Welcome to the Environmental Scientist’s Introduction to Python Course

This course is is an open source training course to give environmental scientists the foundation they need to begin learning and using the scientific tools that have been developed for python. The course focuses on simplifying python language into two buckets: the must haves and the nice to haves. The course is far from comprehensive, but we believe that it’s better for people to get cracking, and fill in the gaps as they develop their skills.

Expected course duration: 1-2 days

Must Have Python Basics

• What is Python
  • A brief history of python
  • Python versions
  • Interactive python, running scripts and IDEs
  • Philosophy of coding, The Zen of Python, and pep8
• Building Python on Your computer
  • Installing python and packages
  • Using python environments
  • Our recommended python installation for this course
  • Our recommended python installation for further work
  • Build your own python environment file for environmental scientists
  • Setting up and managing virtual environments with conda
• Basic Python Objects, Variables, and Operators
  • Variables
  • Numbers: Integers and Floats
  • Boolean
  • Strings
  • The print function
  • The Python None
• The List
  • What’s a list
  • length, indexing, and slicing
  • list specific operations and functions
  • The tuple
• Dictionaries
  • What’s in a dictionary
  • Important dictionary functions
• Strings, the good, the bad, and the ugly
  • String indexing
  • String operators & functions
  • Formatted output
• Conditional Statements
• Loops in Python
  • For loops in python
  • Useful builtins for for loops
  • While loops in Python
• Functions in Python
  • What is a function?
  • Understanding function documentation
  • Creating your own function in python
  • using *args and **kwargs
• Using Packages in python
  • External packages
  • Importing from your own python scripts
  • Adding a folder to the PYTHONPATH

Practice Exercises

We have developed a set of practice exercises to give you a taste of doing your own scripting. These exercises are facillitated through Github Classroom, so we recommend that you wait until you have finished the lesson on version control before you begin to explore the exercises. If you want to get on to the exercises, this link will create a new repository with a copy of the exercises for you to begin working.

exercise	prerequisites / associated lessons
exercise 1	What is Python Building Python on Your computer Basic Python Objects, Variables, and Operators The List Dictionaries
exercise 2	Conditional Statements Loops in Python
exercise 3	Functions in Python

Handy Builtin modules

There are a number of handy builtin modules in python. Rather than trying to cover them all in detail here, below is a a table of the most useful tools, what they do, and a link to some good learning materials:

Module with link	General description
time	Functions for manipulating clock time
math	Provides functions for specialized mathematical operations.
datetime	The datetime module includes functions and classes for doing date and time parsing, formatting, and arithmetic.
itertools	The itertools module includes a set of functions for working with sequence data sets.
glob	Use Unix shell rules to find filenames matching a pattern
os and os.path	portable access to operating system specific features and work on filenames and paths.
shutil	High-level file operations
pickle	Object serialization
timeit	Time the execution of small bits of Python code