Summary and Schedule
In this section we will focus on setting up the computer to get started with Python.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Getting started |
Programming why bother? Why Python? How to learn it? |
| Duration: 00h 12m | 2. Variables, Types, and Operations |
What are input and output (I/O) operations? What do variables do? Why are types and scopes of variables important? What types of operations are used? |
| Duration: 00h 24m | 3. Conditional Statements |
What are conditional statements? How conditional statements are used to make decisions? Why indentation is so important in Python? Is there any hierarchical importance of conditional statements? |
| Duration: 00h 36m | 4. Introduction to Arrays |
What are the different types of arrays? How is data stored and retrieved from an array? What are nested arrays? What are tuples? |
| Duration: 00h 48m | 5. Iterations |
What do we mean by iterations and loops? How are for-loops implemented?Can conditional statements be used in iterations? What are while-loops, and how these
used?
|
| Duration: 01h 48m | 6. Dictionaries |
What is a dictionary, in Python? What are the ways to interact with a dictionary? Can a dictionary be nested? |
| Duration: 01h 58m | 7. Functions |
What are functions? How are functions created? What are optional arguments? What makes functions so powerful? |
| Duration: 02h 10m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Python 3
It is sometimes claimed that biologist should use Python 2, because most biology related libraries in Python are written for that version. This is wrong. The reason why Python 2 is still out there is that following the release of Python 3.0 in December 2008, the CPython interpreter sustained several problems, and was not backward compatible. This meant that, any code written in Python 2, could not be run using Python 3 without modifications. By now, Python 2 is obsolete. Do not use it.
Why Anaconda?
For the purpose of this course, we recommend the Anaconda distribution of Python released by the Python Software Foundation, and maintained by the Anaconda Cloud.
Anaconda automatically installs many packages needed for scientific purposes (over 250 automatically installed). It is easy to install, and it takes care of dependencies between packages. This is particularly important because some of Python’s scientific libraries require Fortran– and C–based libraries, which may be challenging to install for beginners.
Installation
To install the Anaconda distribution of Python, please visit the installation instructions as outlined in the Anaconda documentations, and follow the instructions for your operating system. Ensure that you use the Python 3.x graphical installer for Windows and MacOSX (there is no graphical installer for Linux). Once downloaded, you can proceed to install the distribution as you would any other application on your computer.
Anaconda Navigator is a desktop graphical user interface (GUI) included in Anaconda distribution that allows users to launch applications and manage conda packages, environments and channels without using command-line commands. Navigator can search for packages on Anaconda Cloud or in a local Anaconda Repository, install them in an environment, run the packages and update them. It is available for Windows, macOS and Linux.
The following applications are available by default in Navigator:
JupyterLab
Jupyter Notebook
QtConsole
Spyder
Glue
Orange
RStudio
Visual Studio Code
We recommend using JupyterLab for writing and practicing your codes.