• Title Python Notes for Professionals
• Author(s) Stack Overflow Contributors
• Publisher: lulu.com (January 28, 2018); eBook (Goalkicker.com 2018)
• License(s): Creative Commons BY-SA
• Paperback N/A
• eBook PDF (813 pages)
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
• Share This:  

Book Description

This book goes beyond the basics to teach beginner- and intermediate-level Python programmers the little-known tools and constructs that build concise, maintainable code. Design better architecture and write easy-to-understand code using highly adoptable techniques that result in more robust and efficient applications.

The Python® Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. Text content is released under Creative Commons BY-SA. See credits at the end of this book whom contributed to the various chapters. Images may be copyright of their respective owners unless otherwise specified

Book created for educational purposes and is not affiliated with Python® group(s), company(s) nor Stack Overflow. All trademarks belong to their respective company owners.

• N/A

• Amazon
• Lulu.com

• Python Programming
• Data Analysis and Data Mining
• Data Structures and Algorithms
• Computational Complexity

• Python Notes for Professionals (Stack Overflow)
• The Mirror Site (1) - PDF
• The Mirror Site (2) - PDF

• Automate the Boring Stuff with Python (Albert Sweigart)

  Learn how to use Python to write programs that do in minutes what would take you hours to do by hand - no prior programming experience required. You'll create Python programs that effortlessly perform useful and impressive feats of automation.

• Python for Everybody: Exploring Data in Python 3

  This book is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.

• Beyond the Basic Stuff with Python: Writing Clean Code

  More than a mere collection of advanced syntax and masterful tips for writing clean code, advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control.

• Python Packages (Tomas Beuzen, et al.)

  An open source book that describes modern and efficient workflows for creating Python packages. Covering the entire Python packaging life cycle, this essential guide takes readers from package creation all the way to effective maintenance and updating.

• Inside The Python Virtual Machine (Obi Ike-Nwosu)

  This book describes how Python code is compiled and run, how the language itself can be modified and will demystify the mysterious bytecodes that run on the Python virtual machine.

• Architecture Patterns with Python (Harry Percival, et al.)

  Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices, it introduces proven architectural design patterns to help Python developers manage application complexity, and get the most value out of their test suites.

• Clean Architectures in Python: Better Software Design

  The clean architecture is the opposite of spaghetti code, where everything is interlaced and there are no single elements that can be easily detached from the rest and replaced without the whole system collapsing.

• Problem Solving with Algorithms/Data Structures using Python

  This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

• Fundamentals of Python Programming (Richard L. Halterman)

  It focuses on introducing programming techniques and developing good habits. To that end, our approach avoids some of the more esoteric features of Python and concentrates on the programming basics that transfer directly to other imperative programming.

• O'Reilly® Think Python, 2nd Edition (Allen B. Downey)

  This hands-on guide takes you through the Python programming language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. 2nd edition updated for Python 3.

• Learn Python the Right Way: How to Think like a Computer Scientist

  The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science.

• The Big Book of Small Python Projects: 81 Easy Practice Programs

  This book demonstrates how to combine different libraries and frameworks to build amazing things. It picks up where the complete beginner books leave off, expanding on existing concepts and introducing new tools that you'll use every day.

• Practical Python Projects (Yasoob Khalid)

  This collection of 81 Python projects will have you making digital art, games, animations, counting programs, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches.

• Python Programming Exercises, Gently Explained (Al Sweigart)

  This is the perfect book for beginner and intermediate programmers who want to test their Python skills but aren’t ready to begin professional-level software development. The 42 programming exercises in this book let you practice what you've learned.

• Functional Programming in Python (David Mertz)

  It describes ways to avoid Python’s imperative-style flow control, the nuances of callable functions, how to work lazily with iterators, and the use of higher-order functions. He also lists several third-party Python libraries useful for functional programming.

• Python 3 Patterns, Recipes and Idioms (Bruce Eckel, et al)

  This book is aimed at more experienced Python programmers who are looking to deepen their understanding of the language and modern programming idioms. It focuses on some of the more advanced techniques used by libraries, frameworks, and applications.