The Blender Python API: Precision 3D Modeling and Add-on Development
Conlan, Chris
Sold by SecondSale, Montgomery, IL, U.S.A.
AbeBooks Seller since December 20, 2007
Used - Soft cover
Condition: Good
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Add to basketSold by SecondSale, Montgomery, IL, U.S.A.
AbeBooks Seller since December 20, 2007
Condition: Good
Quantity: 1 available
Add to basketItem in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
Seller Inventory # 00074251662
Understand Blender's Python API to allow for precision 3D modeling and add-on development. Follow detailed guidance on how to create precise geometries, complex texture mappings, optimized renderings, and much more.
This book is a detailed, user-friendly guide to understanding and using Blender’s Python API for programmers and 3D artists. Blender is a popular open source 3D modeling software used in advertising, animation, data visualization, physics simulation, photorealistic rendering, and more. Programmers can produce extremely complex and precise models that would be impossible to replicate by hand, while artists enjoy numerous new community-built add-ons.
The Blender Python API is an unparalleled programmable visualization environment. Using the API is made difficult due to its complex object hierarchy and vast documentation. Understanding the Blender Python API clearly explains the interface. You will become familiar with data structures and low-level concepts in both modeling and rendering with special attention given to optimizing procedurally generated models. In addition, the book:
What You’ll Learn
Who This Book Is For
Python programmers with an interest in data science, game development, procedural generation, and open-source programming as well as programmers of all types with a need to generate precise 3D models. Also for 3D artists with an interest in programming or with programming experience and Blender artists regardless of programming experience.Chris Conlan began his career as an independent data scientist specializing in trading algorithms. He attended the University of Virginia where he completed his undergraduate statistics coursework in three semesters. During his time at UVA, he secured initial fundraising for a privately held high-frequency Forex group as president and chief trading strategist. He is currently managing the development of private technology companies in high-frequency forex, machine vision, and dynamic reporting. Author of Automated Trading with R (Apress).
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