by wesley chun for EuroPython 2011
In Python 101, you learned basic Python syntax, what its flow control mechanisms and basic data types are and how they work. You learned how to write functions and developed executable Python scripts that actually work! You probably also learned how to create files, how to open, read from or write to them, and close them. Perhaps you’ve even learned a little bit of object-oriented programming, developed a couple of Python classes, most with user-defined methods, and have no problems creating instances to use in your applications.
In Python 102 (or equivalent in experience), you explored further, using default values and variable arguments for functions, discovered how to catch exceptions and write handlers for them… perhaps you’ve even created your own exceptions. You have found some useful Python standard library modules and using them actively in your own applications. You’ve quite comfortable with OOP, creating classes and using instances regularly in your programs. In fact, you’ve been coding Python for 6 months to a couple of years now. You’re much more serious about Python now because you’re no longer a “beginner.” You’ve even taken notice at the growing number of jobs requesting or requiring Python skills.
As an aspiring Python developer, you are starting to be more aware of the entire ecosystem around you, and think you may be ready for “prime-time” and feel able to take on a full-time position as a Python programmer. However, if you have experienced one or more of the below questions or problems, this talk may be for you:
Throughout this time, you’ve experienced strange bugs in your code. In particular, you notice that things don’t always behave the way you expect and have spent a good amount of time debugging various parts of your software that you thought were actually correct – you work around them but are disturbed and don’t have the time nor committment to fully investigate.
You’ve created classes and objects just fine but wish that you could use some of Python’s operators (like +, in, len(), etc.) with your objects, which feel like they’re “2nd-class” citizens compared to the standard data types.
Do you know what functional evaluation strategy means? Have you been asked or considered whether Python is “call-by-value” or “call-by-reference”? It is important to you, and can you clearly explain your answer?
What does “mutability” mean? What is the difference between mutable and immutable objects? Which Python objects are mutable and which aren’t?
Can you clearly explain both the output in the two code snippets below, and even more importantly, why the output is the way it is?
SNIPPET A x = 42 y = x x += 1 print x print y
SNIPPET B x = [1, 2, 3] y = x x = 4 print x print y
This is what Python 103 is for… to fill in all the missing gaps, to answer all the questions (including those above) that do not seem to have easy-to-find answers on Google, but only if you have the desire to learn more about the interpreter to take your Python skills to the next level.