100+ Python Software Developer Interview Questions and Answers

The super keyword is used to call the superclass's methods and constructors in a subclass in Python.

• super() is used to call the superclass's methods and constructors in a subclass.

• It helps in achieving method overriding and method resolution order in multiple inheritance.

• super() is commonly used in the __init__() method of a subclass to initialize the superclass's attributes.

Yes, I have implemented context managers in my applications.

• Implemented context managers using the 'with' statement in Python

• Used contextlib module to create custom context managers

• Managed resources like file handling, database connections, and locks using context managers

Byte code is a low-level code that is executed by the Python interpreter. Filter function is used to filter elements from an iterable.

• Byte code is a compiled code that is generated from Python source code.

• It is a platform-independent code that can be executed on any system with a Python interpreter.

• Filter function takes an iterable and a function as input and returns a new iterable with elements for which the function returns True.

• Example: filter(lambda x: x % 2 == 0, [1, 2, ...read more

Static methods are bound to the class itself, while instance methods are bound to instances of the class. Use @staticmethod decorator for static methods.

• Static methods do not have access to class or instance attributes, while instance methods do.

• Instance methods can modify instance state, while static methods cannot.

• To define a static method in Python, use the @staticmethod decorator before the method definition.

• Example: ```python class MyClass: @staticmethod def static_metho...read more

Inheritance is a mechanism in which a new class inherits attributes and methods from an existing class.

• Inheritance allows a class to reuse code from another class.

• Python supports single, multiple, and multilevel inheritance.

• Example: class ChildClass(ParentClass):

To swap two numbers without using a swap function or a third variable, use arithmetic operations.

• Add the two numbers together and store the result in one of the variables

• Subtract the second number from the sum and store the result in the second variable

• Subtract the original first number from the sum and store the result in the first variable

SQL correlated subqueries are subqueries that reference columns from the outer query.

• Correlated subqueries are executed for each row processed by the outer query.

• They are used to filter results based on values from the outer query.

• Example: SELECT * FROM table1 WHERE column1 = (SELECT MAX(column2) FROM table2 WHERE table2.id = table1.id)

API calls are authenticated using tokens or API keys.

• Use tokens or API keys to authenticate API calls

• Implement OAuth for secure authentication

• Set up API rate limiting to prevent abuse

• Use HTTPS to encrypt data during transmission

Access specifiers in Python control the accessibility of class attributes and methods.

• Access specifiers are not explicitly defined in Python like in other languages such as Java or C++.

• By convention, attributes and methods starting with a single underscore (_) are considered 'protected' and should not be accessed directly.

• Attributes and methods starting with double underscores (__) are considered 'private' and are name-mangled to prevent direct access.

List is mutable, tuple is immutable in Python.

• List is mutable, meaning its elements can be changed after creation.

• Tuple is immutable, meaning its elements cannot be changed after creation.

• List is defined using square brackets [], tuple using parentheses ().

• Example: list_example = [1, 2, 3], tuple_example = (4, 5, 6)

Threading allows multiple tasks to run concurrently. Generator functions produce a sequence of values. Decorators modify functions or methods.

• Threading in Python allows for concurrent execution of tasks.

• Generator functions use the yield keyword to produce a sequence of values.

• Decorators in Python are used to modify the behavior of functions or methods.

• Example: Threading - threading.Thread(target=my_function).start()

• Example: Generator function - def my_generator(): yield 1

• Exam...read more

Iterate through the list and check for pairs that sum up to the target value.

• Iterate through the list and for each element, check if the difference between the target and the element is present in a dictionary.

• If the difference is present in the dictionary, then we have found a pair that sums up to the target.

• If the difference is not present, add the current element to the dictionary.

• Return the pairs that sum up to the target.

Tuple is immutable, list is mutable. Lambda functions are used for small, anonymous functions.

• Tuple is immutable, cannot be changed after creation. List is mutable, can be modified.

• Tuple uses parentheses, list uses square brackets. Example: my_tuple = (1, 2, 3), my_list = [1, 2, 3]

• Lambda functions are used for small, anonymous functions. They can be used as arguments to higher-order functions. Example: lambda x: x*2

A number is even if it is divisible by 2, otherwise it is odd.

• Use the modulo operator (%) to check if a number is divisible by 2.

• If number % 2 == 0, then the number is even.

• For example, 4 % 2 == 0, so 4 is even; 5 % 2 != 0, so 5 is odd.

Create a new list with shuffled order and no duplicate elements.

• Use the random.shuffle() function to shuffle the list

• Use a set to keep track of elements already added to the new list to avoid duplicates

• Convert the set back to a list to maintain the order of elements

List comprehension is a concise way to create lists in Python. Lambda is an anonymous function. Find the second largest in a list.

• List comprehension is a compact way to create lists in Python, using a single line of code.

• Lambda functions are small, anonymous functions defined with the lambda keyword.

• To find the second largest in a list, you can sort the list and then access the second last element.

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

• Python is a high-level programming language used for web development, data analysis, artificial intelligence, and more.

