Rust

Language models guess. Knowledge graphs know. Rusty Graph shows you how to build a local AI agent whose memory is a real knowledge graph — typed, validated, reasoned over, and queryable with SPARQL — all inside a single static Rust binary. No JVM. No Docker sidecar. No Python runtime bolted to the side. You will build Ares a research-assistant agent that observes papers, forms beliefs, makes promises to other agents, and tracks the provenance of every fact it holds. Chapter by chapter, Ares grows from an empty Cargo workspace into a full pipeline: > load → reason → validate → query → answer All of it in under a thousand lines of idiomatic Rust, using three crates that actually work today: `oxigraph`, `reasonable`, and `rudof_lib`. `grapfeo` You will learn how to- Model a domain as RDF triples and load them into an embedded store. - Write RDFS and OWL 2 RL axioms that infer trust, identity, and inverse relationships — automatically. - Guard your graph with SHACL shapes that reject bad data at the boundary, not in production. - Query everything with SPARQL, from simple lookups to federated queries across named graphs. - Wire the graph into a hybrid RAG pipeline so your LLM answers are grounded in facts, not vibes. Who it is forRust developers building agents, assistants, or any system where the answer "the model said so" is not good enough. You should be comfortable with Cargo and traits. You do **not** need any prior semantic-web background — every concept is introduced through Ares before any formal definition appears. Why Rust, why nowLocal agents are the next deployment target: a user's laptop, a Raspberry Pi, a WASM sandbox. Python cannot go there comfortably. Rust can. This book is the missing manual for the Rust side of the semantic web — the one that tells you exactly which crates work, where the ecosystem is thin, and how to ship anyway. Stop hoping your model tells the truth. Give it a graph that does.

The latest version of Rust (1.85) has some great new features, like async closures, more stable associated function return types, and const generics that are now mature enough to underpin serious numerical libraries. The linfa and smartcore ecosystems have developed into decent classical machine learning stacks. The Burn training framework feels native to Rust, not like it's been ported from it. The Candle makes it so that loading pre-trained transformer models is more of an engineering task than a research exercise. The crates that used to need all sorts of workarounds now just work.

Learn how to build a modern programming language from scratch in Rust. By implementing a complete language called Rune, you will explore every stage of language design, from lexing and parsing to type checking, virtual machines, LLVM code generation, and developer tooling, with practical code and clear explanations throughout.

We'll be writing kernels in Rust and seeing how they match up with their C++ equivalents. If you feed a GPU properly, you'll see bandwidth quadruple from just one changed subscript. It'll get you working with thousands of threads, pricing a financial option based on an exact formula, and shipping an inference pipeline that outruns its Python equivalent for reasons you can name.

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.

Unlock NVIDIA GPU performance from Rust. This practical guide takes you from GPU architecture and memory hierarchies to writing and optimizing real CUDA Rust kernels. Explore both official Rust CUDA approaches with runnable examples and learn how to build fast, production-ready GPU code without giving up Rust’s safety and clarity.

This book is meant to discover how the language Rust, which is known for being fast and safe, can work with the constantly changing field of machine learning, neural networks and deep learning. The datasets of COVID, CIFAR-10 and practical examples are meant to show how Rust's features can be used to solve problems that come up in machine learning.

Discover how to make Python data processing faster, leaner and ready to scale with Polars. Starting with the basics, this practical guide takes you all the way to production-grade pipelines for massive datasets, with clear explanations of how Polars works, why it is fast and how to get the best performance from it.

Build a complete x86_64 hardware-assisted hypervisor in Rust from the ground up. Through real, compilable code and clear explanations, you'll implement every major subsystem, from CPU and memory virtualization to device emulation, VirtIO, and multi-vCPU scheduling, gaining a practical understanding of modern virtualization.

Learn how modern LLM inference engines work by building one from scratch in Rust. From transformers and tokenization to KV caching, quantization, batching, and GPU optimization, this book combines theory, hands-on code, and performance engineering to help you create fast, production-ready AI systems.

Build a source-level debugger in Rust from the ground up while uncovering the operating system, CPU, and compiler mechanisms behind modern debugging. Through hands-on implementation, you'll learn how processes, memory, breakpoints, and DWARF debug information come together to make source-level debugging possible.

A practical, example driven guide to modern Rust: ownership, traits, async I/O, and real projects like CLIs and web services. Twelve chapters take you from install to shipping confidently, plus a tour of Rust in WebAssembly, Python extensions, and embedded systems.

Explore the power of Rust with "Rust Projects: Write a Redis Clone". This hands-on guide takes you through building a Redis-inspired database from the ground up, introducing key programming concepts like TCP connections, the RESP protocol, and concurrency. Following the CodeCrafters challenge, this book gradually builds your skills, making complex topics accessible. Whether you're new to Rust or looking to deepen your understanding, this project-based journey offers practical, real-world insights into modern systems programming. The book contains 40% discount code for CodeCrafters.io!

Learn Rust the fast way, by mapping it to the JavaScript you already know. Go from ownership and traits to building a CLI, an Axum web server, a SQLx database layer, and WebAssembly modules you can call straight from JavaScript.

What the compiler is really doing