Python Programming

How Python programs are written and run, and the tools you need.

• What Python is and where it is used
• Installing Python and an editor
• Running scripts and the interactive shell
• Your first program with print()
• Comments and style (PEP 8)
• Reading a traceback

• What is Python?
• Install Python on your computer
• Your first Python program

Storing values and working with numbers, text and booleans.

• Variables and name binding
• int, float, str and bool
• Type conversion
• Arithmetic, comparison and logical operators
• Operator precedence
• Input with input()
• Formatted output with f-strings

• Variables and Name Binding
• Numeric Types: int and float
• Formatted Output with f-strings

Making decisions and repeating work with conditions and loops.

• if, elif and else
• Nested conditions and the conditional expression
• while loops
• for loops and range()
• break, continue and loop else
• Tracing a loop by hand

• The if and if-else Statements
• The while Loop
• The for Loop and range()

Breaking programs into small reusable pieces.

• Defining and calling functions
• Parameters, arguments and return values
• Default and keyword arguments
• *args and **kwargs
• Scope: local and global names
• Lambda functions
• Docstrings

• Defining and Calling Functions
• Default Arguments, *args, and **kwargs
• Scope (LEGB Rule) and Lambda Functions

Python's sequence types and how to slice, search and transform them.

• Lists and list methods
• Indexing and slicing
• List comprehensions
• Tuples and unpacking
• String methods and formatting
• Nested lists and 2D grids
• Mutable versus immutable

• What is a List?
• Looping and List Comprehensions
• What is a Tuple?
• String Indexing and Slicing

Key-value lookups, unique values and when to use each.

• Creating and updating dictionaries
• Iterating over keys, values and items
• Dictionary methods and comprehensions
• Sets and set operations
• Counting and grouping data
• Choosing the right collection

• Dictionaries: Key-Value Mapping
• Dictionary Methods and Comprehensions
• Sets: Unique Collections and Membership

Working with data on disk and handling problems gracefully.

• Reading and writing text files
• The with statement
• CSV and JSON files
• pathlib and file paths
• try, except, else and finally
• Raising your own exceptions
• Importing modules and the standard library
• Writing your own modules and using pip

• Reading and Writing Text Files
• CSV Files with the csv Module
• The try and except Blocks
• Writing Your Own Modules

Modelling things as classes with state and behaviour.

• Classes, objects and self
• __init__ and instance attributes
• Class and static methods
• Properties and encapsulation
• Inheritance, super() and polymorphism
• Special methods such as __str__ and __eq__
• Dataclasses

• Classes, Instances and the self Parameter
• The @property Decorator and Setters
• Single Inheritance and Method Overriding
• String Representation: __str__ vs __repr__

Searching, sorting, recursion and measuring cost.

• Linear and binary search
• Bubble, selection and insertion sort
• Merge sort
• Recursion and the call stack
• Big-O notation
• Tracing and testing with assert

• The Classic Binary Search Loop and Its Bounds
• Bubble, Selection and Insertion Sort
• Base Case, Recursive Case and the Call Stack
• What Big-O Means and Counting Steps

Putting it all together and choosing where to go next.

• Planning a small project
• Splitting code into functions and modules
• Virtual environments
• Version control with Git and GitHub
• Next steps: data analysis, web with FastAPI, automation

• Build a Password Strength Auditor
• Build a Warehouse Inventory Manager