Autumn Term, 2011
(10 Sessions) Tuesdays 6 - 9 pm, October 11 through December 13,
downtown Seattle.
UW Certificate Program in Python Programming, also includes Internet Programmming in Python (Winter 2012) and System Development with Python (Spring 2012).
This course will be similar to last year: Autumn 2010, Winter 2011, Spring 2011.The schedule is updated every week, consult frequently (refresh your browser).
Dec 12: Winter quarter begins Tuesday night, January 3
Dec 11: Winter quarter course page
posted with
week 1 reading assignment.
Dec 6: Seattle Python Interest Group (SeaPIG)
meeting next Thurs Dec 15: lightning talks
Dec 4: Fix typos in assignment for Dec 6: def not define
Dec 1: Add recommended readings on Python ecosystem to Week 9 in schedule.
Nov 16: I forgot to link set.py to Nov 8 in schedule last week.
Now fixed.
Nov 9: Seattle Python Interest Group (SeaPIG)
meets Thursday, Nov 10
Oct 31: Some comments on our textbook
Oct 28: And, please read my comments on the homework assignment for
week 3.
Oct 26: Please read my comments on the homework assignment for
week 2.
Oct 19: Summaries of lightning talks
Oct 14: Results of the
entry questionnaire
Oct 12: Add schedule for lightning talks (also below)
Oct 10: Revise schedule, assign more reading for week 2, add exercise
Aug 9: First class Oct 11 6:00 pm, downtown Seattle
Course objectives: Introduce the Python language, its most
important libraries, and its recommended programming styles and
idioms. Teach how to solve typical programming problems in Pythonic
style. Survey some exemplary Python applications and systems. Teach
career skills and work habits including testing and version control.
Students will begin accumulating a portfolio of completed assignments,
working toward a substantial original project in the Spring.
Prerequisites: No previous Python experience is required.
This course is not intended for absolute beginners in programming,
but does include a self-contained review of elementary features.
Students must be able to use a command line, edit a text file, and
download and install software. Students should have some prior
exposure to programming in any language, sufficient to write very
simple programs or scripts that use variables, conditionals (if ...),
and iteration (loops).
Textbooks: The textbook comes in two versions: a
printed book named
Python for Software Design, and a free online version named
Think Python.
Despite the different titles, the two versions have the same contents.
Instructor:
Jonathan Jacky is a research scientist at the University of
Washington. He has experience as a software developer for research
laboratories, hospitals, and systems software companies. He has taught
at universities and in industry, and is the author of two textbooks on
software development and testing. His Python experience includes the
GNU Radio signal processing system, the FLiP proof checker, and the
PyModel testing framework.
Technology Requirements: Students must have access to a
computer for their assignments and projects, where they can install
software (the course does not provide a computer laboratory). Older
computers and computers with modest resources (including netbooks)
will work. Any popular operating system will work, including Windows,
Mac OS X, and Linux. It is recommended that students have a portable
computer to bring to class. Internet access will be provided at
classes.
Assessment criteria: The course is graded Pass/Fail, based on
satisfactory completion of required programming assignments and
classroom presentations. Attendance is required; more than two
unexcused absences will result in a Fail.
Disability accommodation: The University of Washington is
committed to providing access and reasonable accommodation in its
services, programs, activities, education and employment for
individuals with disabilities. For information or to request
disability accommodation contact: Disability Services Office:
206.543.6450/V, 206.543.6452/TTY, 206.685.7264 (FAX), or e-mail at
dso@u.washington.edu.
The textbook comes in two versions, a printed book:
Python for Software Design: How to Think Like a Computer
Scientist by Allen B. Downey. Cambridge University Press, 2009.
and a free online version:
Think Python: How to Think Like a Computer Scientist
Despite the different titles, the two versions have the same contents,
including the same chapter, section, and exercise numbers. You may
use the version you prefer.
This text is an excellent introduction to Python language fundamentals
and semantics. There are many features and topics it does not discuss.
We will discuss them in class and assign supplementary readings. Here are some
comments on the book.
Quick Python Script Explanation for Programmers (one page)
Python 2.6 Quick Reference
(awesomely dense and complete)
The Python Tutorial
(from python.org)
Reference from python.org
Examples and Resources
(other courses and books, sample code, notable Python libraries and scriptable applications)
Students will need Python installed on their computers.
Python comes already installed on Macs and most Linux distributions.
There are two different "current" versions of Python, 2.x and 3.x. We
will be using 2.x, where x means any sufficiently recent version. 2.7
is most recent, but 2.6 will also work.
The current Python 2.x version is available
here. I use this
source for Windows. For the Mac, I
use macports, which manages multiple
Python versions nicely. For Linux, I use the distro's package manager
(Synaptic on Ubuntu, for example).
Tuesdays 6 - 9 pm, October 11 through December 13 (10 sessions).
Additional topics and readings will be added, consult
frequently (refresh your browser).
Read the assignment and do the assigned exercises in the
week before class. Turn in the exercises (hardcopy) in class.
Here PySD/TPy refers to the textbook, either Python for
Software Design (printed) or Think Python (online).
Both versions use the same chapter numbers (but in the TPy
web pages, Chapter 2 is in file book003.html etc.)
Textbook
Summaries
Learn Python in 10 minutes
NanoPy
Reference
Python 2.x documentation
(official documentation from python.org)
Supplementary texts
IDLE Interactive Development Environment
Quick tour with screenshots
Other resources
Software
Schedule and Assignments
| Week | Date | Topics | Assignments due (optional readings in parentheses) |
| 1 | Oct 11 |
Introductions.
