book

Learn Python Programming - Third Edition

Name: Learn Python Programming - Third Edition
ISBN: 9781801815093

by Fabrizio Romano, Heinrich Kruger

October 2021

Beginner

554 pages

12h 52m

English

Packt Publishing

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Preface
Who this book is forWhat this book coversTo get the most out of this bookGet in touch
A Gentle Introduction to Python
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
Built-In Data Types
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
Conditionals and Iteration
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
Functions, the Building Blocks of Code
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
Comprehensions and Generators
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
OOP, Decorators, and Iterators
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
Exceptions and Context Managers
ExceptionsRaising exceptionsDefining your own exceptionsTracebacksHandling exceptionsNot only for errorsContext managersClass-based context managersGenerator-based context managersSummary
Files and Data Persistence
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
Cryptography and Tokens
The need for cryptographyUseful guidelinesHashlibHMACSecretsRandom numbersToken generationDigest comparisonJSON Web TokensRegistered claimsTime-related claimsAuthentication-related claimsUsing asymmetric (public key) algorithmsUseful referencesSummary

Testing
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 and Profiling
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
GUIs and Scripting
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
Data Science in Brief
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
Introduction to API Development
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
Packaging Python Applications
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
Other Books You May Enjoy
Index

Content preview from Learn Python Programming - Third Edition

4 Functions, the Building Blocks of Code

"To create architecture is to put in order. Put what in order? Functions and objects."
– Le Corbusier

In the previous chapters, we have seen that everything is an object in Python, and functions are no exception. But what exactly is a function? A function is a sequence of instructions that perform a task, bundled together as a unit. This unit can then be imported and used wherever it is needed. There are many advantages to using functions in your code, as we'll see shortly.

In this chapter, we are going to cover the following:

Functions—what they are and why we should use them
Scopes and name resolution
Function signatures—input parameters and return values
Recursive and anonymous functions
Importing ...

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Learn Python Programming - Third Edition

by Fabrizio Romano, Heinrich Kruger

4

Functions, the Building Blocks of Code

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.