Python progression path - From apprentice to guru

Question

Hi all,

I've been learning, working, and playing with Python for a year and a half now. As a biologist slowly making the turn to bio-informatics, this language has been a the very core of all the major contributions I have made in the lab. I more or less fell in love with the way Python permits me to express beautiful solutions and also with the semantics of the language that allows such a natural flow from thoughts to workable code.

What I would like to know is your answer to a kind of question I have seldom seen in this or other forums. This question seems central to me for anyone on the path to Python improvement but who wonders what his next steps should be.

Let me sum up what I do NOT want to ask first ;)

• I don't want to know how to QUICKLY learn Python
• Nor do I want to find out the best way to get acquainted with the language
• Finally, I don't want to know a 'one trick that does it all' approach.

What I do want to know your opinion about, is:

What are the steps YOU would recommend to a Python journeyman, from apprenticeship to guru status (feel free to stop wherever your expertise dictates it), in order that one IMPROVES CONSTANTLY, becoming a better and better Python coder, one step at a time. Some of the people on SO almost seem worthy of worship for their Python prowess, please enlighten us :)

The kind of answers I would enjoy (but feel free to surprise the readership :P ), is formatted more or less like this:

• Read this (eg: python tutorial), pay attention to that kind of details
• Code for so manytime/problems/lines of code
• Then, read this (eg: this or that book), but this time, pay attention to this
• Tackle a few real-life problems
• Then, proceed to reading Y.
• Be sure to grasp these concepts
• Code for X time
• Come back to such and such basics or move further to...
• (you get the point :)

I really care about knowing your opinion on what exactly one should pay attention to, at various stages, in order to progress CONSTANTLY (with due efforts, of course). If you come from a specific field of expertise, discuss the path you see as appropriate in this field.

EDIT: Thanks to your great input, I'm back on the Python improvement track! I really appreciate!

Answer 1

Google just recently released an online Python class ("class" as in "a course of study").

http://code.google.com/edu/languages/google-python-class/

I know this doesn't answer your full question, but I think it's a great place to start!

Answer 2

Not precisely what you're asking for, but I think it's good advice.

Learn another language, doesn't matter too much which. Each language has it's own ideas and conventions that you can learn from. Learn about the differences in the languages and more importantly why they're different. Try a purely functional language like Haskell and see some of the benefits (and challenges) of functions free of side-effects. See how you can apply some of the things you learn from other languages to Python.

Answer 3

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.

Answer 4

Download Twisted and look at the source code. They employ some pretty advanced techniques.

Answer 5

I learned python first by myself over a summer just by doing the tutorial on the python site (sadly, I don't seem to be able to find that anymore, so I can't post a link).

Later, python was taught to me in one of my first year courses at university. In the summer that followed, I practiced with PythonChallenge and with problems from Google Code Jam. Solving these problems help from an algorithmic perspective as well as from the perspective of learning what Python can do as well as how to manipulate it to get the fullest out of python.

For similar reasons, I have heard that code golf works as well, but i have never tried it for myself.

Answer 6

Understand Introspection

• write a dir() equivalent
• write a type() equivalent
• figure out how to "monkey-patch"
• use the dis module to see how various language constructs work

Doing these things will

• give you some good theoretical knowledge about how python is implemented
• give you some good practical experience in lower-level programming
• give you a good intuitive feel for python data structures

Answer 7

Thoroughly Understand All Data Types and Structures

For every type and structure, write a series of demo programs that exercise every aspect of the type or data structure. If you do this, it might be worthwhile to blog notes on each one... it might be useful to lots of people!

Answer 8

Have you seen the book "Bioinformatics Programming using Python"? Looks like you're an exact member of its focus group.

Answer 9

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:

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] = 4
print x
print 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!!

Answer 10

Go back on a regular basis to the Python challenge. You'll get better.

Answer 11

Check out Peter Norvig's essay on becoming a master programmer in 10 years: http://norvig.com/21-days.html. I'd wager it holds true for any language.

Answer 12

I'll give you the simplest and most effective piece of advice I think anybody could give you: code.

You can only be better at using a language (which implies understanding it) by coding. You have to actively enjoy coding, be inspired, ask questions, and find answers by yourself.

Got a an hour to spare? Write code that will reverse a string, and find out the most optimum solution. A free evening? Why not try some web-scraping. Read other peoples code. See how they do things. Ask yourself what you would do.

When I'm bored at my computer, I open my IDE and code-storm. I jot down ideas that sound interesting, and challenging. An URL shortener? Sure, I can do that. Oh, I learnt how to convert numbers from one base to another as a side effect!

This is valid whatever your skill level. You never stop learning. By actively coding in your spare time you will, with little additional effort, come to understand the language, and ultimately, become a guru. You will build up knowledge and reusable code and memorise idioms.

Answer 13

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
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.

Answer 14

You already have a lot of reading material, but if you can handle more, I recommend you learn about the evolution of python by reading the Python Enhancement Proposals, especially the "Finished" PEPs and the "Deferred, Abandoned, Withdrawn, and Rejected" PEPs.

By seeing how the language has changed, the decisions that were made and their rationales, you will absorb the philosophy of Python and understand how "idiomatic Python" comes about.

http://www.python.org/dev/peps/