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    Python: Advanced Guide to Programming Code with Python
    Python: Advanced Guide to Programming Code with Python
    Python: Advanced Guide to Programming Code with Python
    Ebook81 pages39 minutesPython Programming Series

    Python: Advanced Guide to Programming Code with Python

    By Charlie Masterson

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    About this ebook

    Have you learned the basics of Python and want to go further? Not sure what to do, where to go or what topics you should be studying?


    You have come to the right place; this book, "Python: Advanced Guide to Programming Code with Python" will take you through several of the more important advanced concepts.


    In this Definitive Python Advanced Level Guide, you’re about to discover...


    • Comprehensions – learn how to use constructs to build a sequence from another sequence

    • Iterators and Generators – Learn how to use generator functions and iterator objects to make your code more efficient

    • Decorators – Learn how to simplify the syntax for calling higher-order functions

    • Context Managers – Learn how to write more effective Python code by managing your resources properly

    • Descriptors – Learn how to add managed attributes to objects

    • ... And much, much more!
      Other Benefits of owning this book:

    • Metaprogramming – Learn how to create functions and classes with the main object of manipulating your code

    • Python Scripting Blender – An overview of Blender and how to script with it

    • Django Web Development – An overview of what Django is and how to use it



    The goal of this book is to enhance your knowledge and, by the end of it, you will have gained sufficient knowledge and experience to consider yourself a proper Python coder!
    By implementing the lessons in this book, not only would you learn one of today’s popular computer language, but it will serve as your guide in accomplishing all your Python goals – whether as a fun hobby or as a starting point into a successful and long term programming career.

    LanguageEnglish
    PublisherE.C. Publishing
    Release dateFeb 9, 2017
    Python: Advanced Guide to Programming Code with Python

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      Book preview

      Python - Charlie Masterson

      Introduction

      Iwant to thank you and congratulate you for downloading the book, Python: Advanced Guide to Programming Code with Python .

      This book contains advanced steps and strategies on how to further your Python programming knowledge.

      This book is exactly what the title says – advanced so, if you have little to no knowledge of programming with Python, this really isn’t the book for you. It is aimed at those who are competent at basic Python programming and want to further their knowledge by learning some of the more advanced concepts but this is by no means a comprehensive guide to all the advanced programming concepts. Instead I have picked some of the more important ones that you should learn and I hope that you gain something from reading this and working through the code examples.

      Thanks again for downloading this book, I hope you enjoy it!

      Chapter 1:

      Python Comprehensions

      Once you get to know a list comprehension, once you get what they are, you will find that they become quite compelling. So, what is a Python comprehension? Basically, they are constructs that let a sequence be built from another sequence. Python 2.0 introduced list comprehensions while Python 3.0 continues with set and dictionary comprehensions.

      List Comprehensions

      A list comprehension is made up of the following components:

      Input sequence

      Variable that represents the members of that input sequence

      Optional predicate expression

      Output expression – this satisfies the predicate by taking the input sequence members and producing the elements of the output list

      Let’s say that you want a list of the integers that are in a sequence and then you want to square them:

      Example codes:

      a_list = [1, ‘4’, 9, ‘a’, 0, 4]

      squared_ints = [ e**2 for e in a_list if type(e) == types.IntType ]

      print squared_ints

      # [ 1, 81, 0, 16 ]

      Here’s how that works:

      The iterator part of the statement will iterate through each individual member if the input sequence known as a_list

      The predicate will then check to see if each one is an integer

      If it is, it will be passed to the output expression and then squared, becoming a member in the output list

      You can get pretty much the same result if you use the Python built-in functions, filter and map or the lambda function:

      The map function will modify the members in the sequence:

      map(lambda e: e**2, a_list)

      While the filter function will apply a predicate to the sequence:

      filter(lambda e: type(e) == types.IntType, a_list)

      You can combine these:

      map(lambda e: e**2, filter(lambda e: type(e) == types.IntType, a_list))

      Ok, so this example is showing you three function calls – map, type and filter – and two calls to lambda. Just be aware that Python function calls can be expensive and note that the input sequence has been traversed twice and filter is what produces an intermediate list.

      List comprehensions are enclosed in lists so it is very easy to see that a list has been produced. You don’t need any call to lambda and only one to type; instead, list comprehensions use iterators, which we will talk about more in the next chapter, as well as an expression and, if you use the optional predicate, an if expression.

      Nested Comprehensions

      Take

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