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Software Architecture with Python
Software Architecture with Python

Software Architecture with Python: Design and architect highly scalable, robust, clean, and high performance applications in Python

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Software Architecture with Python

Chapter 2. Writing Modifiable and Readable Code

In the first chapter, we discussed the various aspects of software architecture and covered some definitions of the terms involved. We looked at the different aspects of software architecture that an architect should be concerned with. Toward the end of the chapter, we discussed the various architectural quality attributes that an architect should focus on when building a system. We went in some detail into each of these attributes and looked at some definitions and various concerns that should be kept in mind when architecting a system for achieving these attributes.

From this chapter onward, we will focus on each of these quality attributes one by one, and discuss them in detail, per chapter. We will delve deep into an attribute—such as its various factors, techniques to achieve it, aspects to keep in mind when programming toward it, and so on. Since our focus in this book is on Python and its ecosystem, we will also look...

What is modifiability?

The architectural quality attribute of modifiability can be defined as follows:

Modifiability is the degree of ease with which changes can be made to a system, and the flexibility with which the system adapts to such changes.

We discussed various aspects of modifiability in the first chapter, such as cohesion, coupling, and others. We will dig a little bit deeper into these aspects in this chapter with some examples. However, before we dig deeper, it might be a good idea to take a look at the big picture of how modifiability fits in with the other quality attributes that are related to it.

Aspects related to modifiability

We have already seen some aspects of modifiability in the previous chapter. Let's discuss this a bit further and look at some of the related quality attributes that are closely related to modifiability:

  • Readability: Readability can be defined as the ease with which a program's logic can be followed and understood. Readable software is code that has been written in a specific style, following guidelines typically adopted for the programming language used, and whose logic uses the features provided by the language in a concise, clear way.
  • Modularity: Modularity means that the software system is written in well-encapsulated modules, which do very specific, well-documented functions. In other words, modular code provides programmer friendly APIs to the rest of the system. Modifiability is closely connected to reusability.
  • Reusability: This measures the number of parts of a software system, including code, tools, designs, and others, that can be reused...

Understanding readability

The readability of a software system is closely tied to its modifiability. Well-written, well-documented code, keeping up with standard or adopted practices for the programming language, tends to produce simple, concise code that is easy to read and modify.

Readability is not only related to the aspect of following good coding guidelines, but it also ties up to how clear the logic is, how much the code uses standard features of the language, how modular the functions are, and so on.

In fact, we can summarize the different aspects of readability as follows:

  • Well-written: A piece of code is well-written if it uses simple syntax and well-known features and idioms of the language, if the logic is clear and concise, and if it uses variables, functions, and class/module names meaningfully, that is, they express what they do.
  • Well-documented: Documentation usually refers to the inline comments in the code. A well-documented piece of code tells what it does, what its input...

Fundamentals of modifiability – cohesion and coupling

Let's now get back to the main topic of modifiability and discuss the two fundamental aspects that affect modifiability of code—namely, cohesion and coupling.

We've already discussed these concepts briefly in the first chapter. Let's do a quick review here.

Cohesion refers to how tightly the responsibilities of a module are related to each other. A module that performs a specific task or group of related tasks has high cohesion. A module in which a lot of functionality is dumped without a thought as to the core functionality would have low cohesion.

Coupling is the degree to which the functionality of two modules, A and B, are related. Two modules are strongly coupled if their functionality overlaps strongly at the code level—in terms of function or method calls. Any changes in module A would probably require changes in module B.

Strong coupling is always prohibitory for modifiability, as it increases...

What is modifiability?


The architectural quality attribute of Modifiability can be defined as:

Modifiability is the degree of ease at which changes can be made to a system, and the flexibility with which the system adapts to such changes.

We discussed various aspects of modifiability in the first chapter, such as cohesion, coupling, and others. We will dig a little bit deeper into these aspects in this chapter with some examples. However, before we dig deeper, it might be a good idea to take a look at the big picture of how modifiability fits in with the other quality attributes that are related to it.

Aspects related to Modifiability


We have already seen some aspects of modifiability in the previous chapter. Let us discuss this a bit further, and look at some of the related quality attributes that are closely related to modifiability:

  • Readability: Readability can be defined as the ease with which a program's logic can be followed and understood. Readable software is code that has been written in a specific style, following guidelines typically adopted for the programming language used, and whose logic uses the features provided by the language in a concise, clear way.

