python Interview Questions

Answer:

Python is a high-level, interpreted programming language known for its simplicity and readability.

Answer:

Key features include dynamic typing, automatic memory management, readability, support for multiple programming paradigms (procedural, object-oriented, functional), and extensive standard libraries.

Answer:

Python 3.x is the current version and is not backwards compatible with Python 2.x. Python 3.x emphasizes simplicity and removes old, redundant features from Python 2.x, such as `print` being a function, integer division returning float, and Unicode support by default.

Answer:

Decorators in Python are functions that modify the functionality of another function or method. They are used to wrap another function, modifying its behavior.

def my_decorator(func):
  def wrapper():
    print('Something is happening before the function is called.')
    func()
    print('Something is happening after the function is called.')
  return wrapper
@my_decorator
def say_hello():
  print('Hello!')
say_hello()

Answer:

Generators in Python are functions that enable us to create iterators. They generate values in an iterative manner using `yield` rather than `return`.

Answer:

`__str__` is used to find the 'informal' or nicely printable string representation of an object, while `__repr__` is used to find the 'official' string representation of an object.

class Person:
  def __init__(self, name):
    self.name = name
  def __str__(self):
    return f'Person({self.name})'
  def __repr__(self):
    return f'Person({self.name})'

Answer:

Lists are mutable (modifiable) sequences, while tuples are immutable (cannot be changed). Lists use square brackets `[]`, whereas tuples use parentheses `()`.

my_list = [1, 2, 3]
my_tuple = (1, 2, 3)
my_list[0] = 4
# my_tuple[0] = 4  # Error: 'tuple' object does not support item assignment

Answer:

Python's built-in data types include integers, floats, complex numbers, strings, lists, tuples, dictionaries, sets, and booleans.

Answer:

`*args` and `**kwargs` allow a function to accept variable-length argument lists. `*args` collects extra positional arguments as a tuple, while `**kwargs` collects extra keyword arguments as a dictionary.

def example(*args, **kwargs):
  print(args)
  print(kwargs)
example(1, 2, a='apple', b='banana')

Answer:

A lambda function in Python is a small anonymous function defined with the `lambda` keyword. It can have any number of arguments but only one expression. Lambda functions are syntactically restricted to a single expression.

add = lambda x, y: x + y
print(add(2, 3)) # 5

Answer:

`pass` is a null statement in Python, used as a placeholder where syntax requires a statement but you have nothing to write.

Answer:

`__init__` is a special method in Python classes that is automatically called when a new instance of the class is created. It initializes the object's attributes.

class Person:
  def __init__(self, name):
    self.name = name
john = Person('John')

Answer:

Exceptions in Python are handled using try-except blocks. Code that might raise an exception is written in the `try` block, and handling of the exception is implemented in the `except` block.

try:
  x = 1 / 0
except ZeroDivisionError as e:
  print('Error:', e)

Answer:

`__getattr__` is called when an attribute lookup has not found the attribute in the usual places, while `__getattribute__` is called for every attribute access.

Answer:

The `with` statement in Python is used to wrap the execution of a block of code within methods defined by the context manager. It ensures that cleanup is properly handled, even if exceptions occur.

Answer:

Modules are Python files containing Python definitions and statements. Packages are namespaces that contain multiple modules.

Answer:

`__str__` is used to find the 'informal' or nicely printable string representation of an object, while `__repr__` is used to find the 'official' string representation of an object.

class Person:
  def __init__(self, name):
    self.name = name
  def __str__(self):
    return f'Person({self.name})'
  def __repr__(self):
    return f'Person({self.name})'

Answer:

File I/O in Python is handled using file objects with methods such as `open()`, `read()`, `write()`, `close()`, and using context managers with the `with` statement for automatic cleanup.

Answer:

Decorators in Python are functions that modify the functionality of another function or method. They are used to wrap another function, modifying its behavior.

Answer:

Generators in Python are functions that enable us to create iterators. They generate values in an iterative manner using `yield` rather than `return`.

