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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 Python's 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.You'll learn about Pythonic data structures, class and object creation, and more. The book then delves into some of Python's lesser-known but incredibly powerful functionalities such as meta-programming, decorators, context managers, generators, and iterators. Additionally, you'll 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, we'll discuss testing frameworks and best practices for testing, packaging, launching, and publishing applications in production environments.This book will empower you as you transition from beginner or competitive Python coding to industry-standard Python software development. Intermediate Python developers will gain a deeper understanding of the language's nuances, enabling them to create better software. 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 Décorators 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 master's 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/

A one-stop guide to teach chemists how to use Python for coding and iterations in a hands-on and practical manner Key Features ? Understand the core Python functions and algorithms for the computation of chemical parameters. ? Learn how to use Cheminformatics modules to process and analyze elemental data and molecular structures. ? Get familiar with the algorithms for numerical and symbolic computations. Description Python is a versatile and powerful computer language without a steep learning curve. It can be deployed to simulate various physicochemical parameters or to analyze complex molecular, bio-molecular, and crystalline structures. The objective of this book is to give a gentle introduction to Python programming with relevant algorithms, iterations, and basic simulations from a chemist's perspective. This book outlines the fundamentals of Python coding through the built-in functions, libraries, and modules as well as with a few selected external packages for physical/materials/inorganic/analytical/organic/ nuclear chemistry in terms of numerical, symbolic, structural, and graphical data analysis using the default, Integrated Development and Learning Environment. You will also learn about the Structural Elucidation of organic molecules and inorganic complexes with specific Cheminformatics modules. In addition to this, the book covers chemical data analysis with Numpy and also includes topics such as SymPy and Matplotlib for Symbolic calculations and Plotting. By the end of the book, you will be able to use Python as a graphical tool or a calculator for numerical and symbolic computations in the interdisciplinary areas of chemistry. What you will learn ? To fetch elemental, nuclear, atomic or molecular data with list or dictionary functions. ? Understanding the algorithms for the computation of Thermodynamic, Electrochemical, Kinetics, Molecular and Spectral parameters. ? Stoichiometrical calculation of the reactant and product coefficients from Matrices. ? Symbolic computations with reference to Physical Chemistry. ? With Matplotlib package, interpretation and plotting of the analyzed data in the desired graphical format. ? With various cheminformatics modules, correlate the structure of complex and bulkier molecules. Who this book is for This book is for Chemists, Chemical Engineers, Material Scientists, Bio-chemists, Biotechnologists, and Physicists. Students of Chemistry, Chemical Engineering, Materials Chemistry, Biochemistry, Biotechnology, and Physics will find this book resourceful. Table of Contents 1. Understanding Python Functions for Chemistry 2. Computations in Chemistry with NumPy 3. Interpolation, Physico-chemical Constants, and Units with SciPy 4. SymPy for Symbolic Computations in Chemistry 5. Interactive Plotting of Physico-chemical Data with Matplotlib 6. Introduction to Cheminformatics with RDKit 7. ChemFormula for Atomic and Molecular Data 8. Chemlib for Physico-chemical Parameters 9. ChemPy for Computations in Chemistry 10. Mendeleev Package For Atomic and Ionic Data 11. Computations of Parameters of Electrolytes with PyEQL 12. STK Module for Molecular Structures

Python is a robust, procedural, object-oriented, and functional language. The features of the language make it valuable for web development, game development, business, and scientific programming. This book deals with problem-solving and programming in Python. It concentrates on the development of efficient algorithms, the syntax of the language, and the ability to design programs in order to solve problems. In addition to standard Python topics, the book has extensive coverage of NumPy, data visualization, and Matplotlib. Numerous types of exercises, including theoretical, programming, and multiple-choice, reinforce the concepts covered in each chapter.

Design and deploy robust state-of-the-art web applications using Flask 2.x and Python 3 frameworks and libraries for streamlined development and optimal performance Purchase of the print or Kindle book includes a free PDF eBook Key Features A practical and rich companion guide for web developers, offering real-world situations and use cases to learn FlaskGet the most out of the powerful Flask framework while preserving the flexibility of your design choicesWrite cleaner, testable, and maintainable code with the help of sample apps Book Description Discover what makes Flask, the lightweight Python web framework, popular, as you delve into its modular design that enables the development of scalable web apps. With this practical guide, you'll explore modern solutions, recommended design patterns, and best practices for Flask web development. Updated to the latest version of Flask and Python, this third edition of the Flask Framework Cookbook moves away from the outdated libraries, updates content to incorporate new coding patterns, and introduces recipes for the latest tools. You'll explore different ways to integrate with GPT to build AI-ready Flask applications. The book starts with an exploration of Flask application configurations and then guides you through working with templates and understanding the ORM and view layers. You’ll also be able to write an admin interface and get to grips with testing using the factory pattern, debugging, and logging errors. Then you’ll discover different ways of using Flask to create, deploy, and manage microservices using AWS, GCP, and Kubernetes. Finally, you’ll gain insights into various deployment and post-deployment techniques for platforms such as Apache, Tornado, and Datadog. By the end of this book, you'll have acquired the knowledge necessary to write Flask applications that cater to a wide range of use cases in the best possible way and scale them using standard industry practices. What you will learn Explore advanced templating and data modeling techniquesDiscover effective debugging, logging, and error-handling techniques in FlaskWork with different types of databases, including RDBMS and NoSQLIntegrate Flask with different technologies such as Redis, Sentry, and DatadogDeploy and package Flask applications with Docker and KubernetesIntegrate GPT with your Flask application to build future-ready platformsImplement continuous integration and continuous deployment (CI/CD) to ensure efficient and consistent updates to your Flask web applications Who this book is for If you are a web developer seeking to expand your knowledge of developing scalable and production-ready applications in Flask, this is the book for you. It is also highly valuable if you are already aware of Flask's major extensions and want to leverage them for better application development. This book will come handy as a quick reference for specific topic on Flask, its popular extensions, or specific use cases. It assumes basic Python programming experience, as well as familiarity with web development and related terminology.