  • Modularity: Modularity means that the software system is written in well-encapsulated modules, which do very specific, well-documented functions. In other words, modular code provides programmer friendly APIs to the rest of the system. Modifiability is closely connected to Reusability.

  • Reusability: This measures the number of parts of a software system, including code, tools, designs, and others, that can be reused in other...

Understanding readability


The readability of a software system is closely tied to its modifiability. Well-written, well-documented code, keeping up with standard or adopted practices for the programming language, tends to produce simple, concise code that is easy to read and modify.

Readability is not only related to the aspect of following good coding guidelines, but it also ties up to how clear the logic is, how much the code uses standard features of the language, how modular the functions are, and so on.

In fact, we can summarize the different aspects of readability as follows:

  • Well-written: A piece of code is well-written if it uses simple syntax, uses well-known features and idioms of the language, the logic is clear and concise, and if it uses variables, functions, and class/module names meaningfully; that is, they express what they do.

  • Well-documented: Documentation usually refers to the inline comments in the code. A well-documented piece of code tells what it does, what its input...

Fundamentals of Modifiability – Cohesion & Coupling


Let us now get back to the main topic of modifiability, and discuss the two fundamental aspects that affect modifiability of code—namely, cohesion and coupling.

We've already discussed these concepts briefly in the first chapter. Let us do a quick review here.

The cohesion refers to how tightly the responsibilities of a module are related to each other. A module which performs a specific task or group of related tasks has high cohesion. A module in which a lot of functionality is dumped without a thought as to the core functionality would have low cohesion.

The coupling is the degree to which the functionality of two modules A and B are related. Two modules are strongly coupled if their functionality overlaps strongly at the code level—in terms of function or method calls. Any changes in module A would probably require changes in module B.

Strong coupling is always prohibitory for modifiability, as it increases the cost of maintaining...

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Key benefits

  • Identify design issues and make the necessary adjustments to achieve improved performance
  • Understand architectural quality attributes from the perspective of a practicing engineer and architect using Python
  • Learn architectural principles and how they can be used to provide accountability and rationale for architectural decisions

Description

This book starts by explaining how Python fits into an application's architecture. As you move along, you will get to grips with architecturally significant demands and how to determine them. Later, you’ll gain a complete understanding of the different architectural quality requirements for building a product that satisfies business needs, such as maintainability/reusability, testability, scalability, performance, usability, and security. You will also use various techniques such as incorporating DevOps, continuous integration, and more to make your application robust. You will discover when and when not to use object orientation in your applications, and design scalable applications. The focus is on building the business logic based on the business process documentation, and understanding which frameworks to use and when to use them. The book also covers some important patterns that should be taken into account while solving design problems, as well as those in relatively new domains such as the Cloud. By the end of this book, you will have understood the ins and outs of Python so that you can make critical design decisions that not just live up to but also surpassyour clients’ expectations.

Who is this book for?

This book is for experienced Python developers who want to become architects of enterprise-grade applications or software architects who would like to leverage Python to create effective application blueprints.

What you will learn

  • Build programs with the right architectural attributes
  • Use Enterprise Architectural Patterns to solve scalable problems on the Web
  • Understand design patterns from a Python perspective
  • Optimize performance testing tools in Python
  • Deploy code in remote environments or on the Cloud using Python
  • Secure architecture applications in Python
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Table of Contents

