid infinite recursions, resulting in stack overflows.
By default, the maximum depth of recursion is 1000. If the limit is crossed, it results in RecursionError. Let's look at one such condition.
def recursor():
    recursor()
recursor()

Disadvantages of Recursion
Sometimes the logic behind recursion is hard to follow through.
Recursive calls are expensive (inefficient) as they take up a lot of memory and time.
Recursive functions are hard to debug.
Output
Traceback (most recent call last):
  File "<string>", line 3, in <module>
  File "<string>", line 2, in a
  File "<string>", line 2, in a
  File "<string>", line 2, in a
  [Previous line repeated 996 more times]
RecursionError: maximum recursion depth exceeded
Advantages of Recursion
Recursive functions make the code look clean and elegant.
A complex task can be broken down into simpler sub-problems using recursion.
Sequence generation is easier with recursion than using some nested iteration.

Python Function Arguments

In Python, you can define a function that takes variable number of arguments. In this article, you will learn to define such functions using default, keyword and arbitrary arguments.

Arguments

In the user-defined function topic, we learned about defining a function and calling it. Otherwise, the function call will result in an error. Here is an example.

def greet(name, msg):
    """This function greets to
    the person with the provided message"""
    print("Hello", name + ', ' + msg)

greet("Monica", "Good morning!")

Output
Hello Monica, Good morning!
Here, the function greet() has two parameters.
Since we have called this function with two arguments, it runs smoothly and we do not get any error.
If we call it with a different number of arguments, the interpreter will show an error message. Below is a call to this function with one and no arguments along with their respective error messages.
>>> greet("Monica")    # only one argument
TypeError: greet() missing 1 required positional argument: 'msg'
>>> greet()    # no arguments
TypeError: greet() missing 2 required positional arguments: 'name' and 'msg'
Variable Function Arguments
Up until now, functions had a fixed number of arguments. In Python, there are other ways to define a function that can take variable number of arguments.
Three different forms of this type are described below.
Python Default Arguments
Function arguments can have default values in Python.
We can provide a default value to an argument by using the assignment operator (=). Here is an example.
def greet(name, msg="Good morning!"):
    """
    This function greets to
    the person with the
    provided message.

    If the message is not provided,
    it defaults to "Good
    morning!"
    """

    print("Hello", name + ', ' + msg)


greet("Kate")
greet("Bruce", "How do you do?")
Output
Hello Kate, Good morning!
Hello Bruce, How do you doIn this function, the parameter name 
does not have a default value and is required (mandatory) during a call.
On the other hand, the parameter msg has a default value of "Good morning!". So, it is optional during a call. If a value is provided, it will overwrite the default value.
Any number of arguments in a function can have a default value. But once we have a default argument, all the arguments to its right must also have default values.
This means to say, non-default arguments cannot follow default arguments. For example, if we had defined the function header above as:
def greet(msg = "Good morning!", name):
We would get an error as:
SyntaxError: non-default argument follows default argument

Python Keyword Arguments
When we call a function with some values, these values get assigned to the arguments according to their position.
For example, in the above function greet(), when we called it as greet("Bruce", "How do you do?"), the value "Bruce" gets assigned to the argument name and similarly "How do you do?" to msg.
Python allows functions to be called using keyword arguments. When we call functions in this way, the order (position) of the arguments can be changed. Following calls to the above function are all valid and produce the same result.
# 2 keyword arguments
greet(name = "Bruce",msg = "How do you do?")

# 2 keyword arguments (out of order)
greet(msg = "How do you do?",name = "Bruce") 

1 positional, 1 keyword argument
greet("Bruce", msg = "How do you do?")           
As we can see, we can mix positional arguments with keyword arguments during a function call. But we must keep in mind that keyword arguments must follow positional arguments.
Having a positional argument after keyword arguments will result in errors. For example, the function call as follows:
greet(name="Bruce","How do you do?")
Will result in an error:
SyntaxError: non-keyword arg after keyword arg
Python Arbitrary Arguments
Sometimes, we do not know in advance the number of arguments that will be passed into a function. Python allows us to handle this kind of situation through function calls with an arbitrary number of arguments.
In the function definition, we use an asterisk (*) before the parameter name to denote this kind of argument. Here is an example.
def greet(*names):
    """This function greets all
    the person in the names tuple."""

    # names is a tuple with arguments
    for name in names:
        print("Hello", name)


greet("Monica", "Luke", "Steve", "John")
Hello Monica
Hello Luke
Hello Steve
Hello John
Here, we have called the function with multiple arguments. These arguments get wrapped up into a tuple before being passed into the function. Inside the function, we use a for loop to retrieve all the arguments back.