Python II: Applied Python

Revision: TE6202_20080222

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Course Length:

4 Days

Course Description:

Once students have mastered the basics of Python, it's time to move on to applying Python to daily programming needs. This course picks up where Python I left off, covering some topics in more detail, and adding new ones. For instance, regular expressions and classes are covered extensively, with network programming (e.g. FTP, Web client and server), graphical programming, database access, and other areas of general need.

Who Should Attend:

This course is appropriate for Python programmers who are ready to ramp their skill up to the next level.

Benefits of Attendance:

Upon completion of this course, students will be able to:

• Apply Python to daily programming needs.

Prerequisites:

Students should be able to write simple Python scripts, using basic data types, program structures, and the standard Python library. Our Python I class provides this necessary background.

Course Outline:

• Python refresher
  1. Basic data
  2. Lists and dictionaries
  3. Program structure
  4. Files and console I/O
  5. Pattern matching
• Data wrangling
  1. Output formatting
  2. The string module
  3. Compiling regular expressions
  4. Text matching and substitution
  5. Extended regular expressions
  6. Subexpressions and backreferences
  7. Alternate data formats
  8. Filename and path manipulation
• OS Services
  1. Using os.path
  2. Working with file systems
  3. Using os
  4. Process parameters
  5. Executing external commands
  6. Time and data data
  7. Environment variables
• Graphical programming
  1. Graphical programming overview
  2. About Tk
  3. The TkInter module
  4. Creating widgets
  5. Packing widgets
  6. Fonts, colors, and other widget attributes
  7. Starting the application
  8. Bindings and events
• Creating modules
  1. Module overview
  2. Understanding namespaces
  3. Writing functions
  4. Variable scope
  5. Documentation
  6. Distributing modules
• Testing and debugging
  1. Debugging issues
  2. Using the debugger
  3. Post-mortem debugging
  4. Designing tests
  5. Creating unit tests
  6. Making and using a test harness
• Fun with objects
  1. Defining classes
  2. Inheritance
  3. Multiple inheritance
  4. Auto-generating methods
• Pythonic Progamming
  1. Python style
  2. Lambda functions
  3. List comprehensions
  4. Generators and iterators
• Network services
  1. Using FTP
  2. Sending with SMTP
  3. Python and CGI
  4. Plain CGI
  5. A shopping cart example
  6. Using templates
• Database access
  1. DB-API overview
  2. The dbi module
  3. The odbc module
  4. Queries
  5. Non-query statements
• Using XML Data
  1. XML Data
  2. SAX vs. DOM
  3. Using xml.sax
  4. Parsing an XML file
  5. Using xml.dom
  6. Accessing XML objects
• Object serialization (AKA Pickling)
  1. About serialization
  2. The pickle module
  3. Using dump()
  4. Using load()
  5. Where to use
• Python Cookbook
  1. Working with zipped data
  2. Copying objects
  3. Obtaining random numbers
  4. Benchmarking code
  5. Application logging
  6. Parsing command line options
  7. Other topics as suggested by students