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Python Fundamentals

Course Length: 5 days

Class Schedule
Call for Class Schedule

  • Hands-on instruction by a certified instructor
  • Includes all course materials
  • On-site Testing
  • Lunch & Snacks provided each day

Learning any programming language as sophisticated as today's Python requires a substantial investment in time and focus, spanning a progression of steps: from initial introduction, to in-depth study, to practical project experience. Especially for less-experienced students, this can be an ongoing process that spans months or years, depending on required skill level.

Our class is designed to optimize the first steps of this process - to jumpstart your Python learning experience.

  • Provide in-depth, hands-on introductions to both the Python language itself, as well as ways to apply it to common programming tasks
  • Focus on fundamentals and core concepts which span application domains and reflect real-world Python programming
  • Allow students to interact with a domain expert and focus on the subject matter, in ways that only live, in-person training can

Prerequisites

In general, this class is designed to work best for students with some prior programming background, though no specific programming language or application is assumed.

Absolute student prerequisites are difficult to set because success in this class depends upon both student background and motivation. While students should ideally have some past experience with at least one programming language, this class has worked well for both relative novices and advanced experts alike. Motivated students find that our classes provide the solid introduction needed to make the next steps of their learning process successful.

What About Beginners?

Absolute beginners who have never done any programming or scripting in the past may find our classes challenging, as we assume some exposure to basic programming concepts in the past. Moreover, some latter portions of the class may be more suitable for a programming proficient crowd. However, no specific prior programming language experience is assumed; the class's pace is dictated by the mix of its students' skill levels; and the more advanced topics late in the class can easily be treated as optional for less experienced students.

Course Outline

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
  • Program execution model
  • Program architecture: modules
  • How to run Python programs
  • Configuration details
  • Module files: a first look
  • The IDLE interface
  • Other python IDEs
  • Time to start coding
3. Types and Operators
  • Core datatypes introduction
  • Dynamic typing
  • Numbers
  • Strings
  • Lists
  • Dictionaries
  • Tuples
  • Files
  • General object properties
  • Summary: Python's type hierarchies
  • Built-in type gotchas
4. Basic Statements
  • General syntax model
  • Assignment
  • Expressions
  • Print
  • If selections
  • Python syntax rules
  • Pydoc and documentation strings
  • Truth tests
  • While loops
  • Break, continue, pass, and the loop else
  • For loops
  • List comprehensions
  • Loop coding techniques
  • Comprehensive examples: file scanners
  • Basic coding gotchas
  • Preview: program unit statements
5. Functions
  • Function basics
  • Scope rules in functions
  • More on "global"
  • More on "return"
  • Argument passing
  • Special argument matching modes
  • Demo: minimum value functions
  • Odds and ends
  • Design concepts: globals, accessors, closures
  • Functions are objects: indirect calls
  • Function gotchas
  • Optional case study set functions
6. Modules
  • Module basics
  • Module files are a namespace
  • Import variants
  • Reloading modules
  • Package imports
  • __name__ and __main__
  • Odds and ends
  • Module design concepts
  • Modules are objects: metaprograms
  • Module gotchas
  • optional Case study: a shared stack module
7. Classes
  • OOP: The big picture
  • Python class basics
  • Demo: People classes database
  • Using the class statement
  • Using class methods
  • Customization via inheritance
  • Specializing inherited methods
  • Operator overloading in classes
  • Namespace rules: the whole story
  • Design: inheritance and composition
  • Classes are objects: factories
  • Methods are objects: bound or unbound
  • Odds and ends
  • Class gotchas
  • optional Case study: a set class
  • Summary: OOP in Python
8. Exceptions
  • Exception basics
  • First examples
  • Exception idioms
  • Exception catching modes
  • Matching variations
  • Exception gotchas
9. Built-in Tools Overview
  • Debugging options
  • Inspecting name-spaces
  • Dynamic coding tools
  • Timing and profiling Python programs
  • Packaging programs for delivery
  • Summary: Python tool-set layers
10. System Interfaces
  • System Modules overview
  • Arguments, Streams, Shell variables
  • File tools
  • Directory tools
  • Demo: finding large files
  • Forking processes
  • Thread modules and queues
  • The subprocess and multiprocessing modules
  • IPC tools: pipes, sockets, signals
  • fork versus spawnv
  • Demo: regression testing
  • Advanced system examples
11. GUI Programming
  • Python GUI Options
  • The Tkinter 'hello world' program
  • Adding buttons, frames, and callbacks
  • Getting input from a user
  • Layout details
  • Demo: a Python/Tkinter GUI
  • Building GUIs by subclassing frames
  • Reusing GUIs by subclassing and attaching
  • Advanced widgets: images, grids, and more
  • Sexier examples
  • Tkinter odds and ends
12. Databases and Persistence
  • Object persistence: shelves
  • Storing class instances
  • Pickling objects without shelves
  • Using simple dbm files
  • Shelve gotchas
  • Python SQL database API
  • ZODB object-oriented database
  • Demo: using MySQL from Python
  • Persistence odds and ends
13. Text Processing
  • String objects: review
  • Splitting and joining strings
  • Demo: parsing data files
  • Regular expressions
  • Parsing languages
  • XML parsing: regex, Sax, DOM, and etree
14. Internet Scripting
  • Using sockets in Python
  • The FTP module
  • email processing
  • Other client-side tools
  • Writing server-side CGI scripts
  • Demo: an interactive Web Site in Python
  • Jython: Python for Java systems
  • Active Scripting and com
  • Python web frameworks
  • Other Internet-related tools
15. Extending Python in C/C++
  • Review: Python tool-set layers
  • Stuff Guido already wrote
  • Why integration?
  • Integration modes
  • A simple C extension module
  • C module structure
  • Binding C extensions to Python
  • Data conversions: Python to/from C
  • C extension types
  • Using C extension types in Python
  • Wrapping C extensions in Python
  • Writing extensions in C++
  • SWIG example
  • Compiling with distutils
  • Other extending options
  • Python and rapid development
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
17. Advanced Topics
  • Unicode text and binary data
  • Managed attributes
  • Decorators
  • Metaclasses
  • Context managers
  • Python 3.0 changes
18. Resources
  • Python portability
  • Major python packages
  • Internet resources
  • Python books
  • Python in the news: articles, chapters
  • Python conferences and services

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