Lecture Materials
Information will be updated here after each lecture.
| Week | Lecture Notes | Lecture Files | Readings / References |
|---|---|---|---|
| 1 (May 14) | Notes Notes (Style Guidelines) |
balanced.py queue.py stack.py teststack.py timestack.py naivepq.py |
1.3, 1.4 (optional), 2.1 - 2.4 (textbook)
First 2 pages of Computer Science and its Relation to Mathematics (optional - accessible from on campus) PEP8: Style Guide for Python Code PEP257: Docstring Conventions |
| 2 (May 21) | Notes |
addressbook.py contact.py catch1.py catch2.py exception1.py exception2.py reraise.py userexception.py userexception2.py vars1.py |
See URLs referenced in the Notes. |
| 3 (May 28) | Notes |
classbind.py enclosing.py namespaces.py redefine.py fact.py fib.py hanoi.py sum.py |
Dynamic Typing/Namespaces/Scopes "Learning Python" by Mark Lutz 3rd edition Chapter 6, pages 112-121; Chapter 16, pages 310-316 OR "Learning Python" by Mark Lutz 2nd edition Chapter 4.6, 13.1, 13.2, 13.3 (As a UofT student you have FREE electronic access to this edition of the book through the UofT library website. All you need is your UTOR id/password). Python Scopes and Name Spaces Naming and Binding (This is from the python language reference and it's rather technical. It contains more than you really need to know.) Namespaces Tutorial Recursion Chapter 3 of your textbook. |
| 4 (June 4) | see readings/references for material covered |
escape.py water.py |
We did some more recursion examples, and also talked about backtracking. This included reviewing the Towers of Hanoi problem from last week, going over the solution for the count_reachable problem from the week 4 lab, and developing recursive functions for finding an escape path out of a maze, and a recursive function for the "Water in Jugs" problem. |
| 5 (June 11) | Notes |
listoflist.py nodesrefs.py traversal.py traversal2.py |
5.1 - 5.5 (textbook) start of 5.6 (Binary search trees) |
| 6 (June 18) | Notes |
bst.py |
5.6 (textbook) |
| 7 (June 25) | Midterm Solutions |
The midterm was written during lecture. Afterwards, we reviewed solutions. | |
| 8 (July 2) | Notes |
bst.py generator.py iteration.py iteration2.py |
Iterators and Generators Python Tutorial: Iterators and Generators Algorithm Analysis 4.1 - 4.2 (textbook) The following are slides on Big-Oh and Algorithm Analysis from a previous offering of the course. The slides include some examples in Java, but the syntax isn't drastically different from Python. You may find these slide useful in addition to the material covered in your text and your lecture notes: 08bigoh.pdf |
| 9 (July 9) | Notes |
sorts.py |
4.4 4.4.1 (bubble sort) 4.4.2 (selection sort) 4.4.3 (insertion sort) 4.4.5 (merge sort) |
| 10 (July 16) | see readings/references for material covered |
mergesort_it.py linked_list.py node.py sorted_list.py test_lists.py |
We discussed the time complexity of mergesort, and
looked at the implementation of iterative mergesort. We also talked about linked lists (see chapter 7.1-7.2 of your text). |
| 11 (July 23) | see readings/references for material covered | pqueue.py |
Heaps - Section 5.7 of textbook. We started discussing how to implement a priority queue using a min heap. |
| 12 (July 30) | see readings/references for material covered | heapsort.py qsort.py |
We finished discussing how to implement a priority
queue using a min heap. We discussed how to build a max heap in-place on a list, and how to use this in conjunction with the percDown helper method to do an in-place heap sort. (See Section 5.7 of textbook. Note, however, that the algorithm presented in class differs slightly from your text.) We also briefly talked about Quick Sort. (See section 4.4.6 of the text.) |
| 13 (August 6) | see readings/references for material covered |
We went through a number of practice questions, including examples on: Object Oriented Analysis, Trees, Algorithm Analysis, Sorting, and Linked Lists. "Reference" page (page 17) of exam is here: Reference Page |