How to Use This Article
The questions are grouped by category (basic -> advanced -> applied) so as to help organize your practice. With each question, read the answer and then work out to formulate your version of the answer in your own words. Use the “Appendix” section for additional practice beyond the 100 basic questions. While interviewing, explain using examples or code snippets instead of reciting definitions.
Basic Python Questions
These are asked quite frequently, and they appear and disappear, so any questions you can get right are absolutely good ones.
Q1: What is Python?
Answer: Python is a high level, interpreted, General purpose programming language that is known by its readability and dynamic typing with Automatic memory management and has an extensive standard library.
Q2: What are the salient features of Python?
Answer: Some of the salient features include:
– Dynamic typing
– Interpreted (No compilation step)
– High-level abstractions
– Extensive standard library
Multi-paradigmatic- Procedural, object-oriented, functional
– Large ecosystem of third-party libraries
Q3: What is the difference between Python version 2 and Python version 3?
Answer: Python 3 brought breaking changes: print is a function, integer division results in floats by default, better Unicode support, removal of old modules, etc. Python 2 ended its life in 2020.
Q4: What is PEP 8?
Answer: PEP 8 is the Python Enhancement Proposal, which is known to have the name of the style of writing code in Python, which is easy to understand (indentation, name of the variable, order of import, and length of the line, etc.
Q5: What are Python literals?
Answer: Literals: Literals are a notable manner for fixed values in code, instance string literals (“hello”), integer literals (123), float lifeless ‘3.14’, Boolean literals (True, False), None, etc.
Q6: What difference del and remove() list have?
Answer: del list[index] deletes the element at the given arrangement (or collection) list.remove(value) deletes the first occurrence of the number at the given value.
Q7: What is dynamic typing?
Answer: In dynamic typing languages such as python, the type of variable is not determined at compile time instead, it is determined at the run time. Various typed values can be assigned to the same variable within the life of the variable.
Q8: What is shallow copy vs. deep Copy?
Answer: In shallow copy, new container refers to same kind of objects that make up the former container therefore changing the mutable nested in the copied structure will be applied on the same. On the other hand, a deep copy recursively creates a copy of any objects encountered this produces an object that is completely independent (and exploration of the code shows that this is how the copy.deepcopy routine works).
Data Structures
Q9: List vs Tuple – what’s the problem?
Answer: Lists are dynamic (allowing them to grow or shrink) and mutable sequences that allow elements to be mutated, have elements added onto them, and removed from them. Tuples, on the other hand, are constant fixed sizes; they are constants so it takes up less storage space than lists and it will serve as the list’s key in a dictionary due to its hashability. As a result of that, tuples are preferred in situations requiring thread security or immutability ensuring tightness.
Q10: What is dictionary? how it is implemented in python?
Answer: A dictionary is the implementation of hash table (associating arbitrary keys with some values). The given implementation of Python uses with open addressing and a probing strategy (usually quadratic probing) to solve collisions, meaning average case constant look-up, insert and delete operation.
Q11: What are sets and frozensets?
Answer: Set is a collection of items that it contains unique elements having mutable properties and also it doesn’t maintain the order, it is unordered collection, its supports randomness of operations that includes membership testing, union, intersection and difference from one set to another set. Its immutable opposing counterpart, the frozenset, does the same but cannot be changed after it has been created allowing it to be used as a key for other dictionaries, or as an element of sets.
Q12: What is meant by the list comprehension?
Answer: List comprehension provides a concise way to use syntax that lets you create lists, creating an iterable using a list iterator and optionally filtering the iterable using a conditional condition. For example, [x * 2 for x in range(5) if x % 2 == 0] will produce another list of the doubled numbers of even numbers in the range.
Q13: What is the concept of generator expressions?
Answer: Generator expressions are just like list comprehensions but they return generator object instead of intermediate list So they will not be evaluated but will produce generator object i.e. they are lazy i.e. they produce elements on demand but what they do it save the memory in case of large or infinite sequence. For example: (x * 2 for x in range(5)) creates such a generator.
