Union-Find (also called Disjoint Set Union or DSU) is a data structure that tracks elements split into non-overlapping groups. It answers one question very fast: “Are these two elements in the same group?” It is the best tool for connected components problems and appears in many graph-related interview questions. In this article, you will learn how Union-Find works, why path compression makes it nearly O(1), and how to use it in coding interviews. ...

Every time you type in a search bar and see suggestions appear, a trie is probably working behind the scenes. A trie (pronounced “try”) is a tree-like data structure designed for fast string operations. It is the go-to data structure for autocomplete, spell checkers, and word search problems. In this article, you will learn how tries work, how to build one from scratch, and how to use them in coding interviews. ...

Graphs are one of the most powerful and versatile data structures in computer science. Social networks, maps, dependency systems, and the internet itself are all graphs. Graph problems appear frequently in coding interviews, especially at top tech companies. In this article, you will learn how to represent graphs, traverse them with BFS and DFS, detect cycles, and perform topological sort. We show every example in Kotlin, Python, and Go. What is a Graph? A graph is a collection of vertices (also called nodes) connected by edges. Unlike trees, graphs can have cycles, and nodes can connect to any other node. ...

Everything you need to use Claude in one page. Bookmark this. Come back whenever you need a quick reference for models, APIs, pricing, or code snippets. This is Article 26 in the Claude AI — From Zero to Power User series. Models (March 2026) Model ID Context Max Output Input (per 1M) Output (per 1M) Opus 4.6 claude-opus-4-6 200K 32K $5.00 $25.00 Sonnet 4.6 claude-sonnet-4-6 200K 16K $3.00 $15.00 Haiku 4.5 claude-haiku-4-5 200K 8K $1.00 $5.00 1M Context (Beta): Available for Opus 4.6 and Sonnet 4.6 on Tier 4+ accounts. Requires header: anthropic-beta: interleaved-thinking-2025-05-14. Premium pricing applies above 200K tokens. ...

Android development has changed a lot in the past few years. The ecosystem is no longer centered on XML layouts and basic CRUD apps. In 2026, Android development is shaped by AI-native features, Kotlin-first tooling, multiplatform code, and performance engineering. Many developers are still learning patterns that teams are already moving away from. So the real question is no longer: “How do I build Android apps?” The real question is: ...

A heap is a data structure that always gives you the smallest (or largest) element instantly. It powers priority queues, scheduling systems, and some of the most common interview patterns like “top K elements.” In this article, you will learn how heaps work, how to implement them, and how to use them in coding interviews. We show every example in Kotlin, Python, and Go. What is a Heap? A heap is a complete binary tree that satisfies the heap property: ...

Trees are one of the most important data structures for coding interviews. They appear in about 20-25% of all interview questions at top tech companies. If you are comfortable with trees, you have a big advantage. In this article, you will learn binary trees, tree traversals, and binary search trees (BST). We show every example in Kotlin, Python, and Go. What is a Tree? A tree is a hierarchical data structure made of nodes connected by edges. It looks like an upside-down tree — the root is at the top, and the leaves are at the bottom. ...

Hash maps are the most useful data structure for coding interviews. If you can only master one data structure beyond arrays, make it hash maps. They give you O(1) average-time lookups, insertions, and deletions. Many interview problems that seem hard become easy once you use a hash map. In this article, you will learn how hashing works, when to use hash maps vs hash sets, and how to solve classic interview problems. We show every example in Kotlin, Python, and Go. ...

Stacks and queues are two of the most fundamental data structures in computer science. They are building blocks for many algorithms and appear frequently in coding interviews. The rules are simple — stacks follow Last In, First Out (LIFO), and queues follow First In, First Out (FIFO). In this article, you will learn how stacks and queues work, how to implement them, and how to solve classic interview problems. We show every example in Kotlin, Python, and Go. ...

Claude API costs add up fast if you are not careful. A simple change like enabling prompt caching can cut your bill by 90%. Using the Batch API saves 50%. Stack them together and you save up to 95%. This is Article 25 in the Claude AI — From Zero to Power User series. You should know Understanding Models and Extended Thinking before this article. The Cost Equation Your Claude API cost is determined by three factors: ...