Advanced Python Mastery

[4.5 days] So you learned Python from an online tutorial, a training course, or from a book, but you want to learn more. Then this is the course for you. Designed for working programmers who want to take their understanding to a whole new level, you'll learn what really makes Python tick. The course starts out by looking at subtle aspects of the Python code you are already writing, but then dives into a wide variety of advanced topics including the object model, data encapsulation, descriptors, generators, coroutines, context managers, decorators, metaclasses, packages, closures, and more. By the end of the course, you'll not only know what these features are, but how they can be applied to a wide range of practical programming problems. Includes a 325 page guidebook and more than 50 hands on exercises.

Note: A suggested prerequisite is my Practical Python Programming course.

Detailed Course Outline

1. Python Review. 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.
2. 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.
3. 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.
4. 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, attribute access methods, and the descriptor protocol.
5. 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.
6. Packaging and Distributing Python Programs. This section covers the basics of how to organize programs so that they can be more easily be given to others. Covers packages and basic use of the distutils module.
7. Working with Functions. 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.
8. 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, context managers, and metaclasses.
9. 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.
10. Extending Python with C and C++. An overview of basic techniques for building C extension modules to Python. Covers the process of writing a hand-written extension module, using the ctypes library, and wrapping C libraries with Swig.

Course Materials

Students will receive a bound fully indexed set of lecture notes along with a complete set class exercises (distributed electronically). All class exercises come with solution code for later study and for use during the class.