Learning Python
Student Workbook
October, 2015
HTML Workbook Version 2.7-3.5
Copyright © Mark Lutz, 1997—2015
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
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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.
● 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.
Contents
Preface
Python 2.X or 3.x?
About this class
Course topics
Daily ScheduLe
Part I: Python Language
1: General Python Introduction
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?
2. Using the Interpreter
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
Lab session 1
3. Types and Operators
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
Lab session 2
4. Basic Statements
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
Lab session 3
5. Functions
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
Lab session 4
6. Modules
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
Lab session 5
7. Classes
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
lab session 6
8. Exceptions
Exception basics
First examples
Exception idioms
Exception catching modes
Class exceptions
Exception gotchas
lab session 7
9. Built-in Tools Overview
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
lab session 7
Part II: Python Applications
10. System Interfaces
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
lab session 8
11. GUI Programming
Python GUI Options
The Tkinter ‘hello world’ program
Adding buttons, frames, and callbacks
Getting input from a user
ASSORTED tkinter details
Building GUIs by subclassing frames
Reusing GUIs by subclassing and attaching
Advanced widgets: Images, grids, and more
LARGer examples
Tkinter odds and ends
lab session 8
12. Databases and Persistence
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
lab session 9
13. Text Processing
String objects: review
Splitting and joining strings
Regular expressions
Parsing languages
XML Parsing: regex, SAX, DOM, and Etree
lab session 10
14. Internet Scripting
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
lab session 10
15. Extending Python in C/C++
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 Û 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
lab session 11
16. Embedding Python in C/C++
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
lab session 12
17. Advanced Topics
unicode text and binary data
Managed attributes
decorators
metaclasses
Context managers
python 3.X changes
lab session 13
18. Resources
Internet resources
Python books
Python conferences and services
And finally
Labwork and Examples
Laboratory Exercises
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
Selected Exercise Solutions
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