Description
COURSE OVERVIEW
Python is a popular, general-purpose, multi-paradigm, open-source, scripting language. It is designed to emphasize code readability – has a clean syntax with high level data types. It is suited for interactive work and quick prototyping, while being powerful enough to write large applications in.
Python has a large number of available and well-written modules for everything from abstract syntax trees to ZIP file manipulation. Its ecosystem features an extensive set of tools and fancy.
This course introduces the student to the Python language. On completion of this class the student should feel comfortable with writing Python programs. The course provides insight to the features of Python that make it an excellent choice for projects of virtually any size.
SKILL GAINED
After completing this course, students will be able to:
- use Python interactively
- execute a Python script at the shell prompt
- use Python types, expressions, and None
- use string literals and string type
- use Python statements (if…elif..else, for, pass, continue, . . . )
- understand the difference between expressions and statements
- understand assignment semantics
- write and call a simple function
- utilize high-level data types such as lists and dictionaries
- understand the difference between mutable and immutable types
- write a simple class and access methods and attributes
- import and utilize a module
- read from and write to a text file
TARGET AUDIENCE
This course is for those who have some experience in using at least one scripting language but who do not know Python. It is assumed that you can edit a text file using your favorite editor, and be able to execute your script file on the command line of a shell.
Course Outline
Module 1 – Why Python?
• Why do people use Python?
• Is Python a scripting language?
• What can I do with Python?
• What are Python’s technical strengths?
Module 2 – How Python Runs Programs
• Introducing the Python interpreter
• Program execution
• Execution model variations
Module 3 -Numbers
• Python program structure
• Why use built-in types?
• Numbers
• Python expression Operators
• Numbers in action
• The dynamic typing interlude
Module 4 – Strings
• String literals
• Strings in action
• String formatting
• String methods
• General type categories
Module 5 – Lists & Dictionaries
• Lists
• Lists in action
• Dictionaries
• Dictionaries in action
Module 6 – Tuples, Files & Everything Else
• Tuples
• Files
• Type categories revisited
• Object generality
• References versus copies
• Comparisons, equality, and truth
• Python’s type hierarchies
• Other types in Python
• Built-in type gotchas
Module 7 – Assignment, Expressions, & Print
• Assignment statements
• Expression statements
• Print statements
Module 8 – If Tests
• If statements
• Python syntax rules
• Truth tests
Module 9 – While and For Loops
• While loops
• Break, continue, pass, and the loop else
• For loops
• Loop variations
Module 10 – Function Basics
• Why use functions?
• Coding functions
• Definition & calls
• Intersecting sequences
Module 11 – Scopes & Arguments
• Scope rules
• The global statement
• Scopes and nested functions
• Passing arguments
• Special argument matching modes
Module 12 – The Big Picture
• Why use modules?
• Python program architecture
• How imports work
Module 13 – Coding Basics
• Module creation
• Module usage
• Module namespaces
• Reloading modules
Module 14 – Packages
• Package import basics
• Package import example
• Why use package imports?
Module 15 – OOP: The Big Picture
• Why use classes?
• OOP from 30,000 feet
Module 16 – Class Coding Basics
• Classes generate multiple instance objects
• Classes are customized by inheritance
• Classes can intercept python operators
Module 17 – Class Coding Details
• The class statement
• Methods
• Inheritance
• Operator overloading
• Namespaces
Module 18 – Designing with Classes
• Python and OOP
• Classes as records
• OOP and inheritance: “is-a” relationships
• OOP and composition: “has-a” relationships
• OOP and delegation
• Multiple inheritance
• Classes are objects: Generic object factories
• Methods are objects: Bound or unbound
• Classes versus modules
Module 19 – Exception Basics
• Why use exceptions?
• Exception handling: The short story
• The try/except/else statement
• The try/finally statement
• The raise statement
• The assert statement
Module 20 – Exception Objects
• String-based exceptions
• Class-based exceptions
• General raise statement forms
Module 21 – Designing with Exceptions
• Nesting exception handlers
• Exception idioms
• Exception design tips
• Exception gotchas
• Core language summary
Module 22 – Common Tasks in Python
• Exploring on your own
• Conversions, numbers and comparisons
• Manipulating strings
• Data structure manipulations
• Manipulating files and directories
• Internet-related modules
• Executing programs
• Debugging, testing, timing, profiling
Module 23 – Advanced Topics
• Web frameworks
• GUI frameworks
• Content management frameworks