• Benefits of using Python include its simplicity, readability, extensive libraries, and community support.

• A dynamically typed language is one where variable types are determined at runtime, allowing for flexibility but potentially leading to err...read more

Decorators in Python are functions that modify the behavior of other functions or methods.

• Decorators are denoted by the @ symbol followed by the decorator function name.

• They are commonly used for adding functionality to existing functions without modifying their code.

• Decorators can be used for logging, timing, authentication, and more.

• Example: @staticmethod decorator in Python is used to define a method that is not bound to a class instance.

There are two types of Python comments: single-line comments and multi-line comments.

• Single-line comments start with a hash symbol (#) and continue until the end of the line. Example: # This is a single-line comment

• Multi-line comments are enclosed within triple quotes (''' or "). Example: ''' This is a multi-line comment '''

SQL databases are relational databases with structured data and predefined schema, while No-SQL databases are non-relational databases with flexible schema and unstructured data.

• SQL databases use structured query language for defining and manipulating data, while No-SQL databases use various query languages like JSON or XML.

• SQL databases have predefined schema, which means the structure of the data must be defined before inserting data, while No-SQL databases have dynamic sch...read more

Inheritance in Python allows a class to inherit attributes and methods from another class.

• Types of inheritance in Python include single inheritance, multiple inheritance, and multilevel inheritance.

• Single inheritance: a class inherits from only one base class.

• Multiple inheritance: a class inherits from multiple base classes.

• Multilevel inheritance: a class inherits from a derived class, which in turn inherits from another class.

Python is a high-level, interpreted programming language used for web development, data analysis, and artificial intelligence.

• Python is easy to learn and has a simple syntax

• It is widely used in web development frameworks like Django and Flask

• Python is used for data analysis and visualization with libraries like Pandas and Matplotlib

• It is also used in artificial intelligence and machine learning with libraries like TensorFlow and Scikit-learn

Sort a list of numbers and count inversions for each number

• Sort the list of numbers using a sorting algorithm like merge sort or bubble sort

• For each number, count the number of elements that are greater than it but appear before it in the sorted list

• Return the list of numbers with their corresponding inversion counts

Python uses automatic memory management through a combination of reference counting and garbage collection.

• Python uses reference counting to keep track of the number of references to an object.

• When the reference count reaches zero, the object is immediately deallocated.

• Python also employs a garbage collector to handle cyclic references and objects with circular dependencies.

• The garbage collector identifies and collects unreachable objects, freeing up memory.

• Python's garbage c...read more

Monkey patching is a technique in Python where existing code or modules are modified at runtime.

• Monkey patching involves dynamically changing or extending the behavior of a module or class at runtime.

• It can be used to fix bugs, add new functionality, or temporarily change the behavior of existing code.

• Monkey patching can be a powerful tool but should be used carefully to avoid unexpected side effects.

• Example: Adding a new method to an existing class by directly modifying the ...read more

Python is a high-level programming language known for its simplicity and readability. It is dynamically typed, allowing for flexibility and faster development.

• Python is a high-level programming language used for web development, data analysis, artificial intelligence, and more.

• It is known for its simplicity and readability, making it easier for developers to write and maintain code.

• Python is dynamically typed, meaning variables do not need to be declared with a specific data ...read more

Data types in Python define the type of data that a variable can hold.

• Python has several built-in data types such as int, float, str, list, tuple, dict, set, bool, etc.

• Each data type has specific characteristics and operations that can be performed on it.

• Examples: int for integers, float for floating-point numbers, str for strings, list for lists of elements.

A simple program to determine if a number is even or odd.

• Use the modulo operator (%) to check if the number divided by 2 leaves a remainder

• If the remainder is 0, the number is even. Otherwise, it is odd

• Example: num = 6, 6 % 2 = 0 (even); num = 7, 7 % 2 = 1 (odd)

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

• Python is developed using an interpreter, which allows for easy and quick development of programs.

• Python uses a syntax that emphasizes code readability and simplicity.

• Commonly used libraries in Python include NumPy, Pandas, and Matplotlib for data analysis and visualization.

• Python code is written in plain text files with a .py extension.

• Python programs can be run using the command line or an ...read more

Unit testing tests individual units of code while integration testing tests how multiple units work together.

• Unit testing is done by developers and focuses on testing individual functions or methods.

• Integration testing is done by testers and focuses on testing how different modules or components work together.

• Unit tests are usually automated and run frequently during development.

• Integration tests are usually manual and run less frequently.

• Unit tests are faster and easier to d...read more

Tuple is immutable, list is mutable, dictionaries are key-value pairs, and set is a collection of unique elements.

• Tuple: Immutable, ordered collection of elements. Example: (1, 2, 3)

• List: Mutable, ordered collection of elements. Example: [1, 2, 3]

• Dictionaries: Key-value pairs, unordered. Example: {'key1': 'value1', 'key2': 'value2'}

• Set: Collection of unique elements, unordered. Example: {1, 2, 3}

Python data types include integers, floats, strings, lists, tuples, dictionaries, and sets.

