Python progression path - From apprentice to guru Python progression path - From apprentice to guru python python

Python progression path - From apprentice to guru


I thought the process of Python mastery went something like:

  1. Discover list comprehensions
  2. Discover generators
  3. Incorporate map, reduce, filter, iter, range, xrange often into your code
  4. Discover Decorators
  5. Write recursive functions, a lot
  6. Discover itertools and functools
  7. Read Real World Haskell (read free online)
  8. Rewrite all your old Python code with tons of higher order functions, recursion, and whatnot.
  9. Annoy your cubicle mates every time they present you with a Python class. Claim it could be "better" implemented as a dictionary plus some functions. Embrace functional programming.
  10. Rediscover the Strategy pattern and then all those things from imperative code you tried so hard to forget after Haskell.
  11. Find a balance.


One good way to further your Python knowledge is to dig into the source code of the libraries, platforms, and frameworks you use already.

For example if you're building a site on Django, many questions that might stump you can be answered by looking at how Django implements the feature in question.

This way you'll continue to pick up new idioms, coding styles, and Python tricks. (Some will be good and some will be bad.)

And when you see something Pythony that you don't understand in the source, hop over to the #python IRC channel and you'll find plenty of "language lawyers" happy to explain.

An accumulation of these little clarifications over years leads to a much deeper understanding of the language and all of its ins and outs.


Understand (more deeply) Python's data types and their roles with regards to memory mgmt

As some of you in the community are aware, I teach Python courses, the most popular ones being the comprehensive Intro+Intermediate course as well as an "advanced" course which introduces a variety of areas of application development.

Quite often, I get asked a question quite similar to, "Should I take your intro or advanced course? I've already been programming Python for 1-2 years, and I think the intro one is too simple for me so I'd like to jump straight to the advanced... which course would you recommend?"

To answer their question, I probe to see how strong they are in this area -- not that it's really the best way to measure whether they're ready for any advanced course, but to see how well their basic knowledge is of Python's objects and memory model, which is a cause of many Python bugs written by those who are not only beginners but those who have gone beyond that.

To do this, I point them at this simple 2-part quiz question:Ex1: x=42; y=x; x+=1; print x,y Ex2: x=[1,2,3];y=x;x[0]=4;print x,y

Many times, they are able to get the output, but the why is more difficult and much more important of an response... I would weigh the output as 20% of the answer while the "why" gets 80% credit. If they can't get the why, regardless how Python experience they have, I will always steer people to the comprehensive intro+intermediate course because I spend one lecture on objects and memory management to the point where you should be able to answer with the output and the why with sufficient confidence. (Just because you know Python's syntax after 1-2 years doesn't make you ready to move beyond a "beginner" label until you have a much better understanding as far as how Python works under the covers.)

A succeeding inquiry requiring a similar answer is even tougher, e.g.,

Example 3

x = ['foo', [1,2,3], 10.4]y = list(x) # or x[:]y[0] = 'fooooooo'y[1][0] = 4print xprint y

The next topics I recommend are to understanding reference counting well, learning what "interning" means (but not necessarily using it), learning about shallow and deep copies (as in Example 3 above), and finally, the interrelationships between the various types and constructs in the language, i.e. lists vs. tuples, dicts vs. sets, list comprehensions vs. generator expressions, iterators vs. generators, etc.; however all those other suggestions are another post for another time. Hope this helps in the meantime! :-)

ps. I agree with the other responses for getting more intimate with introspection as well as studying other projects' source code and add a strong "+1" to both suggestions!

pps. Great question BTW. I wish I was smart enough in the beginning to have asked something like this, but that was a long time ago, and now I'm trying to help others with my many years of full-time Python programming!!


matomo