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Mastering Python: 50 Specific Tips for Writing Better Code: Practical Strategies for Writing High-Quality Python Code

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Unlock the Secrets to Python Mastery! Are you ready to take your Python coding skills to the next level? Look no further! "Mastering Python: 50 Specific Tips for Writing Better Code" is your ultimate guide to becoming a Python expert. Python is one of the most popular and versatile programming languages in the world, and mastering it can open up a world of opportunities. Whether you're a beginner looking to build a solid foundation or an experienced developer aiming to enhance your expertise, this book has something valuable for you. The book is divided into 50 chapters, each of which covers a specific aspect of Python programming. The chapters are organized in a logical and progressive order, with each chapter building upon the previous one. This makes it easy for readers to follow along and learn at their own pace. One of the strengths of the book is its focus on practical examples. The author, Brett Slatkin, is an experienced Python developer who has worked at Google for many years. He draws upon his experience to provide readers with real-world examples that illustrate the concepts he is explaining. This makes it easy for readers to understand how the concepts apply to real-world programming situations. What You'll Discover Inside: - 50 Actionable Tips: Dive deep into Python's intricacies with 50 specific tips and tricks that will help you write cleaner, more efficient, and maintainable code. - Real-World Examples: Learn by doing with practical examples and hands-on exercises that illustrate each tip and make it easy to understand. - In-Depth Explanations: Gain a solid understanding of Python's inner workings, data structures, and best practices to help you solve complex problems. -️ Advanced Techniques: Explore advanced topics like decorators, context managers, and metaclasses to take your Python skills to the expert level. - Comprehensive Reference: Use this book as a reference guide you can revisit whenever you need to optimize your Python code. - Libraries and Frameworks: Learn how to leverage popular Python libraries and frameworks like NumPy, Pandas, Flask, and Django for specific tasks. - Best Practices: Understand the best coding practices and design patterns that will make your Python code stand out and shine. - Debugging and Testing: Discover how to troubleshoot your code effectively and write robust tests to ensure reliability. Python is the language of choice for web development, data analysis, artificial intelligence, and more. With "Mastering Python," you'll gain the skills and knowledge to excel in all these domains. Don't miss this opportunity to become a Python guru. Whether you're a student, a professional developer, or an enthusiast, this book will empower you to write better Python code and build amazing applications. Grab your copy of "Mastering Python: 50 Specific Tips for Writing Better Code" today and embark on your journey to Python mastery.

Author(s): Dane Olsen
Publisher: Ziyob Publisher
Year: 2023

Language: English
Pages: 345

Chapter 1:
Introduction

The Zen of Python

Pythonic thinking

Chapter 2:
Pythonic thinking

Know your data structures

Tuples

Lists

Dictionaries

Sets

Arrays

Queues

Stacks

Heaps

Trees

Graphs

Write expressive code

Choosing good names

Avoiding magic numbers and strings

Using list comprehensions and generator expressions

Leveraging built-in functions

Using the with statement

Using decorators

Writing context managers

Take advantage of Python's features

Using named tuples

Leveraging closures

Using properties

Using descriptors

Using metaclasses

Writing idiomatic Python

Writing Pythonic loops

Using enumerate and zip

Using the ternary operator

Using multiple assignment

Using the walrus operator

Using context managers

Chapter 3:
Functions

Function basics

Function arguments and return values

Documenting functions

Writing doctests

Writing function annotations

Using default arguments

Using keyword arguments

Using *args and **kwargs

Function design

Writing pure functions

Writing functions with side effects

Writing functions that modify mutable arguments

Using the @staticmethod and @classmethod decorators

Using partial functions

Function decorators and closures

Writing simple decorators

Writing decorators that take arguments

Writing class decorators

Using closures

Using functools.partial

Chapter 4:
Classes and Objects

Class basics

Creating and using classes

Defining instance methods

Using instance variables

Understanding class vs instance data

Using slots for memory optimization

Understanding class inheritance

Using multiple inheritance

Class design

Writing clean, readable classes

Writing classes with a single responsibility

Using composition over inheritance

Using abstract base classes

Writing metaclasses

Advanced class topics

Using descriptors to customize attribute access

Using properties to control attribute access

Writing class decorators

Using the super function

Using slots to optimize memory usage

Chapter 5:
Concurrency and Parallelism

Threads and Processes

Understanding the Global Interpreter Lock (GIL)

Using threads for I/O-bound tasks

Using processes for CPU-bound tasks

Using multiprocessing

Using concurrent.futures

2. Coroutines and asyncio

Understanding coroutines

Using asyncio for I/O-bound tasks

Using asyncio for CPU-bound tasks

Using asyncio with third-party libraries

Debugging asyncio code

Chapter 6:
Built-in Modules

Collections

Using namedtuple

Using deque

Using defaultdict

Using OrderedDict

Using Counter

Using ChainMap

Using UserDict

Using UserList

Using UserString

Itertools

Using count, cycle, and repeat

Using chain, tee, and zip_longest

Using islice, dropwhile, and takewhile

Using groupby

Using starmap and product

File and Directory Access

Using os and os.path

Using pathlib

Using shutil

Using glob

Dates and Times

Using datetime

Using time

Using timedelta

Using pytz

Using dateutil

Serialization and Persistence

Using json

Using pickle

Using shelve

Using dbm

Using SQLite

Testing and Debugging

Writing unit tests

Using pytest

Debugging with pdb

Debugging with logging

Using assertions

Chapter 7:
Collaboration and Development

Code Quality

Using linters

Using type checkers

Using code formatters

Using docstring conventions

Writing maintainable code

Code Reviews

Conducting effective code reviews

Giving and receiving feedback

Improving code quality through reviews

Collaboration Tools

Using version control with Git

Using GitHub for collaboration

Using continuous integration

Using code coverage tools

Documentation and Packaging

Writing documentation

Using Sphinx

Packaging Python projects

Distributing Python packages

Managing dependencies