Lecture 1 — Introduction

People

  • Professors: Sibel Adali, Wes Turner
  • Instructional Support Coordinator: Erica Eberwein
  • TAs and programming mentors: see course website

Learning Outcomes

  1. Demonstrate proficiency in the purpose and behavior of basic programming constructs.
  2. Design algorithms and programs to solve small-scale computational programs.
  3. Write, test and debug small-scale programs
  4. Demonstrate an understanding of the wide spread application of computational thinking to real-world problems.

Textbook

  • Practical Programming: An Introduction to Computer Science Using Python by Campbell, Gries, and Montojo
    • Available in e-book form
  • Very important to get the second edition.

Website and On-Line Resources

Other items from the syllabus

  • Prof. Adali’s office hours are:
    • Weds 3:00-6:00
  • Prof. Turner’s office hours are:
    • Tues/Thurs 2:00-3:30
  • Other office hours are posted on-line
  • Lab sections are held Tuesdays and Wednesdays. Full credit will be given for finishing the lab within your lab period. Checkpoints completed before your next lab will receive half credit.
  • Requirements and grading: lecture exercises, labs, homeworks, tests; letter grades
  • Appealing grades
  • Class attendance and participation; lecture notes
  • Homework late policy:
    • 3 LATE DAYS FOR THE WHOLE SEMESTER
    • 2 LATE DAYS ON ANY ONE ASSIGNMENT
  • Academic integrity
  • Other exceptions: report to me right now or as soon as you know
  • Notes on schedule:
    • Labs start next week with Lab 0! This is an installation lab. At the end of the lab you will have all the pieces you need to successfully complete the remaining labs and homeworks for the semester. If you have problems completing Lab 0, please get help. You have to get it done to proceed.
    • No labs during the weeks of October 9-13 (Columbus Day) and November 20-24 (Thanksgiving).
    • Test dates are October 2, October 30, and November 20 all at 6 pm.
    • Final exam will be held during finals week. No exceptions! So, don’t make departure plans until the final exam schedule is posted.

The Magic of Programming

  • Cold, harsh logic, and
  • Seemingly primitive syntax...
  • Leading to soaring creativity!

Types of Problems We Will Study

  • Tools used to help you win at Words with Friends
  • Image processing and manipulation
  • Web searching and crawling
  • Programs that work with data from Twitter and Flicker
  • Numerical examples, including games and physical simulations
  • Perhaps even a simple version of (part of) Pokemon Go.

Jumping In Quickly with Our First Program — Hello World

  • We create a text file called hello.py containing just the two lines of Python code:

    print('Hello, World!')
    print('This is Python')
    
  • This is done by launching the Wing IDE, which is specific to creating and running Python programs

    • IDE stands for ’Integrated Development Environment’

      • Two windows will appear — the top being the editor and the bottom being the Python interpreter
  • Load the hello.py program

  • Run it using the interpreter

  • We can also type Python code directly into the interpreter.

Something a Bit More Interesting

  • We are going to emphasize computational thinking throughout the semester, so let’s look at a fun little problem and get started.

  • This problem is posed in Think Python and taken from the NPR show Car Talk. If you know the answer, do NOT say it!

    “Find the one word in the English language that contains three consecutive double letters.”

  • We will talk through the steps needed to develop and test a Python program to solve this problem.

    • The file containing this program will be posted on the course website after class.
  • We do not intend that you will understand the details of the program at this time. Rather, this is just an exercise that illustrates the steps of solving a fun problem computationally.

  • On the other hand, it does introduce some elements that will be seeing repeatedly throughout the semester:

    • Files
    • Functions
    • Loops
    • Logic
    • Counting
    • Output
    • Libraries
  • In about six weeks, you will understand all parts of this program!

  • You can see the code in three_doubles from Code Developed in CSCI-1100 Fall 2017

Looking Back: What Steps Did We Follow?

  1. Developing an understanding of what the problem is really asking. This usually involves playing around with small examples.
  2. Developing and describing a recipe (an “algorithm”) for solving the problem
    • Most recipes will involve multiple parts — multiple functional steps
  3. Turning this recipe into a program in the formal language of Python, one of many different programming languages.
    • English is too imprecise for specification of programs.
  4. Running this program using the Python interpreter.

Programs, Compilers, Interpreters, Abstractions

  • Python is an interpreted language — run immediately and interactively by the Python interpreter, which is itself another (very complex) program
  • Programs in some other (non-interpreted) languages like C, C++ and Java must be compiled (by a “compiler” — another program) into a new program in machine assembly language and then executed.
  • In both cases, we write programs that require other programs to run.
    • And, we don’t just need just the compiler or interpreter — we need the file system, the operating system, and the command-line interpreter, each of them complicated, multi-part programs themselves.
  • We don’t really think about the details of these programs; we just think of what they do for us.
    • This is called an “abstraction”.
    • It allows us to think about a problem we are trying to solve without thinking about all the details of all the other systems we are depending on.
    • Thinking in terms of abstractions is fundamental to computer science.

Why Python?

  • Python has a very simple syntax
    • The roles of indentation and blank lines cause the most confusion.
  • Intepreted languages provide immediate, useful feedback
  • Python has a powerful set of tools — abstractions
  • Python is widely used in science, engineering and industry.
  • Python is good for rapid prototyping
    • Sometimes, after a Python program is written and working, the most time-consuming steps are rewritten in either C or C++ and then integrated with the Python code.

Two Types of Errors in Our Python Programs

  • A syntax error is a mistake in the form of the Python code that will not allow it to run.
  • A semantic error is a mistake in the “meaning” of the program, causing it to produce incorrect output, even if it runs.
  • We will demonstrate both types of errors by deliberately introducing errors in our triple double example program.

Python Versions

  • Python, like all programming languages, is continually under development.
  • We will be using the latest version, which is 3.6

Lab 0 — Tuesday and Wednesday!

By the end of Lab 0, you should have:

  1. Signed up at the course Piazza web site

  2. Gone to the course page

    and followed the instructions to install the Python environment on your computer.

    • There are installers for “native” versions of the environment for Windows, Mac OS X and Linux machines.
  3. Created a Dropbox account to store back-up copies “in the cloud” of homework and lab solutions and lab for the course.

    • Other cloud-based back-up copies are acceptable.