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Mastering Object-Oriented Python

Mastering Object-Oriented Python

By : Steven F. Lott
3.8 (4)
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Mastering Object-Oriented Python

Mastering Object-Oriented Python

3.8 (4)
By: Steven F. Lott

Overview of this book

Object-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language's unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you'll be shown how to effectively implement OOP in Python, and even explore Python 3.x. Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design offers the best performance. Next, you'll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you'll discover how essential it is to locate the best algorithms and optimal data structures for developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs. By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python.
Table of Contents (25 chapters)
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1
Section 1: Tighter Integration Via Special Methods
11
Section 2: Object Serialization and Persistence
17
Section 3: Object-Oriented Testing and Debugging

Defining indices in the ORM layer

One of the ways to improve the performance of a relational database such as SQLite is to make join operations faster. The ideal way to do this is to include enough index information so that slow search operations aren't done to find matching rows.

When we define a column that might be used in a query, we should consider building an index for that column. This is a simple process that uses SQLAlchemy. We simply annotate the attribute of the class with index=True.

We can make fairly minor changes to our Post table, for example. We can do this to add indexes:

class Post(Base): 
    __tablename__ = "POST" 
    id = Column(Integer, primary_key=True) 
    title = Column(String, index=True) 
    date = Column(DateTime, index=True) 
    blog_id = Column(Integer, ForeignKey('BLOG.id'), index=True) 

Adding two indexes for the title...

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