Answer:

`__str__` is used to find the 'informal' or nicely printable string representation of an object, while `__repr__` is used to find the 'official' string representation of an object.

class Person:
  def __init__(self, name):
    self.name = name
  def __str__(self):
    return f'Person({self.name})'
  def __repr__(self):
    return f'Person({self.name})'

Answer:

Python's built-in data types include integers, floats, complex numbers, strings, lists, tuples, dictionaries, sets, and booleans.

Answer:

`*args` and `**kwargs` allow a function to accept variable-length argument lists. `*args` collects extra positional arguments as a tuple, while `**kwargs` collects extra keyword arguments as a dictionary.

def example(*args, **kwargs):
  print(args)
  print(kwargs)
example(1, 2, a='apple', b='banana')

Answer:

A lambda function in Python is a small anonymous function defined with the `lambda` keyword. It can have any number of arguments but only one expression. Lambda functions are syntactically restricted to a single expression.

Answer:

`pass` is a null statement in Python, used as a placeholder where syntax requires a statement but you have nothing to write.

Answer:

`__init__` is a special method in Python classes that is automatically called when a new instance of the class is created. It initializes the object's attributes.

Answer:

Iterators in Python are objects that implement the iterator protocol, consisting of the `__iter__()` method that returns the iterator object itself and the `__next__()` method that returns the next item in the sequence.

Answer:

`__iter__()` returns the iterator object itself and is called when the iterator is initialized. `__next__()` returns the next item in the sequence and is called subsequently to fetch the next item.

class MyIterator:
  def __init__(self, max=0):
    self.max = max
    self.n = 0
  def __iter__(self):
    return self
  def __next__(self):
    if self.n <= self.max:
      result = 2 ** self.n
      self.n += 1
      return result
    else:
      raise StopIteration
my_iter = MyIterator(3)
for i in my_iter:
  print(i)

Answer:

`range()` in Python 2.x returns a list, while `xrange()` returns an xrange object which is an iterator and yields values on demand, making it more memory efficient for large ranges.

for i in xrange(5):
  print(i)

Answer:

List comprehensions provide a concise way to create lists. They consist of brackets containing an expression followed by a `for` clause, then zero or more `for` or `if` clauses.

Answer:

Decorators in Python are functions that modify the functionality of another function or method. They are used to wrap another function, modifying its behavior.

Answer:

Generators in Python are functions that enable us to create iterators. They generate values in an iterative manner using `yield` rather than `return`.

Answer:

Closures in Python are functions that retain the environment in which they were created. They remember the outer function's variables even after the outer function has finished executing.

def outer_func(x):
  def inner_func(y):
    return x + y
  return inner_func
add_five = outer_func(5)
print(add_five(3)) # 8

Answer:

File I/O in Python is handled using file objects with methods such as `open()`, `read()`, `write()`, `close()`, and using context managers with the `with` statement for automatic cleanup.

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

Answer:

Context managers in Python are objects that define the runtime context to be established when executing a `with` statement. They implement `__enter__()` and `__exit__()` methods to set up and tear down the context.

Answer:

`enumerate()` function adds a counter to an iterable and returns it as an enumerate object. This is useful for obtaining an indexed list along with the values obtained from iterating over it.

Answer:

`__name__` is a special variable in Python that is automatically set for the module in which the code is running. It is mainly used for testing or executing the code within the module.

Answer:

`map()` function applies a given function to all the items in an input iterable and returns an iterator of the results. It allows you to apply a function to each item in a list or other iterable.

def square(x):
  return x * x
numbers = [1, 2, 3, 4]
squared = list(map(square, numbers))

Answer:

Magic methods in Python are special methods that start and end with double underscores (`__`). They enable customization of how objects behave in operations such as addition, comparison, and type conversion.

Answer:

`__str__()` is used to find the 'informal' or nicely printable string representation of an object, while `__repr__()` is used to find the 'official' string representation of an object.

