20 Python Functions Interview Questions and Answers

Python functions are a way to group related code together. Functions make your code more readable and allow you to reuse code. If you are applying for a position that requires knowledge of Python, you should be prepared to answer questions about functions. In this article, we will discuss some common questions about Python functions and how you can answer them.

Python Functions Interview Questions and Answers

Here are 20 commonly asked Python Functions interview questions and answers to prepare you for your interview:

1. What are the two types of functions in Python?

There are two types of functions in Python: built-in functions and user-defined functions. Built-in functions are functions that are already defined in the Python language, such as the print() function. User-defined functions are functions that are created by the user, and they can be created to do anything that the user wants them to do.

2. Can you explain what a call graph is? How do you create one?

A call graph is a visual representation of the relationships between the various functions in a Python program. It can be used to help debug code, optimize code, and understand code flow. To create a call graph, you can use the pycallgraph library.

3. When should you use anonymous functions and when should you use regular ones?

There is no definitive answer to this question, as it depends on the specific situation and what you are trying to accomplish. However, a general rule of thumb is that anonymous functions are best used for simple tasks that can be easily expressed in a single line of code. Regular functions, on the other hand, are better suited for more complex tasks that require multiple lines of code.

4. Do Python functions have return values? If yes, then how many can they have?

Yes, Python functions can have return values. They can have a single return value, or they can have multiple return values.

5. Why does Python support both positional and keyword arguments to its functions?

Python supports both positional and keyword arguments in order to give developers more flexibility when designing their functions. Positional arguments are those that are passed in by position, without explicitly specifying the parameter name. Keyword arguments are those that are passed in by explicitly specifying the parameter name. Python allows for both types of arguments so that developers can choose the approach that makes the most sense for their particular function.

6. Is it possible for a function’s code to read from or write to variables defined outside that function? If yes, then how?

Yes, it is possible for a function’s code to read from or write to variables defined outside that function. This is known as “accessing global variables.” To do this, the function must first use the “global” keyword to declare which variables it is accessing. For example:

global var1

var1 = 5

def func():

print(var1)

func() # Prints 5

7. Can you explain what a closure is in Python? How do you implement closures?

A closure is a function that remembers the values from the enclosing scope even when the program flow is no longer in that scope. Closures are implemented by creating a function that takes in one or more values from the enclosing scope and then returning a new function that uses those values.

8. Can you explain what decorators are in Python?

Decorators are a way to dynamically alter the behavior of a function. They are usually used as a way to add functionality to an existing function without having to modify the code of the function itself. Decorators are typically written in the form of a wrapper function.

9. Is there any way to define static methods in Python? If yes, then how?

Static methods are defined in Python by using the @staticmethod decorator. This decorator can be applied to any method, and will cause the method to be treated as a static method, even if it is not defined as such.

10. Is it possible to pass a variable number of arguments to a function in Python? If yes, then how?

Yes, it is possible to pass a variable number of arguments to a function in Python. This can be done using the *args and **kwargs parameters. *args allows for a variable number of non-keyworded arguments to be passed to a function, while **kwargs allows for a variable number of keyworded arguments to be passed.

11. How would you convert JSON to Python objects?

The json library in Python can help you convert JSON data into Python objects. The process is known as decoding. You can use the json.loads() function to decode JSON data. This function takes a JSON string and returns a Python object.

12. Can you explain what recursion is and why it’s useful?

Recursion is a function that calls itself. It’s useful because it allows you to break down a problem into smaller, more manageable pieces.

13. What is tail-recursion?

Tail-recursion is a type of recursion where the last statement in the function is a recursive call. This is important because it allows the interpreter to optimize the function by not having to keep track of the current state of the function, since it can simply jump to the beginning of the function and start again.

14. Can you explain what memoization is and why it’s useful?

Memoization is a technique for optimizing code by caching and reusing previously-computed results. It can be used to speed up calculations by avoiding redundant work, and it can also be used to make code more memory-efficient by storing the results of expensive function calls and avoiding the need to recalculate them each time the function is called.

15. What is currying?

Currying is the process of taking a function with multiple arguments and turning it into a function that takes a single argument. The single argument is then used to generate a new function that takes the next argument, and so on, until all arguments have been used. Currying is often used in functional programming to make code more concise.

16. Can you give me some examples where I might want to use an assertion function?

Assertions are often used in debugging to check for conditions that should never occur in normal execution. For example, if you are working with a list, you might want to assert that the list is never empty, or that every element in the list is greater than 0.

17. Can you explain the difference between named parameters and keyword parameters in Python?

In Python, named parameters are those that are assigned a name in the function definition, while keyword parameters are those that are assigned a value when the function is called. For example, in the following function definition, the parameter x is a named parameter, while the parameter y is a keyword parameter:

def func(x, y=5):
pass

In this example, the parameter y will always have the value 5 when the function is called, unless a different value is explicitly provided.

18. What’s the difference between positional parameters and default parameters in Python?

Positional parameters are parameters that are required to be provided in order for the function to run. Default parameters are parameters that are not required to be provided, but have a default value that will be used if no other value is provided.

19. How do you access the value returned by a function invoked in another function?

You can access the value returned by a function invoked in another function by using the return statement. For example, if you have a function that calculates the sum of two numbers, you can access the value returned by the function by using the return statement.

20. Can you give me some examples of monkeypatching in Python?

Monkeypatching is the process of dynamically altering the behavior of a function or class at runtime. This can be useful for patching bugs, adding new features, or simply overriding the behavior of a function or class for testing purposes. Some examples of monkeypatching in Python include:

– Altering the behavior of a built-in function:

“`python
>>> import builtins
>>> def my_print(*args, **kwargs):
… print(‘Hello, world!’)
…
>>> builtins.print = my_print
>>> print(‘This will print “Hello, world!”‘)
Hello, world!
“`

– Altering the behavior of a method in a class:

“`python
>>> class MyClass:
… def my_method(self):
… print(‘Hello, world!’)
…
>>> def new_method(self):
… print(‘Goodbye, world!’)
…
>>> MyClass.my_method = new_method
>>> MyClass().my_method()
Goodbye, world!
“`