Q14: What is collections defaultdict?
Answer: defaultdict specialized class of dictionary which gets a factory function at the time of object creation using __init__ method, when a key that does not exist is queried (more academic), the factory is called and a default value is generated automatically, this helps in avoiding Key Error exception and helps in writing code where collections of values are used (aggregation), counters etc.
Q15: How do you count the occurrences of items of a collection?
Answer: collections.Counter class has an interesting and easy mapping of element to itsgew frequency Counter (seq) returns a dictionary like object in which every key is an element present in the given input sequence and its respective value is its count.
Object-Oriented Python
Q16: What is a class in Python?
Answer: The architecture for the development of objects (instances). It classifies the data (attributes) and behaviour (methods).
Q17: What are __init__, __new__, and __del__?
Answer:
Having said that, __new__ is actually the method which performs the actual creation of the instance (it is rarely a method that is overridden).
__init__ is invoked immediately after the creation of instance that is to initialize it.
__del__ is a destructor function which executes when the object is garbage collected edge effect is not ensured to be called.
Q18: What is Method overriding and Method overloading in Python?
Answer:
Overriding: Ex triangular class implements its own version with its own method to implement. if the method that the parent class has already been implementing is called “walking” in the parent class, in the child class we implement it with “triangular walking” in the parent class and implement it with “normal walking” in child class.
Overloading: Python does not support the old-school method overloading (having different methods with same name & different parameters together). Instead, arguments could use defaults, or args and kwargs could be employed to emulate overloading.
Q19: Difference between @staticmethod and @classmethod and instance method?
Answer:
Instance method: takes instance (self) as an argument, and is essentially like an accessor to instance variables.
@classmethod: takes the class is cls and is tied to the class level and not to an instance of the class
staticmethod: does not take an implicit first argument; acts like a regular function that resides in the class namespace
Q20: What is multiple inheritance and MRO (method resolution order)?
Answer: Multiple inheritance: It enables inheriting more than one parent. Python calculates the MRO using the C3 linearization algorithm – a way to calculate the Order of Resolution between bases the various bases defining the same method.
Q21: What is magic / dunder methods?
Answer: Special Methods such as __str__, __repr__, __len__, __eq__, __add__, __init__ etc., using which the class can integrate with some of built-in python’s inbuilt behavior
Functions, Modules & Packages
Q22: What is the difference between import module, and from module import X?
Answer: use ‘import module’ to import the module object; named references to its attributes are of type module.X. use ‘from module import X’; the name X itself is imported directly into the current namespace.
Q23: What is __name__ == “__main__” for?
Answer: What does it give a Python management file to do as a reusable module as well as a command-line script. Since that if block is executed only when the file is executed directly, and not when it is included.
Q24: Explain various scopes of the variable in Python (local, enclosing, global and built-in)?
Answer: The LEGB rule:
Local names that are defined in the immediate function.
Enclosing this gives names in outer (enclosing) function scopes.
Global names at the module level.
Built-in names are defined in the built-in module.
Q25: What is a closure and a decorator?
Answer:
Closure: a function that maintains access to variables from its lexical aggregate, even when called from outside the lexical aggregate.
Decorator: a higher-order function, which takes a function as input, and returns another function which usually adds new behavior, often by using closures to encapsulate the functionality.
Q26: What is *args and *kwargs?
Answer: remembers positional arguments in the form of a tuple. kwargs remembers keyword arguments in the form of a dictionary.
Q27: What are lambda functions?
Answer: Anonymous function using lambda function e.g. lambda x,y: x+y (functions which are defined using lambda function)
Q28: What is the difference between Modules and packages?
Answer: The module is a single file with .py extension which consists of the definition of python A package is a directory which contains an __init__.py file and it can contain submodules or sub-packages.
File Handling, Exceptions & I/O
Q29: Reading and Writing to a file in Python?
Answer: open will fetch an object circling files. Then call opening read, opening, readline or opening. .readlines.
The file should always be closed either via closure or under the form with open(… as f) to automatically close the file.
