A list of Python full stack interview questions that are commonly asked for full stack developer jobs. Helps people get ready for interviews.
30 Python Full Stack Interview Questions & Answers for 2024 – A Comprehensive Guide to Ace Your Next Interview
1. What is the difference between a Shallow Copy and a Deep Copy in Python?
- Shallow Copy: Creates a new object that stores references to the original elements. Changes to the new object will affect the original object.
- Deep Copy: Creates a new object with copies of the original elements. Changes to the new object will not affect the original object.
2. How is Multithreading achieved in Python?
Multithreading in Python is achieved through context switching, as the Python Global Interpreter Lock (GIL) allows only one thread to hold the Python interpreter at a time. Multithreading is different from multiprocessing, which opens up multiple processes across multiple threads.
3. Explain the Django Architecture.
Django follows the Model-View-Template (MVT) architecture:
- Model: Handles the data storage and retrieval
- View: Processes the request and returns the response
- Template: Handles the presentation logic and generates the final HTML
4. What are the key features of Python?
Some key features of Python include:
- Interpreted language
- Dynamic typing
- High-level language
- Extensive standard library
- Object-oriented
- Cross-platform
5. What is PEP 8 and why is it important?
PEP 8 is the style guide for Python code. It provides guidelines and best practices for writing readable and maintainable Python code. Following PEP 8 is important for ensuring consistency across a codebase and making it easier for other developers to understand and work with the code.
6. How is memory managed in Python?
Python uses a private heap space for memory management. The Python interpreter takes care of the memory allocation and deallocation through a process called reference counting. Python also uses a garbage collector to automatically reclaim memory occupied by unreachable objects.
7. What are Python modules and how do you create them?
Python modules are files containing Python definitions and statements. You can create a module by saving a Python script as a .py file. Modules allow you to organize your code into reusable components, which can then be imported and used in other Python programs.
8. What are the differences between a list and a tuple in Python?
The main differences between lists and tuples are:
- Lists are mutable, while tuples are immutable.
- Lists are enclosed in square brackets [], while tuples are enclosed in parentheses ().
- Lists can be modified after creation, while tuples cannot.
9. What is a lambda function in Python?
A lambda function is a small, anonymous function that can take any number of arguments but can only have one expression. It is often used when you need a simple function for a short period of time. Lambda functions are typically used in combination with functions like map(), filter(), and reduce().
10. What are *args and kwargs in Python?
- *args and **kwargs are used to pass a variable number of arguments to a function:
- *args allows a function to accept an arbitrary number of positional arguments, which are then packed into a tuple.
- **kwargs allows a function to accept an arbitrary number of keyword arguments, which are then packed into a dictionary.
11. What is the difference between a for loop and a while loop in Python?
The main differences between for and while loops in Python are:
- for loops are used when you know the number of iterations in advance, while while loops are used when the number of iterations is unknown.
- for loops iterate over a sequence (like a list, tuple, string, etc.), while while loops continue until a specific condition is met.
12. What is a generator function in Python?
A generator function is a special type of function that returns an iterator object, which you can then iterate over. Generator functions use the yield keyword instead of return to return values one at a time, which allows them to generate large sequences of data without using a lot of memory.
13. What is the difference between a list comprehension and a generator expression in Python?
List comprehensions create a new list by applying an expression to each item in an iterable, while generator expressions create a generator object that generates values on-the-fly as they are needed. Generator expressions are more memory-efficient than list comprehensions, especially for large datasets.
14. What is the purpose of the init() method in Python?
The init() method is a special method in Python classes that is used to initialize the attributes of an object when it is created. It is automatically called when an object of the class is created. The init() method is used to set the initial state of the object.
15. What is the difference between a class method and a static method in Python?
The main differences between class methods and static methods in Python are:
- Class methods take the class as the first argument (usually named cls), while static methods do not take the class as an argument.
- Class methods can access and modify class-level attributes, while static methods cannot.
- Static methods are used for utility functions that don’t need to access any class-level or instance-level data.
16. What is the purpose of the super() function in Python?
The super() function is used to call a method in a superclass from a subclass. It allows you to access and execute methods defined in a parent class from within a child class. This is particularly useful when working with inheritance and overriding methods.
