Open-source alternatives to Leetcode

AlgoNote is an algorithm and data structure tutorial and computer science study manual. It serves as a technical library of algorithm implementations and data structure patterns, providing a comprehensive learning guide focused on technical interview preparation. The project functions as a LeetCode solution guide, containing analyzed and implemented solutions for over one thousand coding challenges. All implementations are written in Python to provide a consistent coding reference. The resource covers the study of algorithm fundamentals, the resolution of diverse coding challenges, and prepa

This project is an algorithm interview preparation guide and reference library. It provides a curated collection of solved programming problems and data structure implementations designed for technical interview practice and competitive programming study. The repository distinguishes itself by organizing coding challenges through a system of patterns, difficulty levels, and company-based filtering. It includes instructional resources such as algorithmic concept notes and video explanations to supplement the solution sets. The library covers a wide range of computational areas, including adva

This project is a comprehensive knowledge base and study resource designed for mastering technical interviews. It provides structured guides, roadmaps, and curricula focused on data structures, algorithms, system design, and frontend engineering to help candidates prepare for software engineering screenings. The repository distinguishes itself by offering a holistic approach to professional advancement. Beyond technical drills, it includes a career development handbook covering resume optimization, salary benchmarking, and strategic negotiation coaching. It also provides detailed methodologie

This project is a comprehensive technical knowledge base and study guide focused on data structures, algorithms, and computer science fundamentals. It provides a curated collection of tutorials and educational resources designed to support technical growth and academic learning. The repository distinguishes itself through a heavy emphasis on visual learning, utilizing mind maps, diagrams, and illustrated breakdowns to explain complex algorithmic logic. It further supports career readiness by providing a repository of company-specific interview questions and real-world candidate experiences.

This project is an algorithm study resource, a centralized LeetCode solution repository, and a technical interview study guide. It provides Chinese translations of textbooks and guides on data structures and algorithms for academic study and professional preparation. The project distinguishes itself by delivering multi-language solution repositories and translated academic materials through a static site generation model. This architecture enables compile-time content translation and offline-first delivery of educational assets as static files. The repository covers a wide range of algorithm

Algodeck is an open-source collection of flash cards designed for reviewing algorithms, data structures, and system design concepts, specifically curated for technical interview preparation. The project organizes knowledge into atomic question-and-answer pairs and incorporates spaced repetition scheduling to optimize long-term memory retention. The flash card catalog covers a broad range of computer science topics, including classic sorting algorithms like quicksort and mergesort, data structure operations for arrays, trees, heaps, tries, and graphs, as well as bit manipulation techniques for

leetcode_101 is a curated library of algorithmic problem sets and a repository of solved LeetCode challenges. It serves as a technical interview guide by providing code implementations for common software engineering interview questions. The project supports a technical interview preparation workflow, focusing on LeetCode problem solving and the study of standardized code solutions for data structures and algorithms. It is designed to facilitate coding skill development and the study of technical interview problems. The repository utilizes markdown-based content authoring and a static-file d

This project is a reference library of Java implementations for algorithmic coding challenges and data structure patterns. It serves as a study guide for technical interview preparation, providing a curated collection of LeetCode solutions organized by difficulty and algorithmic technique. The collection includes a mapping system that associates specific algorithm problems with the companies that frequently use them in technical interviews. The repository covers a wide range of capability areas, including tree algorithms for hierarchy construction and verification, string processing for sequ

This project is a LeetCode solution repository and algorithm reference library. It provides a structured collection of solved coding challenges that demonstrate recurring computational strategies, data structure implementations, and complexity optimizations used for technical interview preparation and competitive programming study. The repository transforms structured source code and technical explanations into professional PDF guides using a LaTeX technical documentation system. To ensure consistent typography and environment settings across different systems, the project utilizes a containe

This project is a LeetCode solution repository containing a collection of algorithmic and database problem solutions. It serves as an algorithm implementation guide and a competitive programming reference, providing optimized code to demonstrate data structure usage and efficient coding patterns. The repository includes solutions for complex computational challenges implemented in multiple programming languages and a collection of SQL queries for data retrieval and manipulation across various difficulty levels. These resources are designed for competitive programming study and technical inter

This project is a collection of datasets and study guides consisting of curated algorithmic problems organized by employer for technical interview practice. It serves as a reference for identifying frequently asked coding challenges used by major companies during software engineering recruitment. The repository provides curated company problem sets and a discovery mechanism to identify common coding problems associated with specific employers. These lists are organized by frequency of occurrence to highlight typical technical challenges. The content is structured as a competitive programming

This repository is a collection of optimized source code implementations for LeetCode algorithmic challenges. It serves as both a Python and Java algorithm library, providing solved computational problems for these two languages. The project focuses on data structure implementation, providing code examples that demonstrate how to use complex structures to resolve logical processing tasks. It covers a range of computational problems, including string searching and integer parsing. The repository is designed for competitive programming practice and technical interview preparation, with a focus

This project is a collection of condensed technical references and study guides for the C++ language. It serves as a language cheat sheet and programming reference covering core syntax, standards, and data organization patterns. The resource provides specialized guides for algorithm study, data structure reference, and technical interview preparation. It includes materials for reviewing computational complexity and efficient data structure usage for competitive programming. The content covers broad capability areas including object-oriented programming, memory management, and generic program

This project is a curated collection of solved algorithmic challenges and reference implementations. It serves as a study guide for software engineering, providing a library of data structure and algorithm problems used to analyze efficient problem-solving techniques. The repository functions as a solution reference for coding challenges across multiple programming languages. It includes source code examples and conceptual hints designed for technical interview preparation and the study of common coding patterns. The content is organized as a static source code repository with language-speci

