This lesson is an introduction to programming Python, using Biopython applications as motivation. Please note that this lesson uses Python 3 rather than Python 2.
Prerequisites
Learners need to understand the concepts of files and directories (including the working directory) and how to start a Python interpreter before starting this lesson.
Learners must install Python before class starts: please see the setup instructions for details.
| 10:00 | Running and Quitting (Kai) | How can I run Python programs? |
| 10:15 | Variables and Assignment (Kai) | How can I store data in programs? |
| 10:25 | Data Types and Type Conversion (Kai) |
What kinds of data do programs store?
How can I convert one type to another? |
| 10:35 | Built-in Functions and Help (Kai) |
How can I use built-in functions?
How can I find out what they do? |
| 10:55 | Error Messages (Kai) |
What kind of errors can occur in programs?
How can I identify errors when they occur? |
| 11:10 | Libraries (Kai) |
How can I use software that other people have written?
How can I find out what that software does? |
| 11:20 | Morning Coffee | Break |
| 11:35 | Lists and Indexing (Kai) | How can I store multiple values? |
| 11:55 | For Loops (Kai) | How can I make a program do many things? |
| 12:15 | Conditionals (Kai) | How can programs do different things for different data? |
| 12:30 | Sets (Kai) | What is a set, and how do I use it? |
| 12:40 | Lunch | Break |
| 13:10 | Biopython (Kai) | How do I handle sequence files? |
| 13:30 | Writing Functions (Niko) | How can I create my own functions? |
| 13:55 | Programming Style (Niko) |
How can I make my programs more readable?
How do most programmers format their code? |
| 14:20 | Debugging (Niko) | How can I debug my program? |
| 14:45 | Defensive Programming (Niko) |
What sorts of things frequently go wrong in programs?
How can I make my programs more robust? |
| 15:00 | Afternoon Coffee | Break |
| 15:15 | Reading Tabular Data into Data Frames (Niko) | How can I read tabular data? |
| 15:30 | Pandas Data Frames (Niko) | How can I do statistical analysis of tabular data? |
| 15:50 | Next Steps (Niko) | What else is out there and where do I find it? |
| 16:05 | Wrap-Up (Niko / Kai) | What have we learned? |
| 16:20 | Finish |