python_distilled_preface

Python Distilled Preface

Python: Python Variables, Python Data Types, Python Control Structures, Python Loops, Python Functions, Python Modules, Python Packages, Python File Handling, Python Errors and Exceptions, Python Classes and Objects, Python Inheritance, Python Polymorphism, Python Encapsulation, Python Abstraction, Python Lists, Python Dictionaries, Python Tuples, Python Sets, Python String Manipulation, Python Regular Expressions, Python Comprehensions, Python Lambda Functions, Python Map, Filter, and Reduce, Python Decorators, Python Generators, Python Context Managers, Python Concurrency with Threads, Python Asynchronous Programming, Python Multiprocessing, Python Networking, Python Database Interaction, Python Debugging, Python Testing and Unit Testing, Python Virtual Environments, Python Package Management, Python Data Analysis, Python Data Visualization, Python Web Scraping, Python Web Development with Flask/Django, Python API Interaction, Python GUI Programming, Python Game Development, Python Security and Cryptography, Python Blockchain Programming, Python Machine Learning, Python Deep Learning, Python Natural Language Processing, Python Computer Vision, Python Robotics, Python Scientific Computing, Python Data Engineering, Python Cloud Computing, Python DevOps Tools, Python Performance Optimization, Python Design Patterns, Python Type Hints, Python Version Control with Git, Python Documentation, Python Internationalization and Localization, Python Accessibility, Python Configurations and Environments, Python Continuous Integration/Continuous Deployment, Python Algorithm Design, Python Problem Solving, Python Code Readability, Python Software Architecture, Python Refactoring, Python Integration with Other Languages, Python Microservices Architecture, Python Serverless Computing, Python Big Data Analysis, Python Internet of Things (IoT), Python Geospatial Analysis, Python Quantum Computing, Python Bioinformatics, Python Ethical Hacking, Python Artificial Intelligence, Python Augmented Reality and Virtual Reality, Python Blockchain Applications, Python Chatbots, Python Voice Assistants, Python Edge Computing, Python Graph Algorithms, Python Social Network Analysis, Python Time Series Analysis, Python Image Processing, Python Audio Processing, Python Video Processing, Python 3D Programming, Python Parallel Computing, Python Event-Driven Programming, Python Reactive Programming.

Variables, Data Types, Control Structures, Loops, Functions, Modules, Packages, File Handling, Errors and Exceptions, Classes and Objects, Inheritance, Polymorphism, Encapsulation, Abstraction, Lists, Dictionaries, Tuples, Sets, String Manipulation, Regular Expressions, Comprehensions, Lambda Functions, Map, Filter, and Reduce, Decorators, Generators, Context Managers, Concurrency with Threads, Asynchronous Programming, Multiprocessing, Networking, Database Interaction, Debugging, Testing and Unit Testing, Virtual Environments, Package Management, Data Analysis, Data Visualization, Web Scraping, Web Development with Flask/Django, API Interaction, GUI Programming, Game Development, Security and Cryptography, Blockchain Programming, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotics, Scientific Computing, Data Engineering, Cloud Computing, DevOps Tools, Performance Optimization, Design Patterns, Type Hints, Version Control with Git, Documentation, Internationalization and Localization, Accessibility, Configurations and Environments, Continuous Integration/Continuous Deployment, Algorithm Design, Problem Solving, Code Readability, Software Architecture, Refactoring, Integration with Other Languages, Microservices Architecture, Serverless Computing, Big Data Analysis, Internet of Things (IoT), Geospatial Analysis, Quantum Computing, Bioinformatics, Ethical Hacking, Artificial Intelligence, Augmented Reality and Virtual Reality, Blockchain Applications, Chatbots, Voice Assistants, Edge Computing, Graph Algorithms, Social Network Analysis, Time Series Analysis, Image Processing, Audio Processing, Video Processing, 3D Programming, Parallel Computing, Event-Driven Programming, Reactive Programming.


