Knowledge Factory

Here are 10 advanced Python interview questions related to Data Structures and Algorithms (DSA) , along with in-depth answers: 1. How do you find the k-th largest element in an array? Problem: Find the k-th largest element in an unsorted array. Solution: import heapq def find_kth_largest (nums, k) : return heapq.nlargest(k, nums)[ -1 ] # Example nums = [ 3 , 2 , 1 , 5 , 6 , 4 ] k = 2 print(find_kth_largest(nums, k)) # Output: 5 Step-by-Step Explanation: Importing heapq : The heapq module in Python provides an implementation of the heap queue algorithm, also known as the priority queue algorithm. Defining the Function : The function find_kth_largest(nums, k) takes two arguments: nums : A list of numbers. k : An integer representing the position of the largest element we want to find. Using heapq.nlargest() : The heapq.nlargest(k, nums) function returns a list of the k largest elements from the nums list, sorted in descending order. For example, heapq.nlargest(2, [3, ...

To integrate Google Cloud Storage (GCS) with a Django application for file upload, download, list, and delete operations , follow these steps: 1. Set Up Google Cloud Storage Create a Google Cloud Project : Visit the Google Cloud Console and create a new project or use an existing one. Enable the Cloud Storage API : Navigate to APIs & Services > Library , search for "Cloud Storage," and enable it. Create a GCS Bucket : Go to Storage > Browser in the console. Click Create Bucket , choose a globally unique name, configure settings, and create it. Set Up a Service Account : Go to IAM & Admin > Service Accounts , create a service account, and assign the Storage Admin role. Generate a key (JSON) for the service account and download it to your local machine. 2. Configure Django for GCS Install Required Libraries : Install the Google Cloud Storage and Django libraries: pip install google-cloud- storage django-storages Set Up the Django Storage Backend : Add th...

Integrating Django with Amazon Bedrock's Nova can enable your Django application to leverage advanced AI models for text generation, summarization, or other natural language tasks provided by Nova. A little bit of background What is Amazon Bedrock? Amazon Bedrock is an AWS-managed service that allows developers to build and scale generative AI applications by interacting with pre-trained foundational models. Bedrock supports multiple models from third-party providers and Amazon's proprietary models. Key Features: No infrastructure management. Serverless access to large language models (LLMs). Integrates with AWS ecosystem (IAM, Lambda, etc.). Pay-as-you-go pricing. What is Nova in Amazon Bedrock? Nova is one of the foundational models integrated into Bedrock. These models are designed to handle a variety of generative AI tasks such as: Text generation Summarization Question answering Language understanding Nova's Highlights: General-Purpose Model: Optimized for wide-ranging...