AI-Job-Notes is a curated job hunting guide and technical interview curriculum specifically for artificial intelligence and computer vision roles. It functions as a markdown knowledge base and static site repository that organizes recruitment data, study materials, and company lists. The project provides resources for AI algorithm job hunting, including company directories and salary benchmarks based on geography and educational background. It covers campus recruitment planning through the tracking of application windows and internship cycles. The repository includes materials for technical

tech-vault is a command-line technical interview bank and knowledge base designed for practicing engineering questions across various technical domains. It functions as a terminal-based application that stores structured study materials and interview questions as markdown files, which are then rendered directly within the system console. The project distinguishes itself through a delivery model that uses command-line argument parsing to filter content by topic or difficulty. It also includes a random selection algorithm to pick individual questions from the collection for spontaneous study se

This project is a technical interview study guide and algorithm reference library. It provides a collection of Python implementations for algorithmic challenges and data structure problems common to software engineering coding assessments. The repository serves as a resource for coding interview solutions, featuring documented code samples for sorting, searching, and optimization algorithms. It includes an automated solution test suite to verify the correctness of these implementations across various edge cases. The project emphasizes the use of idiomatic Python patterns and standard library

CLRS is an algorithm implementation library and reference providing code solutions for the classic computer science problems and theoretical concepts found in Introduction to Algorithms. It serves as a computer science study guide and a set of textbook exercise solutions used for academic study and the verification of time and space complexity. The project is a multi-language algorithm library, implementing theoretical algorithms across several programming languages to demonstrate cross-language application and behavior. This approach allows for the study of different memory management and sy

Gridea is a desktop application for writing Markdown blog posts and publishing them as a static site without needing a server. It stores all content as plain Markdown files and JSON in a local folder, compiles them into a static site, and deploys the result to multiple remote targets including GitHub Pages, Coding Pages, and SFTP servers. The application runs as a cross-platform Electron client, providing a native editing and publishing experience. It supports custom themes that can be selected, installed from a built-in marketplace, and configured with settings like social links and analytic

This project is a technical interview study guide and a markdown-driven static site designed to help developers prepare for coding screenings. It serves as a curated collection of common technical questions and expert answers, functioning as a comprehensive educational resource. The platform provides a structured curriculum and reference materials across several key domains. This includes a JavaScript language reference covering programming fundamentals, a frontend engineering curriculum focused on UI patterns and responsive design, and a web security knowledge base detailing attack vectors a

This project is a markdown knowledge base used to maintain a curated collection of concise technical notes and write-ups across various programming languages and tools. It serves as a searchable personal reference library for documenting technical discoveries and software development patterns. The system implements a learning in public workflow, transforming markdown-based content storage into a static site. It utilizes directory-based routing to map folder structures to URL paths and employs schema-driven type generation to ensure data consistency across the knowledge base. The codebase cov

AlgorithmsByPython is a reference library and educational repository providing runnable Python implementations of computer science fundamentals. It serves as a comprehensive guide for algorithmic patterns, core data structures, and solutions for competitive programming and technical interview challenges. The project distinguishes itself by offering a wide array of reference implementations, including a dedicated set of solutions for common LeetCode problems. It focuses on translating theoretical computational logic into practical Python code for educational and practical use. The repository

This project is a technical interview question bank and coding interview study guide. It serves as a company-specific assessment aggregator that organizes curated collections of algorithmic problems and solutions by company and role. The study guide is built as a static site that pre-renders markdown data files into HTML pages. It features a client-side search engine that enables instant filtering of interview questions directly in the browser without server requests. The system manages a broad set of capabilities for technical interview preparation, including the aggregation of company asse

Mianshiya is a community-driven technical interview preparation platform that hosts a curated database of over 10,000 interview questions across programming domains. It functions as a collaborative Q&A platform where users can browse, filter, and sort questions by difficulty, tags, and type, while also editing and improving answers collectively to build a shared knowledge base. The platform distinguishes itself through cross-platform study synchronization, allowing progress to be tracked and resumed seamlessly across web, mini-program, and IDE plugin environments. It includes a custom exam ge

This project is a comprehensive set of roadmaps and curricula designed for technical, behavioral, and architectural interview mastery. It provides structured guides, frameworks, and checklists for mastering algorithmic coding, system design, and behavioral questions. The resource is distinguished by specialized study paths, including a frontend engineering curriculum and a dedicated system design framework for architecting scalable systems. It also features a behavioral interview playbook that utilizes a standardized response method to align professional experience with company values. The g

cp-notebook is an algorithmic knowledge base and implementation library designed for competitive programming practice. It serves as a system for computational problem solving, allowing for the organization of problem sets, solution templates, and the study of competition mathematics. The project utilizes a taxonomy-based tagging system and schema-driven organization to map computational tasks to a consistent file structure. It employs a language-agnostic template engine and markdown-based rendering to transform raw text and code snippets into a formatted, static knowledge base for fast lookup

Assemble is a static site generator and build pipeline system that compiles markdown, templates, and data into static HTML files. It functions as a markdown-to-HTML converter and a data format transformer capable of moving content between JSON, YAML, XML, PLIST, and CSV formats. The project features a pipeline-based build process where users can define ordered sequences of data transformations and file processing steps. It includes project scaffolding tools to bootstrap directory structures and configuration files from predefined boilerplates. The system manages content through collection-ba