Introduction to Python

Learning Objectives:¶

• List key characteristics and benefits of using the Python language for scientific workflows.

• Work with Python in the command prompt

• Know the concepts of variable, data type, and functions

What is Python¶

Python is an easy-to-learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms.

Key Characteristics:

• Interpreted Language: Python is an interpreted programming language. At the most basic level, an interpreted language means that you can run Python code and associated commands without needing additional steps such as compiling the code first before running it. This makes getting started and working with Python quick and easy.

• High Level Programming Language: Python is also a high-level programming language, which provides the ability to work with code that is human readable, as opposed to machine language (such as 0s and 1s). As the Python language abstracts away many of those technical details, you are free to write code and process data using Python without worrying about what type of computer you are using. So you can get more quickly to your science and be able to share your code with others who may be using a different operating system.

• Free and Open Source: Python is a free and open source programming language. This means that the source code for the entire language is freely available, and that anyone can contribute new functionality or documentation for the benefit of the Python community.

Why Use Python For Earth Data Science¶

Each programming language has its benefits and its drawbacks. Python is being used in our earth analytics courses and in this textbook for many reasons including:

1. Python is one of the most commonly used languages in the earth and environmental sciences: Many different sources have identified Python as being one of the most popularly used languages, particularly in the sciences. An analysis conducted by Stack Overflow found that Python is one of the most active programming language threads on their widely used website and the overall fastest-growing major programming language. Earth Lab’s own market research of hiring managers in industry and public agencies also identified Python as a highly desired programming background for new employees.

2. Python is free and open source: This means that anyone can use it without worrying about licenses. This also makes it easy to migrate code over to cloud and high performance computing (HPC) environments, given that there are no license restrictions.

3. Python has an active open source community for science: There is an active open source community who are building Python tools to support scientific applications, such as the widely used scientific packages numpy and pandas.

4. Python is the core language for many spatial data tools: Example tools that use Python as their core include ESRI ArcGIS, QGIS and others. This makes the language versatile if you wish to create macros (i.e. widgets) in a Desktop tool like QGIS.

Where to run Python¶

To run python, open your terminal (or GitBash) and run:

$ python

(Note: your command might be python3m depending on your system.)

Using Python for the first time¶

Variables¶

Any Python interpreter can be used as a calculator:

3 + 5 * 4

23

This is great but not very interesting. To do anything useful with data, we need to assign its value to a variable. In Python, we can assign a value to a variable, using the equals sign =. For example, we can track the weight of a patient who weighs 60 kilograms by assigning the value 60 to a variable weight_kg:

temperature = 60

From now on, whenever we use temperature, Python will substitute the value we assigned to it. In layperson’s terms, a variable is a name for a value.

In Python, variable names:

• can include letters, digits, and underscores

• cannot start with a digit

• are case sensitive.

This means that, for example:

• temperature0 is a valid variable name, whereas 0temperature is not

• temperature and Temperature are different variables

The following identifiers are used as reserved words, or keywords of the language, and cannot be used as ordinary identifiers. They must be spelled exactly as written here:

Expressive Programming: Easy to Understand Variable Names Make Your Code Easier to Read¶

Just like you want to use expressive naming conventions (names that represent what is stored within the directory) for directories on your computer, you also want to use short, clear names for your variables to make your code easier to read. To follow best practices for variable names, avoid the following:

• spaces in your variable names

• complicated wording

• long variable names

• words that do not represent what the variable contains (example: my_variable vs precip_data)

When naming a variable, you want to keep the name short but specific enough that someone reading your code can understand what it contains. It is good practice to use underscores (e.g. denver_precip_in) to create multi-word variable names that provide specifics regarding the variable’s content. The underscore makes the variable name easier to read and follows Python PEP 8 best practices for code readability.

Types of data¶

Python knows various types of data. Three common ones are:

• integer numbers

• floating point numbers, and

• strings.

In the example below, variable temperature has an integer value of 60, whereas precip has a float value of 3.3.

temperature = 60

precip = 3.3

To create a string, we add single or double quotes around some text.

city = 'Golden'

A string can have many words, including punctuation.

city_description = 
"Golden, CO is the home of Colorado School of Mines."

Built-in Python functions¶

To carry out common tasks with data and variables in Python, the language provides us with several built-in functions. The function type tells what type a certain variable is.

type(temperature)
<class 'int'>

When we want to make use of a function, referred to as calling the function, we follow its name by parentheses. The parentheses are important: if you leave them off, the function doesn’t actually run! Sometimes you will include values or variables inside the parentheses for the function to use. In the case of print, we use the parentheses to tell the function what value we want to display. We will learn more about how functions work and how to create our own later in the course.

type(precip)
<class 'float'>

type(city)
<class 'str'>

To display information on the screen, we use the print function:

print(temperature)

print(city)

We can display multiple things at once using only one print call:

print("The temperature in", city, "is", temperature)

We have been running code in the Python prompt, but what if we need to run this again? If you exit Python (ctrl+d) and launch it again, what happens to your code?

temperature
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'temperature' is not defined

Python doesn’t “remember” the code that we typed in the command prompt. So how ca we save code such that we can run it later?

Let’s open a terminal and navigate to your coursework directory

$ cd ~/work/classes/GPGN268/villasboas-coursework/

Now, let’s go to the short-assignments directory.

$ cd short-assignments

We will create a file to save our code

$ vim python-intro.py

# Learning how to write a Python script - GPGN268
# Author: Bia Villas Boas
# Date: Jan 31, 2023

# Temperature in degrees Fahrenheit
temperature = 55
# Location of the measurement
city = "Golden"
print("It is", temperature, "F", "in", city)

and you can run your script with

$ python python-intro.py

Commit your changes¶

Now let’s track the Python script that you created with Git, commit, and push that to GitHub.

$ git add python-inyto.py
$ git commit -m "Add my first python script"
$ git push

Key Points¶

• Python is an interpreted, high-level, open-source language widely used in Earth sciences.

• Variables are names assigned to values using =; use short, specific names with underscores (e.g., denver_precip_in).

• Common data types: integers, floating-point numbers, and strings.

• Built-in functions like type() and print() help you work with variables.

• Python scripts saved in .py files can be run from the terminal using python filename.py.

• Use Git to track and version control your Python scripts.