The promise of this book is to teach about the various data structures and algorithms that are on offer to a programmer, which one is the most suited to a particular problem and the efficiency of the potential solutions. The book's objective is to demonstrate this with the smallest amount of maths as possible.

What you will learn:

• Big O notation is the tool used to evaluate the efficiency/complexity of an algorithm
• How binary search works and its relationship with base two logarithms
• Various implementations of sorting algorithms with their differences explained
• How to use stacks and queues
• Using node based structures in your programs
• How to look up data using hash tables
• How and when to use recursion
• How to speed up your code with binary trees

The promise of this book is to teach you to design amd write professional-quality software that's understandable, maintable, and extensible.

What you will learn:

• How to use the 'separation of concerns' principle in your Python projects
• How to use typing, inheritance, and polymorphism
• Reviewing your code in the context of time and space complexity
• Testing approaches with both the 'unittest' library and pytest
• The differences between inheritance and composition and when to use each
• How to break up code to reduce complexity using measures such as cyclomatic complexity
• How to achieve loose coupling in your programs to make them extensible and flexible

This was my second book in my journey learning Python. It's a great starter book to get to grips with Python because it has simple and clear explanations of Python concepts in a conversational and humorous style. There are annotation call-outs that explain what each part of the code actually does which will really benefit you if you're a visual learner.

What you will learn:

• Python's main core data structures
• Branching and iteration
• How to reuse code with functions and modules
• How to approach exception handling
• How, when and why you should use context managers
• How to create a basic Flask app

This book is much more advanced than the 'Head First Python' book and will take you from someone that understands core concepts to someone that can think in terms of best practises. Coupling this book with the 'Common Sense Guide to Data Structures and Algorithms' is useful because this book enables you to see how those concepts apply in Python.

What you will learn:

• Programming fundamentals: variables, expressions, and statements
• Functions
• Branching and iteration
• Data structures
• Object-oriented programming
• File management
• Analysis of algorithms
• Debugging your code

As the subtitle suggests, this book is a collection of really useful tips and tricks pitched at the intermediate Python programmer. Some of the tricks are so simple, you probably wouldn't have given them a thought in the first place. I certainly learned a lot about writing more Pythonic code as I made the move to Python from having many years of experience in VBA programming.

What you will learn:

• Writing idiomatic and Pythonic code
• Python data structures
• Always end your list/tuple with a comma to reduce git diffs at code reviews
• Use assertions more liberally than most programmers
• Python functions are first-class citizens
• List slicing
• List comprehensions and generator expressions
• How to emulate the traditional case/switch statement

This book is an extremely thick book (706 pages to be exact) and not for the faint-hearted. Written in Python 3.3, some of the references and snippets are a bit old. If you're experienced with Python, you may note there are some instances where you would use more modern language features to accomplish a task. This book gives you plenty of examples that tap into Python's extended library that comes with the base installation of Python.

It's not really a book that should be read from start to finish. It's more of a dip in when you need something kind of a book.

Merely scratching the surface of what you could learn:

• How to use Python's data structures taking advantage of their properties
• How to use Python iterators and generators
• How to use data structures beyond the readily available ones to more easily solve common programming problems.

This book is essentially a developer's reference for the pytest framework including the extended pytest plugins ecosystem. It won't give that much detail in terms of Django specific plugins, however, will set you on the path of all of the main plugins that are used in most pytest projects.

Some of the key takeaway learnings from the book include:

• How to set up fixtures for your entire test suite
• How to use parametrization to give your tests multiple inputs helping you to build robust software
• Use useful command line flags to alter a test's output to gain more insight into your tests
• How to maintain your project's test settings in a 'pytest.ini' file
• Useful plugins and practices to speed up your test suite

Written by the same guy that wrote the Django for Professionals book I just mentioned, this book is a great book to get to grips with Django REST Framework. The book uses a task based code-along approach to teaching and reinforcing its content and is pitched at intermediate level Django developers.

What you will learn:

• What is a RESTful API
• What are the http verbs and how they relate to CRUD
• Using views and serializers to build a RESTful API
• Protecting against cross-site request forgery attacks with Django CORS Headers
• Building a React front-end to consume and present the API
• Permissions and user authentication
• How to use viewsets and routers for rapid prototyping
• How to document your API with schemas and Django REST Swagger