Python Glossary, Python Fundamentals, Python Inventor: Python Language Designer: Guido van Rossum on 20 February 1991; PEPs, Python Scripting, Python Keywords, Python Built-In Data Types, Python Data Structures - Python Algorithms, Python Syntax, Python OOP - Python Design Patterns, Python Module Index, pymotw.com, Python Package Manager (pip-PyPI), Python Virtualization (Conda, Miniconda, Virtualenv, Pipenv, Poetry), Python Interpreter, CPython, Python REPL, Python IDEs (PyCharm, Jupyter Notebook), Python Development Tools, Python Linter, Pythonista-Python User, Python Uses, List of Python Software, Python Popularity, Python Compiler, Python Transpiler, Python DevOps - Python SRE, Python Data Science - Python DataOps, Python Machine Learning, Python Deep Learning, Functional Python, Python Concurrency - Python GIL - Python Async (Asyncio), Python Standard Library, Python Testing (Pytest), Python Libraries (Flask), Python Frameworks (Django), Python History, Python Bibliography, Manning Python Series, Python Official Glossary - Python Glossary, Python Topics, Python Courses, Python Research, Python GitHub, Written in Python, Python Awesome List, Python Versions. (navbar_python - see also navbar_python_libaries, navbar_python_standard_library, navbar_python_virtual_environments, navbar_numpy, navbar_datascience)

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Preface

More than 20 years have passed since I authored the Python Essential Reference. At that time, Python was a much smaller language and it came with a useful set of batteries in its standard library. It was something that could mostly fit in your brain. The Essential Reference reflected that era. It was a small book that you could take with you to write some Python code on a desert island or inside a secret vault. Over the three subsequent revisions, the Essential Reference stuck with this vision of being a compact but complete language reference—because if you’re going to code in Python on vacation, why not use all of it?

Today, more than a decade since the publication of the last edition, the Python world is much different. No longer a niche language, Python has become one of the most popular programming languages in the world. Python programmers also have a wealth of information at their fingertips in the form of advanced editors, IDEs, notebook]]s, web [[pages, and more. In fact, there’s probably little need to consult a reference book when almost any reference material you might want can be conjured to appear before your eyes with the touch of a few keys.

If anything, the ease of information retrieval and the scale of the Python universe presents a different kind of challenge. If you’re just starting to learn or need to solve a new problem, it can be overwhelming to know where to begin. It can also be difficult to separate the features of various tools from the core language itself. These kinds of problems are the rationale for this book.

Python Distilled is a book about programming in Python. It’s not trying to document everything that’s possible or has been done in Python. Its focus is on presenting a modern yet curated (or distilled) core of the language. It has been informed by my years of teaching Python to scientists, engineers, and software professionals. However, it’s also a product of writing software libraries, pushing the edges of what makes Python tick, and finding out what’s most useful.

For the most part, the book focuses on Python programming itself. This includes abstraction techniques, program structure, data, functions, objects, modules, and so forth—topics that will well serve programmers working on Python projects of any size. Pure reference material that can be easily obtained via an IDE (such as lists of functions, names of commands, arguments, etc.) is generally omitted. I’ve also made a conscious choice to not describe the fast-changing world of Python tooling—editors, IDEs, deployment, and related matters.

Perhaps controversially, I don’t generally focus on language features related to large-scale software project management. Python is sometimes used for big and serious things— comprised of millions upon millions of lines of code. Such applications require specialized tooling, design, and features. They also involve committees, and meetings, and decisions to be made about very important matters. All this is too much for this small book. But perhaps the honest answer is that I don’t use Python to write such applications—and neither should you. At least not as a hobby.

In writing a book, there is always a cut-off for the ever-evolving language features. This book was written during the era of Python 3.9. As such, it does not include some of the major additions planned for later releases—for example, structural]] pattern matching. That’s a topic for a different time and place.

Last, but not least, I think it’s important that programming remains fun. I hope that my book will not only help you become a productive Python programmer but also capture some of the magic that has inspired people to use Python for exploring the stars, flying helicopters on Mars, and spraying squirrels with a water cannon in the backyard.

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python_distilled_preface.txt · Last modified: 2024/04/28 03:31 by 127.0.0.1