Learnitweb

Author: Editorial Team

  • Dictionary (dict) in Python

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    This tutorial provides a complete and detailed explanation of Python dictionaries, how they work internally, how to create, access, update, and delete elements, and how dictionaries behave in real-world programs. The structure follows the same format as your earlier Python tutorials on int, float, complex, typecasting, and immutability. 1. Introduction to Python Dictionaries A dictionary…

  • Python Frozen Set Tutorial

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    Introduction Up to this point, we have already covered three major Python data structures: list, tuple, and set. Each of them addresses different requirements depending on whether you need ordering, mutability, or uniqueness. Before learning frozen sets, it is important to recall the core behavior of these three data types so the concept of a…

  • Python Set tutorial

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    Introduction In Python programming, we sometimes need to represent a group of values where the order of elements does not matter, and duplicates should be removed automatically. Lists and tuples allow duplicates and preserve order, but certain situations require the exact opposite. For example, if you are sending SMS messages to a group of students…

  • Python tuple data type

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    Introduction Tuples are one of the most commonly used data structures in Python, especially when you want to represent fixed, read-only data. While they look very similar to lists, their behavior is quite different in one crucial aspect. Lists allow modification, but tuples do not. This difference creates meaningful changes in how Python stores tuples…

  • Pessimistic and Optimistic Locking in Oracle and JPA

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    1. Introduction When multiple users or threads access and modify the same data concurrently, data integrity becomes a serious concern.For example, consider a banking system where two users try to withdraw money from the same account simultaneously — without proper locking, you could easily end up with inconsistent or lost updates. To handle this, databases…

  • Understanding PKCE (Proof Key for Code Exchange) in JWT Authentication

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    1. Introduction When dealing with modern authentication flows, especially in web and mobile applications, security becomes the top priority.OAuth 2.0 introduced the Authorization Code Flow to enable secure access delegation — where users can grant access to applications without sharing their passwords. However, traditional Authorization Code Flow had a weakness — it relied on the…

  • What is Parameter, Token, and Context in Machine Learning

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    1. Introduction Machine learning (ML) models, especially those involved in natural language processing (NLP) and large language models (LLMs) such as GPT, BERT, or Gemini, rely on three fundamental concepts: parameters, tokens, and context. These three ideas describe how: To understand how modern AI systems operate — how they read, remember, and respond intelligently —…

  • Understanding Character Text Splitter vs. Recursive Character Text Splitter

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    In this tutorial, we continue our exploration of text splitting techniques in LangChain, focusing on one of the most fundamental operations in any Retrieval-Augmented Generation (RAG) pipeline — preparing text data for large language models. In the previous tutorial, we discussed the Recursive Character Text Splitter, learned how to use it in code, and explored…

  • Text Splitting Techniques – RecursiveCharacterTextSplitter

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    In this tutorial, we continue our journey into LangChain, a powerful framework that connects large language models (LLMs) with external data sources and tools. In the previous part, we explored data ingestion techniques using different document loaders to read content from PDFs, text files, web pages, and Wikipedia. Now, we move to the next critical…

  • Data Ingestion with Document Loaders

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    In this tutorial, we will explore how data ingestion works in LangChain — the very first step in building any Generative AI pipeline. LangChain provides a structured way to load, transform, and store data so that it can later be used for retrieval-based question answering, semantic search, or chatbot applications powered by large language models…