Q30: What is the distinction between read, readline and readlines?
Answer:
– The contents of a file can be read with a single call to `read()ї.
– To read one line at a time, use: readline.
– readlines() is used to get a list of all the lines.
Q31: How do you write to a file?
Answer: Start with a mode of either: mystr ‘w’, mystr ‘a’ or mystr ‘x’ and execute: mystr.write
Use automatic closing with preference to with.
Q32: What is the treatment of exceptions in Python?
Answer: Use there is a try / except/else/finally.
Specific types of exceptions and perhaps re-raise.
Q33: What is the distinction between Exception and BaseException?
Answer: BaseException is the base of the hierarchy.
Normal exceptions Functions Exception ordinary errors Unusual system-exits exceptions such as system exit exception SystemExit and KeyboardInterrupt BaseException itself.
Q34 How may you conceive of custom exceptions?
Answer: Develop another class that inherits existing classes of type Exception (or a subclass) and choose to override either or both of the functions: __init__ or -str.
Advanced Python Concepts
Q35: What is multithreading in Python and what is the GIL?
Answer: Threading creates threads by the use of the threading module.
Python CPython only allows one thread to interpret Python code at a time due to the Global Interpreter Lock (GIL).
Threads are not appropriate with CPU-bound tasks but I/O-bound tasks.
Q36: What is the meaning of Multiprocessing and what is its difference with Multithreading?
Answer: Multiprocessing creating distinct processes, each having its own interpreter and memory.
This bypasses the GIL and is appropriate to CPU bound work.
Q37: What are coroutines and async / await?
Answer: Corroborated in Python 3.5+, a corroutine is defined as a Python function that is defined with async def.
The await suspends until the awaited coroutine completes, which can be really asynchronous, non-blocking code, particularly to perform I/O.
Q38 What is the iterator protocol?
Answer: An economic iterator accomplishes the methods, just in terms of self.
Iterables use an iterable to implement the method of iterables, which is that each lends an iterable and provides an iterator.
Q39: What is a generator?
Answer: A yield-based function yields an object of a generator which is also an iterative.
Generators are lazy in giving out values.
Q40: What is the context manager / the with statement?
Answer: A context manager keeps the functions of entry operation and the exit operation (Message).
The setup and cleanup (such as opening and closing a file) are guaranteed regardless of the occurrence of exceptions by the use of the <|human|>Setting up and cleaning up (opening and closing files) is guaranteed by the use of the with statement irrespective of the possibilities of some exceptions.
Q41: How does the memory management in Python (reference counting, garbage collection) operate?
Answer: Python records references, when the count of an object is drawn to zero, the reference is set free.
In order to manage reference cycles, it uses a generatoric cyclic garbage collector that searches and collects compelling cycles.
Q42: What are weak references?
Answer: With weakref module, weak references can be used to refer to an object and leave the reference count of the object unwrapped. This avoids reference cycles and morph leaks, particularly in the caches and such the case.
Q43: Python loading modules import internals?
Answer: Python maintains records on loaded modules in sys. modules. When it is importing, it scans sys.path, translates the.py files to byte code (.pyc) and records the resulting module object in the sys.modules.
Libraries, Frameworks & Ecosystem.
Q44: What is pip and what can you do with it?
Answer: pip is the default package manager of Python. You can run packages using pip install package_name, upgrade, uninstall etc. It is effective within virtual environments.
Q45: What is virtualenv / venv?
Answer: The isolated environments reside in separate site-packages. They stop project version conflicts.
Q46: What are significant standard library modules that you frequently use?
Answer: The popular modules are common modules such as os, sys, logging, configparser, json, datetime, recollections, itertools, functools, threading, multiple process- multiprocessing, subprocess etc.
Q47: What is NumPy, Pandas, scikit -learn mostly?
Answer: NumPy provides multi-dimensional arrays and arithmetic. Pandas provides DataFrames on which to manipulate and analyse data, maintenance of missing data, aggregation, combination, etc. scikit-learn is a machine learning library with common algorithms, like classification, regression, clusterer and model-assessment instruments.
