Python Interview Questions and Answers

Top 100 Python Interview Questions for Freshers

Python is one of the most widely used programming languages in top tech companies, including IDM TechPark. Its simplicity, versatility, and powerful libraries make it an essential skill for developers. To secure a Python developer role at IDM TechPark, candidates must be well-versed in Python concepts and ready to tackle both the Python Online Assessment and Technical Interview Round.
To help you succeed, we have compiled a list of the Top 100 Python Interview Questions along with their answers. Mastering these will give you a strong edge in cracking Python interviews at IDM TechPark.

1. What is Python?

Python is a high-level, interpreted programming language known for its simplicity, readability, and flexibility. It supports multiple programming paradigms, including procedural, object-oriented, and functional programming.

2. What are Python's key features?

Easy to learn and use
Interpreted language
Dynamically typed
Extensive standard library
Open-source and community-supported
Supports multiple paradigms
Platform-independent

3. What is PEP 8?

PEP 8 is Python’s style guide that provides best practices for writing clean, readable, and consistent code.

4. What is the difference between a list and a tuple?

List: Mutable (can be changed), uses []
Tuple: Immutable (cannot be changed), uses ()

5. What is the difference between Python 2 and Python 3?

Python 3 supports Unicode by default, uses print() as a function, and has improved syntax and standard library.

6. How is memory managed in Python?

Python uses automatic memory management, including garbage collection, reference counting, and a private heap.

7. What are Python’s data types?

Numeric types: int, float, complex
Sequence types: list, tuple, range
Text type: str
Set types: set, frozenset
Mapping type: dict
Boolean type: bool
Binary types: bytes, bytearray, memoryview

8. What are Python's built-in data structures?

List, Tuple, Dictionary, Set

9. What is the difference between is and ==?

is checks object identity (same memory location).
== checks value equality.

10. What are Python functions?

Functions are reusable blocks of code that perform specific tasks. Defined using def.

11. What is the difference between deepcopy() and copy()?

copy.copy() creates a shallow copy (references nested objects).
copy.deepcopy() creates a deep copy (completely independent clone).

12. What is a lambda function?

A small anonymous function defined using lambda keyword.

add = lambda x, y: x + y print(add(3, 4)) # Output: 7

13. What are Python decorators?

Functions that modify the behavior of other functions without modifying their code.

def decorator(func): def wrapper(): print("Before function call") func() print("After function call") return wrapper @decorator def say_hello(): print("Hello") say_hello()

14. What are args and kwargs in Python?

args: Allows passing a variable number of positional arguments.
kwargs: Allows passing a variable number of keyword arguments.

def example(args, kwargs): print(args, kwargs) example(1, 2, 3, name="Alice", age=25)

15. What is the difference between a module and a package?

Module: A .py file containing Python code.
Package: A collection of modules, containing an __init__.py file.

16. What is the difference between @staticmethod, @classmethod, and instance methods?

Instance method: Works with instance (self).
Class method: Uses @classmethod, takes cls as the first parameter.
Static method: Uses @staticmethod, doesn’t take self or cls.

17. How does exception handling work in Python?

try: x = 1 / 0 except ZeroDivisionError as e: print(f"Error: {e}") finally: print("Execution completed")

18. What are Python’s file handling modes?

"r" – Read
"w" – Write (overwrite)
"a" – Append
"rb"/"wb" – Binary read/write

19. What is list comprehension?

numbers = [x**2 for x in range(10) if x % 2 == 0] print(numbers) # [0, 4, 16, 36, 64]

20. How do you implement multithreading in Python?

import threading def print_numbers(): for i in range(5): print(i) thread = threading.Thread(target=print_numbers) thread.start()

20. What is the difference between is and == in Python?
Answer: == checks if the values of two variables are equal, whereas is checks if the two variables point to the same object in memory.

21. What is a lambda function in Python?
Answer: A lambda function is an anonymous, one-line function defined using the lambda keyword. It can take any number of arguments but has only one expression.

22. What are Python's data types?
Answer: Python has several built-in data types such as int, float, complex (numeric), str (text), bool, list, tuple, dict, set, frozenset, bytes, and NoneType.

23. What is a Python dictionary?
Answer: A dictionary in Python is an unordered collection of key-value pairs. Each key must be unique and immutable, and is used to access the corresponding value.

