Books

Skip the black-box frameworks. Build a production-grade AI coding agent from scratch in pure Python - cloud or local, tested with pytest, all in a single file.

Mastering Modern Time Series Forecasting is your all-in-one guide to building real-world forecasting systems that work — from classical stats to deep learning and beyond. Whether you're modeling retail demand or energy loads, this book gives you the tools, intuition, and code to go from zero to production. You'll cover ARIMA, ML, deep nets, transformers, and even the rise of FTSMs (Foundational Time Series Models). Written by a practitioner who’s built forecasting solutions for multibillion-dollar businesses, this is the hands-on, honest guide every data scientist, analyst, or forecaster needs.

Bad data breaks good code. You’ve written Python that works perfectly in testing, only to watch it fail in production because of a malformed API request, a messy CSV, or a missing config value. That’s the hidden cost of Python’s flexibility: without runtime validation, you’re always one bad input away from a crash. Enter Pydantic. This book takes you from the foundations of data validation to real-world applications in APIs, data pipelines, configurations, and machine learning workflows. Along the way, you’ll explore practical techniques, advanced features, and alternatives like Marshmallow, attrs, and dataclasses, so you’ll always know which tool is right for the job. If you’re a Python developer, data engineer, or FastAPI user, this is your roadmap to writing safer, cleaner, and more reliable code.

Quantitative finance in Python: a hands-on, interactive look at the QuantLib library through the use of Jupyter notebooks as working examples.

Unlock the power of geospatial data with Python! This hands-on guide is designed for beginners and intermediate users eager to explore spatial analysis and interactive mapping using open-source tools. You'll learn how to work with real-world data through practical examples and build skills in Python programming, vector and raster analysis, web mapping, and cloud computing. Whether you're a student, researcher, GIS professional, or data scientist, this book will equip you with the tools to tackle geospatial challenges with confidence. Color-print copies are available through Amazon.

¡Desbloquea el poder de los datos geoespaciales con Python! Esta guía práctica está diseñada para principiantes y usuarios intermedios que desean explorar el análisis espacial y la cartografía interactiva utilizando herramientas de código abierto. Aprenderás a trabajar con datos del mundo real a través de ejemplos prácticos y desarrollarás habilidades en programación con Python, análisis vectorial y ráster, mapeo web y computación en la nube. Ya seas estudiante, investigador, profesional GIS o científico de datos, este libro te proporcionará las herramientas necesarias para enfrentar con confianza los desafíos geoespaciales.

Explore Python code recipes to use market data for designing and deploying algorithmic trading strategies. By following step-by-step instructions, you’ll be proficient in trading concepts and have hands-on experience in a live trading environment.

Get started quickly, creating applications for the Model Context Protocol (MCP) using the official MCP SDKs for Python, Java 21, and Node.js. Quickly master, all of the concepts needed in order to build MCP servers, including transport protocols, tools, resources, prompts, roots, and sampling. Learn how to get familiar with popular MCP client applications such as, Claude Desktop, Postman, and the MCP Inspector.

A pattern language for event sourced applications and reliable distributed systems. Examples are written in the Python programming language. Now includes event-oriented introductions to the pattern language scheme of Christopher Alexander, the process philosophy of Alfred North Whitehead, and the person-centred psychology of Rogers and Rosenberg.

Sblocca la potenza dei dati geospaziali con Python! Questa guida pratica è pensata per principianti e utenti intermedi desiderosi di esplorare l’analisi spaziale e la mappatura interattiva utilizzando strumenti open source. Imparerai a lavorare con dati reali attraverso esempi pratici e a sviluppare competenze in programmazione Python, analisi vettoriale e raster, web mapping e cloud computing. Che tu sia studente, ricercatore, professionista GIS o data scientist, questo libro ti fornirà gli strumenti per affrontare con sicurezza le sfide geospaziali.

A comprehensive guide to learning the Python programming language, written so to be accessible to readers of all levels, from beginner python developers to those who have some experience with python. Even more advanced users may find some utility from the later chapters.

Libérez la puissance de DuckDB pour l’analytique géospatiale moderne. Ce guide pratique aide les professionnels du SIG à maîtriser une gestion efficace des données spatiales, en transformant d’énormes jeux de données réels en informations exploitables grâce au SQL, à Python et à l’extension spatiale de DuckDB. Une édition papier couleur est disponible sur Amazon.

Libérez la puissance des données géospatiales avec Python ! Ce guide pratique s’adresse aux débutants et utilisateurs intermédiaires désireux d’explorer l’analyse spatiale et la cartographie interactive à l’aide d’outils open source. Grâce à des exemples concrets et des données réelles, vous apprendrez à manipuler des données spatiales, à programmer en Python, à analyser des données vectorielles et matricielles, à créer des cartes web interactives, et à utiliser le cloud computing. Étudiant, chercheur, professionnel des SIG ou data scientist : ce livre vous donnera les outils pour relever les défis géospatiaux avec assurance.

Pycairo is a great library for creating high quality vector graphics in Python. This book covers the full features of the library in detail, with practical code examples and illustrations, from an author with many years experience in computer graphics software.

ブラックボックスのフレームワークは不要。純粋なPythonでプロダクションレベルのAIコーディングエージェントをゼロから構築。クラウドでもローカルでも、pytestでテスト済み、すべて1つのファイルに収まります。