Q48: What is the Flask / Django in short?
Answer: Flask is a lightweight, pliable fulfilling micro framework. Django is the full-fledged Web framework powered by opinionated structure, ORM, and administrator interface, among numerous others.
Q49: What do you use Python with databases to interface with?
Answer: DB API compliant drivers such as psycopg2, mysql. connector or sqlite3 can be used. With higher-level abstractions, in ORMs like Django ORM or SQLAlchemy, you operate with, to their higher abstractions.
Q50: What is REST API, and how do you then make calls through HTTP using Python?
Answer: REST is an application-style in a networked application. Using the requests platform is standard in Python requests. Get, requests. Post and so on.
Python Data / Scripting / Automation.
Q51: How do you Pythonically read/write CSV files?
Answer: Load and write with Pandas: еpd.readcsv() Rather, just describe the csv module: pd.readcsv.
Q52: Manipulating the JSON datatype with Python?
Answer: That is done by the json module: json.loads(string) is used to wound up a string, json.dumps(object) to serialize an object, and json.load( file) / json.dump( file).
Q53: What is web scraping and how scraping to do it in Python?
Answer: Web scraping gathers information on the web pages. As customary, fitness items would consist of requests to retrieve HTML and BeautifulSoup, lxml, or Scrapy to read and select the data.
Q54: What is the Python scheduling of periodic jobs?
Answer: cron with Linux, or Python libraries such as schedule or APScheduler. As a case in point, 1/10.schedule.every.do(job).
Q55: How would you have automated file operations (rename, search) in Python?
Answer: Resort to the use of the **os** and shutil modules. As an example, call `os.rename()` to rename a file, and use either of these: `os.walk() or glob.glob()` to find files, and use shutil.move() to move them.
Q56: What is the use of regular expressions in Python?
Answer: Dominator In the re Furthermore motion re.match, re.search, re.findall, re.sub, etc. Reger kallans serve to do complicated matches and substitutions involving strings.
Python Code Issues: Algorithms and Coding.
Q57: Reverse a string in Python?
Answer:
“`python
def reverse_string(s):
return s[::-1]
“`
Q58: Test whether a string is a palindrome or not?
Answer:
“`python
def is_palindrome(s):
return s == s[::-1]
“`
Q59:Compute factorial of an integer or number (recursive/iterative)?
Answer:
“`python
def fact(n):
if n == 0:
return 1
else:
return n * fact(n-1)
“`
The iterative variant is also effective.<|human|>The iterative one is functional.
Q60: Fibonacci number nth?
Answer:
“`python
def fib(n):
a, b = 0, 1
for _ in range(n):
a, b = b, a + b
return a
“`
Q61: Merge two sorted lists?
Answer: Two pointers are used to go through both lists and create a new sorted list.
Q62: Geometry can be described as the maximum subarray sum (Kadane algorithm)?
Answer:
“`python
def max_subarray(arr):
max_ending = max_so_far = arr[0]
for x in arr[1:]:
max_ending = max(x, max_ending + x)
max_so_far = max(max_so far, max ending)
return max_so_far
Q63: Find duplicates in a list?
Answer:
Technique 1: Have a collection of already seen fields and test on repeats.
Technique 2:With the help of collections.Counter, search counts larger than one.
Q64: Sort numbers (current sort vs custom sort)?
Answer: The inbuilt (Timsort, O(n 2)) is sorted. It could be to introduce custom, QuickSort, MergeSort etc.
Q65: Breadth -first search (BFS) / Depth -first search (DFS) through a graph?
Answer: Recursion with a stack or DFS. Queue based BFS. enabled list adjacency and set of visited
Q66: Linked list cycle detection (Floyd)?
Answer: Have two pointers, as the pointers: slow and fast. Also, move a step slowly, and go two steps quickly. There is a cycle in case they do ever meet.
Q67: Reverse a linked list?
Answer: Maintain a prev and current variable and constantly rewire the next ones as you go through the list.