24. What are args and kwargs in function definitions?
Answer: args is used to pass a variable number of positional arguments to a function. kwargs is used to pass a variable number of keyword arguments.

25. How do you handle exceptions in Python?
Answer: Exceptions are handled using try-except blocks. You place the code that might raise an exception inside a try block, and handle the error in the except block.

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1. What is the difference between shallow copy and deep copy?

A shallow copy creates a new object but does not copy nested objects; instead, it references them.
A deep copy creates a completely independent copy, including nested objects.

Example:

import copy list1 = [[1, 2, 3], [4, 5, 6]] shallow = copy.copy(list1) deep = copy.deepcopy(list1) shallow[0][0] = 100 print(list1) # [[100, 2, 3], [4, 5, 6]] (changes reflected) print(deep) # [[1, 2, 3], [4, 5, 6]] (no changes)

2. What is the difference between staticmethod and classmethod?

@staticmethod does not require self or cls and behaves like a regular function within a class.
@classmethod requires cls as the first parameter and can modify class variables.

Example:

class Example: class_var = 10 @staticmethod def static_method(): print("Static method called") @classmethod def class_method(cls): cls.class_var += 1 print("Class method called", cls.class_var) Example.static_method() # Output: Static method called Example.class_method() # Output: Class method called 11

3. What is the difference between generators and iterators?

Iterator: Implements __iter__() and __next__() and maintains state.
Generator: Uses yield to produce values lazily.

Example:

def gen_example(): for i in range(3): yield i gen = gen_example() print(next(gen)) # 0 print(next(gen)) # 1

4. What are Python’s memory management techniques?

Garbage Collection: Python uses automatic garbage collection.
Reference Counting: When an object’s reference count reaches zero, it is deleted.
Generational Garbage Collector: Objects are classified into generations and cleaned accordingly.

5. What is the Global Interpreter Lock (GIL)?

The GIL ensures that only one thread executes Python bytecode at a time, preventing true parallelism.
This affects multi-threading performance for CPU-bound tasks but not for I/O-bound tasks.

Example:

import threading def task(): for _ in range(1000000): pass t1 = threading.Thread(target=task) t2 = threading.Thread(target=task) t1.start() t2.start() t1.join() t2.join()

(Threads will not run truly in parallel due to GIL.)

6. How do you handle circular imports in Python?

Use import inside a function or import specific attributes to break circular dependencies.

Example:

# module1.py import module2 def func1(): module2.func2() # module2.py import module1 def func2(): module1.func1()

(Solution: Import within a function.)

7. What is the difference between is and ==?

is checks object identity (memory address).
== checks value equality.

a = [1, 2, 3] b = a c = [1, 2, 3] print(a is b) # True (same memory) print(a is c) # False (different objects) print(a == c) # True (same value)

8. What is the difference between del, remove(), and pop()?

del: Deletes an element by index or deletes the whole object.
remove(): Removes the first occurrence of a specific value.
pop(): Removes an element by index and returns it.

Example:

my_list = [1, 2, 3, 4] del my_list[1] # Deletes index 1 my_list.remove(3) # Removes value 3 x = my_list.pop(0) # Removes index 0 and returns it

9. What is the difference between map(), filter(), and reduce()?

map(): Applies a function to all elements.
filter(): Filters elements based on a function.
reduce(): Aggregates elements into a single result.

Example:

from functools import reduce nums = [1, 2, 3, 4] squares = list(map(lambda x: x**2, nums)) # [1, 4, 9, 16] evens = list(filter(lambda x: x % 2 == 0, nums)) # [2, 4] product = reduce(lambda x, y: x * y, nums) # 24

10. What is monkey patching in Python?

Monkey patching is modifying or extending a module or class at runtime.

Example:

class Example: def greet(self): print("Hello") def new_greet(self): print("Hi!") Example.greet = new_greet obj = Example() obj.greet() # Hi!

11. What are Python’s built-in hashable and unhashable types?

Hashable: int, float, str, tuple (immutable types).
Unhashable: list, dict, set (mutable types).

print(hash("hello")) # Valid print(hash((1, 2, 3))) # Valid # print(hash([1, 2, 3])) # TypeError: unhashable type: 'list'

12. How can you improve performance in Python?

Use generators instead of lists (yield).
Use built-in functions like sum(), max(), etc.
Use Cython, PyPy, or multiprocessing for performance.
Avoid global variables and unnecessary loops.

