book

Introducing Python

Name: Introducing Python
Author: Bill Lubanovic
ISBN: 9781449359362

by Bill Lubanovic

November 2014

Beginner

481 pages

10h 11m

English

O'Reilly Media, Inc.

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Preface
AudienceOutlinePython VersionsConventions Used in This BookUsing Code ExamplesSafari® Books OnlineHow to Contact UsAcknowledgments
1. A Taste of Py
Python in the Real WorldPython versus Language XSo, Why Python?When Not to Use PythonPython 2 versus Python 3Installing PythonRunning PythonUsing the Interactive InterpreterUse Python FilesWhat’s Next?Your Moment of ZenThings to Do
2. Py Ingredients: Numbers, Strings, and Variables
Variables, Names, and ObjectsNumbersIntegersPrecedenceBasesType ConversionsHow Big Is an int?FloatsMath FunctionsStringsCreate with QuotesConvert Data Types by Using str()Escape with \Combine with +Duplicate with *Extract a Character with []Slice with [ start : end : step ]Get Length with len()Split with split()Combine with join()Playing with StringsCase and AlignmentSubstitute with replace()More String ThingsThings to Do
3. Py Filling: Lists, Tuples, Dictionaries, and Sets
Lists and TuplesListsCreate with [] or list()Convert Other Data Types to Lists with list()Get an Item by Using [ offset ]Lists of ListsChange an Item by [ offset ]Get a Slice to Extract Items by Offset RangeAdd an Item to the End with append()Combine Lists by Using extend() or +=Add an Item by Offset with insert()Delete an Item by Offset with delDelete an Item by Value with remove()Get an Item by Offset and Delete It by Using pop()Find an Item’s Offset by Value with index()Test for a Value with inCount Occurrences of a Value by Using count()Convert to a String with join()Reorder Items with sort()Get Length by Using len()Assign with =, Copy with copy()TuplesCreate a Tuple by Using ()Tuples versus ListsDictionariesCreate with {}Convert by Using dict()Add or Change an Item by [ key ]Combine Dictionaries with update()Delete an Item by Key with delDelete All Items by Using clear()Test for a Key by Using inGet an Item by [ key ]Get All Keys by Using keys()Get All Values by Using values()Get All Key-Value Pairs by Using items()Assign with =, Copy with copy()SetsCreate with set()Convert from Other Data Types with set()Test for Value by Using inCombinations and OperatorsCompare Data StructuresMake Bigger Data StructuresThings to Do
4. Py Crust: Code Structures
Comment with #Continue Lines with \Compare with if, elif, and elseWhat Is True?Do Multiple Comparisons with inRepeat with whileCancel with breakSkip Ahead with continueCheck break Use with elseIterate with forCancel with breakSkip with continueCheck break Use with elseIterate Multiple Sequences with zip()Generate Number Sequences with range()Other IteratorsComprehensionsList ComprehensionsDictionary ComprehensionsSet ComprehensionsGenerator ComprehensionsFunctionsPositional ArgumentsKeyword ArgumentsSpecify Default Parameter ValuesGather Positional Arguments with *Gather Keyword Arguments with **DocstringsFunctions Are First-Class CitizensInner FunctionsClosuresAnonymous Functions: the lambda() FunctionGeneratorsDecoratorsNamespaces and ScopeUses of _ and __ in NamesHandle Errors with try and exceptMake Your Own ExceptionsThings to Do
5. Py Boxes: Modules, Packages, and Programs
Standalone ProgramsCommand-Line ArgumentsModules and the import StatementImport a ModuleImport a Module with Another NameImport Only What You Want from a ModuleModule Search PathPackagesThe Python Standard LibraryHandle Missing Keys with setdefault() and defaultdict()Count Items with Counter()Order by Key with OrderedDict()Stack + Queue == dequeIterate over Code Structures with itertoolsPrint Nicely with pprint()More Batteries: Get Other Python CodeThings to Do
6. Oh Oh: Objects and Classes
What Are Objects?Define a Class with classInheritanceOverride a MethodAdd a MethodGet Help from Your Parent with superIn self DefenseGet and Set Attribute Values with PropertiesName Mangling for PrivacyMethod TypesDuck TypingSpecial MethodsAggregation and CompositionWhen to Use Classes and Objects versus ModulesNamed TuplesThings to Do
7. Mangle Data Like a Pro
Text StringsUnicodeFormatMatch with Regular ExpressionsBinary Databytes and bytearrayConvert Binary Data with structOther Binary Data ToolsConvert Bytes/Strings with binascii()Bit OperatorsThings to Do
8. Data Has to Go Somewhere
File Input/OutputWrite a Text File with write()Read a Text File with read(), readline(), or readlines()Write a Binary File with write()Read a Binary File with read()Close Files Automatically by Using withChange Position with seek()Structured Text FilesCSVXMLHTMLJSONYAMLA Security NoteConfiguration FilesOther Interchange FormatsSerialize by Using pickleStructured Binary FilesSpreadsheetsHDF5Relational DatabasesSQLDB-APISQLiteMySQLPostgreSQLSQLAlchemyNoSQL Data StoresThe dbm FamilyMemcachedRedisOther NoSQLFull-Text DatabasesThings to Do
9. The Web, Untangled
Web ClientsTest with telnetPython’s Standard Web LibrariesBeyond the Standard Library: RequestsWeb ServersThe Simplest Python Web ServerWeb Server Gateway InterfaceFrameworksBottleFlaskNon-Python Web ServersOther FrameworksWeb Services and AutomationThe webbrowser ModuleWeb APIs and Representational State TransferJSONCrawl and ScrapeScrape HTML with BeautifulSoupThings to Do

