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Sonal Raj - The Pythonic Way: An Architect’s Guide to Conventions and Best Practices for the Design, Development, Testing, and Management of Enterprise Python Code (English Edition)

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The Pythonic Way: An Architect’s Guide to Conventions and Best Practices for the Design, Development, Testing, and Management of Enterprise Python Code (English Edition): summary, description and annotation

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Learn to build and manage better software with clean, intuitive, scalable, maintainable, and high-performance Python code.

Key Features

Comparative analysis of regular and Pythonic coding constructs.

Illustrates application design paradigms for Python projects.

Detailed pointers on optimal data processing and application design.

Highlights accepted conventions for testing and managing production code.

Description

The Pythonic Way acquaints you with Pythons capabilities beyond basic syntax. This book will help you understand widely accepted Pythonic constructs and procedures, thus enabling you to write reliable, optimized, and modular applications.
Youll learn about Pythonic data structures, class and object creation, and more. The book then delves into some of Pythons lesser-known but incredibly powerful functionalities such as meta-programming, decorators, context managers, generators, and iterators. Additionally, youll learn how to accelerate computations by using Pandas Series and Dataframes. You will be introduced to various design patterns that work well with Python applications. Finally, well discuss testing frameworks and best practices for testing, packaging, launching, and publishing applications in production environments.

What you will learn

Understand common practices for writing scalable and legible Python code.

Create robust and maintainable production codebases for time and space performant applications.

Master effective data processing practices and features like generators and decorators to improve complex computations on large datasets.

Get familiar with Pythonic design patterns for secure, large-scale applications.


Who this book is for

This book is a valuable reference manual for novice and intermediate programmers and data scientists to learn about Pythonic standards and conventions. For beginners, this book will get you started with Pythonic thinking. This book will serve as a guide to fine-tune your skills beyond syntax and help build robust Python applications for intermediate Python coders.

Table of Contents

1. Introduction to Pythonic Code

2. Pythonic Data Structures

3. Classes and OOP Conventions

4. Python Modules and Metaprogramming

5. Pythonic Dcorators and Context Managers

6. Data Processing Done Right

7. Iterators, Generators, and Coroutines

8. Python Descriptors

9. Pythonic Application Design and Architecture

10. Effective Testing for Python Code

11. Production Code Management

About the Authors

Sonal Raj is an engineer, mathematician, data scientist, and Python evangelist from India, who has carved a niche in the financial services domain. He is a Goldman Sachs and D.E. Shaw alumnus who currently heads the data analytics and research efforts for a high-frequency trading firm.

He holds a dual masters degree in Computer Science and Business Management and is a former research fellow of the Indian Institute of Science. His areas of research range from image processing, real-time graph computations to electronic trading algorithms and data science. He is a doctoral candidate at the Swiss School of Business Management, Geneva. Over the years, he has implemented low latency platforms, trading strategies, and market signal models. With more than a decade of hands-on experience, he is a community speaker and a Python and data science mentor to newcomers in the field.

