Readings

Below, you'll find a set of online resources designed to accompany the 6.00 lectures. We've found that the readings are generally more effective when done after the lecture, though you are of course welcome to read them at any time. "How to Think Like a Computer Scientist" is also available in one big PDF.

(links will be added here incrementally over the term)

Reference (Python 2.5.4)

Python 2.5.4 Documentation
Python 2.5.4 Tutorial
Python 2.5.4 Reserved Words
Python 2.5 Quick Reference Card (Original Source)
Python Programming Wikibook

Lectures 1-3

Intro: Chapter 1 of How to Think Like a Computer Scientist
Variables and statements: Chapter 2 of How to Think Like a Computer Scientist
Strings: Variables and strings section of Programming Python Wikibook (also, the strings section)
Python variables are names: Other languages have "variables," from Code Like A Pythonista: Idiomatic Python
For PS0: Input/output section of Programming Python Wikibook
Conditionals: Chapter 4 of How to Think Like a Computer Scientist (through section 4.8), and the conditional statements section of Programming Python Wikibook
Iteration: Loops section of Programming Python Wikibook
Tuples: Tuples section from Dive Into Python and also the tuples and sequences section of the Python Tutorial
More on traversing and slicing strings: Chapter 7 of How to Think Like a Computer Scientist

Lecture 4

Lists: Chapter 8 of How to Think Like a Computer Scientist
Dictionaries: Chapter 10 of How to Think Like a Computer Scientist
As a reference: the Python tutorial section on lists and dictionaries (feel free to skip 5.1.3 and 5.1.4)

Lecture 5-7

Functions, type conversion, and stack diagrams: Chapter 3 of How to Think Like a Computer Scientist
More about functions: Chapter 5 of How to Think Like a Computer Scientist (through section 5.4)
Documenting functions: Documenting Functions from Dive Into Python
Recursion: Chapter 4 of How to Think Like a Computer Scientist (from section 4.9 on), as well as Chapter 5 of How to Think Like a Computer Scientist (from section 5.5 on)

Lecture 8

Numbers: Floating point arithmetic: issues and limitations from the Python tutorial
Successive approximation: Newton's method, from Wikipedia

Lecture 9

Asymptotic notation: Section 3 from the Spring 2005 6.042 lecture notes on OCW
Order of growth: Sections 2.1 and 2.2 from Computational Modeling and Complexity Science
Binary search: Wikipedia article on binary search (focus on the recursive implementation in Section 4)

Lecture 10

Selection sort: Wikipedia article on selection sort

Lecture 11

Merge sort: Wikipedia on Merge Sort, Sections 1 and 2
Exceptions: Section 11.5 in How to Think Like a Computer Scientist (you might also be interested in the other parts of Chapter 11 about reading and writing to files)

Lectures 12-13

Lots of reading on classes:

Chapter 12 of How to Think Like a Computer Scientist
Chapter 13 of How to Think Like a Computer Scientist
Chapter 14 of How to Think Like a Computer Scientist
Chapter 15 of How to Think Like a Computer Scientist
Chapter 16 of How to Think Like a Computer Scientist

Lecture 14

Testing: A draft chapter from the 6.00 textbook.

Lectures 15-16

Optimization: A draft chapter from the 6.00 textbook.