Answer:

`__init__()` is a special method in Python classes that is automatically called when a new instance of the class is created. It initializes the object's attributes.

Answer:

Python uses reference counting and a garbage collector to manage memory. Objects are automatically deallocated when their reference count reaches zero, and cyclic references are handled by the garbage collector.

Answer:

Exceptions in Python are handled using try-except blocks. Code that might raise an exception is written in the `try` block, and handling of the exception is implemented in the `except` block.

Answer:

Modules are Python files containing Python definitions and statements. Packages are namespaces that contain multiple modules.

Answer:

`sys.argv` is a list in Python that contains command-line arguments passed to a script. The first item in the list is the script's name.

Answer:

`super()` function in Python is used to call a method from a parent class. It allows access to methods and properties of a parent class.

class Parent:
  def __init__(self, name):
    self.name = name

class Child(Parent):
  def __init__(self, name, age):
    super().__init__(name)
    self.age = age

Answer:

Python's built-in decorators include `@staticmethod` and `@classmethod`. `@staticmethod` defines a method that does not access or modify class state and is bound to the class rather than an instance. `@classmethod` defines a method that operates on the class rather than instances.

Answer:

The Global Interpreter Lock (GIL) in Python is a mutex that protects access to Python objects, preventing multiple native threads from executing Python bytecodes at once. This can limit multi-threading performance in CPU-bound tasks but does not affect I/O-bound tasks.

Answer:

`__slots__` is used in Python classes to explicitly declare instance attributes and allocate space for them in memory. It can improve memory usage and performance for classes with a large number of instances.

class Person:
  __slots__ = ['name', 'age']
  def __init__(self, name, age):
    self.name = name
    self.age = age

Answer:

`__getitem__()` and `__setitem__()` are special methods in Python used for indexing and accessing elements of objects. `__getitem__()` allows retrieving items using square bracket notation, while `__setitem__()` allows assigning items using square bracket notation.

Answer:

The `functools` module in Python provides higher-order functions and operations on callable objects. It includes functions like `partial()` for partial function application, `reduce()` for applying a function to a sequence, and `lru_cache()` for caching function results.

Answer:

`asyncio` is a library in Python that provides infrastructure for writing asynchronous I/O-bound and high-level concurrent code using coroutines. It allows managing event loops, asynchronous tasks, and synchronization primitives.

Answer:

Descriptors in Python are objects that define methods `__get__()`, `__set__()`, or `__delete__()` which allow for fine-grained control over attribute access. They are used to create properties, methods, and classes with automatic method invocation.

Answer:

Metaclasses in Python are classes that define the behavior and structure of other classes. They are used for customizing class creation, adding or modifying class attributes and methods, and controlling the initialization of new class instances.

Answer:

Type annotations in Python allow specifying the type of variables, function parameters, and return values. They provide optional static typing for improved code readability, documentation, and tooling support, although they do not enforce type constraints at runtime.

Answer:

`__enter__()` and `__exit__()` methods are used in Python context managers to define the entry and exit points of the runtime context established by the `with` statement. They handle resource management and cleanup.

Answer:

F-strings in Python are formatted string literals prefixed with 'f' or 'F'. They allow embedding expressions inside string literals, making string formatting concise and readable.

Answer:

`__all__` is a list in Python modules that specifies the names of public objects (functions, classes, variables) that should be imported when `from module import *` is used. It controls what is accessible to the outside world.

__all__ = ['public_func', 'PublicClass']

Answer:

`__doc__` is a special attribute in Python that holds the docstring or documentation string of a module, class, function, or method. It is used to provide documentation and help text.

Answer:

`logging` is a built-in module in Python that provides a flexible framework for logging messages from Python programs. It allows logging messages with different severity levels, configuring log handlers and formatters, and integrating with various output destinations.

Answer:

`__call__` method in Python allows an instance of a class to be called as if it were a function. It is useful for creating callable objects that maintain state across multiple calls.