13. What is the difference between repr() and str()?

str() is user-friendly (used for display).
repr() is meant for debugging and development.

class Example: def __repr__(self): return "Example()" def __str__(self): return "This is an example" obj = Example() print(str(obj)) # This is an example print(repr(obj)) # Example()

14. How do you merge two dictionaries in Python?

dict1 = {"a": 1, "b": 2} dict2 = {"b": 3, "c": 4} # Method 1: Using `update()` dict1.update(dict2) # {'a': 1, 'b': 3, 'c': 4} # Method 2: Using dictionary unpacking merged = {**dict1, **dict2} # {'a': 1, 'b': 3, 'c': 4}

15. How does Python’s __call__ method work?

It allows an instance of a class to be called as a function.

class CallableClass: def __call__(self, x): return x * 2 obj = CallableClass() print(obj(5)) # 10

16. What is list comprehension in Python?
Answer: List comprehension provides a concise way to create lists. It is more compact and faster than traditional for loops.

Example:

squares = [x*x for x in range(5)]

17. What is the difference between deep copy and shallow copy?
Answer: A shallow copy creates a new object but inserts references to the original objects. A deep copy creates a new object and recursively copies all objects found in the original.

18. What is a decorator in Python?
Answer: A decorator is a function that takes another function as input and extends or alters its behavior without explicitly modifying it.

19. What is the difference between @staticmethod and @classmethod?
Answer:

@staticmethod defines a method that doesn’t take self or cls as the first argument.
@classmethod takes cls as the first argument and can modify class state.

20. What is the use of the with statement in Python?
Answer: The with statement is used for resource management and exception handling, often with file operations. It ensures proper acquisition and release of resources.

Example:

with open('file.txt', 'r') as file: content = file.read()

21. How is memory managed in Python?
Answer: Python uses reference counting and garbage collection to manage memory. The gc module is used to manually interact with the garbage collector.

22. What are Python modules and packages?
Answer:

A module is a Python file containing code (functions, classes).
A package is a collection of modules organized in directories with an __init__.py file.

23. What is the difference between xrange and range in Python 2?
Answer: In Python 2, range returns a list, while xrange returns a generator-like object for better memory performance. In Python 3, range behaves like xrange.

24. How do you manage dependencies in Python projects?
Answer: Dependencies are managed using tools like pip, venv, and requirements.txt to create isolated environments and list required packages.

25. What are Python’s magic methods?
Answer: Magic methods (dunder methods) are special methods with double underscores (e.g., __init__, __str__, __len__) that allow custom behavior for classes and objects.

1. What are metaclasses in Python?

A metaclass is a class that defines how other classes behave.
Classes are instances of metaclasses.
The default metaclass in Python is type.

Example:

class Meta(type): def __new__(cls, name, bases, attrs): print(f"Creating class {name}") return super().__new__(cls, name, bases, attrs) class Example(metaclass=Meta): pass # Output: Creating class Example

2. What is the difference between deepcopy() and copy()?

copy() creates a shallow copy (references nested objects).
deepcopy() creates a full independent copy.

Example:

import copy list1 = [[1, 2], [3, 4]] shallow = copy.copy(list1) deep = copy.deepcopy(list1) shallow[0][0] = 100 print(list1) # [[100, 2], [3, 4]] (shallow copy modified) print(deep) # [[1, 2], [3, 4]] (deep copy remains unchanged)

3. How does Python handle memory management?

Reference Counting: Objects are deleted when their reference count reaches zero.
Garbage Collection: Python’s GC runs periodically to remove cyclic references.
Generational GC: Objects are divided into generations (young, middle-aged, old) for optimized cleanup.

Example:

import sys a = [1, 2, 3] print(sys.getrefcount(a)) # Output: 2 (1 for variable 'a', 1 for function argument)

4. How does the __slots__ attribute improve performance?

__slots__ prevents dynamic attribute creation and reduces memory usage.

Example:

class Example: __slots__ = ['a', 'b'] obj = Example() obj.a = 10 # obj.c = 20 # AttributeError: 'Example' object has no attribute 'c'

5. What is the difference between staticmethod, classmethod, and instance methods?

Instance Method: Works with self.
Class Method: Works with cls, affects class variables.
Static Method: Independent of class/instance.

