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I applied via LinkedIn and was interviewed in Mar 2024. There were 2 interview rounds.
It was easy
posted on 12 Sep 2021
I applied via LinkedIn and was interviewed in Aug 2021. There were 3 interview rounds.
Design a system for managing car parking.
Determine the size and layout of the parking lot.
Decide on the type of parking system (e.g. self-parking, valet).
Implement a ticketing system for tracking cars and payments.
Use sensors or cameras to monitor parking spaces.
Integrate with a payment gateway for online payments.
Provide real-time information on available parking spaces.
Consider implementing a loyalty program for freq
Designing a system for an elevator
Identify the requirements and constraints
Determine the number of floors and elevators needed
Choose the elevator algorithm (e.g. FCFS, SCAN, LOOK)
Design the elevator controller
Consider safety features (e.g. emergency stop, overload protection)
Include user interface (e.g. buttons, displays)
Consider maintenance and repair
Test and optimize the system
A photo-sharing app system design
Use a scalable architecture to handle large amounts of data
Implement a secure authentication and authorization system
Utilize a content delivery network (CDN) for fast image loading
Allow users to tag and categorize photos for easy search and discovery
Implement a notification system for likes, comments, and new followers
I applied via LinkedIn and was interviewed before Aug 2021. There were 4 interview rounds.
I applied via Recruitment Consultant and was interviewed before May 2020. There were 5 interview rounds.
Very hard question and 4 qs in total
posted on 14 Feb 2023
I applied via Recruitment Consulltant and was interviewed in Jan 2023. There were 2 interview rounds.
The project is a REST API that provides a response to client requests.
The project is built using a RESTful architecture.
It provides endpoints for clients to interact with the server.
The response format is typically JSON or XML.
Examples of endpoints include /users, /products, and /orders.
Pagination in API is done by setting limit and offset parameters in the request.
Set a limit parameter to specify the number of results per page.
Set an offset parameter to specify the starting point of the page.
Return the total number of results and the current page number in the response.
Example: /api/users?limit=10&offset=20
Example response: {"results": [...], "total": 100, "page": 3}
I applied via AmbitionBox and was interviewed in Oct 2022. There were 2 interview rounds.
I applied via LinkedIn and was interviewed in May 2022. There were 3 interview rounds.
General Questions were asked on probability, reasoning, logical etc
Coding questions were easy to medium. There were 2 questions 1 was easy and other was medium. It had 45 mins as time limit
Python has several built-in datatypes including int, float, bool, str, list, tuple, set, and dict.
int - represents integers
float - represents floating-point numbers
bool - represents boolean values True and False
str - represents strings
list - represents ordered sequences of values
tuple - represents ordered, immutable sequences of values
set - represents unordered collections of unique values
dict - represents unordered co
Flask is a micro web framework while Django is a full-stack web framework.
Flask is lightweight and flexible, allowing developers to choose their own libraries and tools.
Django is a batteries-included framework with built-in ORM, admin interface, and authentication system.
Flask is ideal for small to medium-sized projects, while Django is better suited for larger, more complex projects.
Flask has a smaller learning curve ...
Flask is lightweight and good for small projects, while Django is more robust and suitable for larger projects.
Flask is good for small projects with simple requirements
Django is more suitable for larger projects with complex requirements
Flask is lightweight and flexible, allowing for more customization
Django has a lot of built-in features and is more opinionated
Flask is better for RESTful APIs and microservices
Django i...
Decorators are functions that modify the behavior of other functions or classes without changing their source code.
Decorators are denoted by the @ symbol in Python.
They can be used to add functionality to a function or class, such as logging or timing.
Decorators can also be used to modify the behavior of a function or class, such as adding caching or memoization.
Decorators can be chained together to apply multiple modi
Generators are functions that can be paused and resumed, allowing for lazy evaluation of data.
Generators use the yield keyword to pause execution and return a value.
They can be used to generate an infinite sequence of values.
Generators are memory efficient as they only generate values when needed.
They are commonly used in data processing and asynchronous programming.
range and xrange are used to generate a sequence of numbers in Python.
range returns a list of numbers while xrange returns an iterator object.
range is memory-intensive while xrange is memory-efficient.
range is used in Python 3 while xrange is used in Python 2.
range can take three arguments: start, stop, and step while xrange can take two arguments: start and stop.
based on 1 interview
Interview experience
Oracle
Amdocs
Automatic Data Processing (ADP)
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