17. What is the difference between str() and repr() in Python?
- The str() and repr() methods are used to define the string representation of an object:
- str() is used to provide a human-readable string representation of an object, which is used by the str() function and in print statements.
- repr() is used to provide an unambiguous string representation of an object, which is used by the repr() function and in the interactive interpreter.
18. What is the purpose of the @property decorator in Python?
The @property decorator in Python is used to define a method as a read-only attribute of a class. This allows you to access the method like an attribute, rather than having to call it as a function. This is useful for encapsulating logic and providing a more intuitive interface for working with class attributes.
19. What is the difference between a function and a method in Python?
The main differences between functions and methods in Python are:
- Functions are standalone, while methods are associated with a class.
- Methods have access to the instance of the class they belong to (self), while functions do not.
- Methods can access and modify the state of the object they belong to, while functions cannot.
20. What is the purpose of the iter() and next() methods in Python?
The iter() and next() methods are used to implement the iterator protocol in Python. The iter() method returns an iterator object, and the next() method is used to retrieve the next item from the iterator. This allows you to create custom iterator objects that can be used in for loops and other constructs that work with iterables.
21. What is the purpose of the @classmethod decorator in Python?
The @classmethod decorator is used to define a method in a class that takes the class itself as the first argument (usually named cls). Class methods can access and modify class-level attributes, and are often used for creating alternative constructors or utility functions that don’t require an instance of the class.
22. What is the purpose of the @staticmethod decorator in Python?
The @staticmethod decorator is used to define a static method in a class. Static methods are regular functions that don’t take the class (cls) or the instance (self) as the first argument. Static methods are used for utility functions that don’t need to access any class-level or instance-level data.
23. What is the purpose of the call() method in Python?
The call() method in Python allows you to make an instance of a class callable, like a function. When you call an instance of a class that has a call() method defined, the call() method is executed. This is useful for creating callable objects, such as function-like objects or stateful objects.
24. What is the purpose of the len() method in Python?
The len() method is a special method in Python that is used to define the length of an object. When you call the len() function on an object, Python will automatically call the len() method of that object to get its length. This is useful for creating custom objects that can be used in len() calls.
25. What is the purpose of the getitem() and setitem() methods in Python?
The getitem() and setitem() methods are used to define how an object can be accessed using square bracket notation (e.g., obj[key]). The getitem() method is used to define how the object should be accessed, while the setitem() method is used to define how the object should be modified. This is useful for creating custom container-like objects that can be accessed and modified like lists or dictionaries.
26. What is the purpose of the enter() and exit() methods in Python?
The enter() and exit() methods are used to implement the context manager protocol in Python. These methods are used in conjunction with the with statement to ensure that resources are properly acquired and released, even in the presence of exceptions. The enter() method is called when the with block is entered, and the exit() method is called when the with block is exited.
27. What is the purpose of the del() method in Python?
The del() method is a special method in Python that is called when an object is about to be destroyed. This method is typically used for cleanup tasks, such as releasing resources or closing connections. However, it’s important to note that the del() method is not guaranteed to be called in all cases, as it depends on the garbage collector and the reference counting mechanism in Python.
28. What is the purpose of the slots() method in Python?
The slots() method is used to optimize the memory usage of a class by limiting the attributes that can be added to an instance of the class. By default, Python allows you to add arbitrary attributes to an object, which can lead to increased memory usage. By defining slots, you can restrict the attributes to only those that are explicitly defined, which can result in significant memory savings, especially for classes with a large number of instances.
29. What is the purpose of the metaclass() method in Python?
The metaclass() method is used to define the metaclass of a class. A metaclass is the class of a class, and it is responsible for creating the class object when a new class is defined. By defining a custom metaclass, you can control how a class is created, including its attributes, methods, and inheritance. Metaclasses are an advanced feature in Python and are typically used for creating custom frameworks or libraries.
30. What is the purpose of the future() module in Python?
The future module in Python is used to enable new language features that are not part of the current version of Python. This allows you to use features that will be available in future versions of Python, even in the current version. This is particularly useful when writing code that needs to be compatible with multiple versions of Python, as it allows you to use newer features without breaking compatibility with older versions.