Example:

class MyClass: class_var = 10 def instance_method(self): return self.class_var @classmethod def class_method(cls): return cls.class_var @staticmethod def static_method(): return "I don't use class variables" obj = MyClass() print(obj.instance_method()) # 10 print(MyClass.class_method()) # 10 print(MyClass.static_method()) # "I don't use class variables"

6. What is the difference between __str__() and __repr__()?

__str__() is for user-friendly output.
__repr__() is for debugging, should return a valid Python expression.

Example:

class Example: def __repr__(self): return "Example()" def __str__(self): return "This is an example" obj = Example() print(str(obj)) # This is an example print(repr(obj)) # Example()

7. How does Python’s __call__ method work?

It allows objects to be called like functions.

Example:

class CallableExample: def __call__(self, x): return x * 2 obj = CallableExample() print(obj(5)) # 10

8. What are Python descriptors?

Descriptors define how attributes are accessed.
They implement __get__, __set__, and __delete__.

Example:

class Descriptor: def __get__(self, instance, owner): return "Getting value" def __set__(self, instance, value): print(f"Setting value to {value}") class Example: attr = Descriptor() obj = Example() print(obj.attr) # "Getting value" obj.attr = 10 # "Setting value to 10"

9. How does Python implement method resolution order (MRO)?

Python uses C3 linearization (DFS + Breadth-First Search) for method resolution.

Example:

class A: pass class B(A): pass class C(A): pass class D(B, C): pass print(D.mro()) # [D, B, C, A, object]

10. What is monkey patching?

Modifying a class or module at runtime.

Example:

class Example: def greet(self): return "Hello" def new_greet(self): return "Hi!" Example.greet = new_greet print(Example().greet()) # "Hi!"

11. What is a Python closure?

A closure is a function that remembers variables from its enclosing scope.

Example:

def outer_function(x): def inner_function(y): return x + y return inner_function closure = outer_function(10) print(closure(5)) # 15

12. What are weak references in Python?

Weak references allow objects to be garbage collected.

Example:

import weakref class Example: pass obj = Example() weak = weakref.ref(obj) print(weak()) # <__main__.Example object> del obj print(weak()) # None (garbage collected)

13. What is the @property decorator?

@property allows defining getters and setters in a Pythonic way.

Example:

class Example: def __init__(self, value): self._value = value @property def value(self): return self._value @value.setter def value(self, new_value): self._value = new_value obj = Example(10) print(obj.value) # 10 obj.value = 20 print(obj.value) # 20

14. What is a metaclass and how is it used?

A metaclass controls class creation.

Example:

15. How does Python handle multiple inheritance conflicts?

Python resolves conflicts using C3 Linearization (MRO).

Example:

class A: def greet(self): return "A" class B(A): def greet(self): return "B" class C(A): def greet(self): return "C" class D(B, C): pass print(D().greet()) # "B" (MRO: D → B → C → A)

15. What is metaclass in Python?
Answer: A metaclass is a class of a class. It defines how a class behaves. A class is an instance of a metaclass, just as objects are instances of classes. Metaclasses allow

customization of class creation.

16. Explain Python's Global Interpreter Lock (GIL).
Answer: The GIL is a mutex that protects access to Python objects, preventing multiple native threads from executing Python bytecodes simultaneously. This means Python threads are not truly parallel in CPU-bound operations.

17. What is monkey patching in Python?
Answer: Monkey patching refers to modifying or extending code at runtime. It’s often used to replace methods or functions during testing or to add functionality dynamically.

18. How does Python implement memory management?
Answer: Python uses a private heap space for memory management. It employs reference counting and a cyclic garbage collector for reclaiming unused memory.

19. What are coroutines and how are they different from generators?
Answer: Coroutines are special functions that can pause and resume their execution. Unlike generators which only yield values, coroutines can also consume values using send(), making them suitable

for async programming.

20. How does the asyncio library work in Python?
Answer: asyncio provides infrastructure for writing single-threaded concurrent code using coroutines, multiplexing I/O access over sockets and other resources, using an event loop.