10. Systems
FilesCreate with open()Check Existence with exists()Check Type with isfile()Copy with copy()Change Name with rename()Link with link() or symlink()Change Permissions with chmod()Change Ownership with chown()Get a Pathname with abspath()Get a symlink Pathname with realpath()Delete a File with remove()DirectoriesCreate with mkdir()Delete with rmdir()List Contents with listdir()Change Current Directory with chdir()List Matching Files with glob()Programs and ProcessesCreate a Process with subprocessCreate a Process with multiprocessingKill a Process with terminate()Calendars and ClocksThe datetime ModuleUsing the time ModuleRead and Write Dates and TimesAlternative ModulesThings to Do
11. Concurrency and Networks
ConcurrencyQueuesProcessesThreadsGreen Threads and geventtwistedasyncioRedisBeyond QueuesNetworksPatternsThe Publish-Subscribe ModelTCP/IPSocketsZeroMQScapyInternet ServicesWeb Services and APIsRemote ProcessingBig Fat Data and MapReduceWorking in the CloudsThings to Do
12. Be a Pythonista
About ProgrammingFind Python CodeInstall PackagesUse pipUse a Package ManagerInstall from SourceIntegrated Development EnvironmentsIDLEPyCharmIPythonName and DocumentTesting Your CodeCheck with pylint, pyflakes, and pep8Test with unittestTest with doctestTest with noseOther Test FrameworksContinuous IntegrationDebugging Python CodeDebug with pdbLogging Error MessagesOptimize Your CodeMeasure TimingAlgorithms and Data StructuresCython, NumPy, and C ExtensionsPyPySource ControlMercurialGitClone This BookHow You Can Learn MoreBooksWebsitesGroupsConferencesComing Attractions
A. Py Art
2-D GraphicsStandard LibraryPIL and PillowImageMagickGraphical User Interfaces (GUIs)3-D Graphics and AnimationPlots, Graphs, and VisualizationmatplotlibbokehGamesAudio and Music
B. Py at Work
The Microsoft Office SuiteCarrying Out Business TasksProcessing Business DataExtracting, Transforming, and LoadingAdditional Sources of InformationPython in FinanceBusiness Data SecurityMapsFormatsDraw a MapApplications and Data
C. Py Sci
Math and Statistics in the Standard LibraryMath FunctionsWorking with Complex NumbersCalculate Accurate Floating Point with decimalPerform Rational Arithmetic with fractionsUse Packed Sequences with arrayHandling Simple Stats by Using statisticsMatrix MultiplicationScientific PythonNumPyMake an Array with array()Make an Array with arange()Make an Array with zeros(), ones(), or random()Change an Array’s Shape with reshape()Get an Element with []Array MathLinear AlgebraThe SciPy LibraryThe SciKit LibraryThe IPython LibraryA Better InterpreterIPython NotebookPandasPython and Scientific Areas
D. Install Python 3
Install Standard PythonMac OS XWindowsLinux or UnixInstall AnacondaInstall and Use pip and virtualenvInstall and Use conda
E. Answers to Exercises
Chapter 1, A Taste of PyChapter 2, Py Ingredients: Numbers, Strings, and VariablesChapter 3, Py Filling: Lists, Tuples, Dictionaries, and SetsChapter 4, Py Crust: Code StructuresChapter 5, Py Boxes: Modules, Packages, and ProgramsChapter 6, Oh Oh: Objects and ClassesChapter 7, Mangle Data Like a ProChapter 8, Data Has to Go SomewhereChapter 9, The Web, UntangledChapter 10, SystemsChapter 11, Concurrency and Networks
F. Cheat Sheets
Operator PrecedenceString MethodsChange CaseSearchModifyFormatString TypeString Module AttributesFin
Index

Content preview from Introducing Python

Appendix B. Py at Work

“Business!” cried the Ghost, wringing its hands again. “Mankind was my business...”

Charles Dickens, A Christmas Carol

The businessman’s uniform is a suit and tie. But for some reason, when he decides to get down to business, he tosses his jacket over a chair, loosens his tie, rolls up his sleeves, and pours some coffee. Meanwhile the business woman, with little fanfare, is actually getting work done. Maybe with a latte.

In business, we use all of the technologies from the earlier chapters—databases, the Web, systems, and networks. Python’s productivity is making it more popular in the enterprise and with startups.

Businesses have long sought silver bullets to slay their legacy werewolves—incompatible file formats, arcane network protocols, language lock-in, and the universal lack of accurate documentation. However, today we see some technologies and techniques that can actually interoperate and scale. Businesses can create faster, cheaper, stretchier applications by employing the following:

Dynamic languages like Python
The Web as a universal graphical user interface
RESTful APIs as language-independent service interfaces
Relational and NoSQL databases
“Big data” and analytics
Clouds for deployment and capital savings

The Microsoft Office Suite

Business is heavily dependent on Microsoft Office applications and file formats. Although they are not well known, and in some cases poorly documented, there are some Python libraries that can help. ...

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Publisher Resources

ISBN: 9781449361167Errata Page

Cloud Computing

Data Engineering

Data Science

AI & ML

Programming Languages

Software Architecture

IT/Ops

Security

Design

Business

Soft Skills

Introducing Python

by Bill Lubanovic

Appendix B. Py at Work

The Microsoft Office Suite

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.