Q68: Inorder, Preorder, Postorder search through binary tree?
Answer:
Recur, using a stack:
Inorder: left → root → right
Preorder: root → left → right
Postorder: left → right → root
Q69: Buy/sell a binary tree.
Answer: Do DFS or BFS with an express record of none nodes. Reconstruct the tree using the order obtained in record.
Q70: Closest pair / two-sum / target sum / sliding window / etc?
Answer: Depending on the variation, use hash maps to do look-ups, two-pointer to do sorted data, or sliding window to do subarray.
Debugging & Testing in Python
Q71: How do you debug Python code?
Answer: There is an inbuilt module, pdb (python -m pdb script.py), or there are contemporary debuggers in the form of PyCharm or VS Code. You may also add the following to the code and get debugging: in the signature, import pdb; pdb.set break.
Q72: The distinction between assert and exception-raising?
Answer: The assert control is a test to debug with and can be turned off with optimization (python -O). Exception raising is explicit error handling to be run-time.
Q73: What is the language used to write unit tests in Python?
Answer: Tindley use the standard library unittest or 3rd party frameworks such as pytest.
Example:
“`python
import unittest
class TestMath(unittest.TestCase):
def test_add(self):
self.assertEqual(2 + 2, 4)
if __name__ == “__main__”:
unittest.main()“
Q74: What are test fixtures?
Answer: Before and after each test, set-up and tear off code is required. Examples would be setUp / tearDown in unittest or @pytest.fixture in pytest.
Q75: What is Python testing mocking?
Answer: Don’t use The real objects are replaced with lightweight stand-ins (unittest.mock) which means only the part of the code being tested actually executes, and it is easier and faster.
Q76: What is the performance of Python code?
Answer: Time Answers: Basic timing Use the time time() module for basic timing, timeit for micro-benchmarks, or profilers such as cProfile both which provide more detail.
Q77: What are the ways to profile Python applications?
Answer: To view CPU and memory usage, call cProfile or the native profile.py, or third-party tools, including PySpy, line_profiler or memory profiler.
Q78: How are you going to optimize Python?
Answer: Optimize algorithms, use built-in functions, avoid global lookups, use list comprehension, use C extensions (such as NumPy) or convert to PyPy.
Q79: What is python memory view object?
Answer: memoryview offers direct access to the buffer of an object and does not make any copies, hence well suited to large binary data.
Q80: What are the ways of minimizing the memory footprint in Python?
Answer: Use generators, not the lists, tuples instead of lists when necessary, use __slots in classes, and free up references using del or gc.collect.
Q81: What are Python design pattern design common patterns?
Answer: Singleton, Factory, Observer, Decorator, Context Manager and Strategy, et al.
Q82: What is your implementation of Singleton in Python?
Answer: The default behavior of modules is to be singletons, or you can provide occursors desired.
Q83: What is duck typing?
Answer: Python There is a saying that in Python, an object that walks like a duck and quacks like a duck is a duck. One needs to act, not professed type.
Q84: What is monkey patching?
Answer: This is dynamically modification of classes, replaced methods, or modules by defined methods at runtime. Example:
import math
math.sqrt = lambda x: 42
Q85: What is Python dependency injection?
Answer: As least as possible, move objects and dependencies out of components and depend on creating them by other code, since it simplifies testing and makes parts more isolated.
Q86: How is Python used in DevOps?
Answer: Provision infrastructure as code (Ansible, SaltStack)- To automate the pipeline of CI/CD, write deployment scripts and read logs.
Q87: What is your interaction with AWS services with Python?
Answer: Go with the boto3 library, e.g. boto3.client(s3) in case of S3 or boto3.resource(ec2) in case of EC2.
Q88: How can you make REST API in Python?
Answer: With frameworks, such as Flask, Django REST Framework, or FastAPI.
Example:
from flask import Flask
app = Flask(__name__)
@app.route(‘/hello’)
def hello():
return “Hello”
Q89: What are the ways of running Python scripts as jobs?