21. What is the purpose of the __slots__ declaration?
Answer: __slots__ is used to declare fixed attributes for class instances, which saves memory by preventing the creation of __dict__ and speeding up attribute access.

22. What are descriptors in Python?
Answer: Descriptors are objects that define how attribute access is interpreted by implementing any of __get__, __set__, or __delete__ methods. Used heavily in property, staticmethod, and classmethod.

23. What is the difference between a shallow and a deep copy in Python?
Answer: A shallow copy creates a new object but copies references of nested objects, while a deep copy recursively copies all objects, resulting in complete independence from the original.

24. What is the purpose of the @property decorator in Python?
Answer: The @property decorator allows a method to be accessed like an attribute, enabling encapsulation and controlled access to private variables.

25. How can you implement method overloading in Python?
Answer: Python doesn’t support method overloading by default. However, it can be simulated using default arguments, *args, **kwargs, or by checking argument types inside the method.

Python Fundamentals

Q1: What are Python’s key features?

Interpreted
Dynamically typed
Object-oriented
High-level and easy to read
Large standard library
Supports garbage collection

Data Structures in Python

Q2: What are the differences between a list and a tuple?

FeatureList (list)Tuple (tuple)

MutabilityMutable (can be modified)Immutable (cannot be modified)

PerformanceSlowerFaster

Syntaxlist = [1, 2, 3]tuple = (1, 2, 3)

Use CaseWhen frequent modifications are neededWhen data should not change

Example:

my_list = [1, 2, 3] my_list[0] = 10 # Allowed my_tuple = (1, 2, 3) # my_tuple[0] = 10 # TypeError: 'tuple' object does not support item assignment

Functions & Decorators

Q3: What are args and kwargs in Python?

args allows a function to accept any number of positional arguments.
kwargs allows a function to accept any number of keyword arguments.

Example:

def example_function(args, kwargs): print("Positional:", args) print("Keyword:", kwargs) example_function(1, 2, 3, name="Alice", age=25) # Output: # Positional: (1, 2, 3) # Keyword: {'name': 'Alice', 'age': 25}

Object-Oriented Programming (OOP)

Q4: What is method overriding in Python?

Method overriding allows a child class to redefine a method from its parent class.

Example:

class Parent: def show(self): print("Parent method") class Child(Parent): def show(self): # Overriding the parent method print("Child method") obj = Child() obj.show() # Output: Child method

Memory Management

Q5: How does Python manage memory?

Uses reference counting and garbage collection.
Objects with zero references are automatically deleted.
Uses a generational garbage collector for efficiency.

Exception Handling

Q6: What is the difference between try-except and try-finally?

try-except handles exceptions.
try-finally ensures a block of code always runs, even if an exception occurs.

Example:

try: x = 1 / 0 except ZeroDivisionError: print("Cannot divide by zero") finally: print("This will always execute")

Multithreading & Concurrency

Q7: What is the Global Interpreter Lock (GIL)?

The GIL ensures that only one thread runs at a time.
It affects CPU-bound tasks but not I/O-bound tasks.

Example:

import threading def task(): for _ in range(1000000): pass t1 = threading.Thread(target=task) t2 = threading.Thread(target=task) t1.start() t2.start() t1.join() t2.join()

(Thread execution is not truly parallel due to GIL.)

File Handling

Q8: How do you read a file line by line?

Example:

with open("example.txt", "r") as file: for line in file: print(line.strip()) # Removes trailing newline

Database Handling

Q9: How do you connect Python to a database using SQLite?

Example using sqlite3:

import sqlite3 conn = sqlite3.connect("my_database.db") # Connect to database cursor = conn.cursor() cursor.execute("CREATE TABLE IF NOT EXISTS users (id INTEGER, name TEXT)") cursor.execute("INSERT INTO users (id, name) VALUES (?, ?)", (1, "Alice")) conn.commit() conn.close()

Web Development (Flask)

Q10: How do you create a simple Flask API?

Example:

from flask import Flask app = Flask(__name__) @app.route("/") def home(): return "Hello, Flask!" if __name__ == "__main__": app.run(debug=True)

Data Science & Pandas

Q11: How do you handle missing values in Pandas?

import pandas as pd df = pd.DataFrame({"A": [1, None, 3], "B": [4, 5, None]}) df.fillna(0, inplace=True) # Replaces NaN with 0 print(df)Regular Expressions (Regex)

Q12: How do you validate an email using regex?

import re pattern = r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$" email = "test@example.com" if re.match(pattern, email): print("Valid Email") else: print("Invalid Email")

Python Performance Optimization

Q13: How can you optimize Python performance?

