Introduction to Python

Last week was about thinking through a problem before touching code. This week we pick up the tool we will use for the rest of the course.

Why Python

Python is a general-purpose, interpreted, interactive, object-oriented, high-level language. It is dynamically typed and garbage-collected, created by Guido van Rossum between 1985 and 1990. It supports several styles of programming (procedural, object-oriented, functional), and its design leans hard on readability through meaningful indentation.

That readability is why we start here. You can run programs without compiling them first, sit at a prompt and try ideas line by line, and read your own code back a week later and still understand it.

People reach for Python across scripting, data analysis, machine learning, web development, and game development, which is why Google, NASA, Netflix, Amazon, and many others use it.

Getting set up

We use the Anaconda distribution, which bundles Python with the scientific libraries and tools we need, and Jupyter Notebook, where you write and run code one cell at a time.

• Windows: docs.anaconda.com/anaconda/install/windows
• macOS: docs.anaconda.com/anaconda/install/mac-os

In a Jupyter cell, type your code and press Shift + Enter to run it.

Habits worth forming now

• Comment and document what is not obvious.
• Indent consistently. In Python indentation is not decoration; it is how the language groups code.
• Avoid deep nesting. If you are five levels in, rethink the structure.
• Do not repeat yourself (DRY). The same logic should live in one place.
• Organise files and folders. Do not put everything in one file; a clean structure is easier to read, debug, and maintain.

Variables

A variable is a name (an identifier) that refers to a value. The rules:

• A name starts with a letter or an underscore: str, _num, num are all valid.
• A name cannot start with a number: 9num is invalid.
• Only letters, digits, and underscores are allowed, no %, $, #.
• Names are case sensitive: num and NUM are two different variables.

name = "Ada"        # a string
age = 19            # an integer
gpa = 4.33          # a float
print(name, age, gpa)

Data types

A data type is the kind of value a variable holds. 123 is an integer, "hello" is a string, 2.33 is a float. Python splits types into two groups:

• Immutable (cannot be changed in place): numbers, strings, tuples.
• Mutable (can be changed in place): lists, dictionaries, sets.

That distinction matters later when you pass values around and wonder why one changed and another did not.

Keywords

Keywords are reserved words with special meaning, so you cannot use them as variable names. Naming a variable while causes an error, because while already means a loop. Python 3 has 33 of them, including:

False  None  True  and  as  assert  break  class  continue  def  del
elif  else  except  finally  for  from  global  if  import  in  is
lambda  nonlocal  not  or  pass  raise  return  try  while  with  yield

Lab

Create a GitHub repository for your work this semester and clone it. Make a Week_2 folder and keep your notebooks there. Commit and push as you go:

git clone YOUR-REPO-URL
git add .
git commit -m "Week 2 practice"
git push

Then, in a notebook, declare one variable of each basic type, print them, and print their types with type(...).