How can I take my knowledge to the next level?
Free learning resources are preferred. Hopefully ones you have used yourself when in my position.
Thanks!
Raymond Hettinger's "Transforming Code into Beautiful, Idiomatic Python":
http://pyvideo.org/video/1780/transforming-code-into-beautif...
(pyvideo.org has a lot of other great talks and presentations.)
Ned Batchelder's "Loop Like A Native":
http://nedbatchelder.com/text/iter.html
Python Module of the Week is also an excellent resource:
If you really like Codeacademy, there are non-track exercises that involve Python in the API section [0] and a couple of Python challenges [1][2] that aren't listed.
What I'm doing now:
* Solving exercises on Project Euler in Python. [3]
* Working through each example in the Python Cookbook[4]. It was just updated to the third edition.
* Watched Guido's Painless Python talks from a few years ago [5]. I found his concise explanations of language features really helpful.
Some things I intend to do:
* Finish working through Collective Intelligence [6]. The examples are written in Python.
* Work through Introduction to Algorithms [7]. The course uses Python.
* Read, understand and give a shot at extending Openstack [8] code.
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0: http://www.codecademy.com/tracks/apis
1: http://www.codecademy.com/courses/python-intermediate-en-NYX...
2: http://www.codecademy.com/courses/python-intermediate-en-VWi...
5: http://www.youtube.com/watch?v=bDgD9whDfEY
7: http://ocw.mit.edu/courses/electrical-engineering-and-comput...
Project Euler does involve a math, but so does efficient programming.
Efficiency can seem a pretty abstract thing and it might not crop up right away in more typical programming tasks. Working a Euler problem and refining to a solution that runs in 1% or 0.001% of the time required for the most straightforward solution is a great demonstrator.
>It's kinda difficult for those who graduated from social sciences and tries to learn programming from scratch.
Sure, but the context of the question here isn't really from scatch. The OP has already completed at least the 296 exercises in the Python track at Codeacademy to establish a base.
Personally, I haven't graduated from anything and I treat the Euler exercises as an interesting way to practice/learn a bit of programming and math.
Think Python: How To Think Like a Computer Scientist http://www.greenteapress.com/thinkpython/thinkpython.html
Think Complexity: Exploring Complexity Science with Python : http://www.greenteapress.com/compmod/
Think Stats: Probability and Statistics for Programmers : http://www.greenteapress.com/thinkstats/index.html
Coming from a C++ background, I felt uncomfortable using python as more than a glue/scripting language, because the way resources are managed is treated very magically in most tutorials.
Say I want to use the OpenCV library to fling matrices and images around, it's hard to be confident of what the runtime is going to do with the data without having a really good handle on what mechanisms python has for dealing with data. Which is what this book is about.
As useful as they are for interviews, classic algorithms and data structures are probably not a big part of most peoples work, but understanding how they can be done in python helps you to make assumptions and use libraries in smart ways!
Most of all, it's fun and well written, for an algorithms book. It's more about python than algorithms, so if you were student wanting to learn algorithms, this book is better[2].
[1] http://www.amazon.co.uk/Data-Structures-Algorithms-Using-Pyt... [2]http://www.amazon.co.uk/Introduction-Algorithms-T-Cormen/dp/...
If you have "only" completed Codecademy or similar, you're nowhere near the intermediate mark. I have used Codecademy and Code School and they are indeed great. But they give a false sense of security and accomplishment to the user. They are great for introduction to a language but they only introduce you to the language, nothing beyond that.
Don't get me wrong, I applaud you for your will to learn programming. I'm not trying to make your accomplishments look insignificant. But I believe that, at this point, your accomplishment is not finishing Codecademy's very very introductory course on Python but taking the first step in the path in learning programming.
I suggest that you take a look at Zed Shaw's Learn Python The Hard Way. The beginning may look a bit too easy, after all Codecademy does teach you stuff. But midway through you will probably see that Learn Python The Hard Way introduces beginner stuff that hasn't been covered in Codecademy.