Use list comprehensions instead of loops.
Use generators to save memory.
Use built-in functions like sum(), max(), min().
Use NumPy for numerical computations.

Example:

# Using list comprehension (faster) squares = [x**2 for x in range(10)]API Requests

Q14: How do you send an HTTP request using requests?

import requests response = requests.get("https://api.github.com") print(response.status_code) # 200 for success

Multithreading vs Multiprocessing

Q15: When should you use threading vs multiprocessing?

Use threading for I/O-bound tasks (e.g., web scraping, file I/O).
Use multiprocessing for CPU-bound tasks (e.g., large computations).

Example:

from multiprocessing import Pool def square(n): return n * n with Pool(4) as p: print(p.map(square, [1, 2, 3, 4])) # [1, 4, 9, 16]

16. What is a Python virtual environment and why is it important?
Answer: A virtual environment is an isolated environment in Python used to install packages and dependencies for a specific project. It prevents conflicts between project dependencies and ensures the application uses the correct versions of libraries.

17. How does Python handle memory management?
Answer: Python uses a private heap space for memory allocation, with a garbage collector to manage memory. It uses reference counting to track memory usage and collects objects that are no longer in use.

18. What is the purpose of sys.argv in Python?
Answer: sys.argv is a list in Python that contains the command-line arguments passed to a script. It allows you to parse arguments and interact with the script from the command line.

19. Explain the difference between deepcopy and copy in Python.
Answer: The copy() method creates a shallow copy, which copies only the reference to objects within the original object. deepcopy() creates a copy of the object and all objects within it, meaning changes to the copied object won’t affect the original.

20. What are the different ways of creating a thread in Python?
Answer: Python threads can be created by subclassing the Thread class or by passing a target function to the Thread class. The threading module provides tools to manage threads and

synchronization.

21. What are the differences between @staticmethod and @classmethod in Python?
Answer:

@staticmethod defines a method that doesn’t need access to the instance or class.
@classmethod defines a method that receives the class as the first argument, which can be used to modify class-level data.

22. How can you read and write files in Python?
Answer: Python provides built-in functions such as open() to read and write files. Use open(filename, mode) to open a file, and methods like read(), write(), and close() to interact with the file content.

23. What is the difference between a Python list and a tuple?
Answer:

Lists are mutable, meaning their content can be changed after creation.
Tuples are immutable, meaning their content cannot be modified once created, and they are often used for fixed data.

24. What is Python's assert statement used for?
Answer: The assert statement is used for debugging purposes. It tests whether a condition is True. If it is not, the program raises an AssertionError with an optional message.

25. How do you handle exceptions in Python?
Answer: Exceptions in Python are handled using try-except blocks. Optionally, a finally block can be used to execute code that must run regardless of whether an exception occurred.

"Deep Concepts to Elevate Your Career"

This guide provides 100+ Python interview questions along with in-depth concepts to strengthen your expertise.

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Python Interview Questions and Answers

Top 100 Python Interview Questions for Freshers

"Deep Concepts to Elevate Your Career"

This guide provides 100+ Python interview questions along with in-depth concepts to strengthen your expertise.

Contact Us

IDM Techpark Erode
1st floor, 33/15 vasavi complex, nalli
hospital road, annamalai layout, near bus
stand, erode 638011

+91-95853-05700

idmtechpark@gmail.com

Software Courses

Full Stack Developer

Python Interview Questions and Answers

Top 100 Python Interview Questions for Freshers

"Deep Concepts to Elevate Your Career"

This guide provides 100+ Python interview questions along with in-depth concepts to strengthen your expertise.

Contact Us

IDM Techpark Erode 1st floor, 33/15 vasavi complex, nalli hospital road, annamalai layout, near bus stand, erode 638011

+91-95853-05700

idmtechpark@gmail.com

Software Courses

Full Stack Developer

IDM Techpark Erode
1st floor, 33/15 vasavi complex, nalli
hospital road, annamalai layout, near bus
stand, erode 638011