LinkedIn Profile: https://www.linkedin.com/in/sonalraj/

Blog Link: https://www.sonalraj.com/

Sonal Raj: author's other books


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The Pythonic Way An Architects Guide to Conventions and Best Practices - photo 1
The
Pythonic Way
An Architects Guide to Conventions and Best Practices for the Design - photo 2
An Architects Guide to Conventions and Best
Practices for the Design, Development, Testing and
Management of Enterprise Python Code
The Pythonic Way An Architects Guide to Conventions and Best Practices for the Design Development Testing and Management of Enterprise Python Code English Edition - image 3
Sonal Raj
The Pythonic Way An Architects Guide to Conventions and Best Practices for the Design Development Testing and Management of Enterprise Python Code English Edition - image 4
www.bpbonline.com
FIRST EDITION 2022
Copyright BPB Publications, India
ISBN: 978-93-91030-12-4
All Rights Reserved. No part of this publication may be reproduced, distributed or transmitted in any form or by any means or stored in a database or retrieval system, without the prior written permission of the publisher with the exception to the program listings which may be entered, stored and executed in a computer system, but they can not be reproduced by the means of publication, photocopy, recording, or by any electronic and mechanical means.
LIMITS OF LIABILITY AND DISCLAIMER OF WARRANTY
The information contained in this book is true to correct and the best of authors and publishers knowledge. The author has made every effort to ensure the accuracy of these publications, but publisher cannot be held responsible for any loss or damage arising from any information in this book.
All trademarks referred to in the book are acknowledged as properties of their respective owners but BPB Publications cannot guarantee the accuracy of this information.
wwwbpbonlinecom Dedicated to My parents Jugal and Sanjukta All - photo 5
www.bpbonline.com
Dedicated to
My parents, Jugal and Sanjukta,
All thanks to you.
And to my lovely wife, Srishti,
You are the light of my life.
About the Author
Sonal Raj is an Engineer, Mathematician, Data Scientist, and Python evangelist from India, who has carved a niche in the Financial Services domain. He is a Goldman Sachs and D.E.Shaw alumnus who currently heads the data analytics and research efforts for a high frequency trading firm.
Sonal holds dual masters in Computer Science and Business Management and is a former research fellow of the Indian Institute of Science. His areas of research range from image processing, real-time graph computations to electronic trading algorithms. He is a doctoral candidate in data science at the Swiss School of Business Management, Geneva. Over the years, he has implemented low latency platforms, trading strategies, and market signal models. With more than a decade of hands-on experience, he is a community speaker and also a Python and data science mentor to the newcomers in the field.
When not engrossed in reading fiction or playing symphonies on the piano, he spends far too much time watching rockets lift off.
Loving son, husband, and a custodian of his personal library.
About the Reviewer
Shubham Sharma is serving as a Senior Remote Sensing Scientist at GeoSpoc, Bengaluru, India. For the past five years, he has been working on Utilization of Python for Satellite Image Processing Applications and worked on the related projects with the Indian Space Research Organization (ISRO). He has been a presenter at leading Python conferences such as PyCon India and has mentored at conferences such as SciPy. In addition, he conducts workshops related to Python programming for Satellite Image Processing. He enjoys Python programming and takes a great interest in outreach of Python programming amongst the community and exploring the scientific frontiers through Python.
Acknowledgements
There are a few people I want to thank, without whose ideas and motivations, writing this book would not have been possible.
I thank my adorable wife, Srishti; her support, tolerance, and dedication has kept me going.
Thanks to my parents for always being the pillars of support, and for instilling in me, the insatiable thirst for learning. A warm thanks to my brother, Saswat and all my cousins for the inspiration, love, and humor that they bring into my life. Thanks to my friends, who have helped me in all my endeavours. This book would have been impossible without all of you.
I am eternally grateful to my colleagues and associates in the Python, Fintech, and data science communities, who constantly challenge the status quo, and make Python the powerful tool it is today. Special thanks to Travis Oliphant, the founder of NumFOCUS and Anaconda, whose work and words have helped me develop a social aspect to learning, in the few times we have interacted.
I am also grateful to the reviewer of this book, Shubham Sharma, who has provided me with valuable advice to make this book better.
Special thanks to the BPB Publications team, especially Nrip Jain, Sourabh Dwivedi, Anugraha Parthipan, Surbhi Saxena and Shali Deeraj their support, advice, and assistance in creating and publishing this book.
Preface
What makes Python a great language? The idea is that it gets the need to know balance right. When I use the term need to know, I think of how the military uses the term. The intent is to achieve focus. In a military establishment, every individual needs to make frequent life-or-death choices. The more time you spend making these choices, the more likely you are choosing death. Having to consider the full range of ethical factors into every decision is very inefficient.
Since no army wants to lose their own men, they delegate decision-making up through a series of ranks. By the time the individuals are in the field, the most critical decisions are already made, and the soldier has very less room to make their own decisions. They can focus on exactly what they need to know, trusting that their superiors have taken into account everything else that they dont need to know.
Software Libraries and abstractions are fundamentally the same. Another developer has taken the broader context into account, and has provided you the end-developer with only what you need to know. You get to focus on your work, trusting that the rest has been taken care of effectively. Memory Management is probably the simplest example. Languages that decide how the memory management is going to work (such as through a garbage collector) have taken that decision for you. You dont need to know. You get to use the time you would have been thinking about deallocation, to focus on the actual tasks.
Does to ever fail? Of course, it does. Sometimes you need more context in order to make a good decision. In a military organization, there are conventions for requesting more information, ways to get promoted into positions with more context for complex decisions, and systems for refusing to follow orders or protest. In software, to breaks down when you need some functionality that isnt explicitly exposed or documented, when you need to debug the library or the runtime code, or just deal with something that is not behaving as it claims it should. When these situations arise, not being able to incrementally increase what you know, becomes a serious blocker.
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