Course Overview

Advanced Python Programming is a practical, hands-on Python training course that thoroughly explores intermediate to advanced-level topics and skills, focusing on enterprise development.  Throughout the course, students will learn how to leverage OS services, Code graphical interfaces for applications, create modules and run unit tests, work with binary data, interact with network services, query databases, process XML data, and more.  This comprehensive, practical course provides an in-depth exploration of working with the programming language, not an academic overview of syntax and grammar.

Key Learning Areas

This course is approximately 75% hands-on, combining expert lectures, live coding with the instructor, real-world demonstrations, and group discussions with machine-based practical labs and exercises.  Our engaging instructors and mentors are highly experienced practitioners who bring years of current "on-the-job" experience into every classroom.

Working in a hands-on learning environment led by our expert practitioner, attendees will learn advanced skills needed to:

  • Leverage OS services
  • Add enhancements to classes
  • Code graphical interfaces for applications
  • Understand advanced Python metaprogramming concepts
  • Create easy-to-use and easy-to-maintain modules and packages
  • Implement and run unit tests
  • Create multithreaded and multi-process applications
  • Interact with network services
  • Design professional scripts
  • Query databases
  • Process XML, CSV, and JSON data
  • Working with more data types
  • Using type hints

Course Outline

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
  • Packing and Unpacking

OS Services

  • The os and path modules
  • Environment variables
  • Launching external commands with subprocess
  • Paths, directories, and filenames
  • 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 and C Programming

  • What is Binary Data?
  • Binary vs text
  • Using the Struct module
  • Using the Structure Class
  • Calling C Functions from Python
  • Overview C Extensions

Pythonic Programming

  • The Zen of Python
  • Tuples
  • Sorting
  • List comprehensions
  • Generator expressions
  • String formatting

Functions, Modules, and Packages

  • Four types of function parameters
  • Four levels of name scoping
  • Single/multi dispatch
  • Relative imports
  • Using __init__ effectively
  • Decorators
  • Lambda functions

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
  • Monkey patching

Developer Tools

  • Analyzing programs with pylint
  • Code Reformatting with Autopep8 and Black
  • Using the debugger

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
  • Transaction control

PyQt

  • Overview
  • Qt Architecture
  • Standard widgets
  • Event handling

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
  • Async Programming

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

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

Type Hinting

  • 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

Who Benefits

This is an advanced-level Python course geared for students experienced with Python who want to use Python in web development projects or automate or simplify everyday tasks using Python scripts.

Prerequisites

Practical, intermediate-level experience working with Python is required, along with a working, user-level knowledge of Unix/Linux, Mac, or Windows.  This course does not cover Python fundamentals. If you have introductory-level practical experience with Python and are looking for a class to understand those concepts better, please check out our classes on Mastering Python and Python Essentials.

Setup: Students will need the standard Python distribution, Anaconda or Miniconda. For code editing, either Visual Studio Code or PyCharm is supported in the class. Also, the following development tools are needed:

  • GitHub Account
  • Git Command Line Tool
  • Docker Desktop (free version be used for training)
  • Azure Data Studio
  • gcc Compiler
  • Windows Only: Microsoft C++ Build Tools

All can be downloaded for free. Comprehensive setup instructions for Windows, macOS, and Linux will be provided before the start of the course.