10+ Python Developer Lead Interview Questions and Answers

List comprehension is a concise way to create lists in Python by iterating over an existing list or iterable.

• List comprehension is more concise and readable than traditional loops.

• It can be used to filter elements, perform operations on elements, or create new lists based on existing ones.

• Example: squares = [x**2 for x in range(10)]

• Example: even_numbers = [x for x in range(10) if x % 2 == 0]

Hash mapping is a technique used to map keys to values in a data structure.

• Hash mapping involves using a hash function to generate a unique index for each key, allowing for efficient retrieval of values.

• Mutable objects can be modified after creation, while immutable objects cannot be changed.

• Bugsnag is a library used for monitoring and reporting errors in software applications.

• Agile microservices development model involves developing software in small, independent services th...read more

A dictionary in Python is a collection of key-value pairs. It does not accept duplicate keys.

• A dictionary is created using curly braces {}

• Keys in a dictionary must be unique, but values can be duplicated

• Example: my_dict = {'name': 'John', 'age': 30, 'city': 'New York'}

Main principles of OOP include encapsulation, inheritance, polymorphism, and abstraction.

• Encapsulation: Bundling data and methods that operate on the data into a single unit (class). Example: Class with private attributes and public methods.

• Inheritance: Ability to create a new class (derived class) from an existing class (base class), inheriting its attributes and methods. Example: Subclass 'Dog' inheriting from superclass 'Animal'.

• Polymorphism: Ability for objects of differe...read more

Code deployment involves creating pipelines to automate the process of moving code from development to production.

• Use version control systems like Git to manage code changes.

• Set up continuous integration/continuous deployment (CI/CD) pipelines to automate testing and deployment.

• Utilize tools like Jenkins, Travis CI, or GitLab CI to create and manage pipelines.

• Define stages in the pipeline such as build, test, deploy, and monitor for each code change.

• Implement infrastructure a...read more

Use pandas library for efficient loading and processing of large files in Python.

• Use pandas read_csv() function with chunksize parameter to load large files in chunks.

• Optimize memory usage by specifying data types for columns in read_csv() function.

• Use pandas DataFrame methods like groupby(), merge(), and apply() for efficient data processing.

• Consider using Dask library for parallel processing of large datasets.

• Use generators to process data in chunks and avoid loading entire...read more

Code to filter anagram from an array of strings

• Create a dictionary to store sorted strings as keys and original strings as values

• Iterate through the array of strings and sort each string to check for anagrams

• Return the values of the dictionary to get the filtered anagrams

AWS Lambda is a serverless computing service provided by Amazon Web Services.

• Serverless computing service

• Allows running code without provisioning or managing servers

• Automatically scales based on incoming traffic

• Supports multiple programming languages like Python, Node.js, Java, etc.

• Pay only for the compute time consumed

Fibonacci series is a sequence of numbers where each number is the sum of the two preceding ones.

• Initialize variables for the first two numbers in the series (0 and 1)

• Use a loop to calculate the next number by adding the previous two numbers

• Continue the loop until the desired number of terms is reached

List is mutable, tuple is immutable in Python.

• List can be modified after creation, tuple cannot.

• List uses square brackets [], tuple uses parentheses ().

• List is used for dynamic data, tuple for fixed data.

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

Numpy is a powerful library for numerical operations in Python, with efficient array operations and mathematical functions.

• Use vectorized operations instead of loops for better performance.

• Avoid unnecessary copying of arrays to save memory.

• Utilize broadcasting to perform operations on arrays of different shapes.

• Use numpy functions like np.sum(), np.mean(), np.max(), etc. for efficient calculations.

• Optimize code by profiling and identifying bottlenecks.

Type of inheritance in object-oriented programming determines how a subclass can inherit attributes and methods from a superclass.

• Single inheritance: a subclass inherits from only one superclass.

• Multiple inheritance: a subclass inherits from multiple superclasses.

• Multilevel inheritance: a subclass inherits from a superclass, which in turn inherits from another superclass.

• Hierarchical inheritance: multiple subclasses inherit from a single superclass.

• Hybrid inheritance: a combi...read more

Generate all valid combinations of parentheses for given n pairs

• Use backtracking to generate all valid combinations of parentheses

• Keep track of the number of open and close parentheses used

• Add open parenthesis if there are remaining open parentheses, add close parenthesis if there are more open than close parentheses

Optimizing code for better performance and efficiency

• Use built-in functions and libraries for faster execution

• Minimize unnecessary loops and conditions

• Avoid redundant code and optimize data structures

• Implement caching or memoization for repetitive computations

Optimizing Python code involves improving efficiency and performance.

• Use built-in functions and libraries instead of writing custom code

• Avoid unnecessary loops and nested loops for better performance

• Optimize data structures and algorithms for faster execution

A linked list is a data structure consisting of nodes where each node points to the next node in the sequence.

• Create a Node class with data and next pointer

• Create a LinkedList class with methods like insert, delete, search

• Example: Node class - class Node: def __init__(self, data): self.data = data self.next = None