Consolidation and Review

Transcription

1 Consolidation and Review Professor Hugh C. Lauer CS-1004 Introduction to Programming for Non-Majors (Slides include materials from Python Programming: An Introduction to Computer Science, 2 nd edition, by John Zelle and copyright notes by Prof. George Heineman of ) 1

2 At start of term Mixture of skills Smattering of programming experience Mostly Java Some familiarity with formulas in Excel Need to do computing in own fields 2

3 First Problem Find area of a disk: Easy to do manually (for one disk) More difficult for many disks 3

4 Straightforward in Excel This is, in fact, a form of programming! Change value of cell Excel reacts by changing values of all cells depending on that one! Very useful for many types of problems CS-1004, A-Term 2014 First Python Program 4

5 Python Qualitatively different Actions carried out step-by-step Each step does something specific Evaluate expression Test condition Repeat sequences of steps Call function encapsulation of steps Excel: Modify one cell Excel modifies all dependent cells and all cells dependent on them and all cells dependent on them etc., etc., etc. (Internally), Excel keeps lists of dependencies of each cell and then does this whenever a cell changes! 5

6 This course has been about programming in an algorithmic language What is an algorithm? P. 4: step-by-step process for achieving a desired result I.e., a recipe! Approximately 1/3 of this course has been about selecting/designing algorithms i.e., working out the steps Expressing them in Python 6

7 Inherent part of algorithm Places to store data to be available for algorithm at just the right time! Variable: Python: a symbolic name used to refer to a value or computational object (list, dictionary, object, ) Other languages (Java, C, C++, etc.): symbolic name for a place where values are stored! Variables in Python created two ways: 1. Assignment statement associates a name with a value or object Or changes a previous association 2. Arguments in functions calls assigned to parameters of called function! In Python, any kind of value or object can be assigned to any variable Regardless of type of previous assignment Not so in other languages: type must be preserved 7

8 Questions? 8

9 Another key element of programming Function: A computational action agent Takes zero or more parameters Returns zero or more results An encapsulation of a sub-program To solve a subset of problem repeatedly with different arguments (assigned to parameters) May do anything it wants internally so long as it only affects external variables in specified ways Very, very useful for breaking programming problem into smaller pieces Solve one part of problem then forget about it and move on to another part! 9

10 Functions (continued) (Almost) everything we do in Python is part of a function Function design is central part of algorithm design 10

11 Two kinds of numbers in Python Integers For counting things Floating point numbers a.k.a. floats For approximating fractions, decimals, scientific notation Very large Astronomical sizes! Very small Subatomic sizes! Everything in between 11

12 Scope rules and Importing Variables in functions stay in functions! Not visible outside Enables mental isolation I.e., can concentrate on function or subprogram without worrying about reuse of identifiers Esp. inadvertent reuse! Same as in most other programming languages 12

13 Import import pkg Add pkg to current scope All methods and public instance variables accessible with dot notation from pkg name from P import Q Adds Q to current scope (but not P) Q s methods and instance variables accessible via dot notation from P import * Adds everything from P s scope to current scope! Bad idea! People do it anyway! 13

14 Questions or comments? 14

15 Data structures Second part of course has been about designing data representations suitable for solving our problems Bigger deal than algorithm design Data drives the algorithm NOT algorithm drives the data! Note that CS-1101/02 and CS-2102 (for CS majors and related fields) is primarily about design of data Algorithms and programming languages are (almost) corollaries! 15

16 Data structures in CS-1004 Lists Strings Dictionaries Objects 16

17 Lists Linear (ordered) set of things Values Objects Other lists Etc. Accessible by position Easy to append something Easy to find something by position Easy (in Python) to find out if something is in the list Easy to iterate thru But need to know where something will be in list 17

18 Lists (continued) Equivalent to arrays in languages like C, C++, and Java Basis for matrices, many mathematical models Used lists in Homework #2 to plot sin() function Homework #4 to store words from input files Homework #5 to plot probabilities of winning and losing at craps Homework #6??? 18