11 Chapters
1. Principles of Software Architecture Chevron down icon Chevron up icon
2. Writing Modifiable and Readable Code Chevron down icon Chevron up icon
3. Testability – Writing Testable Code Chevron down icon Chevron up icon
4. Good Performance is Rewarding! Chevron down icon Chevron up icon
5. Writing Applications that Scale Chevron down icon Chevron up icon
6. Security – Writing Secure Code Chevron down icon Chevron up icon
7. Design Patterns in Python Chevron down icon Chevron up icon
8. Python – Architectural Patterns Chevron down icon Chevron up icon
9. Deploying Python Applications Chevron down icon Chevron up icon
10. Techniques for Debugging Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.5
(6 Ratings)
5 star 33.3%
4 star 16.7%
3 star 33.3%
2 star 0%
1 star 16.7%
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Bhuvneshwar Chouksey Nov 06, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
#DeepThought#Coding Skills#Lib Overriding#Giving Confidence to create your own module using existing available functionality with extra features#For R&D Guys #Maturity is very HIGH#Papar Quality Ultimate#All d Best guys for creating better Future.
Amazon Verified review Amazon
David Q Mertz May 09, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Anand PIllai touches on a really encyclopedic range of topics with clarity and precision. I'm accustomed to reading books on programming, but this one (as its title fairly indicates) is a different sort of beast. There are definitely very informative chapters on Python programming topics, but the emphasis here is on overall development and engineering practices, and as such serves as a great reference text for software development groups and managers.The many architecture challenges faced by large Python projects are addressed in Anand's book (I confess I've been his colleague and friend for over a decade, hence on first-name terms). It touches on concurrency and parallelism issues, on testing frameworks and best practices, on good documentation practice, on security, and on performance analysis, as well as more topics. It's a long book; but even at such length, any one book must be a guide to the issues that need to be considered rather than in depth documentation of all the relevant tools and libraries. Anand gives you enough to know where to look further, and to evaluate the overall trade-offs among approaches.A challenge in a book like this—which Anand does not wholly overcome—is that any sample code which can be shown on a page or two is automatically somewhat "toy code." As a result, much of the code is somewhat unrealistic to real-world large codebases, and in many cases of necessity represents less than ideal coding choices. Nonetheless, his surrounding text presents well the larger points we are meant to draw from code samples, and these points apply equally, or better, to large projects.
Amazon Verified review Amazon
kracekumar May 09, 2017
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
The book Software Architecture with Python explains various aspects of software architecture like testability, performance, scaling, concurrency and design patterns.The book has ten chapters. The first chapter speaks about different architect roles like solution architect, enterprise architect, technical architect what is the role of an architect and difference between design and architecture. This chapter is theory but worth to know the differences as a software developer.The book covers two lesser spoken topics debugging and code security which I liked. There is very few literature available on debugging. The author has provided real use cases of different debugging tips and tools for Python without picking sides. The book has some good examples on overflow errors in Python.My favorite chapter in the book is 'Writing Applications that scale'. The author explains all the available concurrency primitives like threading, multiprocess, eventlet, twisted, gevent, asyncio, queues, semaphore, locking etc . The author doesn't stop by explaining how to use them but paves the path to figuring out how to profile the code, find out where the bottleneck lies and when to use which concurrency primitives. This chapter is the longest in the book and deluged with examples and insights. The author's approach of using `time` command to measure the performance rather than sticking with wall-clock time gives the developer understanding of where programming is spending most of the time.The book covers vital details on implementing Python Design Patterns and how Python's dynamic nature brings joy while creating the creational, structural and design pattern. The showcased examples teach how Python metaclass works and it's simplicity.The book is indeed a long read and solid one in size and content. Having said that book is pretty hands on and loaded with trivial and non-trivial examples. I won't be surprised if half the book covers the code snippets. The author hasn't shied away from skipping code snippets while explaining any concept. The book introduces a plethora of tools for developing software, and at the same time references required literature and resources.
Amazon Verified review Amazon
sh Apr 04, 2018
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
This book is easy to read and understand, as long as you have an understanding of Python. The example code illustrates the point the author is trying to convey. The main problem, and the reason I deducted 2 stars, is there are a lot of typos. Every 2 or 3 pages, has some sort of typo. There are also some bugs in the code examples (i.e. setting a variable with a value, and then referencing the value instead of the variable name). There is even at least one code example where all of the code is left-justified, so it makes the code technically incorrect without any indentation.
Amazon Verified review Amazon
Paul Hoffman Jul 01, 2017
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
The book is a bit light on usable Python content. It feels like the book started off as "Software Architecture" and then the author plugged in Python at the end.If you're used to well-produced books, this one might set your teeth on edge. The book could use a much better copyedit than what it got, the artwork is amateurish, and the page layout looks like it was chosen to make the book longer.
Amazon Verified review Amazon
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