### Writing tests for functions and classes in Python

Here's a simple example code that I wrote to test a mathOps class in Python. I use the unittest package which is part of the Python Standard Library.

As you can see, the mathOps class has two attributes, a,b, and there are methods defined that take care of addition, subtraction, multiplication and division. Now, I want to write a code, that tests mathOps class objects to make sure that the methods are giving the output we desire.

One interesting thing to note is the last function/test defined in the mathOpsTest class. The decorator @unittest.expectedFailure tells the testing framework that this test is expected to fail, given that we're passing vectors/arrays to the add method, expecting it to perform vector addition, where as the add method expects input of type Float. The traits package does this type-checking to make sure that the inputs we give are of the right kind!

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 import unittest from traits.api import HasTraits, Float class mathOps(HasTraits): a = Float b = Float def add(self, a, b): self.a = a self.b = b return self.a +self.b def sub(self, a, b): self.a = a self.b = b return self.a -self.b def mul(self, a, b): self.a = a self.b = b return self.a*self.b def div(self, a, b): self.a = a self.b = b return self.a/self.b class mathOpsTest(unittest.TestCase): obj = mathOps() def test_add(self): self.assertEqual(self.obj.add(1,1), 2) self.assertEqual(self.obj.add(1,2.0), 3.0) self.assertEqual(self.obj.add(3.0,1), 4.0) self.assertEqual(self.obj.add(5.0,6.0), 11.0) def test_sub(self): self.assertEqual(self.obj.sub(1,1), 0) self.assertEqual(self.obj.sub(1,2.0), -1.0) self.assertEqual(self.obj.sub(3.0,1), 2.0) self.assertEqual(self.obj.sub(4.0,8.0), -4.0) def test_mul(self): self.assertEqual(self.obj.mul(1,1), 1) self.assertEqual(self.obj.mul(1,2.0), 2.0) self.assertEqual(self.obj.mul(4.0,2), 8.0) self.assertEqual(self.obj.mul(3.0,7.0), 21.0) def test_div(self): self.assertEqual(self.obj.div(1,1), 1) self.assertEqual(self.obj.div(1.0,2), 0.5) self.assertEqual(self.obj.div(1,10.0), 0.1) self.assertEqual(self.obj.div(1.0,5.0), 0.2) @unittest.expectedFailure def test_vector_add(self): self.assertIsInstance(self.a, ) self.assertEqual(self.obj.add([1,1],[1,1]),[2,2]) 

### Animation using GNUPlot

Animation using GNUPlotI've been trying to create an animation depicting a quasar spectrum moving across the 5 SDSS pass bands with respect to redshift. It is important to visualise what emission lines are moving in and out of bands to be able to understand the color-redshift plots and the changes in it.
I've tried doing this using the animate function in matplotlib, python but i wasn't able to make it work - meaning i worked on it for a couple of days and then i gave up, not having found solutions for my problems on the internet.
And then i came across this site, where the gunn-peterson trough and the lyman alpha forest have been depicted - in a beautiful manner. And this got me interested in using js and d3 to do the animations and make it dynamic - using sliders etc.
In the meanwhile, i thought i'd look up and see if there was a way to create animations in gnuplot and whoopdedoo, what do i find but nirvana!

In the image, you see 5 static curves and one dynam…

### on MOOCs.

For those of you who don't know, MOOC stands for Massively Open Online Course.

The internet is an awesome thing. It's making education free for all. Well, mostly free. But it's surprising at the width and depth of courses being offered online. And it looks like they are also having an impact on students, especially those from universities that are not top ranked. Students in all parts of the world can now get a first class education experience, thanks to courses offered by Stanford, MIT, Caltech, etc.

I'm talking about MOOCs because one of my new year resolutions is to take online courses, atleast 2 per semester (6 months). And I've chosen the following two courses on edX - Analyzing Big Data with Microsoft R Server and Data Science Essentials for now. I looked at courses on Coursera but I couldn't find any which was worthy and free. There are a lot more MOOC providers out there but let's start here. And I feel like the two courses are relevant to where I …

### On programmers.

I just watched this brilliant keynote today. It's a commentary on Programmers and the software development industry/ecosystem as a whole.

I am not going to give you a tl;dr version of the talk because it is a talk that I believe everyone should watch, that everyone should learn from. Instead, I am going to give my own parallel-ish views on programmers and programming.
As pointed out in the talk, there are mythical creatures in the software development industry who are revered as gods. Guido Van Rossum, the creator of Python, was given the title Benevolent Dictator For Life (BDFL). People flock around the creators of popular languages or libraries. They are god-like to most programmers and are treated like gods. By which, I mean to say, we assume they don't have flaws. That they are infallible. That they are perfect.
And alongside this belief in the infallibility of these Gods, we believe that they were born programmers. That programming is something that people are born wit…