book

Software Architecture with Python

by Anand Balachandran Pillai

April 2017

Intermediate to advanced

556 pages

11h 5m

English

Packt Publishing

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What this book covers

Downloading the example codeDownloading the color images of this bookErrataPiracyQuestions
Defining software architectureSoftware architecture versus designAspects of software architecture
An architecture defines a structureAn architecture picks a core set of elementsAn architecture captures early design decisionsAn architecture manages stakeholder requirementsAn architecture influences the organizational structureAn architecture is influenced by its environmentAn architecture documents the systemAn architecture often conforms to a pattern
ModifiabilityTestabilityScalabilityPerformanceAvailabilitySecurityDeployability
What is modifiability?
Python and readabilityReadability – antipatternsTechniques for readabilityDocument your codeFollow coding and style guidelinesReview and refactor codeCommenting the code
Measuring cohesion and couplingMeasuring cohesion and coupling – string and text processing
Providing explicit interfacesReducing two-way dependenciesAbstract common servicesUsing inheritance techniquesUsing late binding techniques
What are code smells?Cyclomatic complexity – the McCabe metricTesting for metricsRunning static checkers
Refactoring code – fixing complexityRefactoring code – fixing code smellsRefactoring code – fixing styling and coding issues
Understanding testabilitySoftware testability and related attributesTestability – architectural aspectsTestability – strategiesReduce system complexityImproving predictabilityControl and isolate external dependencies
Unit testingUnit testing in actionExtending our unit test caseNosing around with nose2Testing with py.testCode coverageMeasuring coverage using coverage.pyMeasuring coverage using nose2Measuring coverage using pytestMocking things upTests inline in documentation – doctestsIntegration testsTest automationTest automation using Selenium WebDriverTest-driven developmentTDD with palindromes
What is performance?
Measuring time using a context managerTiming code using the timeit moduleMeasuring the performance of our code using timeitFinding out time complexity – graphsMeasuring CPU time with timeit
Deterministic profilingProfiling with cProfile and profilePrime number iterator class – performance tweaksProfiling – collecting and reporting statisticsThird-party profilersLine profilerMemory profilerSubstring (subsequence) problem
objgraphPympler
Mutable containers – lists, dictionaries, and setsListsDictionariesSetsImmutable containers – tuplesHigh performance containers – the collections moduledequedefaultdictOrderedDictDropping duplicates from a container without losing the orderImplementing a Least Recently Used (LRU) cache dictionaryCounterChainMapnamedtupleProbabilistic data structures – bloom filters
Scalability and performance
Concurrency versus parallelismConcurrency in Python – multithreading
Thumbnail generator – producer/consumer architectureThumbnail generator – resource constraint using locksThumbnail generator – resource constraint using semaphoresResource constraint – semaphore versus lockThumbnail generator – URL rate controller using conditions
Concurrency in Python – multiprocessingA primality checkerSorting disk filesSorting disk files – using a counterSorting disk files – using multiprocessing
Concurrecy in Python – Asynchronous Execution
Disk thumbnail generatorConcurrency options – how to choose?Parallel processing librariesJoblibPyMPFractals – the Mandelbrot setFractals – scaling the Mandelbrot set implementation
The Mandelbrot set using CeleryServing with Python on the Web – WSGIuWSGI – WSGI middleware on steroidsGunicorn – unicorn for WSGIGunicorn versus uWSGIScalability architecturesVertical scalability architecturesHorizontal scalability architectures
Information security architecture
Reading inputEvaluating arbitrary inputOverflow errorsSerializing objects
Server Side Template InjectionServer-Side Template Injection – MitigationDenial of ServiceCross-Site Scripting (XSS)Mitigation – DoS and XSS
Design patterns – elements
Pluggable hashing algorithmsSumming up pluggable hashing algorithm
The Singleton patternThe Singleton – do we need a Singleton?State sharing – Borg versus SingletonThe Factory patternThe Prototype patternPrototype – deep versus shallow copyPrototype using metaclassesCombining patterns using metaclassesThe Prototype factoryThe Builder pattern
The Adapter patternThe Facade patternFacades in PythonThe proxy patternAn instance-counting proxy
The Iterator patternThe Observer patternThe State pattern
Introducing MVCModel Template View (MTV) – DjangoDjango admin – automated model-centric viewsFlexible Microframework – Flask
Chat server and client using I/O multiplexing with the select moduleEvent-driven programming versus concurrent programmingTwistedTwisted – a simple web clientChat server using TwistedEventletGreenlets and Gevent
Microservice frameworks in PythonMicroservices example – restaurant reservationMicroservices – advantages
Pipe and filter in Python
DeployabilityFactors affecting deployability
Packaging Python codePIPVirtualenvVirtualenv and pipRelocatable virtual environmentsPyPIPackaging and submission of an applicationThe __init__.py filesThe setup.py fileInstalling the packageSubmitting the package to PyPIPyPARemote deployments using FabricRemote deployments using AnsibleManaging remote daemons using Supervisor
Maximum subarray problemThe power of "print"Analysis and rewriteTiming and optimizing the code
Word searcher programWord searcher program – debugging step 1Word searcher program – debugging step 2Word searcher program – final codeSkipping blocks of codeStopping executionExternal dependencies – using wrappersReplacing functions with their return value/data (mocking)Saving to / loading data from files as cacheSaving to / loading data from memory as cacheReturning random/mock dataGenerating random patient data
Simple application loggingAdvanced logging – logger objectsAdvanced logging – custom formatting and loggersAdvanced logging – writing to syslog
A debugging session with pdbPdb – similar toolsiPdbPdb++
The trace moduleThe lptrace programSystem call tracing using strace

Overview

Embark on a journey to master the concepts of software architecture with Python. This comprehensive guide demystifies creating scalable, robust, high-performance applications by teaching practical techniques and best practices. Filled with real-world use cases, this book ensures you can design and implement software solutions tailored to meet complex requirements.

What this Book will help me do

Develop and evaluate software designs using Python to achieve maintainability, scalability, and performance.
Apply architectural principles in Python projects to solve scalability issues in enterprise systems.
Master design patterns and their application to implement robust, efficient, and reusable code.
Learn to deploy software reliably and securely on remote servers or in cloud environments.
Incorporate DevOps strategies to enable continuous integration and delivery for stable and consistent software builds.

Author(s)

None Balachandran Pillai, an accomplished software engineer and technical author, brings years of experience in designing and implementing effective software systems using Python. With an emphasis on practical, real-world applications, Pillai offers a modern perspective on software architecture. His approachable teaching style ensures clarity and insight for readers of all levels.

Who is it for?

This book is perfect for Python developers aiming to transition into roles as software architects or for existing architects seeking in-depth knowledge of Python's capabilities for designing enterprise-grade systems. Whether you're enhancing your design skills or discovering architecture principles, this book supports motivated learners. It is also suitable for IT professionals with intermediate Python expertise who are interested in architectural design patterns and practices.