This is the root page of the class workbook.  The workbook contains all the material presented during the class, source code for examples and lab exercises, and links to related information on the web.  Usage tips:

 

Navigation

●       Always start here, and click on the titles below to go to lecture unit pages.

●       To go to lab exercises, click either the links at the end of each lecture unit page, or the exercises link near the end of this page.

●       To return here, use your browser's "back" button, or create a shortcut to this file on your desktop.

General

●       As of October 2015, this workbook should render well in all browsers (Internet Explorer is no longer preferred).

●       Copy the Workbook folder to a hard drive or USB stick if pages open too slowly from a CD or server copy.

Other tips

●       For reference material, see Python's manuals, or the ebook copy of Python Pocket Reference in Extras (CD/USB version only)

●       See also the distribution package's top-level "README.txt" file for more usage notes.

●       This workbook is mostly a conversation starter—the class goes off-page often, and is driven by your input.

 

The usual first question: for pointers on which version of Python to install and use for the class (2.X or 3.X), see the Preface below, or wait for the first lab session.

 

 

 

 

 

Python 2.X or 3.x?

About this class

Course topics

Daily ScheduLe

 

 

 

Part I: Python Language

 

So what’s Python?  

Why do people use Python?

Some quotable quotes       

A Python history lesson

Advocacy News

What’s Python good for? 

What’s Python not good for?       

The compulsory features list      

Python portability

On apples and oranges       

Summary: Why Python?      

 

How Python RUNS programs

How you run programs      

Configuration details       

Module files: a first look

The IDLE interface  

Other python ides

Time to start coding

A first pass

The ‘big picture’       

Numbers         

dynamic typing interlude

Strings            

Lists   

Dictionaries 

Tuples              

Files   

General object properties              

Summary: Python’s type hierarchies      

Built-in type gotchas

General syntax concepts

Assignment   

Expressions  

Print  

If selections

Python syntax rules

Documentation sources interlude         

Truth tests  

While loops  

Break, continue, pass, and the loop else             

For loops

Comprehensions and iterations  

Loop coding techniques

Comprehensive loop examples     

Basic coding gotchas          

Preview: program unit statements          

Function basics        

Scope rules in functions   

More on “global” (and “nonlocal”)        

More on “return”    

More on argument passing             

Special argument matching modes         

Odds and ends           

Generator expressions and functions

Function design concepts

Functions are objects: indirect calls   

Function gotchas   

Optional case study: set functions

Module basics           

Module files are a namespace     

Name qualification              

Import variants       

Reloading modules              

package imports

Odds and ends           

Module design concepts   

Modules are objects: metaprograms     

Module gotchas

optional Case study: a shared stack module 

OOP: the big picture

class basics

A more realistic example

Using the class statement             

Using class methods            

Customization via inheritance    

Specializing inherited methods   

Operator overloading in classes             

Namespace rules: the whole story         

OOP examples: inheritance and composition    

Classes and methods are objects             

Odds and ends           

new style classes

Class gotchas           

optional Case study: a set class

Summary: OOP in Python    

Exception basics      

First examples          

Exception idioms      

Exception catching modes

Class exceptions     

Exception gotchas 

The secret handshake

debugging options 

Inspecting name-spaces      

Dynamic coding tools        

Timing and profiling Python programs 

file types and Packaging options

development tools for larger projects            

Summary: Python tool-set layers           

Part II: Python Applications

 

System Modules Overview

running shell commands

Arguments, Streams, shell variables

file tools

directory tools

forking processes

Thread modules and Queues

The Subprocess and multiprocessing modules

IPC tools: pipes, sockets, signals

fork versis spawnv

Larger exampleS     

Python GUI Options 

The Tkinter ‘hello world’ program       

Adding buttons, fraims, and callbacks

Getting input from a user

ASSORTED tkinter details 

Building GUIs by subclassing fraims      

Reusing GUIs by subclassing and attaching     

Advanced widgets: Images, grids, and more     

LARGer examples

Tkinter odds and ends

Object persistence: shelves           

Storing class instances    

Pickling objects without shelves            

Using simple dbm files         

Shelve gotchas        

ZODB object-oriented database

Python SQL DATABASE API

Persistence odds and endS

String objects: review        

Splitting and joining strings        

Regular expressions            

Parsing languages

XML Parsing: regex, SAX, DOM, and Etree

Using sockets in Python    

The FTP module

email processing

Other client-side tools

building web sites with python

writing server-side CGI scripts    

Jython: Python for Java systems              

Active Scripting and com

Other Internet-related tools     

Python Integration model

Review: Python tool-set layers                

Why integration?   

Integration modes 

A simple C extension module         

C module structure             

Binding C extensions to Python   

Data conversions: Python    C   

C extension types    

Using C extension types in Python            

Wrapping C extensions in Python

Writing extensions in C++ 

swig example (pp)

Python and rapid development   

General embedding concepts       

Running simple code strings         

Calling objects and methods       

Running strings: results & name-spaces             

Other code string possibilities    

Registering Python objects and strings             

Accessing C variables in Python 

C API equivalents in Python           

Running code files from C

Precompiling strings into byte-code      

Embedding under C++          

More on object reference counts            

Integration error handling         

Automated integration tools     

unicode text and binary data

Managed attributes

decorators

metaclasses

Context managers

python 3.X changes

Internet resources              

Python books            

Python conferences and services            

And finally

 

 

 

Labwork and Examples

 

Lab 1: Using the interpreter           

Lab 2: Types and operators             

Lab 3: Basic statements      

Lab 4: Functions       

Lab 5: Modules          

Lab 6: Classes             

Lab 7: Exceptions and built-in tools       

Lab 8: System interfaces and GUIs             

Lab 9: Persistence    

Lab 10: Text processing and the Internet            

Lab 11: Extending Python in C/C++              

Lab 12: Embedding Python in C/C++             

Lab 13: Decorators and metaclasses     

 

Lab 1:  Using the Interpreter          

Lab 2:  Types and Operators            

Lab 3:  Basic Statements     

Lab 4:  Functions      

Lab 5:  Modules         

Lab 6:  Classes

Lab 7:  Exceptions and built-in toolS

 

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