1. What Makes Python a Popular Programming Language?
Ans:
Python is popular due to its easy-to-understand syntax, which makes it accessible to beginners while remaining powerful for experienced developers. Numerous applications are supported by it, including web development, automation, artificial intelligence and data science. Python also has a vast standard library and a strong global community, making development faster and troubleshooting more manageable.
2. How Does Python Manage Memory Internally?
Ans:
Python manages memory through a private heap that stores all data and objects. It features a built-in garbage collector that automatically identifies and clears unused objects from memory. This automation helps prevent memory leaks and allows developers to focus more on coding than on manual memory management.
3. What Do Python Namespaces Mean?
Ans:
A namespace in Python is a system that holds the names of variables, functions and objects, ensuring they remain unique and organized. Python uses several types of namespaces such as local, global and built-in to control and where variables are accessed, thus preventing naming conflicts and improving code clarity.
4. What is PEP 8 and Why is it Used?
Ans:
The approved style guide for PEP 8 is writing Python code. It provides conventions on aspects such as indentation, naming, line length and formatting to promote code readability. Following PEP 8 ensures consistency across projects and makes it easier for teams to collaborate on Python codebases.
5. How Are Lists and Tuples Different in Python?
Ans:
Collections of things can be stored in lists or tuples, however they differ in flexibility. Lists are mutable, meaning their content can be modified after creation, while tuples are immutable and remain constant. Lists are better suited for dynamic data, whereas tuples are ideal for fixed, unchanging values.
6. What is a Decorator in Python?
Ans:
A decorator is a special function that adds new functionality to another function without altering its original structure. Decorators are often used to implement common behaviors like logging, access control or performance tracking and they help keep the code modular and clean.
7. What Types of Inheritance Does Python Support?
Ans:
Python supports several forms of inheritance, including single, multiple, multilevel, hierarchical and hybrid. These inheritance types allow one class to derive properties and behavior from other classes, promoting reusability and logical structure within complex programs.
8. How is Multithreading Done in Python?
Ans:
Python uses a built-in module to handle multithreading, which allows multiple tasks to run concurrently. This is especially useful for tasks involving input/output operations like file handling or network communication. However, due to Python's Global Interpreter Lock (GIL), multithreading is less effective for tasks that require heavy CPU usage.
9. What’s the Difference Between a Shallow Copy and a Deep Copy?
Ans:
A new item is produced by a shallow copy, however maintains references to the objects inside it, so changes to nested data affect both the original and the copy. In contrast, a deep copy creates a new object along with copies of all nested objects ensuring that changes in one do not impact the other.
10. How Do You Build Stacks and Queues in Python?
Ans:
Stacks and queues are common data structures in Python. A stack follows a last-in, first-out approach while a queue uses a first-in, first-out method. Stacks can be made with lists and specialized structures are available to efficiently build queues, making them both easy to implement in Python applications.