19 Lists and arrays (continued) Widely used in many programming languages More flexible in Python than in other languages Heterogeneous i.e., different types for different element Built-in methods or operators for sorting, slicing, insertion, deletion, searching, etc. Not as efficient as in C and C++ Much safer than in C and C++ Much, much more efficient in other languages Uses fastest machine instructions for accessing Minimal data overhead All elements must be same type! Same syntax for accessing L[index], M[index1][index3] Acts just like a variable in those languages No checking for illegal indexes in C, C++! 19

20 Strings Immutable Any character set, any human language As of Python 3 Java also uses Unicode C & C++ more primitive Methods similar to lists, other sequences Adding, replicating, searching Indexing, slicing, substrings Many methods return new string I.e., no updating in place! Characters are strings of length 1 Unlike C, C++, and Java 20

21 Questions? Comments? 21

22 Dictionaries Based on Hash Table technology Dates back to early days of computing Built into Python as fundamental data type Unlike all other languages! Easy to use, easy to access Homework #4 Much simpler, faster CSV files Saves having to memorize list positions for specific data Simpler program, easier to understand Adaptable to other data sets with different column orders 22

23 Objects Built into Python, Java, C++ No such thing in C More programmer friendly in Python! Encapsulate information and action Know stuff Do stuff Essential for advanced applications See Chapter 12 in textbook Makes advanced stuff accessible to ordinary people and beginning programmers Homework #3 Homework #6 23

24 Objects (continued) Simple graphics package All in Python Easy to use 24

25 Object notation Thing.method() Widely used in many programming languages Simplifies many applications Central to programming by elementary-school age children Subject of much research 25

26 Questions or comments? 26

27 Third major component of course Doing things! Writing programs Debugging programs Akin to learning to speak a foreign language 27

28 Third major component (continued) Frustrations of Silly mistakes Undetected typos Poor self-organization Tired thinking Misunderstood conceptual material Overlooked details in documentation. or instructions! Incompatibilities between computer types 28

29 Frustrations (continued) Actually getting programs to work! Even if presented with methodical, small steps All of those things that were obvious at the time But aren t so obvious now! Perhaps not even true Practice! Lots and lots of practice! 29

30 Homework #1 & 2 Homework #1 Getting started Simple Expressions (Not unlike Excel!) Simple functions Homework #2 Definite loops Computing a Taylor series Plotting on pyplot/matplotlib Not something you would get to do in other programming languages! This early in course! 30

31 Homework #3 Graphics exercises Way outside of comfort zone! Non-traditional approach of textbook Something you can do and be excited about Especially after only three weeks! 31

32 Homework #4 Word problems String manipulation Traditional problem in non-traditional setting Trying to get heads around splitting, stripping, etc. Simple concepts A lot of work behind the scenes so that you don t have to do it! 32

33 Homework #5 Monte Carlo simulation Small taste of real-life type of problem Likely to encounter in your own fields Random number generation Rolling the dice! Plotting More plotting! 33

34 Homework #6 CSV files Common data format Dictionaries If you choose to use them! Creating visual representation of the outcome of computation Exploit human eye capability of understanding data! Graphics and images A cool problem for finishing up a first course in computer programming 34

35 Comments? Thoughts? Reactions? 35

36 Interested in more CS courses? CS-2004 object oriented design for nonmajors Currently in Java Also known as CS-220X CS-2301 System programming for non-majors Programming in C Prerequisite for ECE 2040, 3849 CS minor See next chart 36

37 CS 1102 CS 1101 CS 1004 OR CS 3043 Social Impl. of Info. Processing CS 2102 Object Oriented Design OR CS 220X Non-Major Building SW Apps with OO CS 2022/ MA 2201 Discrete Mathematics CS 2223 Algorithms CS 2303 Sys. Prog. Concepts CS 2301 Sys. Prog. For Non-majors OR CS 3133 Foundations of Comp. Science CS 3431 Database Systems I CS 3041 Human Comp. Interaction CS 3733 Software Engineering CS 2011 Mach. Org. & Assem. Lang. Artificial Intelligence Other courses for CS Majors Courses for CS Minor CS 4233 CS 3013 Operating Systems CS 4515 CS 4513 CS 4516 CS 3516 Computer Networks CS-1004, A-Term 2014 Introduction 37

38 Thank you! 38