A hands-on guide that will help you to write clean and efficient code in Python Key Features ? Get familiar with the core and advanced Python concepts. ? Work with the most used Data Science libraries in Python. ? Take the first step towards your coding goals with \"Python for Everyone\". Description Python is one of the most popular programming languages in the world, with a vast community of developers and users. In order to start using Python effectively, it is important to have a strong understanding of its core concepts. This comprehensive guide provides you with a solid foundation in the fundamental concepts of Python programming. It covers a range of important topics, including working with strings, flow control statements, exception handling, and regular expressions. You will also learn about the essential functions and data structures, and explore the use of pre-built packages to extend Python's capabilities. Numpy and data visualization with packages like Matplotlib are also discussed in depth, along with the popular data analysis and manipulation package, Pandas. This book is an essential resource for anyone looking to master Python and use its power to tackle real-world projects. With a strong grasp of these core concepts, you will be well-equipped to write efficient and effective Python code. What you will learn ? Learn how to write Python code in different IDEs like VSCode and Jupyter Notebook. ? Create graphical user interfaces (GUIs) in Python using the Tkinter library. ? Get familiar with Python data science libraries. ? Understand how to use Regular expressions in Python. ? Learn how to write Python comments that are clean, concise, and useful. Who this book is for This book is designed to cater to a diverse audience, including students pursuing diplomas, undergraduate, and postgraduate degrees in any branch of Engineering and Science. It is also suitable for programming and software professionals looking to enhance their skills in Python. Table of Contents 1. Basic Python Introduction 2. Concept of Strings in Python 3. Concept of Flow Control Statements in Python 4. Concept of Exception Handling in Python 5. Concept of Regular Expressions in Python 6. Concept of Functions in Python 7. Concept of Data Structures in Python 8. Concept of Packages in Python 9. Numpy Introduction 10. Data Visualization Introduction 11. Pandas Introduction

Learn how to create stunning user interfaces using the tkinter Python library Key Features ? Explore the art of presenting information effectively using display widgets like labels, text boxes, images, and buttons. ? Delve into advanced topics like working with images, canvas drawing, database interactions, and handling multiple windows. ? Develop the skills to build professional and user-friendly GUI applications, regardless of your level of experience. Description Are you looking to create stunning graphical user interfaces (GUIs) using Python? Look no further. This comprehensive guide will take you on a journey through the powerful capabilities of tkinter, Python's standard GUI library. This comprehensive guide explores the power of Python's tkinter library. This book covers various classes of GUI widgets, including buttons, input fields, displays, containers, and item widgets. It teaches you how to create interactive and visually appealing user interfaces, handle file selection, gather widget information, and trace changes. Additionally, it includes a hands-on project on creating a user login system using tkinter and sqlite3 database. Whether you're a beginner or an experienced developer, this book will empower you to build professional and intuitive GUI applications effortlessly. By the end of the book, you will have gained knowledge and skills in creating modern user interfaces using the tkinter Python library. What you will learn ? Gain a solid understanding of the various classes for GUI widgets in tkinter. ? Learn how to create dynamic and interactive buttons that respond to user input and perform actions. ? Explore different layout management options in tkinter. ? Discover how to create dialogs and message boxes using the tkinter library. ? Learn how to use trace mechanisms to monitor and respond to changes in your GUI applications. Who this book is for This book is suitable for a wide range of individuals, including engineering and science students at the diploma, undergraduate, and postgraduate levels. It also caters to programming and software professionals, as well as students in grades 8 to 12 studying under CBSE or state boards. Additionally, GUI and.Net engineers will find value in the book's content. Table of Contents 1. tkinter Introduction 2. Inbuilt Variable Classes for Python tkinter GUI Widgets 3. Getting Insights of Button Widgets in tkinter 4. Getting Insights of Input Widgets in tkinter 5. Getting Insights of Display Widgets in tkinter 6. Getting Insights of Container Widgets in tkinter 7. Getting Insights of Item Widgets in tkinter 8. Getting Insights of tkinter User Interactive Widgets 9. Handling File Selection in tkinter 10. Getting Widget Information and Trace in tkinter 11. UserLogin Project in tkinter GUI Library with sqlite3 Database

Extensive Python 3.x code samples generated using ChatGPT and GPT-4, covering diverse programming tasks and challenges. Comprehensive exploration of data visualization techniques using popular Python libraries such as Matplotlib and Seaborn. This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in Python environments. The book contains an assortment of Python 3.x code samples that were generated by ChatGPT and GPT-4. Chapter 1 provides an overview of ChatGPT and GPT-4, followed by a chapter which contains Python 3.x code samples for solving various programming tasks in Python. Chapter 3 contains code samples for data visualization, and Chapter 4 contains code samples for linear regression. The final chapter covers visualization with Gen AI (Generative AI) and DALL-E. Companion files with source code and figures are available for downloading.