Data Structures

Plain-language explanations, Java implementations, and step-by-step visual walkthroughs help you connect the problem, the code, and the changing state of the data. Every algorithm is printed in full color, so rows, columns, regions, and changing values stand apart at a glance and are easy to trace. 

Think. Implement. Solve. — Learn the logic. Write the code. Solve the problem.

Build collaborative software that keeps working when the network does not. This practical guide takes you from distributed systems fundamentals to working CRDT implementations and production-ready collaboration. Learn how CRDTs work, where they fit and how to handle scaling, security, metadata growth and failure in real systems.

Most algorithm books are catalogues: here is a technique, here is its proof, here are exercises. This one withholds the name of every technique until after you have built it.

What really makes a compression system fast, efficient and effective? Using bzip3 as a practical case study, this book breaks down the building blocks behind modern compression, from data transforms and match finding to entropy coding and parallel processing. Learn how to design, implement and tune compression systems for real-world performance.

What really happens between typing a SQL query and getting a result? Build a database engine from the ground up in Rust and find out. You’ll work through storage, indexing, concurrency, recovery and query processing while turning each chapter’s code into one working system.

An Engineering Reference for Resilient, Scalable, and Autonomous Enterprise InfrastructureEnterprise automation is no longer limited to scheduled scripts and isolated administrative tasks. Reliable infrastructure requires coordinated systems that can detect failures, manage changing state, enforce security policies, and recover from operational problems with minimal manual intervention. Advanced Automation: 50-Chapter Master Script Package is a 50-chapter technical reference for DevOps engineers, Site Reliability Engineers (SREs), cloud architects, and platform engineers.

Running LLMs locally is easy. Running them well is an engineering problem. Practical LLM Inference gets into the details that matter, from quantization and GGUF internals to GPU offloading, benchmarking and production deployment. Learn how to size hardware, find bottlenecks and build fast, reliable inference systems without the AI hand-waving.

Formal verification does not have to live in research papers. This practical guide shows working software engineers how to turn real requirements into precise, machine-checkable guarantees, find bugs before they reach production and bring formal methods into everyday development, from application code to distributed and security-critical systems.

Advanced Rust Programming goes beneath Rust’s safe surface to reveal the machinery that makes high-performance systems possible. Explore unsafe contracts, atomics, async internals, FFI, allocators and more through practical examples that sharpen your instincts and help you build faster, safer production-grade software.

Big O is not about seconds. It is about what happens to your work when your input gets ten times bigger, and that is the question interviewers are really asking. This book builds the notation from a list of names you can watch being searched, then hands you twenty everyday jobs in ten pairs and asks you to name the shape of each one.

Master NumPy from the ground up and learn to write fast, efficient Python for numerical computing. With clear explanations, practical examples and real-world techniques, this guide takes you from array basics to advanced workflows while helping you understand how NumPy really works.

Go beyond using PDF libraries and learn how the format really works. This book walks you through building a complete PDF reader from scratch using the ISO 32000-2 specification, with clear explanations, written in C++ code and a parser that handles real-world PDF files from the ground up.

Build a strong foundation in data structures and algorithms with clear explanations and practical Python examples. From core concepts to advanced techniques, this guide helps you understand how efficient software is designed so you can write better code with confidence and solve real programming challenges.

The Python interview guide written from the interviewer's side of the table. 35 chapters. Every benchmark measured. Every line of code verified. What senior engineers actually get asked — and what separates the ones who get the offer.