Advanced Python Mastery

This is a no-holds barred course that aims to cover the entirety of the core Python language. Major themes include advanced data manipulation, object oriented programming, metaprogramming, design tradeoffs, customization features, and knowing how Python works under the hood.

A three or four day course. Not for beginners to Python.

This course is based on the course Advanced Python Mastery by David Beazley.


  • Python Review (Optional). An accelerated review of the Python language focused on features that you should already know. Covers the basic language statements, program structure, common datatypes, functions, exceptions, modules, and classes.
  • Idiomatic Data Handling. An in-depth look at data handling and data structures. A major focus of this section is on Python’s built-in container types (tuples, lists, sets, dicts, etc.) with an eye towards studying their performance properties and resource use. Also covers important programming data-processing idioms such as the use of list comprehensions and generator expressions.
  • Classes and Objects. A review of the class statement and how to define new objects in Python. A major focus is on how to properly encapsulate data, and when to use features such as static methods, class methods, and properties. Concludes with a review of some common object-oriented programming techniques and advanced topics including mixin classes and weak references.
  • Inside Python Objects. A look at how the Python object system is put together under the covers. Major topics include instance and class representation, attribute binding, inheritance, the rules of the Method Resolution Order, attribute access methods, and the descriptor protocol.
  • Testing, Logging, and Debugging. Learn how to test and debug your code. Covers the doctest, unittest, and logging modules. Information on assertions, optimized run mode, the debugger, and profiler is also presented.
  • Working with Code. A detailed look at more advanced aspects of Python functions. Topics include variable argument functions, anonymous functions (lambda), scoping rules, nested functions, function introspection, closures, delayed-evaluation, and partial function application.
  • Metaprogramming. Finally understand the secret techniques used by the Python framework builders. This section covers features that allow you to manipulate code. Topics include decorators, class decorators, decorator factories, context managers, and metaclasses.
  • Iterators, Generators, and Coroutines. Covers the iteration protocol, generator functions, and coroutines. A major focus of this section is on applying generators and coroutines to problems in data processing. You will learn how to apply these features to large data files and data streams.
  • Modules and Packages. This section covers details related to using modules and packages to organize larger programs. A major focus is understanding the underlying behavior of the import statement and some of the more tricky issues related to organizing packages.