Updated June 2026

Advanced Python Programming

Class Duration

35 hours of live training delivered over 5 days.

Student Prerequisites

Some practical Python experience is required
Comfortable working knowledge of your operating system of choice (Linux, macOS, or Windows)
This course assumes you already know the fundamentals - they are not revisited beyond a short refresher
Students who need to build up those fundamentals first should consider Introduction to Python and Intermediate Python

Target Audience

This is an intermediate-and-beyond Python course aimed at developers who already write Python and want to take it further - whether that's powering web projects, automating routine work, or building production-grade tools and scripts.

Description

Advanced Python Programming is a hands-on course that takes experienced Python developers from intermediate fundamentals into the deeper waters of enterprise-grade development. Across five days, you'll work through OS-level scripting, graphical user interfaces, modular package design, unit testing, class design, network programming, database access, XML and JSON processing, and more. This is a working programmer's course - an in-depth tour of how the language is actually used in production, not a syntax-and-grammar walkthrough. The course is taught on a current Python release (3.13+, with 3.14 features highlighted where relevant).

The course runs roughly 50% hands-on, blending focused lecture and live demonstrations with practical lab exercises and group discussion. Sessions are led by working practitioners who pull examples and patterns straight from their day-to-day engineering work - so what you learn in class lines up with what you'll actually ship at the office.

Learning Outcomes

Tap into OS-level services from Python
Extend and enhance classes with advanced features
Build graphical interfaces for desktop applications
Apply Python's metaprogramming features with confidence
Author clean, maintainable modules and packages
Write and run unit tests with PyTest
Build multithreaded and multi-process applications
Talk to network services and remote systems
Craft polished, production-ready scripts
Query relational databases from Python
Read and produce XML, CSV, and JSON data
Work with additional data types if time permits
Apply type hints for clearer intent and contracts if time permits

Training Materials

Comprehensive courseware is distributed online at the start of class. All students receive a downloadable MP4 recording of the training.

Software Requirements

Permission to install Python 3.13 or later (installing with uv is demonstrated in class)
Text editor or IDE (VS Code with the Python extension recommended)
Permission to install Python packages, including PyQt6, pytest, and requests (SQLite, used for database labs, ships with Python)
Terminal/command-line access on Linux, macOS, or Windows
If a local environment is not possible, a cloud-based environment can be provided

Training Topics

Python Quick Refresher

Built-in data types
Lists and tuples
Dictionaries and sets
Program structure
Files and console I/O
If statement
for and while loops

Pythonic Programming

The Zen of Python
Tuples
Advanced unpacking
Sorting
Lambda functions
List comprehensions
Generator expressions
String formatting

OS Services

The os and os.path modules
Environment variables
Launching external commands with subprocess
Walking directory trees
Paths, directories, and filenames with pathlib
Working with file systems

Dates and Times

Basic date and time classes
Different time formats
Converting between formats
Formatting dates and times
Parsing date/time information

Binary Data

What is binary data?
Binary vs text
Using the struct module

Functions, Modules, and Packages

Four types of function parameters
Four levels of name scoping
Single/multi dispatch
Relative imports
Using init effectively
Documentation best practices

Intermediate Classes

Class/static data and methods
Inheritance (or composition)
Abstract base classes
Implementing protocols (context, iterator, etc.) with special methods

Metaprogramming

Implicit properties
globals() and locals()
Working with object attributes
The inspect module
Callable classes
Decorators
Monkey patching

Developer Tools

Analyzing programs with linters (pylint, ruff)
Using the debugger
Profiling code
Testing speed with benchmarking

Unit Testing with PyTest

What is a unit test?
Writing tests
Working with fixtures
Test runners
Mocking resources

Database Access

The DB API
Available interfaces
Connecting to a server
Creating and executing a cursor
Fetching data
Parameterized statements
Using metadata
Transaction control
ORMs and NoSQL overview

GUI Programming with PyQt

PyQt6 overview
Qt 6 architecture
Using Qt Designer
Standard widgets
Event handling
Extras

Network Programming

Built-in classes
Using requests
Grabbing web pages
Sending email
Working with binary data
Consuming RESTful services
Remote access (SSH)

Multiprogramming

The threading module
Sharing variables
The queue module
The multiprocessing module
Creating pools
The GIL today, and the free-threaded build (PEP 703/779)
About async programming with asyncio

Scripting for System Administration

Running external programs
Parsing arguments
Creating filters to read text files
Logging

Serializing Data - XML and JSON

Working with XML
XML modules in Python
Getting started with ElementTree
Parsing XML
Updating an XML tree
Creating a new document
About JSON
Reading JSON
Writing JSON
Reading/writing CSV files
YAML, other formats as time permits

Advanced Data Handling (time permitting)

Discover the collections module
Use defaultdict, Counter, and namedtuple
Create dataclasses
Store data offline with pickle

Type Hinting (time permitting)

Annotate variables
Learn what type hinting does NOT do
Use the typing module for detailed type hints
Understand union and optional types
Write stub interfaces