• Integers: whole numbers without decimal points, e.g. 5, -3

• Floats: numbers with decimal points, e.g. 3.14, -0.5

• Strings: sequences of characters enclosed in quotes, e.g. 'hello', '123'

• Lists: ordered collections of items, e.g. [1, 'apple', True]

• Tuples: ordered, immutable collections, e.g. (1, 'banana', False)

• Dictionaries: key-value pairs, e.g. {'name': 'Alice', 'age': 30}

• Sets: unordered co...read more

Jinja Templates are important for separating Python code from HTML/CSS in web development.

• Allows for easy integration of Python code into HTML templates

• Promotes code reusability and maintainability

• Helps in creating dynamic web pages by rendering data from Python variables

• Supports template inheritance for creating consistent layouts across multiple pages

Yes, I can handle pressure and work effectively under tight deadlines.

• I thrive in high-pressure situations and have a proven track record of delivering quality work under tight deadlines.

• I prioritize tasks effectively and remain calm and focused when faced with challenging situations.

• I have experience working on projects with tight deadlines, such as developing a critical feature before a product launch.

• I am able to adapt quickly to changing priorities and can efficiently man...read more

A program to check if a given string is a palindrome in Python.

• Create a function that takes a string as input.

• Use string slicing to reverse the input string.

• Compare the reversed string with the original string to check for palindrome.

• Return True if the string is a palindrome, False otherwise.

A one-line function is a function written in a single line of code, typically used for simple operations.

• One-line functions are concise and easy to read, often used for simple tasks like mathematical operations or string manipulation.

• They are commonly used in lambda functions in Python.

• Example: lambda x: x**2

Polymorphism in OOPs refers to the ability of a single function or method to operate on different types of data.

• Polymorphism allows objects of different classes to be treated as objects of a common superclass.

• It enables a single interface to represent different data types.

• There are two types of polymorphism: compile-time (method overloading) and runtime (method overriding).

• Example: In Python, the '+' operator can be used to add numbers or concatenate strings, demonstrating po...read more

Sets are unordered collections of unique elements, while tuples are ordered collections of elements.

• Sets are defined by curly braces {} and tuples are defined by parentheses ()

• Sets do not allow duplicate elements, while tuples can contain duplicate elements

• Sets are mutable, meaning their elements can be added, removed, or modified, while tuples are immutable

• Sets are commonly used for membership testing and eliminating duplicates, while tuples are used for grouping related dat...read more

loc and iloc are methods in Pandas used for selecting rows and columns by label or integer position.

• loc is used for selecting rows and columns by label

• iloc is used for selecting rows and columns by integer position

• Example: df.loc[2, 'column_name'] selects the value at row 2 and column 'column_name'

Python indentation is the spacing at the beginning of a line to define the structure of the code.

• Indentation is used to define blocks of code, such as loops, functions, and classes.

• Python uses indentation to determine the scope and hierarchy of code.

• Incorrect indentation can lead to syntax errors or unexpected behavior.

• Example: if x > 5: print('x is greater than 5')

• Example: def my_function(): print('This is inside my_function')

Mutable data types can be changed after creation, while immutable data types cannot be changed.

• Mutable data types: lists, dictionaries, sets

• Immutable data types: strings, tuples, numbers

• Example: list is mutable - list_1 = [1, 2, 3]; list_1[0] = 4

• Example: tuple is immutable - tuple_1 = (1, 2, 3); tuple_1[0] = 4 will raise an error

During code review, I carefully examine the code for errors, bugs, and adherence to coding standards.

• Check for syntax errors and bugs

• Ensure code follows coding standards and best practices

• Review logic and algorithms for efficiency and correctness

• Provide constructive feedback to the developer

• Verify that tests are included and cover edge cases

Concatenate two strings using lambda functions in Python

• Use a lambda function to concatenate two strings

• Pass the two strings as arguments to the lambda function

• Return the concatenated result

In Python, I have learned about data types, control structures, functions, classes, modules, and libraries.

• Data types such as integers, floats, strings, lists, tuples, dictionaries, and sets

• Control structures like if-else statements, loops, and exception handling

• Functions for code reusability and modularity

• Classes for object-oriented programming

• Modules and libraries for extending Python's functionality

• Example: Learning how to use the 'requests' library for making HTTP request...read more

Use a loop to calculate the cube of each number in the given range and print the result.

• Use a for loop to iterate through the range of numbers

• Calculate the cube of each number using the formula cube = number * number * number

• Print the cube of each number

Shallow copy creates a new object but does not duplicate nested objects, while deep copy creates a new object with all nested objects duplicated.

• Shallow copy only copies the references of nested objects, not the objects themselves.

• Deep copy creates new copies of all nested objects, ensuring complete independence.

• In Python, shallow copy can be achieved using the copy() method, while deep copy can be achieved using the deepcopy() method from the copy module.

Use hashing to find files with duplicate content efficiently.

• Create a hash function to generate a unique identifier for each file's content.

• Store the hash values in a dictionary with the corresponding file paths.

• Identify files with duplicate content by checking for duplicate hash values.

• Return a list of file paths with duplicate content.