❔ Interview question

What happens to a list if you delete almost all its elements?

Answer: list in Python does not automatically reduce allocated memory after deleting elements. For example, if the list had 1,000,000 elements and only 100 remain, it still occupies memory for a million elements until it is recreated (lst = lst[:] or lst = list(lst)).

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❔ Interview Question

Why is list.sort() faster than sorted(list) when sorting the same list?

Answer: The list.sort() method performs an in-place sort, modifying the original list without creating a new copy. This makes it more efficient in terms of memory and performance.

The sorted(list) function creates a new sorted list, which requires additional memory allocation and copying of elements before sorting, potentially increasing time and memory costs.

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❔ Interview question

What is the difference between "is" and "=="?

Answer: The "is" operator checks whether two objects are the same object in memory, whereas the "==" operator checks whether the values of those objects are equal.

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❔ Interview Question

What is the structure of a JWT token?

Answer: JWT (JSON Web Token) consists of three parts separated by dots:

▶️ Header — contains the token type (JWT) and the signing algorithm, such as HMAC SHA256 or RSA

▶️ Payload — includes so-called “claims”: data like user ID, token expiration, roles, and other metadata

▶️ Signature — created from the header and payload using a secret key. It ensures the token’s content has not been tampered with.

These parts are base64 encoded and joined by dots: header.payload.signature.

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❔ Interview question

What is Dependency Injection and how is it used in Python?

Answer: Dependency Injection is a technique where an object receives external dependencies (such as classes, functions, settings) through parameters rather than creating them internally.

In Python, DI is most often implemented explicitly: dependencies are passed to constructors, functions, or arguments, which increases code modularity and facilitates testing. For example, you can easily replace a service with a mock during unit testing.

Unlike Java, where DI containers like Spring are common, Python usually uses explicit dependency passing but can use libraries like dependency-injector for more complex automation if needed.

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❔ Interview Question

What are the parts of an HTTP request?

Answer: An HTTP request consists of a start line (defines the type of message), headers (transmit transfer parameters and message characteristics), and the message body (contains data, separated from the headers by a blank line).

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❔ Interview Question

What is a list comprehension in Python and how does it work?

Answer: A list comprehension is a concise way to create lists in Python by applying an expression to each item in an iterable, optionally with a condition (e.g., [x**2 for x in range(10) if x % 2 == 0]), making code more readable and efficient than traditional for loops for generating lists.

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❔ Interview Question

What is the difference between __str__ and __repr__ methods in Python classes, and when would you implementstr
__str__ returns a human-readable string representation of an object (e.g., via print(obj)), making it user-friendly for displayrepr__repr__ aims for a more detailed, unambiguous string that's ideally executable as code (like repr(obj)), useful for debugging—imstr __str__ for end-user outrepr__repr__ for developer tools or str __str__ is defined.

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❔ Interview Question

Explain the concept of generators in Python and how they differ from regular iterators in terms of memory efficiency.

Generators are functions that use yield to produce a sequence of values lazily (e.g., def gen(): yield 1; yield 2), creating an iterator that generates items on-the-fly without storing the entire sequence in memory, unlike regular iterators or lists which can consume more RAM for large datasets—ideal for processing big data streams efficiently.

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❔ Interview question

Why can frozenset be a key in a dict, but set cannot?

Answer: Keys in a dict must be hashable, meaning their value must not change after creation.

frozenset is immutable, so its hash can be computed once and used as a key.

set is mutable, its contents can change, so its hash function is unstable, which is why dict does not allow using set as a key.

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❔ Interview Question

Which tasks parallelize well, and which do not?

Answer: Tasks with a large number of input-output operations scale well with multithreading — network requests, file access, waiting for database responses. While one thread is waiting, the interpreter can switch to another without wasting time.

Tasks that heavily load the CPU and actively use memory parallelize poorly. In Python, this is especially noticeable due to the GIL: CPU-bound calculations will still use only one thread, and parallel execution will not provide a speedup. Moreover, due to thread switching, the program may even slow down.

If a task combines IO and heavy processing — for example, downloading and parsing — it is better to separate it: keep IO in threads, and assign CPU load to processes (via multiprocessing) or move it to a queue.

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❔ Interview question

What is the order of execution of decorators if there are several on one function?

Answer: Decorators are executed from bottom to top — the bottom one is called first, then the upper one, wrapping the function in several layers.

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❔ Interview Question

How to get the current module's name?

Answer: The module name is available through the built-in variable name. If the module is imported, name contains its full name in the namespace. If the module is run as the main script, name automatically takes the value "main".

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