book

Learn Python Programming - Third Edition

by Fabrizio Romano, Heinrich Kruger

October 2021

Beginner

554 pages

12h 52m

English

Packt Publishing

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Who this book is forWhat this book coversTo get the most out of this bookGet in touch
A proper introductionEnter the PythonAbout PythonPortabilityCoherenceDeveloper productivityAn extensive librarySoftware qualitySoftware integrationSatisfaction and enjoymentWhat are the drawbacks?Who is using Python today?Setting up the environmentPython 2 versus Python 3Installing PythonSetting up the Python interpreterAbout virtual environmentsYour first virtual environmentInstalling third-party librariesYour friend, the consoleHow to run a Python programRunning Python scriptsRunning the Python interactive shellRunning Python as a serviceRunning Python as a GUI applicationHow is Python code organized?How do we use modules and packages?Python's execution modelNames and namespacesScopesObjects and classesGuidelines for writing good codePython cultureA note on IDEsSummary
Everything is an objectMutable or immutable? That is the questionNumbersIntegersBooleansReal numbersComplex numbersFractions and decimalsImmutable sequencesStrings and bytesEncoding and decoding stringsIndexing and slicing stringsString formattingTuplesMutable sequencesListsBytearraysSet typesMapping types: dictionariesData typesDates and timesThe standard libraryThird-party librariesThe collections modulenamedtupledefaultdictChainMapEnumsFinal considerationsSmall value cachingHow to choose data structuresAbout indexing and slicingAbout namesSummary
Conditional programmingA specialized else: elifThe ternary operatorLoopingThe for loopIterating over a rangeIterating over a sequenceIterators and iterablesIterating over multiple sequencesThe while loopThe break and continue statementsA special else clauseAssignment expressionsStatements and expressionsUsing the walrus operatorA word of warningPutting all this togetherA prime generatorApplying discountsA quick peek at the itertools moduleInfinite iteratorsIterators terminating on the shortest input sequenceCombinatoric generatorsSummary
Why use functions?Reducing code duplicationSplitting a complex taskHiding implementation detailsImproving readabilityImproving traceabilityScopes and name resolutionThe global and nonlocal statementsInput parametersArgument-passingAssignment to parameter names Changing a mutable objectPassing argumentsPositional argumentsKeyword argumentsIterable unpackingDictionary unpackingCombining argument typesDefining parametersOptional parametersVariable positional parametersVariable keyword parametersPositional-only parametersKeyword-only parametersCombining input parametersMore signature examplesAvoid the trap! Mutable defaultsReturn valuesReturning multiple valuesA few useful tipsRecursive functionsAnonymous functionsFunction attributesBuilt-in functionsDocumenting your codeImporting objectsRelative importsOne final exampleSummary
The map, zip, and filter functionsmapzipfilterComprehensionsNested comprehensionsFiltering a comprehensionDictionary comprehensionsSet comprehensionsGeneratorsGenerator functionsGoing beyond nextThe yield from expressionGenerator expressionsSome performance considerationsDon't overdo comprehensions and generatorsName localizationGeneration behavior in built-insOne last exampleSummary
DecoratorsA decorator factoryObject-oriented programming (OOP)The simplest Python classClass and object namespacesAttribute shadowingThe self argumentInitializing an instanceOOP is about code reuseInheritance and compositionAccessing a base classMultiple inheritanceMethod resolution orderClass and static methodsStatic methodsClass methodsPrivate methods and name manglingThe property decoratorThe cached_property decoratorOperator overloadingPolymorphism – a brief overviewData classesWriting a custom iteratorSummary
ExceptionsRaising exceptionsDefining your own exceptionsTracebacksHandling exceptionsNot only for errorsContext managersClass-based context managersGenerator-based context managersSummary
Working with files and directoriesOpening filesUsing a context manager to open a fileReading and writing to a fileReading and writing in binary modeProtecting against overwriting an existing fileChecking for file and directory existenceManipulating files and directoriesManipulating pathnamesTemporary files and directoriesDirectory contentFile and directory compressionData interchange formatsWorking with JSONCustom encoding/decoding with JSONI/O, streams, and requestsUsing an in-memory streamMaking HTTP requestsPersisting data on diskSerializing data with pickleSaving data with shelveSaving data to a databaseSummary
The need for cryptographyUseful guidelinesHashlibHMACSecretsRandom numbersToken generationDigest comparisonJSON Web TokensRegistered claimsTime-related claimsAuthentication-related claimsUsing asymmetric (public key) algorithmsUseful referencesSummary

Testing your applicationThe anatomy of a testTesting guidelinesUnit testing Writing a unit testMock objects and patchingAssertionsTesting a CSV generatorBoundaries and granularityTesting the export functionFinal considerationsTest-driven developmentSummary
Debugging techniquesDebugging with printDebugging with a custom functionUsing the Python debuggerInspecting logsOther techniquesReading tracebacksAssertionsWhere to find informationTroubleshooting guidelinesWhere to inspectUsing tests to debugMonitoringProfiling PythonWhen to profileMeasuring execution timeSummary
First approach: scriptingThe importsParsing argumentsThe business logicSecond approach: a GUI applicationThe importsThe layout logicThe business logicFetching the web pageSaving the imagesAlerting the userHow can we improve the application?Where do we go from here?The turtle modulewxPython, Kivy, and PyQtThe principle of least astonishmentThreading considerationsSummary
IPython and Jupyter NotebookUsing AnacondaStarting a NotebookDealing with dataSetting up the NotebookPreparing the dataCleaning the dataCreating the DataFrameUnpacking the campaign nameUnpacking the user dataCleaning everything upSaving the DataFrame to a fileVisualizing the resultsWhere do we go from here?Summary
What is the Web?How does the Web work?Response status codesType hinting: An overviewWhy type hinting?Type hinting in a nutshellAPIs: An introductionWhat is an API?What is the purpose of an API?API protocolsAPI data-exchange formatsThe railway APIModeling the databaseMain setup and configurationAdding settingsStation endpointsReading dataCreating dataUpdating dataDeleting dataUser authenticationDocumenting the APIConsuming an APICalling the API from DjangoWhere do we go from here?Summary
The Python Package Index The train schedule projectPackaging with setuptoolsRequired filespyproject.tomlLicenseREADMEChangelogsetup.cfgsetup.pyMANIFEST.inPackage metadataAccessing metadata in your codeDefining the package contentsAccessing package data filesSpecifying dependenciesEntry pointsBuilding and publishing packagesBuildingPublishingAdvice for starting new projectsAlternative toolsFurther readingSummary

Overview

Learn Python Programming, Third Edition, provides a comprehensive introduction to Python, a flexible and powerful programming language widely used in various fields. Through this book, you'll not only learn the fundamentals of Python, but also gain hands-on experience in API development, GUI programming, and data science.

What this Book will help me do

Understand Python setup and configuration across multiple platforms.
Learn to write clean, reusable, and efficient Python code.
Gain expertise in implementing Python for web APIs and GUIs.
Explore Python's data structures for effective data manipulation.
Delve into advanced topics like data persistence and cryptography.

Author(s)

None Romano and None Kruger bring their years of Python programming and teaching experience to this volume. They are dedicated to making Python accessible and comprehensive for learners of all backgrounds. Their practical examples and project-based approach ensure readers not only learn programming, but also how to apply it effectively.

Who is it for?

This book is aimed at individuals new to programming who wish to start with Python, as well as intermediate programmers who want a deeper understanding of Python's capabilities. It's suitable for professionals looking to expand their skills in API development, data science, or GUI programming. While prior programming experience isn't required, some familiarity with basic concepts will enhance the learning experience.