| 01 Introduction to Python Epiphanies | |||
| 0101 Introduction to Python Epiphanies.flv | 7.28 MB | ||
| 02 Objects | |||
| 0201 Back to Basics - Objects.flv | 136.29 MB | ||
| 0202 Exercises - Objects.flv | 24.4 MB | ||
| 03 Names | |||
| 0301 Back to Basics - Names.flv | 109.2 MB | ||
| 0302 Exercises - Names.flv | 47.39 MB | ||
| 04 More About Namespaces | |||
| 0401 Namespaces Scope and Search Order.flv | 98.63 MB | ||
| 0402 Namespaces- Function Locals.flv | 86.1 MB | ||
| 0403 The Built-ins Namespace.flv | 59.31 MB | ||
| 0404 Exercises - The Built-ins Namespace.flv | 21.87 MB | ||
| 05 Import | |||
| 0501 The import Statement.flv | 81.68 MB | ||
| 0502 Exercises - The import Statement.flv | 50.57 MB | ||
| 06 Functions | |||
| 0601 Functions.flv | 93.68 MB | ||
| 0602 Exercises - Functions.flv | 41.72 MB | ||
| 0603 Augmented Assignment Statements.flv | 110.95 MB | ||
| 0604 Function Arguments are Passed by Assignment.flv | 50.31 MB | ||
| 07 Decorators | |||
| 0701 Decorators Simplified.flv | 148.15 MB | ||
| 0702 Exercises - Decorators.flv | 44.25 MB | ||
| 08 How Classes Work | |||
| 0801 Decontructing the Class Statement.flv | 227.41 MB | ||
| 0802 Creating Classes with the type Function.flv | 79.78 MB | ||
| 0803 Exercises - The Class Statement.flv | 48.54 MB | ||
| 0804 Class Decorator Example.flv | 29.09 MB | ||
| 09 Special Methods | |||
| 0901 Special Methods of Classes.flv | 91.42 MB | ||
| 0902 Exercises - Special Methods of Classes.flv | 27.78 MB | ||
| 10 Iterators and Generators | |||
| 1001 Iterables, Iterators, and the Iterator Protocol.flv | 56.42 MB | ||
| 1002 Exercises - Iterables, Iterators, and the Iterator Protocol.flv | 17.09 MB | ||
| 1003 Generator Functions.flv | 57.32 MB | ||
| 1004 Exercises - Generator Functions.flv | 34.9 MB | ||
| 11 Taking Advantage of First Class Objects | |||
| 1101 First Class Objects.flv | 99.36 MB | ||
| 1102 Binding Data with Functions.flv | 70.44 MB | ||
| 1103 Exercises - Binding Data with Functions.flv | 49.17 MB |
Python Epiphanies: Exploring Fundamental Concepts
Python is an amazing language.
However, many intermediate Python developers aren’t achieving their full potential with the language because of features and concepts they don't know, or that they partly know but find confusing because their understanding isn't quite right. This video tutorial will help you by:
- Clarifying exactly how names work. Names are one of features of Python most often poorly understood, especially for developers who think in terms of variables as containers for values.
- Explaining namespaces and going into detail on all the language features that change them from assignment and del to function and class definitions. You’ll then learn potentially confusing aspects of Python that, once you correctly understand names and namespaces, are no longer confusing.
- Demonstrating several powerful features in Python that are often lacking in other language, such as generators and first class objects, in order to help you imagine more Pythonic solutions to problems.
Topics include:
- The details of object creation and naming
- Namespace changing features including assignment, del, import, function definition, class definition, and decorators
- Disassembling CPython bytecode to understand some Python features
- Iterables, iterators, and the iterator protocol
- How to use generators to make your code easier to read and understand
- Monkey patching classes, creating classes dynamically, and how bound methods work
- Using special methods in classes
- Several ways other than classes to bind data with functions
- Python 3 features such as tuple assignment with extended iterable unpacking and keyword-only function arguments
Stuart Williams has been teaching Python for over a decade to audiences as diverse as adults in industry and at PyCon, students in university, high school students at a week-long Python summer camp, and grade school students learning Raspberry Pi.
He holds a B.Sc. degree in Physics and Math/Computer Science, and a M.Sc. in Computer Science and Engineering from the University of Washington.
He works in the financial services industry with Python in domains ranging from batch systems, to software architecture, to helping quantitative analysts. He also teaches Python and coaches development teams at startups
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