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portada Modern Python Workflows with uv: Lightning-Fast Packaging, Dependency, and Project Management
Type
Physical Book
Publisher
Author
Year
2026
Language
English
Pages
307
Format
Paperback
ISBN13
9798896653998

Modern Python Workflows with uv: Lightning-Fast Packaging, Dependency, and Project Management

Wexford, Caelan (Author) · NobleTrex Press · Paperback

Modern Python Workflows with uv: Lightning-Fast Packaging, Dependency, and Project Management - Wexford, Caelan

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Synopsis "Modern Python Workflows with uv: Lightning-Fast Packaging, Dependency, and Project Management"

"Modern Python Workflows with uv: Lightning-Fast Packaging, Dependency, and Project Management" Python packaging and environment management have long been powerful but fragmented. This book is for experienced Python developers, platform engineers, and technical leads who want a sharper, faster, and more coherent workflow built around uv. Rather than treating uv as a simple performance upgrade, it presents it as a unified operational surface for modern Python development, from interpreter management to dependency locking, tool execution, packaging, and CI automation. Readers will learn how uv models projects through `pyproject.toml`, `uv.lock`, and virtual environments; how dependency declarations, groups, extras, and alternative sources interact; and how exact synchronization creates reproducible systems. The book also covers controlled upgrades, pip-compatible migration paths, isolated CLI tool workflows, monorepo workspaces, package building and publishing, and high-performance CI caching strategies. By the end, readers will be able to design and operate uv-based workflows that are fast, deterministic, and scalable across teams. The treatment is advanced, practical, and architecture-aware. It assumes familiarity with Python packaging concepts and focuses on deep operational understanding, trade-offs, and implementation choices rather than introductory explanations. Structured as a progressive guide, the book helps readers move from core mental models to production-grade adoption patterns with confidence.

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