Working with Python: functions and modules

Presenters

This course will cover concepts and strategies for working more effectively with Python with the aim of:

Writing reusable code, using functions and libraries
Acquiring a working knowledge of key concepts which are prerequisites for advanced programming in Python e.g. writing modules and classes
During this course you will learn about:
- Writing functions
- Best practices to write reusable code
- Structuring code in a custom module
- Using Python libraries
- Drawing plots with Matplotlib and working with biological data using BioPython

There are two course webpages with links to the materials, example solutions to the exercises etc.:
- http://pycam.github.io
- https://github.com/pycam
We’d like you to follow along with the example code as we go through the material, and attempt the exercises to practice what you’ve learned
Questions are welcome at any point!
If you have specific projects/problems that you think could be attempted using Python, we are happy to (try to) help during the exercises. Just let us know!

Python is a dynamic, interpreted general purpose programming language initially created by Guido van Rossum in 1991
It is a powerful language that supports several popular programming paradigms:
- procedural
- object-oriented
- functional
Python is widely used in bioinformatics and scientific computing, as well as many other academic areas and in industry too
Python is available on all popular operating systems
- Mac
- Windows
- Linux

Python is considered to come with "batteries included" and the standard library (some of which we will see in this course) provides built-in support for lots of common tasks:
- numerical & mathematical functions
- interacting with files and the operating system
- ...
There is also a wide range of external libraries for areas not covered in the standard library, such as Matplotlib the Python plotting library and the BioPython Library which provides tools for bioinformatics - we look at this later

Python is an interpreted language, this means that your computer does not run Python code natively, but instead we run our code using the Python interpreter
There are three ways in which you can run Python code:
- Directly typing commands into the interpreter: Good for experimenting with the language, and for some interactive work
- Using a Jupyter notebook: Great for experimenting with the language, and for sharing and learning
- Typing code into a file and then telling the interpreter to run the code from this file: Good for larger programs, and when you want to run the same code repeatedly

On a Mac or Linux machine you should start a terminal and then just type the command python3.

Running Python code is as simple as opening a Terminal window and typing the command python3 followed by the name of the script.

python3 scripts/hello.py

The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text.
Jupyter provides a rich architecture for interactive data science and scientific computing with:
- Over 40 programming languages such as Python, R, Julia and Scala.
- A browser-based notebook with support for code, rich text, math expressions, plots and other rich media.
- Support for interactive data visualization.
- Easy to use tools for parallel computing.

We recommend using a virtual environment after having installed Python 3.

python3 -m venv venv
source venv/bin/activate # activate your virtual environment
pip install jupyter