Answer: Schedule on Linux with cron or Task Scheduler on windows or Python libraries like schedule or APScheduler.
Q90: In what way do you package Python applications and distribute the apps?
Answer: Good follow setuptools, pip, build wheels and release to PyPI using twine.
AI/ML & Data Science in Python
Q91: What are the primary libraries of Python?
Answer: scikit-learn, Tensorflow, PyTorch, Keras, XGBoost, and LightGBM.
Q92: Foundation: What do you do with missing right in Pandas?
Answer: Reminder Use dropna on simple dropped rows, fillna(value) on filled rows, or interpolation.
Q93: How does NumPy cast anything?
Answer: Expand automatically arrays of shapes of different shapes to perform element-wise operations.
Q94: What are the methods of loading big data in Python?
Answer: Read in big swarms (pd.read_csv(…, chunksize=10000)) or a dask or memory-mapped files.
Q95: Which are python data-visualization libraries?
Answer: Matplotlib, Seaborn, Plotly, Bokeh and Altair.
20. Security and Newest Python Features.
Q96: How do you have Python applications under security?
Answer: Parameterized queries to prevent SQL injection, input hygiene, use the bcrypt password hash algorithm, and adhere to the OWASP.
Q97: What do you mean by type hinting in Python?
Answer: Python supports annotations since Python 3.5, including such an annotation as def add(x: int, y: int) -> int: help.
Q98: What is f‑string formatting?
Answer: This is added in 3.6, e.g. name=“John; print (f”Hello {name})) is quicker and more understandable than the use of either %.format() or.format.
Q99: What is the walrus operator (:=)?
Answer: Coming in 3.8, can be assigned within expressions:
if (n := len(data)) > 5:
print(f”Too long: {n}”)
Q100: What is pattern matching in Python?
Answer: New in 3.10, e.g.,
match status:
case 200: print(“OK”)
case 404: print(“Not Found”)
Q101: Describe dataclasses in Python?
Answer: Von 3.7, @dataclass will be able to automatically create a __init, a __repr, and a __eq called method.
Q102: What is typing.Protocol?
Answer: It was introduced in 3.8 and it specifies structural subtyping (interfaces) without inheritance.
Q103: How is the difference between the Python language synchronous and asynchronous programming?
Answer: Async runs in a line and blocks after each step; asynchronous allows tasks to yield to give away concurrency with asyncio.
Q104: What is the Python approach to string and tuple immutability?
Answer: Strings and tuples are fixed; when changed by altering them, not the key itself is changed but a new object is being formed.
Q105: What is the distinction between shallow copy, deep copy, and assignment?
Answer: Task: both names are identical to this object.
The shallow copy: It reproduces the container but not if the container contains objects that are nested.
Deep copy All Recursively copies the container and its inner objects.
Tips & Best Practices
Should you be asked a question just explain how you thought it out in the interview–oh demonstrate how you got the answer.
Give examples or edge cases to demonstrate your response.
To code mention time and space complexity.
In cases of stalling, brainstorm about trade-offs or subproblems.
Make your code small and readable.
Be familiar with the standard library and do not revisit the wheel.
Python Practice on places such as LeetCode or HackerRank.
Conclusion
Python remains one of the most helpful capabilities in the experts involved in software development, data analysis, automation, and artificial intelligence. Interviewing in Python involves the skill of not just practicing the coding questions but also acquiring a proper perception of the characteristics and libraries of Python along with the commonest practices. It is possible to reinforce your backgrounds, enhance your skills in solving real-life questions, and feel confident even about the interviewing by researching the 100+ questions and answers of this guide.
Nevertheless, with systematic learning and professional training, one can be prepared. Here is where GoLogica can help you along the way. GoLogica has industry-specific Python training sessions, which encompass central as well as advance concepts, real-life projects, interview preparation, and live examples. With such training materials and practice, you can increase the probability of success in the job interviews as well as in development. Having proper training and encouragement, one can learn Python and rise to challenge after challenge in competitive job markets.
