book

Python Essentials

Name: Python Essentials
Author: Steven F. Lott
ISBN: 9781784390341

by Steven F. Lott

June 2015

Intermediate to advanced

298 pages

7h 15m

English

Packt Publishing

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Python Essentials
Table of Contents
Python Essentials
Credits
About the Author
About the Reviewers
www.PacktPub.com
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Preface
What this book covers
What you need for this book
Who this book is for

Conventions
Reader feedback
Customer support
Downloading the example codeErrataPiracyQuestions
1. Getting Started
Installation or upgradeInstalling Python on WindowsConsidering some alternativesUpgrading to Python 3.4 in Mac OS XAdding the Tkinter packageUpgrading to Python 3.4 in Linux
Using the Read-Evaluate-Print Loop (REPL)
Confirming that things are workingDoing simple arithmeticAssigning results to variablesUsing import to add features
Interacting with the help subsystem
Using the pydoc program
Creating simple script files
Simplified syntax rules
The Python ecosystem
The idea of extensibility via add-onsUsing the Python Package Index – PyPIUsing pip to gather modulesUsing easy_install to add modulesInstalling modules manually
Looking at other Python interpreters
Summary
2. Simple Data Types
Introducing the built-in operatorsMaking comparisonsUsing integersUsing the bit-oriented operatorsUsing rational numbersUsing decimal numbersUsing floating-point numbersUsing complex numbers
The numeric tower
The math libraries
Using bits and Boolean values
Working with sequences
Slicing and dicing a sequence
Using string and bytes values
Writing string literalsUsing raw string literalsUsing byte string literalsUsing the string operatorsConverting between Unicode and bytesUsing string methodsAccessing the details of a stringParsing strings into substrings
Using the tuple collection
The None object
The consequences of immutability
Using the built-in conversion functions
Summary
3. Expressions and Output
Expressions, operators, and data typesUsing operators on non-numeric data
The print() function
Examining syntax rules
Splitting, partitioning, and joining strings
Using the format() method to make more readable output
Summary of the standard string libraries
Using the re module to parse stringsUsing regular expressionsCreating a regular expression stringWorking with Unicode, ASCII, and bytesUsing the locale module for personalization
Summary
4. Variables, Assignment and Scoping Rules
Simple assignment and variables
Multiple assignment
Using repeated assignment
Using the head, *tail assignment
Augmented assignment
The input() function
Python language concepts
Object types versus variable declarationsAvoiding confusion when naming variablesGarbage collection via reference countingThe little-used del statement
The Python namespace concept
Globals and locals
Summary
5. Logic, Comparisons, and Conditions
Boolean data and the bool() function
Comparison operators
Combining comparisons to simplify the logicTesting float valuesComparing object IDs with the is operatorEquality and object hash values
Logic operators – and, or, not, if-else
Short-circuit (or non-strict) evaluation
The if-elif-else statement
Adding elif clauses
The pass statement as a placeholder
The assert statement
The logic of the None object
Summary
6. More Complex Data Types
The mutability and immutability distinction
Using the list collection
Using list operatorsMutating a list with subscriptsMutating a list with method functionsAccessing a list
Using collection functions
Using the set collection
Using set operatorsMutating a set with method functionsUsing augmented assignment with setsAccessing a set with operators and method functions
Mappings
Using dictionary operatorsUsing dictionary mutatorsUsing methods for accessing items in a mappingUsing extensions from the collections module
Processing collections with the for statement
Using literal lists in a for statementUsing the range() and enumerate() functions
Iterating with the while statement
The continue and break statements
Breaking early from a loop
Using the else clause on a loop
Summary
7. Basic Function Definitions
Looking at the five kinds of callables
Defining functions with positional parameters
Defining multiple parametersUsing the return statementEvaluating a function with positional or keyword argumentsWriting a function's docstring
Mutable and immutable argument values
Defining optional parameters via default values
A warning about mutable default values
Using the "everything else" notations of * and **
Using sequences and dictionaries to fill in *args and *kw
Nested function definitions
Working with namespaces
Assigning a global variableAssigning a non-local variable
Defining lambdas
Writing additional function annotations
Summary
8. More Advanced Functions
Using the for statement with iterable collectionsIterators and iterable collections
Consequences and next steps
Using generator expressions and comprehensions
Limitations of generator expressionsUsing multiple loops and conditionsWriting comprehensions
Defining generator functions with the yield statement
Using the higher-order functions
Writing our own higher-order functions
Using the built-in reductions – max, min, and reduce
Three ways to sort a sequence
Sorting via a key functionSorting via wrapping and unwrapping
Functional programming design patterns
Summary
9. Exceptions
The core exception conceptExamining the exception object
Using the try and except statements
Using nested try statements
Matching exception classes in an except clause
Matching more general exceptionsThe empty except clause
Creating our own exceptions
Using a finally clause
Use cases for exceptions
Issuing warnings instead of exceptions
Permission versus forgiveness – a Pythonic approach
Summary
10. Files, Databases, Networks, and Contexts
The essential file conceptOpening text filesFiltering text linesWorking with raw bytesUsing file-like objects
Using a context manager via the with statement
Closing file-like objects with contextlib
Using the shelve module as a database
Using the sqlite databaseUsing object-relational mapping
Web services and Internet protocols
Physical format considerations
Summary
11. Class Definitions
Creating a class
Writing the suite of statements in a class
Using instance variables and methods
Pythonic object-oriented programming
Trying to do type castingDesigning for encapsulation and privacy
Using properties
Using inheritance to simplify class definitions
Using multiple inheritance and the mixin design pattern
Using class methods and attributes
Using mutable class variablesWriting static methods
Using __slots__ to save storage
The ABCs of abstract base classes
Writing a callable class
Summary
12. Scripts, Modules, Packages, Libraries, and Applications
Script file rules
Running a script by the filename
Running a script by its module nameRunning a script using OS shell rulesChoosing good script names
Creating a reusable module
Creating a hybrid library/application module
Creating a package
Designing alternative implementations
Seeing the package search path
Summary
13. Metaprogramming and Decorators
Simple metaprogramming with decorators
Defining our own decorator
More complex metaprogramming with metaclasses
Summary
14. Fit and Finish – Unit Testing, Packaging, and Documentation
Writing docstrings
Writing unit tests with doctest
Using the unittest library for testing
Combining doctest and unittest
Using other add-on test libraries
Logging events and conditions
Configuring the logging system
Writing documentation with RST markup
Creating HTML documentation from an RST sourceUsing the Sphinx tool
Organizing Python code
Summary
15. Next Steps
Leveraging the standard library
Leveraging PyPI – the Python Package Index
Types of applications
Building CLI applications
Getting command-line arguments with argparseUsing the cmd module for interactive applications
Building GUI applications
Using more sophisticated packages
Building web applications
Using a web frameworkBuilding a RESTful web service with Flask
Plugging into a MapReduce framework
Summary
Index

Content preview from Python Essentials

Defining generator functions with the yield statement

A generator function has properties similar to a generator expression. Rather than a single expression, a generator function is a full Python function. It has all of the features of the functions described in Chapter 7, Basic Function Definitions. It has the additional characteristic of being an iterator, capable of generating a sequence of items.

When we use a yield statement, the semantics of the function are changed. Without a yield, a function will return a single value. With a yield statement, a function will behave like an iterator, providing multiple values to a consumer.

Here's an example of a generator function that applies a range of values to a model to compute a domain of results. ...

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ISBN: 9781784390341

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Python Essentials

by Steven F. Lott

Defining generator functions with the yield statement

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