Transcript CIT 590 Intro to Programming Lecture 2 Questions regarding enrollment • The cap is still in effect • The course will be offered again.

CIT 590
Intro to Programming
Lecture 2
Questions regarding enrollment
• The cap is still in effect
• The course will be offered again in the spring
• The waitlist is closed as well
• If you know programming, please consider dropping the
course and taking courses like
• Computational linguistics
• Software engineering
• If you do not want to spend a fair amount of time
programming please drop the course
• If you can take CIS 110 (the undergrad intro to
programming) they have 1 section still open
• If you really absolutely have to do this course, you will
have to talk to Mike Felker and convince him
Agenda
• ‘import’
• IDLE frustrations
• Abstraction
• Functions
• Testing
• The concept of scope
One big giant python file ….
• Python is full of modules
• import math
• from math import *
• the same logic can be used for your own functions
• areaFuncs.py and usageOfFuncs.py
• Importing a module within another module
Agenda
• ‘import’
• IDLE frustrations
• Abstraction
• Functions
• Testing
• The concept of scope
Things you cannot do in IDLE
• Line numbers – there are some extensions that I have not
tried out
• Do not forget the .py extension
• History using the up and down keys
• Configure idle
• For other complaints …
• http://inventwithpython.com/blog/2011/11/29/the-things-i-hateabout-idle-that-i-wish-someone-would-fix/
Agenda
• ‘import’
• IDLE frustrations
• Abstraction
• Functions
• Testing
• The concept of scope
Abstraction
• A good program will have layers of abstraction
• Sometimes you only care about the input and output and
do not really want or even need to know the intrinsics
• math.sqrt() how is implemented
• Who cares!
• APIs (Application Programming Interfaces)
• https://code.google.com/p/python-twitter/
PennApps!!!
• http://2013f.pennapps.com/
Modular programming
• Software design technique that emphasizes separating
the functionality of a program into independent,
interchangeable modules
• each module contains everything necessary to execute
only one aspect of the desired functionality.
• You’ll also hear this referred to as top-down design and
stepwise refinement
functions
• In accordance with the concept of abstraction
• Divide a program up into its ‘functional’ portions
• Testing becomes much easier
• Test each component really well
• Think about a few integration tests
• vowelCounter.py
Information hiding
• David Parnas first introduced the concept of information
hiding around 1972.
• hiding "difficult design decisions or design decisions which
are likely to change."
• Hiding information in that manner isolates clients from
requiring intimate knowledge of the design to use a
module, and from the effects of changing those decisions.
Software reuse
• Do not reinvent the wheel
• The reuse of programming code is a common technique
which attempts to save time and energy by reducing
redundant work.
• Software libaries/modules - good example of code reuse
Good program design
• Separate your program into the building blocks
• Write a function for each of the building blocks
• Simple methods of separation
• Separate functions for the calculations
• Separate function for the input
• Separate function for the output
The coke machine example
• Cokemachine1 and cokemachine2.py
Testing functions
• Debugging via test cases
• Reading code – romanNumeral.py
• Code reviews
Scoping
• local variables versus global variables
• changing the value of a global variable within a function
using the global keyword
Summary
• Understanding the importance of modular programming
• Functions
• Testing a function and code walkthroughs
• Variable scope