After that, continue reading about Python. Sadly, the real world isn't divided into categories marked as "Beginner, Intermediate, Advanced". Read source codes that actually interest you. You are bound to come across stuff that you have no idea about. Start reading about that stuff. Chances are really high that you will come across other stuff that you don't know about when you're reading about the first stuff that you didn't know about. You will probably end up reading (and learning) craploads of stuff, but in my experience that's how you really learn stuff.
I have learned this during my journey in programming. In the end, you are the only one who knows how much you know. Don't measure your knowledge by Codecademy's standards. They may tell you that you are intermediate but you may not even understand how a relatively simple library works.
To anyone who will flame me for writing this, try Codecademy's or (Code School's) courses. Try and choose a language which you don't know. Don't read any of the info, just read what is expected of you. You will still pass the course. That is a VERY big problem. I'm a beginner, I have felt that false sense of accomplishment. It hurts a lot when you see what real intermediate and advanced people do with a programming language.
SICP is an introductory course in computing. It covers meta-linguistic abstractions. The Code Academy course in JavaScript I completed required a bit of filling in the boiler plate for its final project.
Code Academy is a great project, in part because it is designed to help students achieve success without the pain of the real world. That is also a weakness.
I just found out about Neckbeard Republic [2] today - it looks to be similar to Railscasts. I haven't watched any of their stuff yet, but I plan to.
Do take a look.
And good ol' quicktime to stitch it up.
Then maybe try implementing some of the fundamental data structures such as queue's and linked lists[1] along with their basic operations (such as push and pop for queues). Try to see if you can use pythons built-in data structures[2], or do it yourself with object oriented programming.
0:https://en.wikipedia.org/wiki/Sorting_algorithm#Summaries_of...
https://class.coursera.org/matrix-001/wiki/view?page=overvie...
This session started on Monday (July 1st) and if you have an interest in Computer Vision, Machine Learning, or Cryptography I'd recommend you join us.
As well as that, look into some of the advanced language features and idioms, and try to use them in your programs, or rewrite old programs to use them.
http://scipy-lectures.github.io
https://github.com/jrjohansson/scientific-python-lectures
https://github.com/ipython/ipython/wiki/A-gallery-of-interes...
Exercises are great, but unless you have a way of getting feedback on your solutions, you will progress slowly. Practice doesn't make perfect: perfect practice does.
There's a lot of good code to read. I'd recommend starting with Flask - you already have the context of using it. You might also consider checking out something that Kenneth Reitz has written. Whenever you don't understand why they chose to write something a certain way, ask! Both have very active irc channels.
Speaking of irc, #python is a great place to find reviewers. There are (mostly) friendly folks there at any time of day. You'll maximize your chances of a good review by:
1) having a concrete question to ask: "I'm not sure about my use of kwarg unpacking on line 12; would anyone have done it a different way?"
2) providing a small program (or section of a program) for review. People are generous, but likely won't spend an hour reviewing a few hundred lines of code =)
I hope that helps! Feel free to email me if you're having trouble finding reviewers; I'm no Armin Ronacher, but I've written a good amount of Python.
then you might ask: what exact is the pythonic way? then it is hard to say. on a deeper level (that is coding style): you'd prefer list comprehensions over for loops (not always, but for simple iterables); prefering the functional approach -- immutable input/output on functions etc, learning map/reduce/etc; understanding the performance kinks of python, etc.
on a higher-level, there is the python-for-humans. learn what it means to be beautiful code, not just in terms code style, but how people will use your code. a splendid example which i have immense amount of respect is the requests library by kennethreitz.
retain your curiousity always. the day you lose these curiousity is when you become a mediocre programmer. don't be that guy.
after you're done with these, go deeper. keep going. understand why the fuck people whine about GIL, about concurrency and how bitchy it is in python (and why), and even alternatives to python: for example. when not to use python.
i wish you the best :)
Another thing you might try is taking a book with examples in one language and try to implement them in Python. It's a little weird but it can be a great way to have a framework for a task but have to explore on your own.
At some point you just have to start coding and there you'll push your boundaries. I fooled around online python learning but didn't get far until I built a web scrapper. I completely over engineered a one time use script just to learn... IMHO its what can I build to learn?
It involves learning/hardening your Python knowledge by fixing unit tests.
Think complexity is a free python book on algorithms and science.
Python 3 Object Oriented Programming is a very good book (not free) on OOP.