Some Python applications and systems.
Installing Python.
Using the command interpreter and development environment.
Finding and using the documentation. Getting help. Lecture notes: intro.txt, python.txt, lightning.txt, values.txt Code and data: schedule.py, students.txt, schedule.txt |
Summaries (here), (here). |
| 2 | Oct 18 |
Variables, values, expressions, and assignment.
Functions. Definition and use. Arguments.
Block structure. Scope.
Modules and import. Boolean expressions. Conditionals and control flow. Iteration and recursion. Lecture notes: review_2.txt, assign.txt, boolean.txt, iteration.txt, functions.txt Code: repetition.py, avg.py, scope.py Exercise: my solution and comments Lightning talks: Greg C, Deborah C, Shruti M, Ted S |
PySD/TPy, Chs.
(1),
2,
3,
(4) PySD/TPy 5, 6, 7 Exercise due Oct 18 |
| 3 | Oct 25 |
Data types. Sequences. Strings. Files. Exceptions. Text
Processing. Regular expressions. Unicode. Lecture notes: functions.txt again, strings.txt, files.txt, biopython.txt Code and data: functions.py, parameters.py, strings_files.py, command_line.py, concordance.py, bio_demo.py, ceru_human.sp (same as ceru_human.txt) Exercise: my solution and comments Lightning talks: Noah G, Chris K, Mark P, Conor R |
PySD/TPy, Chs.
8,
9,
14 ( String methods) (RegEx How-To) (Unicode How-To, more) Exercise due Oct 25 |
| 4 | Nov 1 |
Data types. Sequences again. Tuples, Lists, Dictionaries. Mutability. Aliasing.
Argument passing. List comprehensions. Lecture notes: week_4.txt, sequence.txt Code: traffic.py, phones.py Exercise: my solution and comments Lightning talks: Jenny L, Andy N, Shashi P, Kamal S |
PySD/TPy, Chs.
10,
11,
12,
13 Exercise due Nov 1 |
| 5 | Nov 8 |
Data types, comprehensions again. Sets and Bags. Arrays. Functional programming and lambda.
Data type case studies and review. Lecture notes: week_5.txt, collections.txt, functional.txt Code: phones.py, comprehensions.py, roman.py, corrector.py, set.py Sample data: big.txt, words Exercise: my solutions sorted_string.py and sorted_list.py, and comments Lightning talks: Diana M, John M, Tony M, Michele W | Python Tutorial, sections
3.1.4,
5 Spelling corrector Exercise due Nov 8 |
| 6 | Nov 15 |
Classes, instances, and methods. Object-oriented programming.
Inheritance and duck typing. Lecture notes: classes.txt Code: patient.py, vehicle.py, simulator.py, pedestrian.py Exercise: my solution unlisted_words.py Lightning talks: Bob A, Scott B, Anton F, Daniel M |
PySD/TPy, Chs.
15,
16,
17,
18 Exercise due Nov 15 |
| 7 | Nov 22 |
Extending Python. Special attributes and methods. Iterators and
Generators. Protocols. Lecture notes: week_7.txt, vector.txt, generator.txt, protocol.txt Code: vector.py, generator.py Lab Exercise: objects_lab.py Exercise: my solution atom.py Recommended readings (read as much as your time and interest allows): Special Methods, learn about __str__, __add__ and their many many cousins. Generator Tricks for Systems Programmers Lightning talks: Stefan C, Martin C, Lotus L |
Python Tutorial, Section
9
(except 9.9 - 9.11) Recommended: See panel at left Exercise due Nov 22 |
| 8 | Nov 29 |
Classes and inheritance again. Decorators. The debugger. Lecture notes: week_8.txt, decorator.txt, debugger.txt Code: decorator.py, repetition.py Lab Exercise: inheritance_lab.py Exercise: my solution bag.py Recommended readings (read as much as your time and interest allows): Decorators, gives some idea of what's possible pdb - The Python Debugger Python Types and Objects, Attributes and Methods, if you want to know what's really going on Lightning talks: Gregg L, Alex W, Josh W |
Python Tutorial, Sections
9.9 - 9.11 Recommended: See panel at left Exercise due Nov 29 |
| 9 | Dec 6 |
Python ecosystem. Packages. PyPI. Installation.
Python with other languages. Lecture notes: week_9.txt, packages.txt, install.txt, other_languages.txt Code: setup.py, integrate.py, integrate.pyx, setup_integrate.py, integrate.c Lab Exercise: isa_hasa_lab.py Exercise: my solution decorator_generator.py Recommended readings (read as much as your time and interest allows): Modules and Packages CheeseShop Tutorial (PyPI) Installation and distutils C-API, SWIG, Cython Lightning talks: Dimitry V |
See panel at left Exercise due Dec 6 |
| 10 | Dec 13 |
Databases and Python Recommended readings (read as much as your time and interest allows): Introduction to relational databases and SQL (source of the mailing list example), more here, here, and here. SQLite: quick start, shell commands, language reference Python's built-in sqlite3 library Lecture notes: week_10.txt, databases.txt Code: mailing_list, mailing_list_data, mailing_list_queries, mailing_list_queries.py Lab Exercise: database_lab.txt, solution: database_lab.py Python Glossary, a summary of where we've been, with hints about topics we didn't cover. Lightning talks: Ben B, Maryam A, Brittany N |
See panel at left Exercise due Dec 13 |
Jonathan Jacky, jon at u dot washington dot edu
